Interference Management via Sliding-Window Superposition Coding
|
|
- Carmella Welch
- 6 years ago
- Views:
Transcription
1 Globecom 24 Worksho - Emerging Technologies for 5G Wireless Cellular Networks Interference Management via Sliding-Window Suerosition Coding Hosung ark, Young-Han Kim, Lele Wang University of California, San Diego La Jolla, CA 9293, USA {hark,yhk,lew}@ucsd.edu Abstract The sliding-window suerosition coding scheme achieves the erformance of simultaneous decoding with ointto-oint channel codes and low-comlexity decoding. This aer rovides a case study of how this concetual coding scheme can be transformed to a ractical coding technique for two-user Gaussian interference channels. Simulation results demonstrate that sliding-window suerosition coding can sometimes double the erformance of the conventional method of treating interference as noise, still using the standard LTE turbo codes. I. INTODUCTION For high data rates and massive connectivity, the nextgeneration cellular networks are exected to deloy many small base stations. While such dense deloyment rovides the benefit of bringing radio closer to end users, it also increases the amount of interference from neighboring cells. Consequently, smart management of interference would become one of the key enabling technologies for high-sectral-efficiency, low-ower, broad-coverage wireless communication. Over the ast decades, several techniques at different rotocol layers have been roosed to mitigate adverse effects of interference in wireless networks; see, for examle, [] [3]. One imortant concetual technique at the hysical layer is simultaneous decoding [4], [5], whereby each receiver decodes for the desired signal as well as art or whole of interference. When interference is strong [6], [7], this simultaneous decoding technique achieves the otimal erformance for the twouser Gaussian interference channel using good oint-to-oint codes. Moreover, it achieves the otimal maximum likelihood decoding erformance in general, when the encoders are restricted to oint-to-oint random code ensembles [8], [9]. The celebrated Han-Kobayashi coding scheme [], which achieves the best known erformance for general two-user interference channels, also uses simultaneous decoding as a crucial comonent. As a main drawback, however, each receiver in simultaneous decoding has to emloy some form of multiuser sequence detection, which usually requires high comutational comlexity to imlement. This issue has been tackled lately by a few aroaches [], [2] based on emerging satially couled [3] and olar [4] codes, but these solutions require the develoment of new families of codes (instead of using conventional oint-to-oint channel codes This work was suorted in art by the National Science Foundation under Grant CCF such as LDC codes [5] and turbo codes [6]) and involve very long block lengths. For this reason, most existing communications systems, which use conventional oint-to-oint channel codes, treat interference as noise. While this simle scheme can achieve good erformance with low comutational comlexity when interference is weak [7] [9], the erformance degrades as interference becomes stronger, which is often the case for dense wireless networks. In articular, in the high signal-tonoise ratio/interference-to-noise ratio limit, the erformance of treating interference as noise has an unbounded ga from that of simultaneous decoding. ecently, the sliding-window suerosition coding scheme was roosed [2] that achieves the theoretical erformance of simultaneous decoding with oint-to-oint channel codes and low-comlexity decoding. This scheme is built on basic comonents of network information theory, combining the ideas of block Markov coding and sliding-window decoding (commonly used for multiho relaying and feedback communication, but not for single-ho communication) and suerosition coding and successive cancellation decoding (allowing low-comlexity decoding with oint-to-oint codes). In this aer, we investigate the erformance of slidingwindow suerosition coding (SWSC) for the two-user Gaussian interference channel and demonstrate that SWSC rovides a feasible solution to achieve the erformance of simultaneous decoding with existing oint-to-oint codes. We first evaluate the theoretical erformance of SWSC under modulation constraints and comare it with the erformance of treating interference as noise and simultaneous decoding. As is fully described in Section III, SWSC tracks the erformance of simultaneous decoding when interference is moderate to strong. To further test the feasibility of SWSC, we then translate the concetual coding scheme behind the theoretical erformance to a ractical imlementation based on actual turbo codes used in the LTE standard [2]. In Section IV, we show that our imlementation achieves the erformance guaranteed by the theory, even when the block length is relatively short (248). In articular, our imlementation outerforms conventional systems that treat interference as noise when interference is moderate to strong. In the next section, we begin our discussion by reviewing the basic oerations of SWSC [2] for the secial case of the two-user Gaussian interference channel /4/$3. 24 IEEE 972
2 Globecom 24 Worksho - Emerging Technologies for 5G Wireless Cellular Networks II. SLIDING-WINDOW SUEOSITION CODING FO THE GAUSSIAN INTEFEENCE CHANNEL The two-user Gaussian interference channel is defined as Y = g X + g 2 X 2 + Z, Y 2 = g 2 X + g 22 X 2 + Z 2. Here, X i 2 X n, i =, 2, is a transmitted signal from sender i with average ower constraint i, where n is the block length and Y i 2 n is a received signal at receiver i, and Z i 2 n N(, ), i =, 2, are noise comonents. We assume that each receiver i knows local channel gain coefficients g ij 2, j =, 2, from both senders, which are held fixed during the communication. The block diagram of this channel is shown in Fig.. () where U(j), V (j), and W (j) 2 {, +} n are BSK signals. Fig. 2 reresents the suerosition coding with U and V for X. U V W Y Y Fig. 2. Suerosition coding with virtual inut signals U, V, and W. Fig.. The two-user Gaussian interference channel. Sliding-window suerosition coding (SWSC) [2] is based on several basic building blocks in network information theory such as suerosition coding [22], block Markov coding [23], [24], successive cancellation decoding [22], [25], [26], and sliding-window decoding [27] [29]. Sender i encodes its messages by using suerosition coding with multile suerimosed layers and block Markov coding throughout multile blocks. eceiver i erforms successive cancellation decoding of all suerimosed layers from sender i and some suerimosed layers from the other sender within a window length according to a redetermined decoding order and slides the decoding window until it reaches the end of blocks. We now elaborate the encoding/decoding rocess of the secific version of SWSC considered in this aer. For block j =,...,b, let m i (j) 2 {, 2,...,2 nri } be the message to be communicated from sender i to receiver i. Similarly, let X i (j), Y i (j), and Z i (j) be the channel inut, outut, and noise for sender/receiver i in block j. The original SWSC allows for full flexibility in the number of suerimosed layers, the number and structure of auxiliary random variables for suerosition coding, and the decoding order. Here, we limit our attention to two layers of BSK signals that form a 4-AM signal by suerosition and a fixed decoding order. In articular, X (j) = U(j)+ V (j), X 2 (j) = 2 W (j), Y Y (2) The encoding and decoding oerations are deicted in Fig. 3. The signal U(j) carries the message m (j ) from the revious block, and V (j) and W (j) carry m (j) and m 2 (j), resectively, from the current block. By convention, we set m () = m (b) =. The arameter determines the ratio of owers slit into U(j) and V (j). Throughout this aer, =.8, which makes X 2 { 3 / 5, / 5, + / 5, +3 / 5} a uniformly-saced 4-AM signal. The corresonding channel oututs are Y (j) =g U(j)+g V (j) + g 2 2 W (j)+z (j), Y 2 (j) =g 2 U(j)+g2 V (j) + g 22 2 W (j)+z 2 (j). At the end of block j +, receiver first decodes Y (j) and Y (j + ) to recover m (j) carried by V (j) and U(j + ). Note that U(j) and W (j) are already known from the revious decoding window and thus the effective channel outut from Y (j) is g V (j)+z (j). This decoding ste is successful if r ale I(U; Y )+I(V ; Y U, W ). (3) eceiver then decodes Y (j+) to recover m 2 (j+) carried by W (j +), where U(j +) is known from the first ste and V (j + ) is interference. This decoding ste is successful if r 2 ale I(W ; Y U). (4) At the end of block j +, receiver 2 first decodes Y 2 (j) and Y 2 (j + ) to recover m (j) carried by V (j) and U(j + ), where U(j) is known from the revious decoding window and V (j) is interference. eceiver 2 then decodes Y 2 (j) to recover m 2 (j) carried by W (j), where U(j) and V (j) are already known. These decoding stes are successful if r ale I(U, V ; Y 2 ), (5) r 2 ale I(W ; Y 2 U, V ). (6) 973
3 Globecom 24 Worksho - Emerging Technologies for 5G Wireless Cellular Networks block U m m m m m m V m m m m m m W m m m m m m m decoding at receiver decoding at receiver 2 Fig. 3. The encoding and decoding oerations for b =7blocks. The message m (2) is carried by signals V (2) and U(3) (shaded in blue), while the message m 2 (5) is carried by W (5) (shaded in red). The sliding-window decoding of m (2) at receiver is based on its received signals Y (2) and Y (3) over two blocks. eceiver first recovers m (2) (equivalently, V (2) and U(3)) and then recovers m 2 (3) (equivalently, W (2)). The signals U(2) and W (2) are already known from the revious decoding window (shaded in gray). eceiver 2 oerates slightly differently by recovering first m (5) from and then m 2 (5) based on two blocks Y (5) and Y (6). At the end of the last block j = b, receiver 2 addtionally decodes Y 2 (b) to recover m 2 (b) carried by W (b), which is again successful if (6) holds. Since m (),...,m (b ) and m 2 (),...,m 2 (b) are sent over b blocks, the actual rate for sender/receiver is = r (b )/b and the actual rate for sender/receiver 2 is 2 = r 2. Combining these results (4) (6), we can asymtotically achieve the following rate region with SWSC: ale min{i(u; Y )+I(V ; Y U, W ),I(U, V ; Y 2 )}, 2 ale min{i(w ; Y U),I(W ; Y 2 U, V )}, where U, V, and W are indeendent Unif{, +} random variables. III. THEOETICAL EFOMANCE COMAISON In this section, we consider treating interference as noise and simultaneous decoding for the channel model in () and comare the theoretical erformance of SWSC to them. A. Treating Interference as Noise The achievable rate region of treating interference as noise is characterized by ale I(X ; Y ), (8) 2 ale I(X 2 ; Y 2 ), where X is Unif{ 3 / 5, / 5, + / 5, +3 / 5} and X 2 is Unif{ 2, + 2 } as in (2). Note that the receivers here use the constellation (modulation) information of interference instead of the simle signal-tointerference-noise ratio (SIN) metric, but they do not decode for the interference codewords. B. Simultaneous Nonunique Decoding In simultaneous decoding, each receiver recovers codewords from both senders. Here we consider a variant called simultaneous nonunique decoding, which rovides an imroved erformance by disregarding the uniqueness of the interference codeword [3]. The achievable rate region of simultaneous nonunique decoding is characterized by ale I(X ; Y X 2 ), 2 ale I(X 2 ; Y 2 X ), (9) + 2 ale min{i(x,x 2 ; Y ),I(X,X 2 ; Y 2 )}, (7) where X and X 2 are again given as in (2). Note that simultaneous nonunique decoding achieves the caacity region when interference is strong, that is, g 2 2 g 2 and g 2 2 g C. Comarison with SWSC We demonstrate the theoretical erformance of slidingwindow suerosition coding () comared to the theoretical erformance for simultaneous nonunique decoding () and treating interference as noise (). In the original SWSC scheme, the auxiliary signals U, V, and W as well as the suerosition maing x (u, v) can be chosen otimally, which guarantees that is identical to. In our setting, however, we have restricted the auxiliary signals to be BSK so that X is uniformly-saced 4- AM. Therefore, it is a riori unclear whether would be close to. For simlicity, assume the symmetric rate, ower, and channel gains, that is, = 2 =, = 2 =, g = g 22 =, and g 2 = g 2 = g. We control signalto-noise ratio (SN) and interference-to-noise ratio (IN) by varying transmit ower and find the minimum ower that achieves the given rate for,, and. The lots of the minimum symmetric transmit ower vs. the achievable symmetric rate are shown in Fig. 4 for g =.9,.,.,.2. Note that the ga between and is due to the subotimal choice of U and V under our modulation constraints. Nonetheless, aroaches and significantly outerforms in high SN. IV. IMLEMENTATION WITH LTE TUBO CODES To imlement SWSC with oint-to-oint channel codes, we use a binary linear code of length 2n and rate r /2 for [V (j) U(j+)] as U(j+) and V (j) carry m (j) in common. Similarly, we use a binary linear code of length n and rate r 2 for W (j) to carry m 2 (j). We adot the turbo codes used in the LTE standard [2], which allow flexibility in code rate and block length. In articular, we start with the rate /3 mother code and adjust the rates and lengths according to the rate matching algorithm in the standard. Note that for r < 2/3, some code bits are reeated and for r > 2/3, some code bits are unctured. To evaluate the erformance of SWSC, the block length n and the number of blocks b are set to
4 Globecom 24 Worksho - Emerging Technologies for 5G Wireless Cellular Networks (a) g = (b) g = (c) g = (d) g =.2 Fig. 4. The transmit ower vs. achievable symmetric rate for the symmetric Gaussian interference channel. and 2, resectively. We use the LOG-MA algorithm for the turbo decoding with the maximum number of iterations set to 8 for each stage of decoding. We assume that a rate air (, 2 ) is achieved for given i and g ij if the resulting bit-error rate (BE) is below 3 over indeendent sets of simulations. We first consider the symmetric case studied in the revious section. Our simulation results are overlaid in Fig. 4 along with the theoretical erformance curves. It can be checked that the erformance of our imlementation,, tracks the theoretical erformance of, confirming the feasibility It should be stressed that b is the total number of blocks, not the size of the decoding window (which is 2). Every message is recovered with oneblock delay. While a larger b reduces the rate enalty of /b, it also incurs error roagation over multile blocks, both of which were roerly taken into account in our rate and BE calculation. of sliding-window suerosition coding. Note that outerforms in high SN. ecall that the latter is the theoretical erformance bound of treating interference as noise, whose actual erformance (under a fair comarison) would be even worse. As another feasibility test, we consider the Gaussian fading interference channel, where g ij are i.i.d. N(, ). We indeendently generate 25 sets of channel gain coefficients, in order to evaluate the erformance of SWSC under various channel conditions. We calculate the average minimum ower avg over the 25 channel realizations for =.3,,,. As shown in Fig. 5, is very close to, which is tracked by the actual imlementation. Note that is consistently better than, with the ga becoming larger in high rate/high SN regime. 975
5 Globecom 24 Worksho - Emerging Technologies for 5G Wireless Cellular Networks avg Fig. 5. The average transmit ower vs. achievable symmetric rate for the Gaussian interference channel with random coefficients. V. CONCLUDING EMAKS While there should be more extensive studies on its feasibility, the results in this aer indicate that the sliding-window suerosition coding (SWSC) scheme has some otential as a ractical channel coding technique for interference management. We remark on two directions in imroving the current imlementation. First, the decoding orders at the receivers can be further otimized; for examle, SWSC can always achieve the erformance of treating interference as noise under certain decoding orders. Second, the structure of the suerosition maing can be further otimized, esecially, by the ower ratio control ( 6=.8). EFEENCES [] G. Boudreau, J. anicker, N. Guo,. Chang, N. Wang, and S. Vrzic, Interference coordination and cancellation for 4G networks, IEEE Commun. Mag., vol. 47, no. 4,. 74 8, Ar. 29. [2] C. Seol and K. Cheun, A statistical inter-cell interference model for downlink cellular OFDMA networks under log-normal shadowing and multiath ayleigh fading, IEEE Trans. Commun., vol. 57, no., , Oct. 29. [3] V. Cadambe and S. Jafar, Interference alignment and degrees of freedom of the K-user interference channel, IEEE Trans. Inf. Theory, vol. 54, no. 8, , Aug. 28. [4] A. El Gamal and Y.-H. Kim, Network Information Theory. Cambridge, MA: Cambridge University ress, 2. [5] S. S. Bidokhti, V. M. rabhakaran, and S. N. Diggavi, Is non-unique decoding necessary? in roc. IEEE Int. Sym. Inf. Theory, Boston, MA, Jul. 22. [6] M. H. M. Costa and A. El Gamal, The caacity region of the discrete memoryless interference channel with strong interference, IEEE Trans. Inf. Theory, vol. 33, no. 5,. 7 7, May 987. [7] H. Sato, On the caacity region of a discrete two-user channel for strong interference, IEEE Trans. Inf. Theory, vol. 24, no. 3, , May 978. [8] A. S. Motahari and A. K. Khandani, To decode the interference or to consider it as noise, IEEE Trans. Inf. Theory, vol. 57, no. 3, , Mar. 2. [9] F. Baccelli, A. El Gamal, and D. N. C. Tse, Interference networks with oint-to-oint codes, IEEE Trans. Inf. Theory, vol. 57, no. 5, , May 2. [] T. S. Han and K. Kobayashi, A new achievable rate region for the interference channel, IEEE Trans. Inf. Theory, vol. 27, no.,. 49 6, Jan. 98. [] A. Yedla,. Nguyen, H. fister, and K. Narayanan, Universal codes for the gaussian mac via satial couling, in roc. 49th Ann. Allerton Conf. Comm. Control Comut., 2, [2] L. Wang and E. Sasoglu, olar coding for interference networks, rerint. [Online]. Available: htt://arxiv.org/abs/ [3] S. Kudekar, T. J. ichardson, and. L. Urbanke, Threshold saturation via satial couling: Why convolutional LDC ensembles erform so well over the BEC, IEEE Trans. Inf. Theory, vol. 57, no. 2, , Feb. 2. [4] E. Arıkan, Channel olarization: A method for constructing caacityachieving codes for symmetric binary-inut memoryless channels, IEEE Trans. Inf. Theory, vol. 55, no. 7, , Jul. 29. [5]. G. Gallager, Low Density arity Check Codes. Cambridge, MA: MIT ress, 963. [6] C. Berrou, A. Glavieux, and. Thitimajshima, Near Shannon limit errorcorrecting coding and decoding: Turbo codes, in roc. IEEE Int. Conf. Commun., Geneva, Switzerland, May 993, [7] X. Shang, G. Kramer, and B. Chen, A new outer bound and the noisyinterference sum-rate caacity for Gaussian interference channels, IEEE Trans. Inf. Theory, vol. 55, no. 2, , Feb. 29. [8] V. S. Annaureddy and V. V. Veeravalli, Gaussian interference networks: Sum caacity in the low interference regime and new outer bounds on the caacity region, IEEE Trans. Inf. Theory, vol. 55, no. 7, , Jul. 29. [9] A. S. Motahari and A. K. Khandani, Caacity bounds for the Gaussian interference channel, IEEE Trans. Inf. Theory, vol. 55, no. 2, , Feb. 29. [2] L. Wang, E. Sasoglu, and Y.-H. Kim, Sliding-window suerosition coding for interference networks, in roc. IEEE Int. Sym. Inf. Theory 24, Jul. 24, [2] 3G TS 36.22: Multilexing and channel coding, elease 2, 23. [22] T. M. Cover, Broadcast channels, IEEE Trans. Inf. Theory, vol. 8, no.,. 2 4, Jan [23] T. M. Cover and A. El Gamal, Caacity theorems for the relay channel, IEEE Trans. Inf. Theory, vol. 25, no. 5, , Se [24] T. M. Cover and C. S. K. Leung, An achievable rate region for the multile-access channel with feedback, IEEE Trans. Inf. Theory, vol. 27, no. 3, , 98. [25]. Ahlswede, Multiway communication channels, in roc. Int. Sym. Inf. Theory, Tsahkadsor, Armenian SS, 97, [26] H. H. J. Liao, Multile access channels. h.d. thesis, University of Hawaii, Honolulu, HI, 972. [27] A. B. Carleial, Multile-access channels with different generalized feedback signals, IEEE Trans. Inf. Theory, vol. 28, no. 6, , Nov [28] L.-L. Xie and.. Kumar, An achievable rate for the multile-level relay channel, IEEE Trans. Inf. Theory, vol. 5, no. 4, , Ar. 25. [29] G. Kramer, M. Gastar, and. Guta, Cooerative strategies and caacity theorems for relay networks, IEEE Trans. Inf. Theory, vol. 5, no. 9, , Se. 25. [3] B. Bandemer, A. El Gamal, and Y.-H. Kim, Otimal achievable rates for interference networks with random codes, rerint. [Online]. Available: htt://arxiv.org/abs/
Adaptive Sliding-Window Coded Modulation in Cellular Networks
Adaptive Sliding-Window Coded Modulation in Cellular Networks Kwang Taik Kim, Seok-Ki Ahn, Young-Han Kim, Hosung Park Lele Wang,Chiao-YiChen, Jeongho Park Digital Media & Communications Research Center,
More informationMulti-user Two-way Deterministic Modulo 2 Adder Channels When Adaptation Is Useless
Forty-Ninth Annual Allerton Conference Allerton House, UIUC, Illinois, USA September 28-30, 2011 Multi-user Two-way Deterministic Modulo 2 Adder Channels When Adaptation Is Useless Zhiyu Cheng, Natasha
More informationPerformance Analysis of MIMO System using Space Division Multiplexing Algorithms
Performance Analysis of MIMO System using Sace Division Multilexing Algorithms Dr.C.Poongodi 1, Dr D Deea, M. Renuga Devi 3 and N Sasireka 3 1, Professor, Deartment of ECE 3 Assistant Professor, Deartment
More informationCapacity Gain From Two-Transmitter and Two-Receiver Cooperation
3822 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 53, NO. 10, OCTOBER 2007 Caacity Gain From Two-Transmitter and Two-Receiver Cooeration Chris T. K. Ng, Student Member, IEEE, Nihar Jindal, Member, IEEE,
More informationInvestigation on Channel Estimation techniques for MIMO- OFDM System for QAM/QPSK Modulation
International Journal Of Comutational Engineering Research (ijceronline.com) Vol. 2 Issue. Investigation on Channel Estimation techniques for MIMO- OFDM System for QAM/QPSK Modulation Rajbir Kaur 1, Charanjit
More informationEvolutionary Circuit Design: Information Theory Perspective on Signal Propagation
Evolutionary Circuit Design: Theory Persective on Signal Proagation Denis Poel Deartment of Comuter Science, Baker University, P.O. 65, Baldwin City, KS 66006, E-mail: oel@ieee.org Nawar Hakeem Deartment
More informationTO IMPROVE BIT ERROR RATE OF TURBO CODED OFDM TRANSMISSION OVER NOISY CHANNEL
TO IMPROVE BIT ERROR RATE OF TURBO CODED TRANSMISSION OVER NOISY CHANNEL 1 M. K. GUPTA, 2 VISHWAS SHARMA. 1 Deartment of Electronic Instrumentation and Control Engineering, Jagannath Guta Institute of
More informationThe Z Channel. Nihar Jindal Department of Electrical Engineering Stanford University, Stanford, CA
The Z Channel Sriram Vishwanath Dept. of Elec. and Computer Engg. Univ. of Texas at Austin, Austin, TX E-mail : sriram@ece.utexas.edu Nihar Jindal Department of Electrical Engineering Stanford University,
More informationTransmitter Antenna Diversity and Adaptive Signaling Using Long Range Prediction for Fast Fading DS/CDMA Mobile Radio Channels 1
Transmitter Antenna Diversity and Adative Signaling Using ong Range Prediction for Fast Fading DS/CDMA Mobile Radio Channels 1 Shengquan Hu, Tugay Eyceoz, Alexandra Duel-Hallen North Carolina State University
More informationLDPC-Coded MIMO Receiver Design Over Unknown Fading Channels
LDPC-Coded MIMO Receiver Design Over Unknown Fading Channels Jun Zheng and Bhaskar D. Rao University of California at San Diego Email: juzheng@ucsd.edu, brao@ece.ucsd.edu Abstract We consider an LDPC-coded
More informationInterference: An Information Theoretic View
Interference: An Information Theoretic View David Tse Wireless Foundations U.C. Berkeley ISIT 2009 Tutorial June 28 Thanks: Changho Suh. Context Two central phenomena in wireless communications: Fading
More informationProduct Accumulate Codes on Fading Channels
Product Accumulate Codes on Fading Channels Krishna R. Narayanan, Jing Li and Costas Georghiades Det of Electrical Engineering Texas A&M University, College Station, TX 77843 Abstract Product accumulate
More informationAn Overview of PAPR Reduction Optimization Algorithm for MC-CDMA System
RESEARCH ARTICLE OPEN ACCESS An Overview of PAPR Reduction Otimization Algorithm for MC-CDMA System Kanchan Singla*, Rajbir Kaur**, Gagandee Kaur*** *(Deartment of Electronics and Communication, Punjabi
More informationSPACE-FREQUENCY CODED OFDM FOR UNDERWATER ACOUSTIC COMMUNICATIONS
SPACE-FREQUENCY CODED OFDM FOR UNDERWATER ACOUSTIC COMMUNICATIONS E. V. Zorita and M. Stojanovic MITSG 12-35 Sea Grant College Program Massachusetts Institute of Technology Cambridge, Massachusetts 02139
More informationDEGRADED broadcast channels were first studied by
4296 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 54, NO 9, SEPTEMBER 2008 Optimal Transmission Strategy Explicit Capacity Region for Broadcast Z Channels Bike Xie, Student Member, IEEE, Miguel Griot,
More informationD-BLAST Lattice Codes for MIMO Block Rayleigh Fading Channels Λ
D-BLAST Lattice Codes for MIMO Block Rayleigh Fading Channels Λ Narayan Prasad and Mahesh K. Varanasi e-mail: frasadn, varanasig@ds.colorado.edu University of Colorado, Boulder, CO 80309 October 1, 2002
More informationJoint Relaying and Network Coding in Wireless Networks
Joint Relaying and Network Coding in Wireless Networks Sachin Katti Ivana Marić Andrea Goldsmith Dina Katabi Muriel Médard MIT Stanford Stanford MIT MIT Abstract Relaying is a fundamental building block
More informationBlock Markov Encoding & Decoding
1 Block Markov Encoding & Decoding Deqiang Chen I. INTRODUCTION Various Markov encoding and decoding techniques are often proposed for specific channels, e.g., the multi-access channel (MAC) with feedback,
More informationMULTILEVEL CODING (MLC) with multistage decoding
350 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 52, NO. 3, MARCH 2004 Power- and Bandwidth-Efficient Communications Using LDPC Codes Piraporn Limpaphayom, Student Member, IEEE, and Kim A. Winick, Senior
More informationPrimary User Enters the Game: Performance of Dynamic Spectrum Leasing in Cognitive Radio Networks
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 9, NO., DECEMBER 365 Primary User Enters the Game: Performance of Dynamic Sectrum Leasing in Cognitive Radio Networks Gonzalo Vazquez-Vilar, Student Member,
More informationHigh resolution radar signal detection based on feature analysis
Available online www.jocr.com Journal of Chemical and Pharmaceutical Research, 4, 6(6):73-77 Research Article ISSN : 975-7384 CODEN(USA) : JCPRC5 High resolution radar signal detection based on feature
More informationANALYSIS OF ROBUST MILTIUSER DETECTION TECHNIQUE FOR COMMUNICATION SYSTEM
ANALYSIS OF ROBUST MILTIUSER DETECTION TECHNIQUE FOR COMMUNICATION SYSTEM Kaushal Patel 1 1 M.E Student, ECE Deartment, A D Patel Institute of Technology, V. V. Nagar, Gujarat, India ABSTRACT Today, in
More informationData-precoded algorithm for multiple-relayassisted
RESEARCH Oen Access Data-recoded algorithm for multile-relayassisted systems Sara Teodoro *, Adão Silva, João M Gil and Atílio Gameiro Abstract A data-recoded relay-assisted (RA scheme is roosed for a
More informationAn Overview of Substrate Noise Reduction Techniques
An Overview of Substrate Noise Reduction Techniques Shahab Ardalan, and Manoj Sachdev ardalan@ieee.org, msachdev@ece.uwaterloo.ca Deartment of Electrical and Comuter Engineering University of Waterloo
More informationAntenna Selection Scheme for Wireless Channels Utilizing Differential Space-Time Modulation
Antenna Selection Scheme for Wireless Channels Utilizing Differential Sace-Time Modulation Le Chung Tran and Tadeusz A. Wysocki School of Electrical, Comuter and Telecommunications Engineering Wollongong
More informationInterference Mitigation in MIMO Interference Channel via Successive Single-User Soft Decoding
Interference Mitigation in MIMO Interference Channel via Successive Single-User Soft Decoding Jungwon Lee, Hyukjoon Kwon, Inyup Kang Mobile Solutions Lab, Samsung US R&D Center 491 Directors Pl, San Diego,
More informationand assigned priority levels in accordance with the QoS requirements of their applications.
Effect of Priority Class Ratios on the Novel Delay Weighted Priority Scheduling Algorithm Vasco Quintyne *, Adrian Als Deartment of Comuter Science, Physics and Mathematics University of the West Indies
More informationUplink Scheduling in Wireless Networks with Successive Interference Cancellation
1 Ulink Scheduling in Wireless Networks with Successive Interference Cancellation Majid Ghaderi, Member, IEEE, and Mohsen Mollanoori, Student Member, IEEE, Abstract In this aer, we study the roblem of
More informationDelivery Delay Analysis of Network Coded Wireless Broadcast Schemes
22 IEEE Wireless Communications and Networking Conference: Mobile and Wireless Networks Delivery Delay Analysis of Network Coded Wireless Broadcast Schemes Amy Fu and Parastoo Sadeghi The Australian National
More informationSAR IMAGE CLASSIFICATION USING FUZZY C-MEANS
SAR IMAGE CLASSIFICATION USING FUZZY C-MEANS Debabrata Samanta, Goutam Sanyal Deartment of CSE, National Institute of Technology, Durgaur, Mahatma Gandhi Avenue, West Bengal, India ABSTRACT Image Classification
More informationExploiting Interference through Cooperation and Cognition
Exploiting Interference through Cooperation and Cognition Stanford June 14, 2009 Joint work with A. Goldsmith, R. Dabora, G. Kramer and S. Shamai (Shitz) The Role of Wireless in the Future The Role of
More informationPerformance Analysis of Battery Power Management Schemes in Wireless Mobile. Devices
Performance Analysis of Battery Power Management Schemes in Wireless Mobile Devices Balakrishna J Prabhu, A Chockalingam and Vinod Sharma Det of ECE, Indian Institute of Science, Bangalore, INDIA Abstract
More informationarxiv: v1 [cs.it] 26 Oct 2009
K-User Fading Interference Channels: The Ergodic Very Strong Case Lalitha Sanar, Jan Vondra, and H. Vincent Poor Abstract Sufficient conditions required to achieve the interference-free capacity region
More informationOptimal p-persistent MAC algorithm for event-driven Wireless Sensor Networks
Otimal -ersistent MAC algorithm for event-driven Wireless Sensor Networks J. Vales-Alonso,E.Egea-Lóez, M. V. Bueno-Delgado, J. L. Sieiro-Lomba, J. García-Haro Deartment of Information Technologies and
More informationInitial Ranging for WiMAX (802.16e) OFDMA
Initial Ranging for WiMAX (80.16e) OFDMA Hisham A. Mahmoud, Huseyin Arslan Mehmet Kemal Ozdemir Electrical Engineering Det., Univ. of South Florida Logus Broadband Wireless Solutions 40 E. Fowler Ave.,
More informationImproved Water-Filling Power Allocation for Energy-Efficient Massive MIMO Downlink Transmissions
INTL JOUNAL OF ELECTONICS AND TELECOMMUNICATIONS, 17, VOL. 63, NO. 1,. 79-84 Manuscrit received October 7, 16; revised December, 16. DOI: 1.1515/eletel-17-11 Imroved Water-Filling ower Allocation for Energy-Efficient
More informationSHANNON showed that feedback does not increase the capacity
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 57, NO. 5, MAY 2011 2667 Feedback Capacity of the Gaussian Interference Channel to Within 2 Bits Changho Suh, Student Member, IEEE, and David N. C. Tse, Fellow,
More informationA Pricing-Based Cooperative Spectrum Sharing Stackelberg Game
A Pricing-Based Cooerative Sectrum Sharing Stackelberg Game Ramy E. Ali, Karim G. Seddik, Mohammed Nafie, and Fadel F. Digham? Wireless Intelligent Networks Center (WINC), Nile University, Smart Village,
More informationThe Optimization Model and Algorithm for Train Connection at Transfer Stations in Urban Rail Transit Network
Send Orders for Rerints to rerints@benthamscienceae 690 The Oen Cybernetics & Systemics Journal, 05, 9, 690-698 Oen Access The Otimization Model and Algorithm for Train Connection at Transfer Stations
More informationThis document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore.
This document is downloaded from DR-NTU, Nanyang Technological University Library, Singaore. Title Author(s) Citation Relative hase noise estimation and mitigation in Raman amlified coherent otical communication
More informationSelf-Driven Phase Shifted Full Bridge Converter for Telecom Applications
Self-Driven Phase Shifted Full Bridge Converter for Telecom Alications SEVILAY CETIN Technology Faculty Pamukkale University 7 Kinikli Denizli TURKEY scetin@au.edu.tr Abstract: - For medium ower alications,
More informationRandom Access Compressed Sensing in Underwater Sensor Networks
Random Access Comressed Sensing in Underwater Sensor Networks Fatemeh Fazel Northeastern University Boston, MA 2115 Email: ffazel@ece.neu.edu Maryam Fazel University of Washington Seattle, WA 98195 Email:
More informationStatistical Evaluation of the Azimuth and Elevation Angles Seen at the Output of the Receiving Antenna
IEEE TANSACTIONS ON ANTENNAS AND POPAGATION 1 Statistical Evaluation of the Azimuth and Elevation Angles Seen at the Outut of the eceiving Antenna Cezary Ziółkowski and an M. Kelner Abstract A method to
More informationTurbo Embedded Estimation with imperfect Phase/Frequency Recovery
Turbo mbedded stimation with imerfect Phase/Frequency ecovery Stefano Cioni, Giovanni. Corazza, Alessandro Vanelli Coralli niversity of ologna Deartment of lectronics, Comuter Science, and Systems D..I.S.
More informationServo Mechanism Technique based Anti-Reset Windup PI Controller for Pressure Process Station
Indian Journal of Science and Technology, Vol 9(11), DOI: 10.17485/ijst/2016/v9i11/89298, March 2016 ISSN (Print) : 0974-6846 ISSN (Online) : 0974-5645 Servo Mechanism Technique based Anti-Reset Windu
More informationPerformance of Chaos-Based Communication Systems Under the Influence of Coexisting Conventional Spread-Spectrum Systems
I TRANSACTIONS ON CIRCUITS AND SYTMS I: FUNDAMNTAL THORY AND APPLICATIONS, VOL. 50, NO., NOVMBR 2003 475 Performance of Chaos-Based Communication Systems Under the Influence of Coexisting Conventional
More informationAdaptive Switching between Spatial Diversity and Multiplexing: a Cross-layer Approach
Adative Switching between Satial Diversity and ultilexing: a Cross-layer Aroach José Lóez Vicario and Carles Antón-Haro Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) c/ Gran Caità -4, 08034
More informationState-Dependent Relay Channel: Achievable Rate and Capacity of a Semideterministic Class
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 59, NO. 5, MAY 2013 2629 State-Dependent Relay Channel: Achievable Rate and Capacity of a Semideterministic Class Majid Nasiri Khormuji, Member, IEEE, Abbas
More informationPerformance Analysis and PAPR Calculation of OFDM System Under Different Modulation schemes
SSRG International Journal of Electronics andoncommunication 2017) - Secial 2nd ndinternational Conference Innovations and- (2'ICEIS Solutions -(2'ICEIS - 2016)Issue - Aril 2017 2 International Conference
More informationA Genetic Algorithm Approach for Sensorless Speed Estimation by using Rotor Slot Harmonics
A Genetic Algorithm Aroach for Sensorless Seed Estimation by using Rotor Slot Harmonics Hayri Arabaci Abstract In this aer a sensorless seed estimation method with genetic algorithm for squirrel cage induction
More informationRajbir Kaur 1, Charanjit Kaur 2
Rajbir Kaur, Charanjit Kaur / International Journal of Engineering Research and Alications (IJERA) ISS: -9 www.ijera.com Vol., Issue 5, Setember- October 1,.139-13 based Channel Estimation Meods for MIMO-OFDM
More informationPolar Codes for Magnetic Recording Channels
Polar Codes for Magnetic Recording Channels Aman Bhatia, Veeresh Taranalli, Paul H. Siegel, Shafa Dahandeh, Anantha Raman Krishnan, Patrick Lee, Dahua Qin, Moni Sharma, and Teik Yeo University of California,
More informationFOUNTAIN codes [1], [2] have been introduced to achieve
Controlled Flooding of Fountain Codes Waqas bin Abbas, Paolo Casari, Senior Member, IEEE, Michele Zorzi, Fellow, IEEE Abstract We consider a multiho network where a source node must reliably deliver a
More informationISSN Vol.03,Issue.17 August-2014, Pages:
www.semargroup.org, www.ijsetr.com ISSN 2319-8885 Vol.03,Issue.17 August-2014, Pages:3542-3548 Implementation of MIMO Multi-Cell Broadcast Channels Based on Interference Alignment Techniques B.SANTHOSHA
More informationMULTIPATH fading could severely degrade the performance
1986 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 12, DECEMBER 2005 Rate-One Space Time Block Codes With Full Diversity Liang Xian and Huaping Liu, Member, IEEE Abstract Orthogonal space time block
More informationMLSE Diversity Receiver for Partial Response CPM
MLSE Diversity Receiver for Partial Resonse CPM Li Zhou, Philia A. Martin, Desmond P. Taylor, Clive Horn Deartment of Electrical and Comuter Engineering University of Canterbury, Christchurch, New Zealand
More informationUltra Wideband System Performance Studies in AWGN Channel with Intentional Interference
Ultra Wideband System Performance Studies in AWGN Channel with Intentional Interference Matti Hämäläinen, Raffaello Tesi, Veikko Hovinen, Niina Laine, Jari Iinatti Centre for Wireless Communications, University
More informationPerformance Analysis of LTE Downlink under Symbol Timing Offset
Performance Analysis of LTE Downlink under Symbol Timing Offset Qi Wang, Michal Šimko and Markus Ru Institute of Telecommunications, Vienna University of Technology Gusshausstrasse 25/389, A-1040 Vienna,
More informationEfficient Importance Sampling for Monte Carlo Simulation of Multicast Networks
Efficient Imortance Samling for Monte Carlo Simulation of Multicast Networks P. Lassila, J. Karvo and J. Virtamo Laboratory of Telecommunications Technology Helsinki University of Technology P.O.Box 3000,
More informationMulti-period Channel Assignment
Multi-eriod Channel Assignment Hakim Mabed, Alexandre Caminada and Jin-Kao Hao 2 France Télécom R&D, 6 Avenue des Usines, BP 382, 97 Belfort, France {hakim.mabed,alexandre.caminada}@francetelecm.com Tel:
More informationReduced Complexity MUD-MLSE Receiver for Partially-Overlapping WLAN-Like Interference
Author manuscrit, ublished in "IEEE VTC Sring 2007 (2007)" Reduced Comlexity MUD-MLSE Receiver for Partially-Overlaing WLAN-Like Interference P. Mary 1,2,J.M.Gorce 2, G. Villemaud 2, M. Dohler 1, M. Arndt
More informationCapacity-Achieving Rateless Polar Codes
Capacity-Achieving Rateless Polar Codes arxiv:1508.03112v1 [cs.it] 13 Aug 2015 Bin Li, David Tse, Kai Chen, and Hui Shen August 14, 2015 Abstract A rateless coding scheme transmits incrementally more and
More informationMulti-TOA Based Position Estimation for IR-UWB
Multi-TOA Based Position Estimation for IR-UWB Genís Floriach, Montse Nájar and Monica Navarro Deartment of Signal Theory and Communications Universitat Politècnica de Catalunya (UPC), Barcelona, Sain
More informationA Novel Image Component Transmission Approach to Improve Image Quality and Energy Efficiency in Wireless Sensor Networks
Journal of Comuter Science 3 (5: 353-360, 2007 ISSN 1549-3636 2007 Science Publications A Novel Image Comonent Transmission Aroach to Imrove Image Quality and nergy fficiency in Wireless Sensor Networks
More informationAdaptive Pilot Design for Massive MIMO HetNets with Wireless Backhaul
Adative Pilot Design for Massive MIMO HetNets with Wireless Backhaul Mingjie Feng and Shiwen Mao Det. Electrical & Comuter Engineering, Auburn University, Auburn, AL 36849-5201, USA Email: mzf0022@auburn.edu,
More informationA Multi-View Nonlinear Active Shape Model Using Kernel PCA
A Multi-View Nonlinear Active Shae Model Using Kernel PCA Sami Romdhani y, Shaogang Gong z and Alexandra Psarrou y y Harrow School of Comuter Science, University of Westminster, Harrow HA1 3TP, UK [rodhams
More informationUniversity of Twente
University of Twente Faculty of Electrical Engineering, Mathematics & Comuter Science Design of an audio ower amlifier with a notch in the outut imedance Remco Twelkemeijer MSc. Thesis May 008 Suervisors:
More informationSemi Blind Channel Estimation: An Efficient Channel Estimation scheme for MIMO- OFDM System
Australian Journal of Basic and Alied Sciences, 7(7): 53-538, 03 ISSN 99-878 Semi Blind Channel Estimation: An Efficient Channel Estimation scheme for MIMO- OFDM System Arathi. Devasia, Dr.G. Ramachandra
More informationDegrees of Freedom of the MIMO X Channel
Degrees of Freedom of the MIMO X Channel Syed A. Jafar Electrical Engineering and Computer Science University of California Irvine Irvine California 9697 USA Email: syed@uci.edu Shlomo Shamai (Shitz) Department
More informationReliability and Criticality Analysis of Communication Networks by Stochastic Computation
> EPLACE HIS LINE WIH YOU PAPE IDENIFICAION NUMBE (DOUBLE-CLICK HEE O EDI) < 1 eliability and Criticality Analysis of Communication Networks by Stochastic Comutation Peican Zhu, Jie Han, Yangming Guo and
More informationControl of Grid Integrated Voltage Source Converters under Unbalanced Conditions
Jon Are Suul Control of Grid Integrated Voltage Source Converters under Unbalanced Conditions Develoment of an On-line Frequency-adative Virtual Flux-based Aroach Thesis for the degree of Philosohiae Doctor
More informationState of the Cognitive Interference Channel
State of the Cognitive Interference Channel Stefano Rini, Ph.D. candidate, srini2@uic.edu Daniela Tuninetti, danielat@uic.edu Natasha Devroye, devroye@uic.edu Interference channel Tx 1 DM Cognitive interference
More informationJOINT COMPENSATION OF OFDM TRANSMITTER AND RECEIVER IQ IMBALANCE IN THE PRESENCE OF CARRIER FREQUENCY OFFSET
JOINT COMPENSATION OF OFDM TRANSMITTER AND RECEIVER IQ IMBALANCE IN THE PRESENCE OF CARRIER FREQUENCY OFFSET Deeaknath Tandur, and Marc Moonen ESAT/SCD-SISTA, KULeuven Kasteelark Arenberg 10, B-3001, Leuven-Heverlee,
More informationUnderwater acoustic channel model and variations due to changes in node and buoy positions
Volume 24 htt://acousticalsociety.org/ 5th Pacific Rim Underwater Acoustics Conference Vladivostok, Russia 23-26 Setember 2015 Underwater acoustic channel model and variations due to changes in node and
More informationJoint Tx/Rx Energy-Efficient Scheduling in Multi-Radio Networks: A Divide-and-Conquer Approach
Joint Tx/Rx Energy-Efficient Scheduling in Multi-Radio Networs: A Divide-and-Conquer Aroach Qingqing Wu, Meixia Tao, and Wen Chen Deartment of Electronic Engineering, Shanghai Jiao Tong University, Shanghai,
More informationJoint Frame Design, Resource Allocation and User Association for Massive MIMO Heterogeneous Networks with Wireless Backhaul
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL.XXX, NO.XXX, MONTH YEAR 1 Joint Frame Design, Resource Allocation and User Association for Massive MIMO Heterogeneous Networks with Wireless Backhaul Mingjie
More informationCHAPTER 5 INTERNAL MODEL CONTROL STRATEGY. The Internal Model Control (IMC) based approach for PID controller
CHAPTER 5 INTERNAL MODEL CONTROL STRATEGY 5. INTRODUCTION The Internal Model Control (IMC) based aroach for PID controller design can be used to control alications in industries. It is because, for ractical
More informationPerformance Enhancement of Interference Alignment Techniques for MIMO Multi Cell Networks
Performance Enhancement of Interference Alignment Techniques for MIMO Multi Cell Networks B.Vijayanarasimha Raju 1 PG Student, ECE Department Gokula Krishna College of Engineering Sullurpet, India e-mail:
More informationA Bit of network information theory
Š#/,% 0/,94%#(.)15% A Bit of network information theory Suhas Diggavi 1 Email: suhas.diggavi@epfl.ch URL: http://licos.epfl.ch Parts of talk are joint work with S. Avestimehr 2, S. Mohajer 1, C. Tian 3,
More informationTHE idea behind constellation shaping is that signals with
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 52, NO. 3, MARCH 2004 341 Transactions Letters Constellation Shaping for Pragmatic Turbo-Coded Modulation With High Spectral Efficiency Dan Raphaeli, Senior Member,
More informationA-BLAST: A Novel Approach to Adaptive Layered Space- Time Processing
A-BLAST: A Novel Aroac to Adative Layered Sace- Time Processing Jason R. Lee Soma Networks Inc. Ottawa, ON, Canada +1.613.56.9936 mailto:jlee@somanetworks.com Moamed. Amed Memorial University St. Jon s,
More informationDecoding of Block Turbo Codes
Decoding of Block Turbo Codes Mathematical Methods for Cryptography Dedicated to Celebrate Prof. Tor Helleseth s 70 th Birthday September 4-8, 2017 Kyeongcheol Yang Pohang University of Science and Technology
More informationApplication of Notch Filtering under Low Sampling Rate for Broken Rotor Bar Detection with DTFT and AR based Spectrum Methods
Alication of Notch Filtering under Low Samling Rate for Broken Rotor Bar Detection with DTFT and AR based Sectrum Methods B. Ayhan H. J. Trussell M.-Y. Chow M.-H. Song IEEE Student Member IEEE Fellow IEEE
More informationOn the Achievable Diversity-vs-Multiplexing Tradeoff in Cooperative Channels
On the Achievable Diversity-vs-Multiplexing Tradeoff in Cooperative Channels Kambiz Azarian, Hesham El Gamal, and Philip Schniter Dept of Electrical Engineering, The Ohio State University Columbus, OH
More informationAn Efficient VLSI Architecture Parallel Prefix Counting With Domino Logic Λ
An Efficient VLSI Architecture Parallel Prefix Counting With Domino Logic Λ Rong Lin y Koji Nakano z Stehan Olariu x Albert Y. Zomaya Abstract We roose an efficient reconfigurable arallel refix counting
More informationInterference Management in Wireless Networks
Interference Management in Wireless Networks Aly El Gamal Department of Electrical and Computer Engineering Purdue University Venu Veeravalli Coordinated Science Lab Department of Electrical and Computer
More informationFOR THE PAST few years, there has been a great amount
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 4, APRIL 2005 549 Transactions Letters On Implementation of Min-Sum Algorithm and Its Modifications for Decoding Low-Density Parity-Check (LDPC) Codes
More informationA Resource Allocation Algorithm using Frequency Borrowing in Hierarchical CDMA Cellular Systems
A Resource Allocation Algorithm using Frequency Borrowing in Hierarchical CDMA Cellular Systems Young-uk Chung and Dong-Ho Cho Division o Electrical Engineering Deartment o Electrical Engineering and Comuter
More informationPolar Codes for Probabilistic Amplitude Shaping
Polar Codes for Probabilistic Amplitude Shaping Tobias Prinz tobias.prinz@tum.de Second LNT & DLR Summer Workshop on Coding July 26, 2016 Tobias Prinz Polar Codes for Probabilistic Amplitude Shaping 1/16
More informationWireless Multicasting with Channel Uncertainty
Wireless Multicasting with Channel Uncertainty Jie Luo ECE Dept., Colorado State Univ. Fort Collins, Colorado 80523 e-mail: rockey@eng.colostate.edu Anthony Ephremides ECE Dept., Univ. of Maryland College
More informationTWO-STAGE SPEECH/MUSIC CLASSIFIER WITH DECISION SMOOTHING AND SHARPENING IN THE EVS CODEC
TWO-STAGE SPEECH/MUSIC CLASSIFIER WITH DECISION OOTHING AND SHARPENING IN THE EVS CODEC Vladimir Malenovsky *, Tommy Vaillancourt *, Wang Zhe, Kihyun Choo, Venkatraman Atti *VoiceAge Cor., Huawei Technologies,
More informationFeedback via Message Passing in Interference Channels
Feedback via Message Passing in Interference Channels (Invited Paper) Vaneet Aggarwal Department of ELE, Princeton University, Princeton, NJ 08544. vaggarwa@princeton.edu Salman Avestimehr Department of
More informationNotes 15: Concatenated Codes, Turbo Codes and Iterative Processing
16.548 Notes 15: Concatenated Codes, Turbo Codes and Iterative Processing Outline! Introduction " Pushing the Bounds on Channel Capacity " Theory of Iterative Decoding " Recursive Convolutional Coding
More informationProperties of Mobile Tactical Radio Networks on VHF Bands
Proerties of Mobile Tactical Radio Networks on VHF Bands Li Li, Phil Vigneron Communications Research Centre Canada Ottawa, Canada li.li@crc.gc.ca / hil.vigneron@crc.gc.ca ABSTRACT This work extends a
More informationInterference Alignment for Heterogeneous Full-Duplex Cellular Networks. Amr El-Keyi and Halim Yanikomeroglu
Interference Alignment for Heterogeneous Full-Duplex Cellular Networks Amr El-Keyi and Halim Yanikomeroglu 1 Outline Introduction System Model Main Results Outer bounds on the DoF Optimum Antenna Allocation
More informationAligned Interference Neutralization and the Degrees of Freedom of the Interference Channel
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 58, NO 7, JULY 2012 4381 Aligned Interference Neutralization and the Degrees of Freedom of the 2 2 2 Interference Channel Tiangao Gou, Student Member, IEEE,
More information3062 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 50, NO. 12, DECEMBER 2004
3062 IEEE TANSACTIONS ON INFOMATION THEOY, VOL. 50, NO. 12, DECEMBE 2004 Cooperative Diversity in Wireless Networks: Efficient Protocols and Outage Behavior J. Nicholas Laneman, Member, IEEE, David N.
More informationDesign and Evaluation of Localization Protocols and Algorithms in Wireless Sensor Networks Using UWB
Design and valuation of Localization Protocols and Algorithms in Wireless Sensor Networks Using UWB Di Wu, Lichun Bao, Min Du, Renfa Li Donald Bren School of ICS, University of California, Irvine, USA
More informationThe Impact of Random Waypoint Mobility on Infrastructure Wireless Networks
The Imact of Random Wayoint Mobility on Infrastructure Wireless Networks Dennis Pong and Tim Moors School of Electrical Engineering and Telecommunications The University of New South Wales, NSW 5 Australia
More informationAnalysis of Mean Access Delay in Variable-Window CSMA
Sensors 007, 7, 3535-3559 sensors ISSN 44-80 007 by MDPI www.mdi.org/sensors Full Research Paer Analysis of Mean Access Delay in Variable-Window CSMA Marek Miśkowicz AGH University of Science and Technology,
More information