Contract No U-BROAD D2.2 Analysis of Multiuser Capacities and Capacity Regions

Size: px
Start display at page:

Download "Contract No U-BROAD D2.2 Analysis of Multiuser Capacities and Capacity Regions"

Transcription

1 U-BROAD D2.2 Contract No U-BROAD D2.2 Analysis of Multiuser Capacities and Capacity Regions Prepared by: Telecommunication System Institute (TSI) - Greece Bar Ilan University (BIU) - Israel Abstract: This document describes the results of statistical analysis of capacity for short DSL loops, based on actual insertion loss and NEXT/FEXT channel measurement data provided by France Telecom R&D. The channel measurement process and the resulting data have been described in detail in Deliverable D2.1. The focus of the present document is on assessing the capacity of both single-line and coordinated (vectored) DSL transmission systems, using the aforementioned data. Since the selection of direct (vectored) loops and interferers in the binder is random, the resulting capacity is a random variable. For this reason, statistical analysis is appropriate. The pertinent metrics are the mean, minimum, maximum, and standard deviation of capacity, as well as capacity outage. These are all derived from capacity histograms, which are also provided herein. Both exhaustive (enumeration-based) computation, and Monte-Carlo sampling have been considered, for short DSL loop lengths and bandwidth up to 3 MHz. We find that capacities in the order of several hundred Megabits per second per loop are attainable, and the ratio of minimum to mean capacity is often quite high. We also find that transmitreceive coordination yields a significant boost in average per-loop capacity only when the number of coordinated loops is higher than the number of alien interferers. In situations wherein the number of alien interferers exceeds the number of coordinated loops, coordination improves the capacity spread. The results drive R&D efforts under WP3, and will have an impact on several other U-BROAD WPs; they are also very timely for the VDSL community-at-large. Keyword list: DSL, VDSL, channel capacity, outage, coordinated (vectored) transmission, analysis of measurements, experimental capacity estimates for short DSL loops

2 Executive Summary This document describes the results of statistical analysis of capacity for short DSL loops, based on actual insertion loss and NEXT/FEXT channel measurement data provided by France Telecom R&D. The channel measurement process and the resulting data have been described in detail in Deliverable D2.1, [1]. The focus of the present document is on assessing the capacity of both single-line and coordinated (vectored) DSL transmission systems, using the aforementioned data. Since the selection of direct (vectored) loops and interferers in the binder is random, the resulting capacity is a random variable. For this reason, statistical analysis is appropriate. Pertinent metrics include the mean, minimum, maximum, and standard deviation of capacity, as well as capacity outage. These are all derived from capacity histograms, which are also provided herein. Both exhaustive (enumeration-based) computation and Monte-Carlo sampling have been considered, for short DSL loop lengths and bandwidth up to 3 MHz. We find that: Capacities in the order of several hundred Megabits per second per loop are attainable, and the ratio of minimum to mean capacity is often quite high; Coordination yields a more significant boost in average per-loop capacity only when the number of coordinated loops is higher than the number of alien interferers. When the number of coordinated loops is smaller than the number of alien interferers, there is usually less than 25% increase in the average per-loop capacity; however: Coordination significantly reduces the capacity spread, even when only a small fraction of loops in the binder are coordinated. This is important because it reduces the ratio of minimum to average capacity, which is a measure of outage. The results drive R&D efforts under WP3, and will have an impact on several other U-BROAD WPs; they are also very timely for the VDSL community-atlarge. 1

3 Contents 1 Introduction & Roadmap Capacity calculations and related assumptions Capacity Statistics via Full Combinatorial Calculation Capacity versus number of disturbers Light vs. Full crosstalk: Capacity versus number of coordinated pairs Capacity Statistics via Reduced Monte-Carlo Sampling Average Capacity Capacity CDFs Conclusions & Coordination Benefit Assessment 31 5 Appendix A: Capacity Histograms and Moments via Full Combinatorial Calculations FEXT plus NEXT FEXT only Appendix B: Capacity Statistics via Reduced Monte-Carlo Sampling for 3m and 6m loops Average Capacity Capacity CDFs

4 1 Introduction & Roadmap This document is structured as follows. We begin with a short introduction to capacity calculations for single-loop and coordinated DSL transmission subject to crosstalk. For coordinated Multiple-Input Multiple-Output (MIMO) transmission, we start from the general MIMO capacity formula, and work our way through the various application-specific assumptions and simplifications. In particular, we briefly discuss self-next echo-cancellation, and self-fext transmit precompensation, and their effect on the crosstalk covariance. Since capacity depends on the specific configuration of interferers (not only on the number thereof), it is important to calculate the capacity distribution and associated summary metrics (minimum, mean, maximum capacity; plus standard deviation and outage) as a function of the number of coordinated loops and the type and number of interferers. For this purpose, one can either opt for full enumeration-based computation of the capacity distributions, or computationally simpler Monte-Carlo sampling-based estimates. We decided to pursue both. The TUC team worked using the enumeration-based approach, and the BIU team worked using the Monte-Carlo approach. Section 2 contains the results of enumeration-based capacity calculations, whereas Section 3 contains those of Monte-Carlo sampling-based capacity calculations. 1.1 Capacity calculations and related assumptions For general background on capacity, we refer the reader to Cover & Thomas [1]. On the capacity of Multiple-Input Multiple-Output (MIMO) systems, see [2,3]. References [4,5] are good background on DSL system capacity. One of the earliest references on coordinated transmission over a pair of DSL lines is [6]; see Ginis & Cioffi [7] for an overview of the current state-of-art on coordinated transmission for DSL. Crosstalk cancellation techniques for DSL systems are discussed in [8]. Let there be N loops in the binder (N =28for France Telecom s data), out of which p loops are employed for coordinated (vectored) transmission. Let L NEXT (L FEXT ) denote the number of NEXT (respectively, FEXT) loops that interfere with the p coordinated loops. Let σ 2 denote the additive white Gaussian noise (AWGN) power spectral density (PSD) - typically at -14 dbm/hz (or 1 17 W/Hz in absolute scale) for DSL systems. For a single direct loop (p = 1), and a certain configuration of interfering loops, the Shannon capacity is given by [1,4] C = log 2 (1 + SINR(f))df (1) BW where BW denotes the available bandwidth, and the Signal to Interference plus 3

5 Noise Ratio is given by H IL (f) 2 p(f) SINR(f) = σ 2 + L NEXT i=1 H NEXT,i (f) 2 p NEXT (f)+ L FEXT j=1 H FEXT,j (f) 2 p FEXT (f) (2) Here, H IL (f) is the insertion loss (frequency response) of the direct channel, H NEXT,i (f) (H FEXT,j (f)) is the frequency response of the i-th NEXT (resp. j-th FEXT) channel, p(f) is the PSD (or, spectral mask) employed for the direct channel, while p NEXT (f) (p FEXT (f)) is the PSD of NEXT (resp. FEXT) interferers. Assuming that all spectral masks are equal equation (2) simplifies to H IL (f) 2 SINR(f) = σ 2 + L NEXT p(f) i=1 H NEXT,i (f) 2 + L FEXT (3) j=1 H FEXT,j (f) 2 In the vectored case (p >1) the capacity of the coordinated system is given by [2,3] C = log 2 det(i + p(f)h(f)r 1 nn(f)h (f))df (4) BW where H(f) is the p p input-output MIMO channel transfer matrix at frequency f, denotes Hermitian (conjugate) transpose, and R nn (f) is the p p interference plus noise covariance matrix at the output of the MIMO subsystem at frequency f: R nn = p NEXT (f)g NEXT (f)g NEXT(f)+p FEXT (f)g FEXT (f)g FEXT(f)+σ 2 I (5) where G NEXT (f) is a p L NEXT crosstalk transfer matrix, whose (m, l)-element is the complex coupling coefficient from the l-th NEXT disturber to the m-th loop in the vectored subsystem at frequency f; and similarly for the p L FEXT FEXT coupling matrix, G FEXT (f). The matrix H is diagonally-dominated in DSL systems, wherein insertion loss is usually 2 or more db higher than interference. For this reason, it is possible to pre-equalize H at the transmitter s side, without a significant penalty in terms of transmission power. Thus, upon pre-multiplication by H 1 diag ([H IL,1 (f),,h IL,p (f)]), the effective MIMO channel transfer matrix becomes diag ([H IL,1 (f),,h IL,p (f)]) (note that we do not invert the direct insertion loss channels; that would entail a significant power penalty, esp. at higher frequencies). 4

6 If we further assume that all insertion loss channels of the vectored subsystem are approximately equal [9] (this is well-justified, for insertion loss primarily depends on length, termination and bridge taps), then the capacity expression further simplifies to C = log 2 det(i + H IL (f) 2 p(f)r 1 nn(f))df (6) BW A few remarks are in order: Equation (6) effectively assumes that self-fext (from within the vectored subsystem) has been pre-compensated at the transmitter. External (often called alien) FEXT, from the remaining loops in the binder, is accounted for in R nn (f) (the p FEXT (f)g FEXT (f)g FEXT(f) term). Self-NEXT at the receiver can be mitigated by employing echo cancellation techniques, which essentially amount to subtracting self-next interference to a given loop from other loops in the coordinated subsystem, taking into account the associated frequency-dependent coupling factor. If echo cancellation is employed at the receiver, then there is only alien NEXT, if any. If upstream-downstream Frequency Division Duplex (FDD) is further employed, then alien NEXT is effectively suppressed as well. In this case, only alien FEXT remains. In non-fdd systems, however, alien NEXT is the performance-limiting factor, for FEXT is usually much lower than NEXT, even for relatively short loops (one significant exception is very short loops, under 1 meters, wherein FEXT looks much like NEXT, for obvious reasons). Because interference is generally correlated (R nn (f) in Equation (6) is not diagonal), the capacity in Equation (6) implicitly assumes that the coordinated system s receiver employs multiuser detection. Capacity in Equation (4) depends on the particular configuration of coordinated loops and interferers in the binder. Even under the simplifying assumptions leading to Equation (6), capacity depends not only on the number, but also on the particular configuration of interferers, through the coupling coefficients in G NEXT (f) and G FEXT (f). For this reason, we are interested in assessing the capacity distribution for a given number of FEXT interferers, as is appropriate for echo-cancelled, FDD, transmit precompensated coordinated subsystems of order p. We are interested in measuring the per-loop capacity as a function of p, and L FEXT. The per-loop capacity is the MIMO capacity of the coordinated subsystem divided by p. Furthermore, in the case of non-fdd systems, we are interested in the 5

7 distribution of C/p as a function of p, L NEXT, and L FEXT. This will allow us to assess the capacity benefit afforded by vectoring, i.e., the impact of coordinated transmission on the per-loop capacity as a function of the size of the coordinated subsystem and the number, type, and configuration of disturbers. For each p, L NEXT, and L FEXT, we will thus obtain a capacity distribution. This distribution can be summarized by means of a few statistics: minimum, mean, maximum, standard deviation, and outage capacity. We will compute those for a range of configurations of interest, and plot as a function of the parameters p, L NEXT, and L FEXT. Capacity also depends on the spectral mask, p(f). Depending on whether or not frequency planning is used (e.g., FDD and coarse frequency-dependent power-loading), p(f) may vary with f. We will thus consider two cases: one in which p(f) is set to -6 dbm/hz (1 9 W/Hz in absolute scale) for all f (this is a typical PSD level for DSL modems, and maintaining it across the 3 MHz bandwidth will yield slightly optimistic capacity results); but also use a standard FDD frequency plan (VDSL 998) and its extension to frequencies up to 3 MHz (extended VDSL 998). In the first case (constant p(f) at -6 dbm/hz), since we are interested in assessing theoretical bounds on performance, we will also ignore implementation issues like modulation loss, noise margin, and coding gain. In the second case (VDSL 998 / extended VDSL 998), we will incorporate these practical considerations. Pursuing both scenarios will allow us to gauge how far practical implementations will be from theoretical capacity. 2 Capacity Statistics via Full Combinatorial Calculation Assuming, as we did, that the insertion loss for all coordinated loops is identical, the clear-cut way of calculating the capacity distribution is to go over all possible configurations of (L NEXT, L FEXT ) alien interferers, calculate the capacity for each configuration using Equation (6), and then generate a histogram of the results. The difficulty is that certain combinations of p, L NEXT, L FEXT generate an immense number of possible configurations; e.g., for a total of N =28loops in the binder, p =4, and L NEXT = L FEXT =12, generates about 246 million possibilities, for each of which the integral in Equation (6) must be approximated. It is easy to get into situations wherein generating the capacity distribution for a given p, L NEXT, L FEXT takes about 1 week in a state-of-art PC. For this reason, we restrict ourselves 6

8 to looking at carefully selected combinations of p, L NEXT, L FEXT, which provide sufficient insights at a relatively moderate computational cost. To further reduce complexity, we assume that whenever p is even, quads (i.e., pairs of loops in the same quad) are chosen for vectoring, as is likely to be the case in practice. In Section 3 we will complement our results with Monte-Carlo sampling-based estimates of the capacity distribution, wherein loops are drawn in random from the binder. Monte-Carlo techniques yield an estimate of the capacity distribution, but allow us to consider cases that are essentially intractable using the enumerationbased approach. In order to keep this document manageable, we chose to present statistical summary results (minimum, mean, and maximum capacity; standard deviation of capacity) for various scenarios (p, L NEXT, L FEXT ) in this section. All these quantities are derived from capacity histograms. Histograms convey further information (e.g., allow the calculation of the of outage events), but since there are numerous such histograms, we preferred to defer them to Appendix A. 7

9 2.1 Capacity versus number of disturbers 7 x Minimum capacity for 75m loop p = 1 p = 2 p = 4 p = 6 p = 8 p = 14 p = 2 p = Number of disturbers L NEXT = L FEXT = L Figure 1: Minimum capacity per loop; 75m 7.5 x Maximum capacity for 75m loop p = 1 p = 2 p = 4 p = 6 p = 8 p = 14 p = 2 p = Number of disturbers L NEXT = L FEXT = L Figure 2: Maximum capacity per loop; 75m 8

10 7 x Average capacity for 75m loop p = 1 p = 2 p = 4 p = 6 p = 8 p = 14 p = 2 p = Number of disturbers L NEXT = L FEXT = L Figure 3: Average capacity per loop; 75m 7 x Standard deviation from average capacity for 75m loop p = 1 p = 2 p = 4 p = 6 p = 8 p = 14 p = 2 p = Number of disturbers L = L = L NEXT FEXT Figure 4: Standard deviation of capacity per loop; 75m 9

11 7 x Minimum capacity for 15m loop p = 1 p = 2 p = 4 p = 6 p = 8 p = 14 p = 2 p = Number of disturbers L NEXT = L FEXT = L Figure 5: Minimum capacity per loop; 15m 6.5 x Maximum capacity for 15m loop p = 1 p = 2 p = 4 p = 6 p = 8 p = 14 p = 2 p = Number of disturbers L = L = L NEXT FEXT Figure 6: Maximum capacity per loop; 15m 1

12 6.5 x Average capacity for 15m loop p = 1 p = 2 p = 4 p = 6 p = 8 p = 14 p = 2 p = Number of disturbers L NEXT = L FEXT = L Figure 7: Average capacity per loop; 15m 8 x Standard deviation from average capacity for 15m loop p = 1 p = 2 p = 4 p = 6 p = 8 p = 14 p = 2 p = Number of disturbers L = L = L NEXT FEXT Figure 8: Standard deviation of capacity per loop; 15m 11

13 2.2 Light vs. Full crosstalk: Capacity versus number of coordinated pairs 7 x 18 Minimum capacity m, Lnext = Lfext = 1 75m, Lnext = Lfext = 27 p 15m, Lnext = Lfext = 1 15m, Lnext = Lfext = 27 p Number p of coordinated pairs Figure 9: Minimum capacity per loop; FEXT and NEXT 8 x 18 Maximum capacity m, Lnext = Lfext = 1 75m, Lnext = Lfext = 27 p 15m, Lnext = Lfext = 1 15m, Lnext = Lfext = 27 p Number p of coordinated pairs Figure 1: Maximum capacity per loop; FEXT and NEXT 12

14 7 x 18 Average capacity m, Lnext = Lfext = 1 75m, Lnext = Lfext = 27 p 15m, Lnext = Lfext = 1 15m, Lnext = Lfext = 27 p Number p of coordinated pairs Figure 11: Average capacity per loop; FEXT and NEXT 8 x 17 7 Standard deviation from average capacity 75m, Lnext = Lfext = 1 75m, Lnext = Lfext = 27 p 15m, Lnext = Lfext = 1 15m, Lnext = Lfext = 27 p Number p of coordinated pairs Figure 12: Standard deviation of capacity per loop; FEXT and NEXT 13

15 7.5 x 18 Minimum capacity, FEXT only m, Lfext = 1 75m, Lfext = 27 p 15m, Lfext = 1 15m, Lfext = 27 p Number p of coordinated pairs Figure 13: Minimum capacity per loop; FEXT only 7.5 x 18 Maximum capacity, FEXT only m, Lfext = 1 75m, Lfext = 27 p 15m, Lfext = 1 15m, Lfext = 27 p Number p of coordinated pairs Figure 14: Maximum capacity per loop; FEXT only 14

16 7.5 x 18 Average capacity, FEXT only m, Lfext = 1 75m, Lfext = 27 p 15m, Lfext = 1 15m, Lfext = 27 p Number p of coordinated pairs Figure 15: Average capacity per loop; FEXT only 8 x 17 7 Standard deviation from average capacity, FEXT only 75m, Lfext = 1 75m, Lfext = 27 p 15m, Lfext = 1 15m, Lfext = 27 p Number p of coordinated pairs Figure 16: Standard deviation of capacity per loop; FEXT only 15

17 3 Capacity Statistics via Reduced Monte-Carlo Sampling In this section, we assess the capacity performance of multichannel DSL systems, using Monte-Carlo sampling to randomly select loops from the binder. This is a computationally simpler alternative to enumeration-based full-binder capacity calculations, presented in the previous section. We assume that a coordinated system with p channels is employed, along with L other alien interferers drawn from the same binder. Unlike the results presented in the previous section (which assumed a flat transmission power spectrum at -6 dbm/hz), in this section we employ two frequency band plans, and associated spectral masks. The first is VDSL 998 with downstream frequency bands as MHz, MHz, and 12-2 MHz; while the second plan is called extended VDSL L998 with frequency bands as MHz, MHz, and 12-3 MHz. In the first two frequency bands, the transmitter has -6 dbm/hz, while in the third one, the transmitter has -7 dbm/hz, as shown in figure 17, and figure 18. The noise is assumed to be AWGN with PSD of -14 dbm/hz. For the FEXT-limited case, we focus herein on loop lengths of 75m and 15m, for which France Telecom s FEXT channel measurements are reliable. As concluded in Deliverable D2.1, associated FEXT measurements for longer loop lengths are not reliable (especially at higher frequencies), due to the noise floor effect. For this reason, we defer the corresponding plots to Appendix B of this document. NEXT channels are essentially invariant to varying loop length, and the corresponding measurements are reliable all the way up to 6m. For the NEXTlimited case, we therefore include results for all loop lengths considered (75m, 15m, 3m, and 6m) in this section. Attaining Shannon capacity requires Gaussian signaling and long codes. In reality, there is an effective SINR loss due to the use of practical modulation schemes and the need to guarantee a certain noise margin. This SINR penalty is alleviated to a certain extent by the use of advanced coding techniques. The combined effect of modulation loss, coding gain, and noise margin, can be captured by replacing SINR by SINR/Γ, where the gap Γ := l mod + m noise g coding. Here, l mod is the modulation loss (9.8 db for QAM at BER of 1 7 ), m noise is the noise margin, and g coding is the coding gain. For coding gain and noise margin, we use three choices: [g coding, m noise ]= [3.8, 6], [6.8, 6], or [9.8, ] db, which result in a gap Γ =12, 9, and db, respectively, at BER 1 7. As before, the channel insertion loss, NEXT and FEXT come from the France Telecom R&D data. 16

18 5 VDSL downstream PSD PSD [dbm/hz] f [khz] Figure 17: VDSL 998 PSD mask. 5 VDSL + downstream PSD PSD [dbm/hz] f [khz] Figure 18: Extended VDSL 998 PSD mask. 17

19 3.1 Average Capacity We first present average total capacity results for all p coordinated loops. We begin with p =8, and L {1, 2, 4, 8, 12, 16}. Figures 19, 2, depict the average capacity from 1 independent runs for loop length of 75 m, and 15 m, respectively, where both self cross-talk and alien interference are due to FEXT. The three curves in the upper part of each figure follow the extended VDSL 998 frequency band, with difference choices for the coding gain and the noise margin, while the rest three curves, in the lower part, follow the VDSL 998 frequency band Average of 1 independent runs for 8 channels when line length is 75m [3.8 6] db [7.8 6] db [9.8 ] db [3.8 6] db [7.8 6] db [9.8 ] db Data rate (M) Number of alien noise (fext 75) Figure 19: Average capacity of 1 independent runs vs. the number of disturbers for 75m loop. The self cross-talk and alien interferences are all from FEXT. 18

20 2 18 Average of 1 independent runs for 8 channels when line length is 15m [3.8 6] db [7.8 6] db [9.8 ] db [3.8 6] db [7.8 6] db [9.8 ] db 16 Data rate (M) Number of alien noise (fext 15) Figure 2: Average capacity of 1 independent runs vs. the number of disturbers for 15m loop. The self cross-talk and alien interferences are all from FEXT. We now assume that p =12, and L {1, 2, 4, 8, 12, 16}. Figures 21, and 22, depict the average capacity of 1 independent runs for loop length of 75 m, and 15 m respectively, when the self cross-talk and alien interferences are all from FEXT. Again, the three curves in the upper part of each figure follow the extended VDSL 998 frequency band, with difference choices for the coding gain and the noise margin, while the rest three curves, in the lower part, follow the VDSL 998 frequency band. 19

21 Average of 1 independent runs for 12 channels when line length is 75m(coding gain=3.8 db, margin=6 db) VDSL 998 Extended VDSL Data rate (M) Number of alien noise (fext 75) Figure 21: Average capacity of 1 independent runs vs. the number of disturbers for 75m loop. The self cross-talk and alien interferences are all from FEXT. Average of 1 independent runs for 12 channels when line length is 15m(coding gain=3.8 db, margin=6 db) 22 2 VDSL 998 Extended VDSL Data rate (M) Number of alien noise (fext 15) Figure 22: Average capacity of 1 independent runs vs. the number of disturbers for 15m loop. The self cross-talk and alien interferences are all from FEXT. 2

22 3.2 Capacity CDFs We now present estimated Cumulative Distribution Functions (CDFs) for capacity. Again, the total capacity of all p coordinated loops is shown. Firstly, the case where p =8is considered. Figures 23, 24, and 25 depict capacity CDFs from 1 independent runs for different choices of coding gain and noise margin when the loop length is 75 m. The self cross-talk and alien interferences are all from FEXT. The frequency band follows VDSL 998. Figures 26, 27, and 28 contain the corresponding results for the extended VDSL 998 frequency band. 1 Capacity distribution of 8 pair systems(coding gain=3.8 db, margin=6 db).9.8 prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 8 Figure 23: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 3.8 db, margin 6 db. The loop length is 75 m. Self cross-talk and alien noise are from FEXT. The frequency band follows VDSL

23 1 Capacity distribution of 8 pair systems(coding gain=7.8 db, margin=6 db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 8 Figure 24: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 7.8 db, margin 6 db. The loop length is 75 m. Self cross-talk and alien noise are from FEXT. The frequency band follows VDSL Capacity distribution of 8 pair systems(coding gain=9.8 db, margin= db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 25: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 9.8 db, margin db. The loop length is 75 m. Self cross-talk and alien noise are from FEXT. The frequency band follows VDSL

24 1 Capacity distribution of 8 pair systems(coding gain=3.8 db, margin=6 db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 26: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 3.8 db, margin 6 db. The loop length is 75 m. Self cross-talk and alien noise are from FEXT. The frequency band follows extended VDSL Capacity distribution of 8 pair systems(coding gain=7.8 db, margin=6 db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 27: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 7.8 db, margin 6 db. The loop length is 75 m. Self cross-talk and alien noise are from FEXT. The frequency band follows extended VDSL

25 1 Capacity distribution of 8 pair systems(coding gain=9.8 db, margin= db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 28: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 9.8 db, margin db.the loop length is 75 m. Self cross-talk and alien noise are from FEXT. The frequency band follows extended VDSL 998 Figures 29, 3, and 31 depict the capacity CDF from 1 independent runs for different choices of coding gain and noise margin, when the loop length is 15 m. The self cross-talk and alien interferences are all from FEXT. The frequency band follows VDSL 998. Figures 32, 33, and 34 depict the corresponding results for the extended VDSL 998 frequency band. 24

26 1 Capacity distribution of 8 pair systems(coding gain=3.8 db, margin=6 db).9.8 prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 8 Figure 29: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 3.8 db, margin 6 db. The loop length is 15 m. Self cross-talk and alien noise are from FEXT. The frequency band follows VDSL Capacity distribution of 8 pair systems(coding gain=7.8 db, margin=6 db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 8 Figure 3: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 7.8 db, margin 6 db. The loop length is 15 m. Self cross-talk and alien noise are from FEXT. The frequency band follows VDSL

27 1 Capacity distribution of 8 pair systems(coding gain=9.8 db, margin= db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 8 Figure 31: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 9.8 db, margin db. The loop length is 15 m. Self cross-talk and alien noise are from FEXT. The frequency band follows VDSL Capacity distribution of 8 pair systems(coding gain=3.8 db, margin=6 db).9.8 prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 32: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 3.8 db, margin 6 db. The loop length is 15 m. Self cross-talk and alien noise are from FEXT. The frequency band follows extended VDSL

28 1 Capacity distribution of 8 pair systems(coding gain=7.8 db, margin=6 db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 33: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 7.8 db, margin 6 db. The loop length is 15 m. Self cross-talk and alien noise are from FEXT. The frequency band follows extended VDSL Capacity distribution of 8 pair systems(coding gain=9.8 db, margin= db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 34: Capacity distribution of 8 pair systems from 1 independent runs for coding gain 9.8 db, margin db. The loop length is 15 m. Self cross-talk and alien noise are from FEXT. The frequency band follows extended VDSL

29 Now the case where p =12is considered. Figures 35, 36 depict the capacity CDF for the frequency band of VDSL 998, and extended VDSL 998, respectively, from 1 independent runs when the loop length is 75 m. Here the coding gain is 3.8 db and noise margin is 6 db. The self cross-talk and alien interferences are all from FEXT. 1 Capacity distribution of 12 pair systems(coding gain=3.8 db, margin=6 db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 35: Capacity distribution of 12 pair systems from 1 independent runs for coding gain 3.8 db, margin 6 db. The loop length is 75 m. Self cross-talk and alien noise are from FEXT. The frequency band follows VDSL

30 1 Capacity distribution of 12 pair systems(coding gain=3.8 db, margin=6 db).9.8 prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 36: Capacity distribution of 12 pair systems from 1 independent runs for coding gain 3.8 db, margin 6 db. The loop length is 75 m. Self cross-talk and alien noise are from FEXT. The frequency band follows Extended VDSL 998 Figures 37, 38 depict the capacity CDF for the frequency band of VDSL 998, and extended VDSL 998, respectively, from 1 independent runs when the loop length is 15 m. Here the coding gain is 3.8 db and noise margin is 6 db. The self cross-talk and alien interferences are all from FEXT. 29

31 1 Capacity distribution of 12 pair systems(coding gain=3.8 db, margin=6 db).9.8 prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 37: Capacity distribution of 12 pair systems from 1 independent runs for coding gain 3.8 db, margin 6 db. The loop length is 15 m. Self cross-talk and alien noise are from FEXT. The frequency band follows VDSL Capacity distribution of 12 pair systems(coding gain=3.8 db, margin=6 db) prob(rate<x) L=1 L=2 L=4 L=8 L=12 L= Total rate () x 1 9 Figure 38: Capacity distribution of 12 pair systems from 1 independent runs for coding gain 3.8 db, margin 6 db. The loop length is 15 m. Self cross-talk and alien noise are from FEXT. The frequency band follows Extended VDSL 998 3

32 4 Conclusions & Coordination Benefit Assessment Our conclusions can be summarized as follows: Rates in the order of several hundred M per loop are attainable over very short DSL loops. Sum rates in the order of several G are attainable over a 28-loop binder, even if practical limitations, like modulation loss, are taken into account. Coordinated transmission can boost the per-loop capacity by as much as 8% when a significant fraction of the loops in the binder are coordinated. Coordinating a few loops can still afford a 2-3% increase in per-line capacity, but only if most of the remaining loops in the binder are silent. Even though a 2% boost in per-loop capacity may not appear impressive, it yields one more line for every five lines. This can be important in certain situations. Furthermore, Coordination appears to improve the ratio of minimum capacity to mean capacity. This can be quickly seen from the standard deviation plots in Section 2, and it is important from the operator s perspective as it limits outage. 31

33 5 Appendix A: Capacity Histograms and Moments via Full Combinatorial Calculations 32

34 5.1 FEXT plus NEXT.12.1 Capacity per line histogram of 75m loop for p=1 and Lnext=2, Lfext=2 Min = 2.63E+8 Mean = 3.96E+8 Max = 5.81E+8 Std = 5.21E+7 Min/Mean = x 1 8 Figure 39: Capacity histogram of 75m loop for uncoordinated transmission and 2 disturbers Capacity per line histogram of 15m loop for p=1 and Lnext=2, Lfext=2 Min = 1.88E+8 Mean = 3.16E+8 Max = 5.14E+8 Std = 5.8E+7 Min/Mean = x 1 8 Figure 4: Capacity histogram of 15m loop for uncoordinated transmission and 2 disturbers 33

35 .12.1 Capacity per line histogram of 75m loop for p=1 and Lnext=3, Lfext=3 Min = 2.55E+8 Mean = 3.69E+8 Max = 5.61E+8 Std = 4.3E+7 Min/Mean = x 1 8 Figure 41: Capacity histogram of 75m loop for uncoordinated transmission and 3 disturbers.12.1 Capacity per line histogram of 15m loop for p=1 and Lnext=3, Lfext=3 Min = 1.79E+8 Mean = 2.87E+8 Max = 4.92E+8 Std = 4.82E+7 Min/Mean = x 1 8 Figure 42: Capacity histogram of 15m loop for uncoordinated transmission and 3 disturbers 34

36 Capacity per line histogram of 75m loop for p=1 and Lnext=25, Lfext=25 Min = 2.25E+8 Mean = 2.57E+8 Max = 3.31E+8 Std = 1.92E+7 Min/Mean = x 1 8 Figure 43: Capacity histogram of 75m loop for uncoordinated transmission and 25 disturbers Capacity per line histogram of 15m loop for p=1 and Lnext=25, Lfext=25 Min = 1.48E+8 Mean = 1.73E+8 Max = 2.56E+8 Std = 1.72E+7 Min/Mean = x 1 8 Figure 44: Capacity histogram of 15m loop for uncoordinated transmission and 25 disturbers 35

37 Capacity per line histogram of 75m loop for p=2 and Lnext=2, Lfext=2 Min = 3.13E+8 Mean = 4.18E+8 Max = 5.81E+8 Std = 4.65E+7 Min/Mean = x 1 8 Figure 45: Capacity per line histogram of 75m loop for 2 coordinated pairs and 2 disturbers Capacity per line histogram of 15m loop for p=2 and Lnext=2, Lfext=2 Min = 2.34E+8 Mean = 3.45E+8 Max = 5.9E+8 Std = 5.14E+7 Min/Mean = x 1 8 Figure 46: Capacity per line histogram of 15m loop for 2 coordinated pairs and 2 disturbers 36

38 .12.1 Capacity per line histogram of 75m loop for p=2 and Lnext=3, Lfext=3 Min = 2.96E+8 Mean = 3.87E+8 Max = 5.58E+8 Std = 3.91E+7 Min/Mean = x 1 8 Figure 47: Capacity per line histogram of 75m loop for 2 coordinated pairs and 3 disturbers Capacity per line histogram of 15m loop for p=2 and Lnext=3, Lfext=3 Min = 2.12E+8 Mean = 3.1E+8 Max = 4.85E+8 Std = 4.42E+7 Min/Mean = x 1 8 Figure 48: Capacity per line histogram of 15m loop for 2 coordinated pairs and 3 disturbers 37

39 .12.1 Capacity per line histogram of 75m loop for p=2 and Lnext=24, Lfext=24 Min = 2.45E+8 Mean = 2.7E+8 Max = 3.42E+8 Std = 1.87E+7 Min/Mean = x 1 8 Figure 49: Capacity per line histogram of 75m loop for 2 coordinated pairs and 24 disturbers Capacity per line histogram of 15m loop for p=2 and Lnext=24, Lfext=24 Min = 1.59E+8 Mean = 1.88E+8 Max = 2.65E+8 Std = 2.3E+7 Min/Mean = x 1 8 Figure 5: Capacity per line histogram of 15m loop for 2 coordinated pairs and 24 disturbers 38

40 Capacity per line histogram of 75m loop for p=4 and Lnext=1, Lfext=1 Min = 5.27E+8 Mean = 5.8E+8 Max = 6.58E+8 Std = 2.25E+7 Min/Mean = x 1 8 Figure 51: Capacity per line histogram of 75m loop for 4 coordinated pairs and 1 disturber Capacity per line histogram of 15m loop for p=4 and Lnext=1, Lfext=1 Min = 4.55E+8 Mean = 5.8E+8 Max = 5.85E+8 Std = 2.41E+7 Min/Mean = x 1 8 Figure 52: Capacity per line histogram of 15m loop for 4 coordinated pairs and 1 disturber 39

41 .12.1 Capacity per line histogram of 75m loop for p=4 and Lnext=2, Lfext=2 Min = 3.35E+8 Mean = 4.48E+8 Max = 5.96E+8 Std = 3.35E+7 Min/Mean = x 1 8 Figure 53: Capacity per line histogram of 75m loop for 4 coordinated pairs and 2 disturbers Capacity per line histogram of 15m loop for p=4 and Lnext=2, Lfext=2 Min = 2.82E+8 Mean = 3.85E+8 Max = 5.29E+8 Std = 3.52E+7 Min/Mean = x 1 8 Figure 54: Capacity per line histogram of 15m loop for 4 coordinated pairs and 2 disturbers 4

42 .12.1 Capacity per line histogram of 75m loop for p=4 and Lnext=3, Lfext=3 Min = 3.15E+8 Mean = 4.2E+8 Max = 5.38E+8 Std = 2.8E+7 Min/Mean = x 1 8 Figure 55: Capacity per line histogram of 75m loop for 4 coordinated pairs and 3 disturbers Capacity per line histogram of 15m loop for p=4 and Lnext=3, Lfext=3 Min = 2.47E+8 Mean = 3.32E+8 Max = 4.62E+8 Std = 3.8E+7 Min/Mean = x 1 8 Figure 56: Capacity per line histogram of 15m loop for 4 coordinated pairs and 3 disturbers 41

43 .12.1 Capacity per line histogram of 75m loop for p=4 and Lnext=23, Lfext=23 Min = 2.52E+8 Mean = 2.74E+8 Max = 3.12E+8 Std = 1.26E+7 Min/Mean = x 1 8 Figure 57: Capacity per line histogram of 75m loop for 4 coordinated pairs and 23 disturbers.12.1 Capacity per line histogram of 15m loop for p=4 and Lnext=23, Lfext=23 Min = 1.7E+8 Mean = 1.92E+8 Max = 2.39E+8 Std = 1.39E+7 Min/Mean = x 1 8 Figure 58: Capacity per line histogram of 15m loop for 4 coordinated pairs and 23 disturbers 42

44 .12.1 Capacity per line histogram of 75m loop for p=6 and Lnext=1, Lfext=1 Min = 5.93E+8 Mean = 6.23E+8 Max = 6.74E+8 Std = 1.23E+7 Min/Mean = x 1 8 Figure 59: Capacity per line histogram of 75m loop for 6 coordinated pairs and 1 disturber Capacity per line histogram of 15m loop for p=6 and Lnext=1, Lfext=1 Min = 5.19E+8 Mean = 5.47E+8 Max = 6.1E+8 Std = 1.34E+7 Min/Mean = x 1 8 Figure 6: Capacity per line histogram of 15m loop for 6 coordinated pairs and 1 disturber 43

45 .12.1 Capacity per line histogram of 75m loop for p=6 and Lnext=2, Lfext=2 Min = 4.57E+8 Mean = 5.16E+8 Max = 6.14E+8 Std = 1.82E+7 Min/Mean = x 1 8 Figure 61: Capacity per line histogram of 75m loop for 6 coordinated pairs and 2 disturbers.12.1 Capacity per line histogram of 15m loop for p=6 and Lnext=2, Lfext=2 Min = 3.93E+8 Mean = 4.47E+8 Max = 5.45E+8 Std = 1.95E+7 Min/Mean = x 1 8 Figure 62: Capacity per line histogram of 15m loop for 6 coordinated pairs and 2 disturbers 44

46 Capacity per line histogram of 75m loop for p=6 and Lnext=21, Lfext=21 Min = 2.62E+8 Mean = 2.8E+8 Max = 3.17E+8 Std = 9.92E+6 Min/Mean = x 1 8 Figure 63: Capacity per line histogram of 75m loop for 6 coordinated pairs and 21 disturbers.12.1 Capacity per line histogram of 15m loop for p=6 and Lnext=21, Lfext=21 Min = 1.78E+8 Mean = 1.98E+8 Max = 2.41E+8 Std = 1.11E+7 Min/Mean = x 1 8 Figure 64: Capacity per line histogram of 15m loop for 6 coordinated pairs and 21 disturbers 45

47 Capacity per line histogram of 75m loop for p=8 and Lnext=1, Lfext=1 Min = 6.28E+8 Mean = 6.47E+8 Max = 6.85E+8 Std = 7.95E+6 Min/Mean = x 1 8 Figure 65: Capacity per line histogram of 75m loop for 8 coordinated pairs and 1 disturber.12.1 Capacity per line histogram of 15m loop for p=8 and Lnext=1, Lfext=1 Min = 5.51E+8 Mean = 5.7E+8 Max = 6.9E+8 Std = 8.78E+6 Min/Mean = x 1 8 Figure 66: Capacity per line histogram of 15m loop for 8 coordinated pairs and 1 disturber 46

48 Capacity per line histogram of 75m loop for p=8 and Lnext=19, Lfext=19 Min = 2.68E+8 Mean = 2.87E+8 Max = 3.2E+8 Std = 8.32E+6 Min/Mean = x 1 8 Figure 67: Capacity per line histogram of 75m loop for 8 coordinated pairs and 19 disturbers Capacity per line histogram of 15m loop for p=8 and Lnext=19, Lfext=19 Min = 1.85E+8 Mean = 2.6E+8 Max = 2.46E+8 Std = 9.58E+6 Min/Mean = x 1 8 Figure 68: Capacity per line histogram of 15m loop for 8 coordinated pairs and 19 disturbers 47

49 Capacity per line histogram of 75m loop for p=14 and Lnext=1, Lfext=1 Min = 6.75E+8 Mean = 6.81E+8 Max = 7.2E+8 Std = 3.43E+6 Min/Mean = x 1 8 Figure 69: Capacity per line histogram of 75m loop for 14 coordinated pairs and 1 disturber Capacity per line histogram of 15m loop for p=14 and Lnext=1, Lfext=1 Min = 5.94E+8 Mean = 6.2E+8 Max = 6.22E+8 Std = 3.87E+6 Min/Mean = x 1 8 Figure 7: Capacity per line histogram of 15m loop for 14 coordinated pairs and 1 disturber 48

50 .12.1 Capacity per line histogram of 75m loop for p=14 and Lnext=13, Lfext=13 Min = 3.1E+8 Mean = 3.19E+8 Max = 3.49E+8 Std = 6.5E+6 Min/Mean = x 1 8 Figure 71: Capacity per line histogram of 75m loop for 14 coordinated pairs and 13 disturbers Capacity per line histogram of 15m loop for p=14 and Lnext=13, Lfext=13 Min = 2.25E+8 Mean = 2.46E+8 Max = 2.84E+8 Std = 7.86E+6 Min/Mean = x 1 8 Figure 72: Capacity per line histogram of 15m loop for 14 coordinated pairs and 13 disturbers 49

51 Capacity per line histogram of 75m loop for p=2 and Lnext=1, Lfext=1 Min = 6.94E+8 Mean = 6.97E+8 Max = 7.7E+8 Std = 2.7E+6 Min/Mean = x 1 8 Figure 73: Capacity per line histogram of 75m loop for 2 coordinated pairs and 1 disturber Capacity per line histogram of 15m loop for p=2 and Lnext=1, Lfext=1 Min = 6.12E+8 Mean = 6.16E+8 Max = 6.28E+8 Std = 2.35E+6 Min/Mean = x 1 8 Figure 74: Capacity per line histogram of 15m loop for 2 coordinated pairs and 1 disturber 5

52 Capacity per line histogram of 75m loop for p=2 and Lnext=2, Lfext=2 Min = 6.5E+8 Mean = 6.56E+8 Max = 6.76E+8 Std = 3.2E+6 Min/Mean = x 1 8 Figure 75: Capacity per line histogram of 75m loop for 2 coordinated pairs and 2 disturbers Capacity per line histogram of 15m loop for p=2 and Lnext=2, Lfext=2 Min = 5.7E+8 Mean = 5.77E+8 Max = 6.E+8 Std = 3.41E+6 Min/Mean = x 1 8 Figure 76: Capacity per line histogram of 15m loop for 2 coordinated pairs and 2 disturbers 51

53 Capacity per line histogram of 75m loop for p=2 and Lnext=3, Lfext=3 Min = 6.7E+8 Mean = 6.15E+8 Max = 6.37E+8 Std = 3.89E+6 Min/Mean = x 1 8 Figure 77: Capacity per line histogram of 75m loop for 2 coordinated pairs and 3 disturbers Capacity per line histogram of 15m loop for p=2 and Lnext=3, Lfext=3 Min = 5.28E+8 Mean = 5.39E+8 Max = 5.63E+8 Std = 4.35E+6 Min/Mean = x 1 8 Figure 78: Capacity per line histogram of 15m loop for 2 coordinated pairs and 3 disturbers 52

54 Capacity per line histogram of 75m loop for p=2 and Lnext=6, Lfext=6 Min = 4.85E+8 Mean = 4.98E+8 Max = 5.24E+8 Std = 5.89E+6 Min/Mean = x 1 8 Figure 79: Capacity per line histogram of 75m loop for 2 coordinated pairs and 6 disturbers Capacity per line histogram of 15m loop for p=2 and Lnext=6, Lfext=6 Min = 4.12E+8 Mean = 4.29E+8 Max = 4.55E+8 Std = 6.49E+6 Min/Mean = x 1 8 Figure 8: Capacity per line histogram of 15m loop for 2 coordinated pairs and 6 disturbers 53

55 .8.7 Capacity per line histogram of 75m loop for p=2 and Lnext=7, Lfext=7 Min = 4.47E+8 Mean = 4.62E+8 Max = 4.87E+8 Std = 6.53E+6 Min/Mean = x 1 8 Figure 81: Capacity per line histogram of 75m loop for 2 coordinated pairs and 7 disturbers Capacity per line histogram of 15m loop for p=2 and Lnext=7, Lfext=7 Min = 3.78E+8 Mean = 3.94E+8 Max = 4.21E+8 Std = 7.15E+6 Min/Mean = x 1 8 Figure 82: Capacity per line histogram of 15m loop for 2 coordinated pairs and 7 disturbers 54

56 Capacity per line histogram of 75m loop for p=22 and Lnext=1, Lfext=1 Min = 6.98E+8 Mean = 7.E+8 Max = 7.8E+8 Std = 1.82E+6 Min/Mean = x 1 8 Figure 83: Capacity per line histogram of 75m loop for 22 coordinated pairs and 1 disturber.12.1 Capacity per line histogram of 15m loop for p=22 and Lnext=1, Lfext=1 Min = 6.16E+8 Mean = 6.19E+8 Max = 6.28E+8 Std = 2.7E+6 Min/Mean = x 1 8 Figure 84: Capacity per line histogram of 15m loop for 22 coordinated pairs and 1 disturber 55

57 Capacity per line histogram of 75m loop for p=22 and Lnext=2, Lfext=2 Min = 6.58E+8 Mean = 6.62E+8 Max = 6.77E+8 Std = 2.72E+6 Min/Mean = x 1 8 Figure 85: Capacity per line histogram of 75m loop for 22 coordinated pairs and 2 disturbers Capacity per line histogram of 15m loop for p=22 and Lnext=2, Lfext=2 Min = 5.77E+8 Mean = 5.83E+8 Max = 6.1E+8 Std = 3.8E+6 Min/Mean = x 1 8 Figure 86: Capacity per line histogram of 15m loop for 22 coordinated pairs and 2 disturbers 56

58 Capacity per line histogram of 75m loop for p=22 and Lnext=3, Lfext=3 Min = 6.18E+8 Mean = 6.25E+8 Max = 6.41E+8 Std = 3.51E+6 Min/Mean = x 1 8 Figure 87: Capacity per line histogram of 75m loop for 22 coordinated pairs and 3 disturbers.12.1 Capacity per line histogram of 15m loop for p=22 and Lnext=3, Lfext=3 Min = 5.39E+8 Mean = 5.48E+8 Max = 5.67E+8 Std = 3.95E+6 Min/Mean = x 1 8 Figure 88: Capacity per line histogram of 15m loop for 22 coordinated pairs and 3 disturbers 57

59 .12.1 Capacity per line histogram of 75m loop for p=22 and Lnext=4, Lfext=4 Min = 5.8E+8 Mean = 5.88E+8 Max = 6.5E+8 Std = 4.26E+6 Min/Mean = x 1 8 Figure 89: Capacity per line histogram of 75m loop for 22 coordinated pairs and 4 disturbers Capacity per line histogram of 15m loop for p=22 and Lnext=4, Lfext=4 Min = 5.3E+8 Mean = 5.13E+8 Max = 5.32E+8 Std = 4.77E+6 Min/Mean = x 1 8 Figure 9: Capacity per line histogram of 15m loop for 22 coordinated pairs and 4 disturbers 58

60 Capacity per line histogram of 75m loop for p=22 and Lnext=5, Lfext=5 Min = 5.43E+8 Mean = 5.52E+8 Max = 5.7E+8 Std = 5.E+6 Min/Mean = x 1 8 Figure 91: Capacity per line histogram of 75m loop for 22 coordinated pairs and 5 disturbers Capacity per line histogram of 15m loop for p=22 and Lnext=5, Lfext=5 Min = 4.68E+8 Mean = 4.79E+8 Max = 4.98E+8 Std = 5.57E+6 Min/Mean = x 1 8 Figure 92: Capacity per line histogram of 15m loop for 22 coordinated pairs and 5 disturbers 59

61 5.2 FEXT only.8.7 Capacity per line histogram of 75m loop for p=1 and Lnext=, Lfext=2 Min = 3.26E+8 Mean = 4.78E+8 Max = 6.42E+8 Std = 5.99E+7 Min/Mean = x 1 8 Figure 93: Capacity histogram of 75m loop for uncoordinated transmission and 2 disturbers.7.6 Capacity per line histogram of 15m loop for p=1 and Lnext=, Lfext=2 Min = 2.87E+8 Mean = 4.41E+8 Max = 5.95E+8 Std = 6.2E+7 Min/Mean = x 1 8 Figure 94: Capacity histogram of 15m loop for uncoordinated transmission and 2 disturbers 6

62 Capacity per line histogram of 75m loop for p=1 and Lnext=, Lfext=25 Min = 2.99E+8 Mean = 3.33E+8 Max = 4.36E+8 Std = 2.18E+7 Min/Mean = x 1 8 Figure 95: Capacity histogram of 75m loop for uncoordinated transmission and 25 disturbers Capacity per line histogram of 15m loop for p=1 and Lnext=, Lfext=25 Min = 2.57E+8 Mean = 2.91E+8 Max = 4.5E+8 Std = 2.33E+7 Min/Mean = x 1 8 Figure 96: Capacity histogram of 15m loop for uncoordinated transmission and 25 disturbers 61

The Impact of Upstream Power Back-Off on VDSL Frequency Planning. Abstract

The Impact of Upstream Power Back-Off on VDSL Frequency Planning. Abstract T1E1.4/99-414 Project: Title: Source: VDSL The Impact of Upstream Power Back-Off on VDSL Frequency Planning Presenter: Krista S. Jacobsen Author: K.S. Jacobsen Texas Instruments 243 Samaritan Drive San

More information

PERFORMANCE EVALUATION OF A GIGABIT DSL MODEM USING SUPER ORTHOGONAL COMPLETE COMPLEMENTARY CODES UNDER PRACTICAL CROSSTALK CONDITIONS

PERFORMANCE EVALUATION OF A GIGABIT DSL MODEM USING SUPER ORTHOGONAL COMPLETE COMPLEMENTARY CODES UNDER PRACTICAL CROSSTALK CONDITIONS 144 SOUTH AFRICAN INSTITUTE OF ELECTRICAL ENGINEERS Vol.108 4) December 2017 PERFORMANCE EVALUATION OF A GIGABIT DSL MODEM USING SUPER ORTHOGONAL COMPLETE COMPLEMENTARY CODES UNDER PRACTICAL CROSSTALK

More information

CHAPTER 4 ADAPTIVE BIT-LOADING WITH AWGN FOR PLAIN LINE AND LINE WITH BRIDGE TAPS

CHAPTER 4 ADAPTIVE BIT-LOADING WITH AWGN FOR PLAIN LINE AND LINE WITH BRIDGE TAPS CHAPTER 4 ADAPTIVE BIT-LOADING WITH AWGN FOR PLAIN LINE AND LINE WITH BRIDGE TAPS 4.1 Introduction The transfer function for power line channel was obtained for defined test loops in the previous chapter.

More information

Optimal Transmit Spectra for Communication on Digital Subscriber Lines

Optimal Transmit Spectra for Communication on Digital Subscriber Lines Optimal Transmit Spectra for Communication on Digital Subscriber Lines Rohit V. Gaikwad and Richard G. Baraniuk æ Department of Electrical and Computer Engineering Rice University Houston, Texas, 77005

More information

TITLE: Reducing ADC Resolution by Using Analog Band-pass Filters in FDD based VDSL

TITLE: Reducing ADC Resolution by Using Analog Band-pass Filters in FDD based VDSL COMMITTEE T1-TELECOMUNICATIONS Working Group T1E1.4 (DSL Access) Ottawa, Canada, June 7-11, 1999 T1E1.4/99-334 TITLE: Reducing ADC Resolution by Using Analog Band-pass Filters in FDD based VDSL SOURCE:

More information

Crosstalk Models for Short VDSL2 Lines from Measured 30 MHz Data. E. Karipidis, N. Sidiropoulos, A. Leshem, Li Youming, R. Tarafi, and M.

Crosstalk Models for Short VDSL2 Lines from Measured 30 MHz Data. E. Karipidis, N. Sidiropoulos, A. Leshem, Li Youming, R. Tarafi, and M. 1 Crosstalk Models for Short VDSL2 Lines from Measured 30 MHz Data E. Karipidis, N. Sidiropoulos, A. Leshem, Li Youming, R. Tarafi, and M. Ouzzif Abstract In recent years, there is growing interest in

More information

Power back-off for multiple target bit rates. Authors: Frank Sjöberg, Rickard Nilsson, Sarah Kate Wilson, Daniel Bengtsson, Mikael Isaksson

Power back-off for multiple target bit rates. Authors: Frank Sjöberg, Rickard Nilsson, Sarah Kate Wilson, Daniel Bengtsson, Mikael Isaksson T1E1.4/98-371 1(8) Standards Project: T1E1.4 VDSL Title : Power bac-off for multiple target bit rates Source : Telia Research AB Contact: Göran Övist Telia Research AB, Aurorum 6, SE-977 75 Luleå, Sweden

More information

Channel Characteristics and Impairments

Channel Characteristics and Impairments ELEX 3525 : Data Communications 2013 Winter Session Channel Characteristics and Impairments is lecture describes some of the most common channel characteristics and impairments. A er this lecture you should

More information

Course 2: Channels 1 1

Course 2: Channels 1 1 Course 2: Channels 1 1 "You see, wire telegraph is a kind of a very, very long cat. You pull his tail in New York and his head is meowing in Los Angeles. Do you understand this? And radio operates exactly

More information

Contract No U-BROAD D2.1 Statistical Characterization and Modelling of the Copper Physical Channel

Contract No U-BROAD D2.1 Statistical Characterization and Modelling of the Copper Physical Channel Contract No. 506790 - U-BROAD D2.1 Statistical Characterization and Modelling of the Copper Physical Channel Prepared by: Telecommunication System Institute (TSI) - Greece Bar Ilan Univesity (BIU) - Israel

More information

COMMITTEE T1 TELECOMMUNICATIONS. Plano, Texas; 2 December 1998 CONTRIBUTION

COMMITTEE T1 TELECOMMUNICATIONS. Plano, Texas; 2 December 1998 CONTRIBUTION COMMITTEE T TELECOMMUNICATIONS Working Group TE.4 Plano, Texas; 2 December 998 TE.4/98-36 CONTRIBUTION TITLE: Equivalent Loss and Equivalent Noise: Figures of Merit for use in Deployment and Spectrum Management

More information

ACIF C559:2003 PART 2 SPECTRAL COMPATIBILITY DETERMINATION PROCESS

ACIF C559:2003 PART 2 SPECTRAL COMPATIBILITY DETERMINATION PROCESS ACIF C559:2003 PART 2 SPECTRAL COMPATIBILITY DETERMINATION PROCESS CONTENTS 1. INTRODUCTION AND OVERVIEW 1 1.1 Introduction 1 1.2 Overview 1 2. ACIF SPECTRAL COMPATIBILITY DETERMINATION PROCESS 3 2.1

More information

Time-Domain MIMO Precoding for FEXT Cancellation in DSL Systems

Time-Domain MIMO Precoding for FEXT Cancellation in DSL Systems Time-Domain MIMO Precoding for FEXT Cancellation in DSL Systems Fabian A. Mruck, Clemens Stierstorfer, Johannes B. Huber Lehrstuhl für Informationsübertragung Friedrich-Alexander-Universität Erlangen-Nürnberg

More information

Survey of Power Control Schemes for LTE Uplink E Tejaswi, Suresh B

Survey of Power Control Schemes for LTE Uplink E Tejaswi, Suresh B Survey of Power Control Schemes for LTE Uplink E Tejaswi, Suresh B Department of Electronics and Communication Engineering K L University, Guntur, India Abstract In multi user environment number of users

More information

Multiple Input Multiple Output (MIMO) Operation Principles

Multiple Input Multiple Output (MIMO) Operation Principles Afriyie Abraham Kwabena Multiple Input Multiple Output (MIMO) Operation Principles Helsinki Metropolia University of Applied Sciences Bachlor of Engineering Information Technology Thesis June 0 Abstract

More information

Performance Evaluation of the VBLAST Algorithm in W-CDMA Systems

Performance Evaluation of the VBLAST Algorithm in W-CDMA Systems erformance Evaluation of the VBLAST Algorithm in W-CDMA Systems Dragan Samardzija, eter Wolniansky, Jonathan Ling Wireless Research Laboratory, Bell Labs, Lucent Technologies, 79 Holmdel-Keyport Road,

More information

CHAPTER 3 ADAPTIVE MODULATION TECHNIQUE WITH CFO CORRECTION FOR OFDM SYSTEMS

CHAPTER 3 ADAPTIVE MODULATION TECHNIQUE WITH CFO CORRECTION FOR OFDM SYSTEMS 44 CHAPTER 3 ADAPTIVE MODULATION TECHNIQUE WITH CFO CORRECTION FOR OFDM SYSTEMS 3.1 INTRODUCTION A unique feature of the OFDM communication scheme is that, due to the IFFT at the transmitter and the FFT

More information

On Using Channel Prediction in Adaptive Beamforming Systems

On Using Channel Prediction in Adaptive Beamforming Systems On Using Channel rediction in Adaptive Beamforming Systems T. R. Ramya and Srikrishna Bhashyam Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai - 600 036, India. Email:

More information

Arbitrary Partial FEXT Cancellation in Adaptive Precoding for Multichannel Downstream VDSL

Arbitrary Partial FEXT Cancellation in Adaptive Precoding for Multichannel Downstream VDSL 5754 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 60, NO. 11, NOVEMBER 2012 Arbitrary Partial FEXT Cancellation in Adaptive Precoding for Multichannel Downstream VDSL Ido Binyamini, Itsik Bergel, Senior

More information

Signal Processing for Gigabit-Rate Wireline Communications

Signal Processing for Gigabit-Rate Wireline Communications 1 Signal Processing for Gigabit-Rate Wireline Communications S. M. Zafaruddin, Member, IEEE, Itsik Bergel, Senior Member, IEEE, Amir Leshem, Senior Member, IEEE Faculty of Engineering, Bar-Ilan University,

More information

Signal Processing for Gigabit-Rate Wireline Communications

Signal Processing for Gigabit-Rate Wireline Communications 1 Signal Processing for Gigabit-Rate Wireline Communications S. M. Zafaruddin, Member, IEEE, Itsik Bergel, Senior Member, IEEE, Amir Leshem, Senior Member, IEEE Faculty of Engineering, Bar-Ilan University,

More information

EFM Capabilities with Plan 998

EFM Capabilities with Plan 998 EFM Capabilities with Plan 998 Performance analysis of the standard VDSL technology using spectral plan 998 Vladimir Oksman Broadcom Corporation October 2001 Slide 1 Supporters Sabit Say, Todd Pett: Next

More information

Cohere Technologies Performance evaluation of OTFS waveform in single user scenarios Agenda item: Document for: Discussion

Cohere Technologies Performance evaluation of OTFS waveform in single user scenarios Agenda item: Document for: Discussion 1 TSG RA WG1 Meeting #86 R1-167593 Gothenburg, Sweden, August 22-26, 2016 Source: Cohere Technologies Title: Performance evaluation of OTFS waveform in single user scenarios Agenda item: 8.1.2.1 Document

More information

EELE 6333: Wireless Commuications

EELE 6333: Wireless Commuications EELE 6333: Wireless Commuications Chapter # 4 : Capacity of Wireless Channels Spring, 2012/2013 EELE 6333: Wireless Commuications - Ch.4 Dr. Musbah Shaat 1 / 18 Outline 1 Capacity in AWGN 2 Capacity of

More information

An HARQ scheme with antenna switching for V-BLAST system

An HARQ scheme with antenna switching for V-BLAST system An HARQ scheme with antenna switching for V-BLAST system Bonghoe Kim* and Donghee Shim* *Standardization & System Research Gr., Mobile Communication Technology Research LAB., LG Electronics Inc., 533,

More information

Adaptive Modulation, Adaptive Coding, and Power Control for Fixed Cellular Broadband Wireless Systems: Some New Insights 1

Adaptive Modulation, Adaptive Coding, and Power Control for Fixed Cellular Broadband Wireless Systems: Some New Insights 1 Adaptive, Adaptive Coding, and Power Control for Fixed Cellular Broadband Wireless Systems: Some New Insights Ehab Armanious, David D. Falconer, and Halim Yanikomeroglu Broadband Communications and Wireless

More information

The Impact of Broadband PLC Over VDSL2 Inside The Home Environment

The Impact of Broadband PLC Over VDSL2 Inside The Home Environment The Impact of Broadband PLC Over VDSL2 Inside The Home Environment Mussa Bshara and Leo Van Biesen line Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium Tel: +32 (0)2 629.29.46, Fax: +32

More information

MIMO Channel Capacity in Co-Channel Interference

MIMO Channel Capacity in Co-Channel Interference MIMO Channel Capacity in Co-Channel Interference Yi Song and Steven D. Blostein Department of Electrical and Computer Engineering Queen s University Kingston, Ontario, Canada, K7L 3N6 E-mail: {songy, sdb}@ee.queensu.ca

More information

10GBASE-T T Tutorial. SolarFlare Communications IEEE Kauai, Hawaii. November 11, 2002

10GBASE-T T Tutorial. SolarFlare Communications IEEE Kauai, Hawaii. November 11, 2002 10GBASE-T T Tutorial IEEE 802.3 Kauai, Hawaii November 11, 2002 Communications Communications 10GBASE-T IEEE Tutorial, 11/11/2002 1 Agenda Introduction, Cabling & Challenges - George Zimmerman, Ph.D. CEO

More information

Date: December 5, 1999 Dist'n: T1E1.4

Date: December 5, 1999 Dist'n: T1E1.4 12/04/99 1 T1E1.4/99-560 Project: T1E1.4: VDSL Title: Revisiting Bridged Tap and Spectrum Issue for VDSL Performance (560) Contact: J. Cioffi, W. Yu, and G. Ginis Dept of EE, Stanford U., Stanford, CA

More information

Multiple Antenna Processing for WiMAX

Multiple Antenna Processing for WiMAX Multiple Antenna Processing for WiMAX Overview Wireless operators face a myriad of obstacles, but fundamental to the performance of any system are the propagation characteristics that restrict delivery

More information

3 RANGE INCREASE OF ADAPTIVE AND PHASED ARRAYS IN THE PRESENCE OF INTERFERERS

3 RANGE INCREASE OF ADAPTIVE AND PHASED ARRAYS IN THE PRESENCE OF INTERFERERS 3 RANGE INCREASE OF ADAPTIVE AND PHASED ARRAYS IN THE PRESENCE OF INTERFERERS A higher directive gain at the base station will result in an increased signal level at the mobile receiver, allowing longer

More information

CT-516 Advanced Digital Communications

CT-516 Advanced Digital Communications CT-516 Advanced Digital Communications Yash Vasavada Winter 2017 DA-IICT Lecture 17 Channel Coding and Power/Bandwidth Tradeoff 20 th April 2017 Power and Bandwidth Tradeoff (for achieving a particular

More information

REMOTE CONTROL OF TRANSMIT BEAMFORMING IN TDD/MIMO SYSTEMS

REMOTE CONTROL OF TRANSMIT BEAMFORMING IN TDD/MIMO SYSTEMS The 7th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 6) REMOTE CONTROL OF TRANSMIT BEAMFORMING IN TDD/MIMO SYSTEMS Yoshitaa Hara Kazuyoshi Oshima Mitsubishi

More information

UNEQUAL POWER ALLOCATION FOR JPEG TRANSMISSION OVER MIMO SYSTEMS. Muhammad F. Sabir, Robert W. Heath Jr. and Alan C. Bovik

UNEQUAL POWER ALLOCATION FOR JPEG TRANSMISSION OVER MIMO SYSTEMS. Muhammad F. Sabir, Robert W. Heath Jr. and Alan C. Bovik UNEQUAL POWER ALLOCATION FOR JPEG TRANSMISSION OVER MIMO SYSTEMS Muhammad F. Sabir, Robert W. Heath Jr. and Alan C. Bovik Department of Electrical and Computer Engineering, The University of Texas at Austin,

More information

Contribution of Multidimensional Trellis Coding in VDSL Systems

Contribution of Multidimensional Trellis Coding in VDSL Systems SETIT 005 3 rd International Conference: Sciences of Electronic, Technologies of Information and Telecommunications March 7-31, 005 TUNISIA Contribution of Multidimensional Trellis Coding in VDSL Systems

More information

Optimal Power Allocation over Fading Channels with Stringent Delay Constraints

Optimal Power Allocation over Fading Channels with Stringent Delay Constraints 1 Optimal Power Allocation over Fading Channels with Stringent Delay Constraints Xiangheng Liu Andrea Goldsmith Dept. of Electrical Engineering, Stanford University Email: liuxh,andrea@wsl.stanford.edu

More information

Francis J. Smith CTO Finesse Wireless Inc.

Francis J. Smith CTO Finesse Wireless Inc. Impact of the Interference from Intermodulation Products on the Load Factor and Capacity of Cellular CDMA2000 and WCDMA Systems & Mitigation with Interference Suppression White Paper Francis J. Smith CTO

More information

Antennas and Propagation. Chapter 6b: Path Models Rayleigh, Rician Fading, MIMO

Antennas and Propagation. Chapter 6b: Path Models Rayleigh, Rician Fading, MIMO Antennas and Propagation b: Path Models Rayleigh, Rician Fading, MIMO Introduction From last lecture How do we model H p? Discrete path model (physical, plane waves) Random matrix models (forget H p and

More information

Coexistence of G.fast and VDSL2 systems in copper access networks

Coexistence of G.fast and VDSL2 systems in copper access networks Coexistence of G.fast and VDSL2 systems in copper access networks Vedran Mikac, Željko Ilić, Marin Šilić, Goran Jurin, and Velimir Švedek Abstract Paper analyzes scenarios for expanding deployed twisted

More information

Towards 100G over Copper

Towards 100G over Copper IEEE 8.3 Higher Speed Study Group Towards G over Copper Faculty Investigator: Dr. M. Kavehrad Graduate Researchers: Mr. A. Enteshari Mr. J. Fadlullah The Pennsylvania State University Center for Information

More information

SPLIT MLSE ADAPTIVE EQUALIZATION IN SEVERELY FADED RAYLEIGH MIMO CHANNELS

SPLIT MLSE ADAPTIVE EQUALIZATION IN SEVERELY FADED RAYLEIGH MIMO CHANNELS SPLIT MLSE ADAPTIVE EQUALIZATION IN SEVERELY FADED RAYLEIGH MIMO CHANNELS RASHMI SABNUAM GUPTA 1 & KANDARPA KUMAR SARMA 2 1 Department of Electronics and Communication Engineering, Tezpur University-784028,

More information

ETSI TR V1.1.1 ( )

ETSI TR V1.1.1 ( ) TR 101 830-2 V1.1.1 (2005-10) Technical Report Transmission and Multiplexing (TM); Access networks; Spectral management on metallic access networks; Part 2: Technical methods for performance evaluations

More information

Chapter 2 Channel Equalization

Chapter 2 Channel Equalization Chapter 2 Channel Equalization 2.1 Introduction In wireless communication systems signal experiences distortion due to fading [17]. As signal propagates, it follows multiple paths between transmitter and

More information

Exam 3 is two weeks from today. Today s is the final lecture that will be included on the exam.

Exam 3 is two weeks from today. Today s is the final lecture that will be included on the exam. ECE 5325/6325: Wireless Communication Systems Lecture Notes, Spring 2010 Lecture 19 Today: (1) Diversity Exam 3 is two weeks from today. Today s is the final lecture that will be included on the exam.

More information

GIGABIT ETHERNET CONSORTIUM

GIGABIT ETHERNET CONSORTIUM GIGABIT ETHERNET CONSORTIUM Clause 126 2.5G/5GBASE-T PMA Test Suite Version 1.2 Technical Document Last Updated: March 15, 2017 2.5, 5 and 10 Gigabit Ethernet Testing Service 21 Madbury Road, Suite 100

More information

VOL. 3, NO.11 Nov, 2012 ISSN Journal of Emerging Trends in Computing and Information Sciences CIS Journal. All rights reserved.

VOL. 3, NO.11 Nov, 2012 ISSN Journal of Emerging Trends in Computing and Information Sciences CIS Journal. All rights reserved. Effect of Fading Correlation on the Performance of Spatial Multiplexed MIMO systems with circular antennas M. A. Mangoud Department of Electrical and Electronics Engineering, University of Bahrain P. O.

More information

Contract No U-BROAD D3.1 Characterization of the generic framework for coding and vectoring

Contract No U-BROAD D3.1 Characterization of the generic framework for coding and vectoring U-BROAD Deliverable No. D3.1 Contract No. 506790 - U-BROAD D3.1 Characterization of the generic framework for coding and vectoring Prepared by: Amir Leshem and Li Youming - Bar Ilan University Eyal Barnea

More information

2.5G/5G/10G ETHERNET Testing Service

2.5G/5G/10G ETHERNET Testing Service 2.5G/5G/10G ETHERNET Testing Service Clause 126 2.5G/5GBASE-T PMA Test Plan Version 1.3 Technical Document Last Updated: February 4, 2019 2.5, 5 and 10 Gigabit Ethernet Testing Service 21 Madbury Road,

More information

Local Oscillator Phase Noise and its effect on Receiver Performance C. John Grebenkemper

Local Oscillator Phase Noise and its effect on Receiver Performance C. John Grebenkemper Watkins-Johnson Company Tech-notes Copyright 1981 Watkins-Johnson Company Vol. 8 No. 6 November/December 1981 Local Oscillator Phase Noise and its effect on Receiver Performance C. John Grebenkemper All

More information

Multiuser Detection for Synchronous DS-CDMA in AWGN Channel

Multiuser Detection for Synchronous DS-CDMA in AWGN Channel Multiuser Detection for Synchronous DS-CDMA in AWGN Channel MD IMRAAN Department of Electronics and Communication Engineering Gulbarga, 585104. Karnataka, India. Abstract - In conventional correlation

More information

ADJACENT BAND COMPATIBILITY OF TETRA AND TETRAPOL IN THE MHZ FREQUENCY RANGE, AN ANALYSIS COMPLETED USING A MONTE CARLO BASED SIMULATION TOOL

ADJACENT BAND COMPATIBILITY OF TETRA AND TETRAPOL IN THE MHZ FREQUENCY RANGE, AN ANALYSIS COMPLETED USING A MONTE CARLO BASED SIMULATION TOOL European Radiocommunications Committee (ERC) within the European Conference of Postal and Telecommunications Administrations (CEPT) ADJACENT BAND COMPATIBILITY OF TETRA AND TETRAPOL IN THE 380-400 MHZ

More information

ADAPTIVITY IN MC-CDMA SYSTEMS

ADAPTIVITY IN MC-CDMA SYSTEMS ADAPTIVITY IN MC-CDMA SYSTEMS Ivan Cosovic German Aerospace Center (DLR), Inst. of Communications and Navigation Oberpfaffenhofen, 82234 Wessling, Germany ivan.cosovic@dlr.de Stefan Kaiser DoCoMo Communications

More information

System Performance of Cooperative Massive MIMO Downlink 5G Cellular Systems

System Performance of Cooperative Massive MIMO Downlink 5G Cellular Systems IEEE WAMICON 2016 April 11-13, 2016 Clearwater Beach, FL System Performance of Massive MIMO Downlink 5G Cellular Systems Chao He and Richard D. Gitlin Department of Electrical Engineering University of

More information

Achievable Unified Performance Analysis of Orthogonal Space-Time Block Codes with Antenna Selection over Correlated Rayleigh Fading Channels

Achievable Unified Performance Analysis of Orthogonal Space-Time Block Codes with Antenna Selection over Correlated Rayleigh Fading Channels Achievable Unified Performance Analysis of Orthogonal Space-Time Block Codes with Antenna Selection over Correlated Rayleigh Fading Channels SUDAKAR SINGH CHAUHAN Electronics and Communication Department

More information

Block Processing Linear Equalizer for MIMO CDMA Downlinks in STTD Mode

Block Processing Linear Equalizer for MIMO CDMA Downlinks in STTD Mode Block Processing Linear Equalizer for MIMO CDMA Downlinks in STTD Mode Yan Li Yingxue Li Abstract In this study, an enhanced chip-level linear equalizer is proposed for multiple-input multiple-out (MIMO)

More information

ADJACENT BAND COMPATIBILITY BETWEEN TETRA TAPS MOBILE SERVICES AT 870 MHz

ADJACENT BAND COMPATIBILITY BETWEEN TETRA TAPS MOBILE SERVICES AT 870 MHz Electronic Communications Committee (ECC) within the European Conference of Postal and Telecommunications Administrations (CEPT) ADJACENT BAND COMPATIBILITY BETWEEN TETRA TAPS MOBILE SERVICES AT 870 MHz

More information

Capacity of the swedish copper access network

Capacity of the swedish copper access network Capacity of the swedish copper access network Magesacher, Thomas; Ödling, Per; Börjesson, Per Ola Published in: Proceedings of RVK 5 RadioVetenskap och Kommunikation 25 Link to publication Citation for

More information

TRANSMIT diversity has emerged in the last decade as an

TRANSMIT diversity has emerged in the last decade as an IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 3, NO. 5, SEPTEMBER 2004 1369 Performance of Alamouti Transmit Diversity Over Time-Varying Rayleigh-Fading Channels Antony Vielmon, Ye (Geoffrey) Li,

More information

Design concepts for a Wideband HF ALE capability

Design concepts for a Wideband HF ALE capability Design concepts for a Wideband HF ALE capability W.N. Furman, E. Koski, J.W. Nieto harris.com THIS INFORMATION WAS APPROVED FOR PUBLISHING PER THE ITAR AS FUNDAMENTAL RESEARCH Presentation overview Background

More information

NOISE, INTERFERENCE, & DATA RATES

NOISE, INTERFERENCE, & DATA RATES COMP 635: WIRELESS NETWORKS NOISE, INTERFERENCE, & DATA RATES Jasleen Kaur Fall 2015 1 Power Terminology db Power expressed relative to reference level (P 0 ) = 10 log 10 (P signal / P 0 ) J : Can conveniently

More information

Orthogonal vs Non-Orthogonal Multiple Access with Finite Input Alphabet and Finite Bandwidth

Orthogonal vs Non-Orthogonal Multiple Access with Finite Input Alphabet and Finite Bandwidth Orthogonal vs Non-Orthogonal Multiple Access with Finite Input Alphabet and Finite Bandwidth J. Harshan Dept. of ECE, Indian Institute of Science Bangalore 56, India Email:harshan@ece.iisc.ernet.in B.

More information

Spectral Optimization and Joint Signaling Techniques for Communication in the Presence of Crosstalk. Rohit Gaikwad and Richard Baraniuk

Spectral Optimization and Joint Signaling Techniques for Communication in the Presence of Crosstalk. Rohit Gaikwad and Richard Baraniuk Spectral Optimization and Joint Signaling Techniques for Communication in the Presence of Crosstalk Rohit Gaikwad and Richard Baraniuk ECE Technical Report #9806 Rice University July 1998 1 Spectral optimization

More information

SUPPLEMENT TO THE PAPER TESTING EQUALITY OF SPECTRAL DENSITIES USING RANDOMIZATION TECHNIQUES

SUPPLEMENT TO THE PAPER TESTING EQUALITY OF SPECTRAL DENSITIES USING RANDOMIZATION TECHNIQUES SUPPLEMENT TO THE PAPER TESTING EQUALITY OF SPECTRAL DENSITIES USING RANDOMIZATION TECHNIQUES CARSTEN JENTSCH AND MARKUS PAULY Abstract. In this supplementary material we provide additional supporting

More information

Comparative Analysis of Different Modulation Schemes in Rician Fading Induced FSO Communication System

Comparative Analysis of Different Modulation Schemes in Rician Fading Induced FSO Communication System International Journal of Electronics Engineering Research. ISSN 975-645 Volume 9, Number 8 (17) pp. 1159-1169 Research India Publications http://www.ripublication.com Comparative Analysis of Different

More information

OFDM Transmission Corrupted by Impulsive Noise

OFDM Transmission Corrupted by Impulsive Noise OFDM Transmission Corrupted by Impulsive Noise Jiirgen Haring, Han Vinck University of Essen Institute for Experimental Mathematics Ellernstr. 29 45326 Essen, Germany,. e-mail: haering@exp-math.uni-essen.de

More information

Effect of Oscillator Phase Noise and Processing Delay in Full-Duplex OFDM Repeaters

Effect of Oscillator Phase Noise and Processing Delay in Full-Duplex OFDM Repeaters Effect of Oscillator Phase Noise and Processing Delay in Full-Duplex OFDM Repeaters Taneli Riihonen, Pramod Mathecken, and Risto Wichman Aalto University School of Electrical Engineering, Finland Session

More information

Cooperative Orthogonal Space-Time-Frequency Block Codes over a MIMO-OFDM Frequency Selective Channel

Cooperative Orthogonal Space-Time-Frequency Block Codes over a MIMO-OFDM Frequency Selective Channel Cooperative Orthogonal Space-Time-Frequency Block Codes over a MIMO-OFDM Frequency Selective Channel M. Rezaei* and A. Falahati* (C.A.) Abstract: In this paper, a cooperative algorithm to improve the orthogonal

More information

A Soft-Limiting Receiver Structure for Time-Hopping UWB in Multiple Access Interference

A Soft-Limiting Receiver Structure for Time-Hopping UWB in Multiple Access Interference 2006 IEEE Ninth International Symposium on Spread Spectrum Techniques and Applications A Soft-Limiting Receiver Structure for Time-Hopping UWB in Multiple Access Interference Norman C. Beaulieu, Fellow,

More information

Maximising Average Energy Efficiency for Two-user AWGN Broadcast Channel

Maximising Average Energy Efficiency for Two-user AWGN Broadcast Channel Maximising Average Energy Efficiency for Two-user AWGN Broadcast Channel Amir AKBARI, Muhammad Ali IMRAN, and Rahim TAFAZOLLI Centre for Communication Systems Research, University of Surrey, Guildford,

More information

Requirements and Test Methods for Very-High-Bit-Rate Digital Subscriber Line (VDSL) Terminal Equipment

Requirements and Test Methods for Very-High-Bit-Rate Digital Subscriber Line (VDSL) Terminal Equipment VDSL(E) Issue 1 (Provisional) January 2003 Terminal Attachment Program Requirements and Test Methods for Very-High-Bit-Rate Digital Subscriber Line (VDSL) Terminal Equipment Aussi disponible en français

More information

BER PERFORMANCE AND OPTIMUM TRAINING STRATEGY FOR UNCODED SIMO AND ALAMOUTI SPACE-TIME BLOCK CODES WITH MMSE CHANNEL ESTIMATION

BER PERFORMANCE AND OPTIMUM TRAINING STRATEGY FOR UNCODED SIMO AND ALAMOUTI SPACE-TIME BLOCK CODES WITH MMSE CHANNEL ESTIMATION BER PERFORMANCE AND OPTIMUM TRAINING STRATEGY FOR UNCODED SIMO AND ALAMOUTI SPACE-TIME BLOC CODES WITH MMSE CHANNEL ESTIMATION Lennert Jacobs, Frederik Van Cauter, Frederik Simoens and Marc Moeneclaey

More information

Rec. ITU-R F RECOMMENDATION ITU-R F *

Rec. ITU-R F RECOMMENDATION ITU-R F * Rec. ITU-R F.162-3 1 RECOMMENDATION ITU-R F.162-3 * Rec. ITU-R F.162-3 USE OF DIRECTIONAL TRANSMITTING ANTENNAS IN THE FIXED SERVICE OPERATING IN BANDS BELOW ABOUT 30 MHz (Question 150/9) (1953-1956-1966-1970-1992)

More information

Lab 3.0. Pulse Shaping and Rayleigh Channel. Faculty of Information Engineering & Technology. The Communications Department

Lab 3.0. Pulse Shaping and Rayleigh Channel. Faculty of Information Engineering & Technology. The Communications Department Faculty of Information Engineering & Technology The Communications Department Course: Advanced Communication Lab [COMM 1005] Lab 3.0 Pulse Shaping and Rayleigh Channel 1 TABLE OF CONTENTS 2 Summary...

More information

DIGITAL Radio Mondiale (DRM) is a new

DIGITAL Radio Mondiale (DRM) is a new Synchronization Strategy for a PC-based DRM Receiver Volker Fischer and Alexander Kurpiers Institute for Communication Technology Darmstadt University of Technology Germany v.fischer, a.kurpiers @nt.tu-darmstadt.de

More information

PERFORMANCE OF DISTRIBUTED UTILITY-BASED POWER CONTROL FOR WIRELESS AD HOC NETWORKS

PERFORMANCE OF DISTRIBUTED UTILITY-BASED POWER CONTROL FOR WIRELESS AD HOC NETWORKS PERFORMANCE OF DISTRIBUTED UTILITY-BASED POWER CONTROL FOR WIRELESS AD HOC NETWORKS Jianwei Huang, Randall Berry, Michael L. Honig Department of Electrical and Computer Engineering Northwestern University

More information

Results You Can Count On

Results You Can Count On 20 khz to 300 MHz Noise Generator for Realistic Gfast Testing Up to 24 Independent Noise Ports Gfast technology promises to bring a wealth of new opportunities to Service Providers as well as manufacturers

More information

Analysis of maximal-ratio transmit and combining spatial diversity

Analysis of maximal-ratio transmit and combining spatial diversity This article has been accepted and published on J-STAGE in advance of copyediting. Content is final as presented. Analysis of maximal-ratio transmit and combining spatial diversity Fumiyuki Adachi a),

More information

Channel Capacity Estimation in MIMO Systems Based on Water-Filling Algorithm

Channel Capacity Estimation in MIMO Systems Based on Water-Filling Algorithm Channel Capacity Estimation in MIMO Systems Based on Water-Filling Algorithm 1 Ch.Srikanth, 2 B.Rajanna 1 PG SCHOLAR, 2 Assistant Professor Vaagdevi college of engineering. (warangal) ABSTRACT power than

More information

AWGN Channel Performance Analysis of QO-STB Coded MIMO- OFDM System

AWGN Channel Performance Analysis of QO-STB Coded MIMO- OFDM System AWGN Channel Performance Analysis of QO-STB Coded MIMO- OFDM System Pranil Mengane 1, Ajitsinh Jadhav 2 12 Department of Electronics & Telecommunication Engg, D.Y. Patil College of Engg & Tech, Kolhapur

More information

Proposal for ACP requirements

Proposal for ACP requirements AMCP WG D9-WP/13 Proposal for requirements Presented by the IATA member Prepared by F.J. Studenberg Rockwell-Collins SUMMARY The aim of this paper is to consider what level of is achievable by a VDL radio

More information

Performance Evaluation of Adaptive MIMO Switching in Long Term Evolution

Performance Evaluation of Adaptive MIMO Switching in Long Term Evolution Performance Evaluation of Adaptive MIMO Switching in Long Term Evolution Muhammad Usman Sheikh, Rafał Jagusz,2, Jukka Lempiäinen Department of Communication Engineering, Tampere University of Technology,

More information

ECE 476/ECE 501C/CS Wireless Communication Systems Winter Lecture 6: Fading

ECE 476/ECE 501C/CS Wireless Communication Systems Winter Lecture 6: Fading ECE 476/ECE 501C/CS 513 - Wireless Communication Systems Winter 2003 Lecture 6: Fading Last lecture: Large scale propagation properties of wireless systems - slowly varying properties that depend primarily

More information

Making Noise in RF Receivers Simulate Real-World Signals with Signal Generators

Making Noise in RF Receivers Simulate Real-World Signals with Signal Generators Making Noise in RF Receivers Simulate Real-World Signals with Signal Generators Noise is an unwanted signal. In communication systems, noise affects both transmitter and receiver performance. It degrades

More information

NEAR-END CROSSTALK MITIGATION USING WAVELETS

NEAR-END CROSSTALK MITIGATION USING WAVELETS NEAR-END CROSSTALK MITIGATION USING WAVELETS R. C. Nongpiur QNX Software Systems - Wavemakers Vancouver, British Columbia Canada email: rnongpiur@ieee.org ABSTRACT A new method to mitigate near-end crosstalk

More information

Spread Spectrum Communications and Jamming Prof. Kutty Shajahan M G S Sanyal School of Telecommunications Indian Institute of Technology, Kharagpur

Spread Spectrum Communications and Jamming Prof. Kutty Shajahan M G S Sanyal School of Telecommunications Indian Institute of Technology, Kharagpur Spread Spectrum Communications and Jamming Prof. Kutty Shajahan M G S Sanyal School of Telecommunications Indian Institute of Technology, Kharagpur Lecture - 06 Tutorial I Hello friends, welcome to this

More information

Nonuniform multi level crossing for signal reconstruction

Nonuniform multi level crossing for signal reconstruction 6 Nonuniform multi level crossing for signal reconstruction 6.1 Introduction In recent years, there has been considerable interest in level crossing algorithms for sampling continuous time signals. Driven

More information

Laboratory 1: Uncertainty Analysis

Laboratory 1: Uncertainty Analysis University of Alabama Department of Physics and Astronomy PH101 / LeClair May 26, 2014 Laboratory 1: Uncertainty Analysis Hypothesis: A statistical analysis including both mean and standard deviation can

More information

Electronic Communications Committee (ECC) within the European Conference of Postal and Telecommunications Administrations (CEPT)

Electronic Communications Committee (ECC) within the European Conference of Postal and Telecommunications Administrations (CEPT) Electronic Communications Committee (ECC) within the European Conference of Postal and Telecommunications Administrations (CEPT) THE POSSIBILITIES AND CONSEQUENCES OF CONVERTING GE06 DVB-T ALLOTMENTS/ASSIGNMENTS

More information

THE EFFECT of multipath fading in wireless systems can

THE EFFECT of multipath fading in wireless systems can IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 47, NO. 1, FEBRUARY 1998 119 The Diversity Gain of Transmit Diversity in Wireless Systems with Rayleigh Fading Jack H. Winters, Fellow, IEEE Abstract In

More information

An Analytical Design: Performance Comparison of MMSE and ZF Detector

An Analytical Design: Performance Comparison of MMSE and ZF Detector An Analytical Design: Performance Comparison of MMSE and ZF Detector Pargat Singh Sidhu 1, Gurpreet Singh 2, Amit Grover 3* 1. Department of Electronics and Communication Engineering, Shaheed Bhagat Singh

More information

RECOMMENDATION ITU-R F *, ** Signal-to-interference protection ratios for various classes of emission in the fixed service below about 30 MHz

RECOMMENDATION ITU-R F *, ** Signal-to-interference protection ratios for various classes of emission in the fixed service below about 30 MHz Rec. ITU-R F.240-7 1 RECOMMENDATION ITU-R F.240-7 *, ** Signal-to-interference protection ratios for various classes of emission in the fixed service below about 30 MHz (Question ITU-R 143/9) (1953-1956-1959-1970-1974-1978-1986-1990-1992-2006)

More information

CEPT WGSE PT SE21. SEAMCAT Technical Group

CEPT WGSE PT SE21. SEAMCAT Technical Group Lucent Technologies Bell Labs Innovations ECC Electronic Communications Committee CEPT CEPT WGSE PT SE21 SEAMCAT Technical Group STG(03)12 29/10/2003 Subject: CDMA Downlink Power Control Methodology for

More information

Variable Step-Size LMS Adaptive Filters for CDMA Multiuser Detection

Variable Step-Size LMS Adaptive Filters for CDMA Multiuser Detection FACTA UNIVERSITATIS (NIŠ) SER.: ELEC. ENERG. vol. 7, April 4, -3 Variable Step-Size LMS Adaptive Filters for CDMA Multiuser Detection Karen Egiazarian, Pauli Kuosmanen, and Radu Ciprian Bilcu Abstract:

More information

TESTING OF FIXED BROADBAND WIRELESS SYSTEMS AT 5.8 GHZ

TESTING OF FIXED BROADBAND WIRELESS SYSTEMS AT 5.8 GHZ To be presented at IEEE Denver / Region 5 Conference, April 7-8, CU Boulder, CO. TESTING OF FIXED BROADBAND WIRELESS SYSTEMS AT 5.8 GHZ Thomas Schwengler Qwest Communications Denver, CO (thomas.schwengler@qwest.com)

More information

Decrease Interference Using Adaptive Modulation and Coding

Decrease Interference Using Adaptive Modulation and Coding International Journal of Computer Networks and Communications Security VOL. 3, NO. 9, SEPTEMBER 2015, 378 383 Available online at: www.ijcncs.org E-ISSN 2308-9830 (Online) / ISSN 2410-0595 (Print) Decrease

More information

Robust Frequency-Hopping System for Channels with Interference and Frequency-Selective Fading

Robust Frequency-Hopping System for Channels with Interference and Frequency-Selective Fading Robust Frequency-Hopping System for Channels with Interference and Frequency-Selective Fading Don Torrieri 1, Shi Cheng 2, and Matthew C. Valenti 2 1 US Army Research Lab 2 Lane Department of Computer

More information

INTERFERENCE SELF CANCELLATION IN SC-FDMA SYSTEMS -A CAMPARATIVE STUDY

INTERFERENCE SELF CANCELLATION IN SC-FDMA SYSTEMS -A CAMPARATIVE STUDY INTERFERENCE SELF CANCELLATION IN SC-FDMA SYSTEMS -A CAMPARATIVE STUDY Ms Risona.v 1, Dr. Malini Suvarna 2 1 M.Tech Student, Department of Electronics and Communication Engineering, Mangalore Institute

More information

Performance of Wideband Mobile Channel with Perfect Synchronism BPSK vs QPSK DS-CDMA

Performance of Wideband Mobile Channel with Perfect Synchronism BPSK vs QPSK DS-CDMA Performance of Wideband Mobile Channel with Perfect Synchronism BPSK vs QPSK DS-CDMA By Hamed D. AlSharari College of Engineering, Aljouf University, Sakaka, Aljouf 2014, Kingdom of Saudi Arabia, hamed_100@hotmail.com

More information

SNR Estimation in Nakagami-m Fading With Diversity Combining and Its Application to Turbo Decoding

SNR Estimation in Nakagami-m Fading With Diversity Combining and Its Application to Turbo Decoding IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 11, NOVEMBER 2002 1719 SNR Estimation in Nakagami-m Fading With Diversity Combining Its Application to Turbo Decoding A. Ramesh, A. Chockalingam, Laurence

More information