Lecture 6. Network Deployment (2) Basics of Transmission Schemes (1)

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Transcription:

Lecture 6 Network Deployment (2) Basics of Transmission Schemes (1)

Capacity Expansion 2 nmain investment in deploying a cellular network is the cost of infrastructure, land, base station equipment, switches installation, interconnection, etc. n Income is proportional to subscriber base ninitial installment may not be able to support increasing subscriber demand nhow can capacity be increased without replicating deployment?

Techniques to expand capacity 3 n Additional spectrum n Very hard to obtain also expensive n 1900 MHz bands for PCS; 700 MHz bands from TV n Architectural approaches n Cell splitting n Cell sectorization n Reuse partitioning n Lee s microcell zone technique n Changing to digital TDMA or CDMA n Dynamic channel allocation

Cell Splitting 4 n Hotspots are created in certain areas n Introduce a smaller cell of half the size midway between two co-channel cells n Interference problems n Channels must be split between the larger and smaller cells a A-a

The Overlaid Cell Concept 5 D L,(1) DL,(2) n Channels are divided between a larger macro-cell that co-exists with a smaller micro-cell that is completely contained within the macro-cell n D 2 /R 2 is larger than D 1 /R 1 R 1 n Split-band analog systems n Reuse partitioning n Used in LTE (Revisit) R 2

Cell Sectoring 6 n Use directional antennas to reduce interference n Radio propagation is focused in certain directions n Antenna coverage is restricted to part of a cell called a sector n By reducing interference, the cluster size can be reduced (J s is reduced, and so we can reduce N c )

Three-sector cells and a cluster size 7 of N c = 4 B B C G C D C D B A E A E G F C D G F C D B A D B A E G F A E G F C D F C D B A E B A E G F G F 120 o directional antennas are employed Channels allocated to a cell are further divided into three parts Without directional antennas, S r = 13.8 db which is inadequate With directional antennas, S r = 18.5 db Cell Sector Under Consideration E Interfering Sectors Non-Interfering Sectors S r R 4 J s D 4 = R 4 2D 4 = 1 2 # % $ D R & ( ' 4 = 9 2 N 2 c

Sectored Frequency Planning 8 n Example: Allocate frequencies for an AMPS operator in cellular B-block who uses a 7 cell frequency reuse pattern with 3 sectors per cell n Use a Frequency Chart available from FCC web site n Groups frequencies into 21 categories Cells 1-7 and sectors A-B-C in each cell

Sectored Frequency Planning 9 n Example: Allocate frequencies for a GSM operator in U.S. PCS B-block who uses a 7 cell frequency reuse pattern with 3 sectors per cell n Use a Frequency Chart available from FCC web site n Groups frequencies into 21 categories Cells A-G and sectors 1-3 in each cell

Summary: Cell sectoring 10 n The cluster size can be reduced by employing directional antennas n The capacity increase is 1.67 times for N = 4 and 2.3 times for N = 3 compared to N = 7 n Sectoring is better than splitting n No new base station has to be set up n No new planning efforts are needed to maintain interference levels n Sectoring leads to handoff between sectors which increases signaling load and some loss of call quality n A cell cannot be ideally sectored and the signal to interference values obtained here are optimistic

Channel Allocation Techniques 11 n Idea: n n n During the day on weekdays, downtown areas have a lot of demand for wireless channels In weekends and evenings, suburban areas have a larger demand and downtown areas have very little demand Instead of allocating channels statically to cells, allocate channels on demand while maintaining signal-to-interference ratio requirements n The (voice) user does not care how the channels are allocated as long as n n He/she gets access to the channel whenever required The quality of the signal is acceptable

Channel Allocation Techniques (2) 12 nfixed channel allocation (FCA) n Channel borrowing ndynamic channel allocation (DCA) n Centralized DCA n Distributed DCA n Cell-based n Measurement-based nhybrid channel allocation (HCA)

Channel borrowing 13 Affected Cells (Locked Channels) B C D B A E G F C D B A E G F C B G n Idea: Borrow channels from low loaded cells and return them whenever required n Temporary channel borrowing C B G C A G Borrow Channels D A F n Return channel after call is completed D A E F C D D B A E G F F C D B A E E G F n Locks channel in co-channel cells n Static channel borrowing n Distribute channels nonuniformly but change them in a predictable way E

Dynamic Channel Allocation 14 n All channels are placed in a pool n When a new call comes in, a channel is selected based on the overall SIR in the cell n Selection of the channel in this way is costly n Needs a search and computation of SIR values n Centralized n A central entity selects channels for use and returns it to the pool after completion of calls n Distributed n Base stations locally compute the channels that can be used n Cell-based BSs communicate with each other on the wired backbone to determine the best way to select channels n Measurement-based BSs measure RSS or receive RSS reports from MSs that they use in their decisions

Comparison of FCA and DCA 15 Attribute Fixed Channel Allocation Dynamic Channel Allocation Traffic Load Better under heavy traffic load Better under light/moderate traffic load Flexibility in channel allocation Low High Reusability of channels Maximum possible Limited Temporal and spatial changes Very sensitive Insensitive Grade of service Fluctuating Stable Forced Call Termination Large probability Low/moderate probability Suitability of cell size Macro-cellular Micro-cellular Radio equipment Covers only the channels Has to cover all possible channels that allocated to the cell could be assigned to the cell Computational effort Low High Call set up delay Low Moderate/High Implementation complexity Low Moderate/High Frequency planning Laborious and complex None Signaling load Low Moderate/High Control Centralized Centralized, decentralized or distributed

Interference Management in LTE- 16 OFDMA n Borrows ideas from Reuse Partitioning and Dynamic Channel Allocation n Aims for a frequency reuse of 1 n Sub-carriers and resource blocks (RBs) may not be universally reused n Base stations talk with each other to manage interference and also scheduling RBs to users

Strict and Soft Fractional 17 Frequency Reuse in LTE Power Power f 1 f 2 f 3 f 4 frequency f 2 f 3 f 4 frequency Power distribution in this cell f 2 +f 4 f 2 +f 3 f 4 +f 3 (a) Strict FFR with reuse of 3+1 (b) Soft FFR with reuse of 3

Femtocells 18 n Initial Idea n Coverage challenged areas with good Internet connectivity n Progressive Benefits n High spectrum efficiencies n Typically indoor! n High data rates are possible n Reducing subscriber churn n Reducing CAPEX and OPEX costs for service providers n Backhaul capacity and capital expenditures are reduced

Issues with Femtocell deployment 19 n Femtocell base station cannot transmit at high power nor at low power n Should not swamp users that do not belong to femtocell n Should not deny coverage to someone who installs the femtocell n Femtocell base station reception has to be dynamic n A mobile that is near should not swamp it because of its minimum transmit power n A mobile far away should not be forced to transmit at high power to reach the femtocell n This may interfere with transmissions in a macrocell

Design Issues in Local Area Wireless Data 20 n IEEE 802.11 n Initial deployments were based on the 915 MHz bands n There was only one channel n In the 2.4 GHz bands n There are three non-overlapping channels à frequency reuse is possible n Thresholds! n In the 5 GHz bands, there are eleven non-overlapping channels n Three dimensional planning is required n Antenna patterns and building architecture n There are three levels of transmit power at the AP n Not clear what can be done at the MS

Overlapping channels in the 802.11 21 specifications 1 2 3 4 5 6 7 8 9 10 11 2.412 2.462 5 MHz Use three non-overlapping channels

Using overlapping channels 22 1 2 3 4 5 6 7 8 9 10 11 2.412 2.462 5 MHz n It is possible to use Channels 1, 4, 7 and 11 instead of 1, 6 and 11 n There is a drop in throughput n There are some results of actual performance but they are inconclusive n It is not clear whether the drop in throughput is due to backoff or packet loss

SIRs in 802.11 WLANs (@2Mbps) 23 n Reports of measurements and models of 802.11 RSS and throughputs are vendor specific n One report says that a minimum SIR of 15 db is required for good throughput n Used UDP streams and estimated the SIR using a path loss model n Throughput falls from 1.8 Mbps to 1 Mbps as the SIR reduces from 15 db to 10 db n Reuse issues are then simulated n Unlike voice, data is bursty so the design and deployment issues are different n Most real deployments design the network for coverage rather than specific QoS goals

WLAN Deployment Methods 24 n Random deployment by users narrange access points in a grid n Optimally place access points for coverage/interference

Coexistence? 25 ninterference n Two wireless technologies interfere if co-location causes significant performance degradation ncoexistence n Two wireless technologies coexist if there is no significant impact on the performance ninteroperable n Devices belonging to two different wireless technologies are interoperable if they can communicate and exchange data between them

Coexistence between HomeRF and IEEE 26 802.11 nhomerf uses very slow frequency hopping n 50 hops/s frame is 20 ms long n Compare with Bluetooth 1600 hops/s and 625 µs n Also operates in the 2.4 GHz bands nexperiments on studying the impact of HomeRF on 802.11 throughput n HomeRF is very detrimental to 802.11 throughput n HomeRF is an interference

Bluetooth and 802.11 (1) 27 n Impact of BT on 802.11 n At large RSS, the throughput is fairly good n As the RSS falls, the throughput falls drastically n BT causes substantial interference, but there is some kind of capture when the RSS is good Source: J. Lansford et al., IEEE Network, September 2001

Bluetooth and IEEE 802.11 (2) 28 n Impact of IEEE 802.11 on BT n 802.11 signal is like a wideband jammer n As the RSS from the AP falls, the throughput improves n As the RSS from the AP increases, voice packets are dropped randomly n The transition occurs suddenly n Short ACKs are less likely to cause errors than long frames Source: J. Lansford et al., IEEE Network, September 2001

Communication Issues and Radio 29 Propagation Fading Channels Large Scale Fading Small Scale Fading Path-Loss & Shadowing Time Variation Time Dispersion Angular Dispersion Impacts Coverage Impacts signal design, receiver design, coding, BER

Before we get into small-scale 30 fading nwhat is the best we can do when there is NO fading? nwhat are the tradeoffs between bit errors, power, noise, and bandwidth?

Digital Modulation (Revisited) 31 n Changing the parameters of a sinusoid is called shift keying if information is digital n Types n Amplitude-shift keying (ASK) n Amplitude difference of carrier n Frequency-shift keying (FSK) n Frequency difference near carrier frequency n Phase-shift keying (PSK) n Phase of carrier signal shifted n Quadrature amplitude modulation (QAM) n Both amplitude and phase of the carrier carry data n Bits/Symbol n Binary (one bit in one symbol => two symbols) n M-ary (log 2 M bits in one symbol => M symbols)

Binary Amplitude-Shift Keying 32 n Idea n One binary digit represented by the presence of the carrier, at constant amplitude n The other binary digit is represented by the absence of the carrier n Remarks: n The carrier signal is A cos(2πf c t) n The symbol duration is T seconds n Also called On-Off keying or OOK Average Power in Signal = A 2 /4 Average Energy per bit E b = A 2 T/4

Amplitude-Shift Keying 33 n Susceptible to sudden gain changes n Inefficient modulation technique (what do we mean by this?) n Used on voice-grade lines up to 1200 bps n Used to transmit digital data over optical fiber and in IR systems ON OFF ON

Binary Frequency-Shift Keying 34 (BFSK) ntwo binary digits represented by two different frequencies near the carrier frequency Average Power in Signal = A 2 /2 nf 1 and f 2 are offset from carrier frequency f c by equal but opposite amounts E b = A 2 T/2

Frequency-Shift Keying (FSK) 35 n Less susceptible to error than ASK n On voice-grade lines, used up to 1200bps n Used for high-frequency (3 to 30 MHz) radio transmission n Can be used at higher frequencies on LANs that use coaxial cable 0 1 0

Binary Phase-Shift Keying (PSK) 36 n Uses two phases to represent binary digits n OR n We revisit BPSK later Average Power in Signal = A 2 /2 E b = A 2 T/2

M-ary Modulation Schemes 37 n M-ary => M symbols n The symbols are a 1, a 2,, a M n Each symbol carries k = log 2 M bits n Example: M = 4 => the symbols are a 1, a 2, a 3, a 4 n Let a 1 = 00, a 2 = 01, a 3 = 10, and a 4 = 11 n We have k = 2 bits/symbol n The symbols can once again be represented by the amplitude, phase, or frequency of the carrier

Example: 4-ASK Average Power in Signal = 7A 2 /4 E b = 7A 2 T/8 38 nin 4-ASK, we need 4 different amplitudes of the carrier to represent 4 symbols nlet the amplitudes be 0,1,2 and 3 nthe symbols will be: s(t) = 8 0! 00 : >< 1! 01 : 2! 11 : >: 3! 10 : 0, 0 apple t apple T cos(2 f c t), 0 apple t apple T 2 cos(2 f c t), 0 apple t apple T 3 cos(2 f c t), 0 apple t apple T

More on M-ary modulation 39 nm-ask (also called PAM) is not common nmore common are nmpsk There are M phases of the carrier to represent the M symbols nmfsk There are M frequencies around f c to represent the M symbols nquadrature amplitude modulation (QAM) nuses a combination of amplitude and phase nm-qam

Advanced Modulation Schemes 40 nvariations on ASK, FSK and PSK possible nattempt to improve performance n Increase data for a fixed bandwidth n Remove requirement for phase synchronization n Differential modulation and detection n Improve BER performance nmain schemes for wireless systems are based on FSK and PSK because they are more robust to noise

Orthogonal signaling with codes 41 What is orthogonality? Show in time and frequency Show in space Bandwidth

Modulation schemes used in wireless 42 networks n GMSK n GSM, CDPD, Mobitex, GPRS, HIPERLAN/1 n p/4 DQPSK n Tetra, IS-136 n OQPSK n IS-95, cdma2000 n FSK n ARDIS, 802.11 FHSS, Bluetooth n BPSK, QPSK, 16-QAM, 64- QAM n HIPERLAN/2, IEEE 802.11a (with OFDM), LTE n BPSK, QPSK n IS-95, IEEE 802.11 (with DSSS) n Pulse Position Modulation n IEEE 802.11 IR n Orthogonal Modulation n IS-95, cdma2000

Communication Issues 43 n Noise (unwanted interfering signals) is not necessarily additive, white or Gaussian n Examples: Inter-symbol interference (ISI), Adjacent channel interference (ACI), Co-channel interference (CCI) n In CDMA interference from users etc. n Noise affects the Bit Error Rate (BER) n Fraction of bits that are inverted at the receiver n Also, the radio channel has multiplicative components that degrade the performance n The behavior of the radio channel can increase ISI, reduce the signal strength, and increase the bit error rate

Performance in General 44 n What determines how successful a receiver will be in interpreting an incoming signal? n Signal-to-noise ratio => power n Data rate n Bandwidth n Typical trends n An increase in data rate increases bit error rate n An increase in SNR decreases bit error rate n An increase in bandwidth allows an increase in data rate n In mobile wireless systems both bandwidth and power are in short supply

Wireless Performance Considerations 45 n In wireless communications, the primary issues are n Spectrum n Power n Effects of the radio channel n When we look at modulation schemes, we are interested in the following n Performance in AWGN channels n Provides a baseline performance n Performance in multipath fading channels n Expected performance in realistic channels n Bandwidth efficiency n Cost and complexity

Performance in AWGN Channels 46 n Suppose the communications channel is only affected by AWGN (thermal noise) n This is the most ideal conditions you may get n Similar to a wire Bit Error Rate or BER is a function of n Provides a benchmark or baseline performance n Can get some insight into whether one modulation scheme is better than another n Ideally we want n Very low bit error rates at small signal-to-noise ratio n Ensures we can conserve battery power by transmitting at low powers n Yet the information can be recovered reliably E b N 0 = b

Performance in AWGN channels (2) 47 n AWGN = Additive White Gaussian Noise n This has a flat noise spectrum with average power spectral density of N 0 Binary Modulation Schemes n The probability of bit error (bit error rate) is measured as a function of ratio of the energy per bit E b to the average noise PSD value n BER or P e variation with E b /N 0 n E b /N 0 is a measure of the power requirements n Tradeoffs!

Signal Constellation (1) 48

Signal Constellation (2) 49 n Given any modulation scheme, it is possible to obtain its signal constellation. n Represent each possible signal as a vector in a Euclidean space. 8-PSK n In symbol detection decode incoming signal as closest symbol in the signal constellation space n If we know the signal constellation, we can estimate the performance in terms of the probability of symbol error given the noise parameters n Probability of error depends on the minimum distance between the constellation points 16-QAM

Probability of Error 50

Performance in AWGN(2) 51

M-ary modulation schemes 52 phase shift keying or QAM n Bits per symbol = log 2 M n Phase shift keying n Signal points are on a circle n More bits/sec/hz but larger P e for given E b /N 0 n Orthogonal keying n M-dimensional constellation n FSK n Pulse position modulation n Orthogonal keying/signaling n Less bits/sec/hz but much smaller P e for given E b /N 0 n QAM n Works mostly like PSK orthogonal keying increasing M increasing M

Bandwidth Efficiency and Complexity 53 n Bandwidth efficiency (related to spectral efficiency) n n n n For a given bit error rate what is the required bandwidth for a specified data rate? n n Recall discussion of capacity Example At a BER of 10-5, BPSK requires 2 MHz for a data rate of 2 Mbps Ideally our goal is to stuff as many bits as possible in a given bandwidth Bandwidth (spectrum) efficiency is measured in terms of the data rate supported over a given bandwidth Units: bits/sec/hz. n Cost/Complexity n n In achieving good performance and bandwidth efficiency, the modulation scheme should not be too expensive or complex to implement Circuitry should be simple to implement and inexpensive (e.g. detection, amplifiers)

Bandwidth of modulation schemes 54 GMSK

Tradeoffs between BER, power and 55 bandwidth n (1) Trade BER performance for power fixed data rate n (2) Trade data rate for power fixed BER n (3) Trade BER for data rate fixed power

Next Week 56 nsmall Scale Fading