Cooperative Communication in Spatially Modulated MIMO systems

Size: px
Start display at page:

Download "Cooperative Communication in Spatially Modulated MIMO systems"

Transcription

1 Cooperative Communication in Spatially Modulated MIMO systems Multimedia Wireless Networks (MWN) Group, Department Of Electrical Engineering, Indian Institute of Technology, Kanpur, India Electrical and Computer Engineering, University of Illinois, Urbana, Illinois April 5, 2016

2 Overview 1 Introduction

3 Introduction Spatial modulation (SM) 1 has been recently gaining popularity due to its ability to enable MIMO communication with fewer transmit RF chains. SM systems can be combined with STBC to obtain a substantial improvement in performance due to the additional transmit diversity and enhanced spectral efficiency 2. In the STBC-SM scheme, both STBC symbols and the indices of the transmit antennas from which these symbols are transmitted, carry information. The end-to-end reliability of the STBC-SM system can be further enhanced by exploiting the cooperative diversity along with spatial diversity. 1 R. Y. Mesleh, H. Haas, S. Sinanovic, C. W. Ahn, and S. Yun, Spatial modulation, IEEE Transactions on Vehicular Technology, vol. 57, no. 4, pp , E. Basar, U. Aygolu, E. Panayirci, and H. V. Poor, Space-time block coded spatial modulation, IEEE Transactions on Communications, vol. 59, no. 3, pp , 2011.

4 I Figure: Selective DF based SM MIMO-STBC Cooperative System.

5 II Kronecker channel model is employed to model MIMO channel matrices with receive/transmit antenna correlation as 3, H SD =R 1 2 d HSD R T 2 s, H SR =R 1 2 r HSR R T 2 s, H RD =R 1 2 d HRD R T 2 r, where R s,r d and R r denote the spatial correlation matrices at the source, destination and relay nodes respectively. The coefficients of H SD, H SR and H RD are distributed as CN(0,δ 2 sd ), CN(0,δ2 sr ) and CN(0,δ2 rd ) respectively. 3 D.-S. Shiu, G. J. Foschini, M. J. Gans, and J. M. Kahn, Fading correlation and its effect on the capacity of multielement antenna systems, IEEE Transactions on Communications, vol. 48, no. 3, pp , 2000.

6 III The received codeword matrices Y SD C Nd T,Y SR C Nr T at the destination and relay respectively in the first phase are given as, P0 Y SD = H SD X+W SD, N a P0 Y SR = H SR X+W SR, N a where X C Ns T denotes the transmitted codeword, P 0 is the transmit power at the source, N a denotes number of active antennas at the transmitter. Entries of matrices W SD C N d T and W SR C Nr T are symmetric complex Gaussian with variance η 0. (1)

7 IV The received codeword matrix Y RD C Nd T at the destination, in the second phase, is given as, P1 Y RD = H RD X+W RD, (2) N a where P 1 is the transmit power at the relay, Entries of matrix W RD C N d T is symmetric complex Gaussian with variance η 0 /2 per dimension.

8 Pair-wise Error Probability (PEP) I Theorem (Average PEP) The average PEP bound at the destination for the cooperative SM MIMO-STBC system is given by C C P e Pr(X i ) P e (X i X j ), (3) i=1 j=1,j i where the end-to-end PEP for the error event X i X j is P e (X i X j ) =P S D (X i X j ) P e S R (X i) +P S D,R D (X i X j ) (1 P e S R (X i)), and the average error probability at the relay is C PS R e (X i) = P S R (X i X k ). k=1,k i

9 Pair-wise Error Probability (PEP) II The PEP for the error event corresponding to the transmitted codeword X i C being confused for codeword X k C at the relay, where k i, conditioned on H SR, is given as 4, P P S R (X i X k H SR ) =Q 0 H SR (X i X k ) 2 F, 2N a η 0 = 1 π π/2 0 exp( P0 H SR (X i X k ) 2 F 4N a η 0 sin 2 θ ) dθ, 4 N. Varshney, A. Krishna, and A. K. Jagannatham, Selective DF protocol for MIMO STBC based single/multiple relay cooperative communication: End-to-end performance and optimal power allocation, IEEE Transactions on Communications, vol. 63, no. 7, pp , 2015.

10 Pair-wise Error Probability (PEP) III The average PEP at the relay can now be obtained as, π/2 1 P0 H SR (X i X k ) P S R (X i X k )=E HSR exp( 2 ) F π 4N a η 0 sin 2 dθ θ, = 1 π π/2 0 0 φ ik H SR ik 2 F ( ) P 0 4N a η 0 sin 2 dθ, (4) θ where φ ik H SR ik 2 F(s) denotes the moment generating function of H SR (X i X k ) 2 F = H SR ik 2 F, where ik = X i X k.

11 Pair-wise Error Probability (PEP) IV The moment generating function of H SR ik 2 F obtained as 5, can be φ ik H SR ik 2 F(s) = γa ik a=1b=1 γb (1 sµ ik a λ b δ2 SR ) 1, where µ ik a is the a th eigenvalue of the matrix ik H ik R s, λ b is the bth eigenvalue of the correlation matrix R r, γa ik denotes the rank of the matrix ik H ik R s, γb denotes the rank of the correlation matrix R r. 5 A. Hedayat, H. Shah, and A. Nosratinia, Analysis of space-time coding in correlated fading channels, IEEE Transactions on Wireless Communications, vol. 4, no. 6, pp , 2005.

12 Pair-wise Error Probability (PEP) V Using φ ik H SR ik 2 F(s) = γa ik a=1b=1 γb (1 sµ ik a λ b δ2 SR ) 1, the average error probability at the relay can be solved as, π/2 P S R (X i X k ) = 1 π 0 where = G γa ik γ b a=1b=1 γa ik γ b a=1b=1 (1+ P 0µ ik a λ ) 1 b δ2 SR 4N a η 0 sin 2 dθ θ (1+ P 0µ ik a λ ) b δ2 SR, 4N a η 0 sin 2 (5) θ The quantity G(v(θ)) is defined as G(v(θ))= 1 π π/2 1 v(θ) dθ. 0

13 Pair-wise Error Probability (PEP) VI Following a similar approach, the average PEP of confusion event X i X j at the destination when the relay decodes all the symbols erroneously, can be solved as, γ ij ( ) a γ b P S D (X i X j )=G 1+ P 0µ ij aλ b δsd 2, 4N a η 0 sin 2 (6) θ a=1b=1 where µ ij a is the a th eigenvalue of the matrix ij H ij R s, λ b is the b th eigenvalue of the correlation matrix R d, γa ij denotes the rank of the matrix ij H ij R s, γ b denotes the rank of the correlation matrix R d.

14 Pair-wise Error Probability (PEP) VII The average PEP of the error event X i X j at the destination when the relay decodes all the symbols correctly, is given as, P S D,R D (X i X j ) = E HSD,H RD { 1 π = G ( γ ij a γ b a=1b=1 π/2 0 exp( P0 H SD ij 2 F P 1 H RD ij 2 F 4N a η 0 sin 2 θ (1+ P 0µ ij aλ b δ 2 SD 4N a η 0 sin 2 θ ) γp ij γ q ( p=1q=1 1+ P 1µ ij pλ q δ 2 RD 4N a η 0 sin 2 θ ) } dθ )) where µ ij p is the pth eigenvalue of the matrix ij H ij R r, λ q represents the q th eigenvalue of the correlation matrix R d, γp ij denotes the rank of the matrix ij H ij R r, γ q denotes the rank of the correlation matrix R d.,

15 Diversity Order Analysis I Using the fact that at high SNR 1 P e S R (X i) 1, 1+ P0µij a λ bδsd 2 4N aη 0 sin 2 θ P0µij a λ b δsd 2 4N aη 0 sin 2 θ 1+ P1µij p λqδ2 RD 4N aη 0 sin 2 θ C P e i=1,1+ P0µik a λ b δ2 SR 4N aη 0 sin 2 θ P0µik a λ b δ2 SR 1, the asymptotic PEP is given as, [ C C j=1, j i k=1, k i 4N aη 0 sin 2 θ and ( ) (γ ij P a γ b+γ ik a γ b ) ( ) (γ ij P a γ b+γ ij γq)] p A 1 +A 2 η 0 η 0 ( ) (γaγ P b +γ aγb ) ( ) (γaγ P b +γ pγ q) =C 1 +C 2, (7) η 0 η 0 where γ ij a = rank( ij H ij R s) = γ a and γ ij p = rank( ij H ij R r) = γ p. This assumption is true if spatial correlation matrices have full rank and all the codeword difference-matrices have equal rank.

16 Diversity Order Analysis II The diversity order of the above system is log(p lim ( e) P log P = γ a γ b +min{γ a γb,γ pγ q } η η0) 0 For uncorrelated systems, the diversity order is γ a N d +min{γ a N r,γ p N d }, where γ a = γ p denotes the rank of the matrix ij H ij. This result shows that both the performance of the system and the resulting diversity order depend on the the correlation. If the correlation matrix at any of the nodes is not full rank, the diversity order of the system decreases.

17 Optimal Power Allocation I The convex optimization problem for optimal source-relay power allocation can be formulated as, { } α β min + a γaγ, b 0 a γpγq 1 (8) where α=c 1 a0 =1 ( P η0 a γaγ b+γ aγ b 0 s.t. a 0 +a 1 = 1, ) (γaγ b +γ aγ b ) and β=c 2 a0 =1,a 1 =1 ( P η0 ) (γaγ b +γ pγ q).

18 Optimal Power Allocation II Theorem (Optimal Power Allocation) One non-negative zero of the polynomial equation below α(γ a γ b +γ a γ b )(1 a 0) 1+γpγq β(γ a γ b +γ p γ q )a 1+γaγ b 0 +β(γ a γ b )a γaγ b 0 =0, determines the optimal power factor a0 at the source and hence, the optimal powers at the source and relay are P0 = a 0 P and P1 = (1 a 0 )P for a given total cooperative power budget P.

19 Simulation Result I: PEP Performance 10 0 Pair wise Error Probability (PEP) STBC (Simulated) [6] STBC SM (Simulated) [7] Cooperative STBC (Simulated) [8] Proposed Cooperative STBC SM (Simulated) Proposed Cooperative STBC SM (Analytical) SNR (db) Asymptotic Bound, Diversity Order = 8 Figure: Comparison of the PEP performance of the proposed scheme with that of existing works for unity average channel gains V. Tarokh, H. Jafarkhani, and A. R. Calderbank, Space-time block coding for wireless communications: performance results, IEEE Journal on Selected Areas in Communications, vol. 17, no. 3, pp , E. Basar, U. Aygolu, E. Panayirci, and H. V. Poor, Space-time block coded spatial modulation, IEEE Transactions on Communications, vol. 59, no. 3, pp , N. Varshney, A. Krishna, and A. K. Jagannatham, Selective DF protocol for MIMO STBC based single/multiple relay cooperative communication: End-to-end performance and optimal power allocation, IEEE Transactions on Communications, vol. 63, no. 7, pp , 2015.

20 Simulation Result II: PEP Performance 10 0 Pair wise Error Probability (PEP) PEP (Simulated), r = 0 PEP (Analytical), r = 0 PEP (Simulated), r = PEP (Analytical), r = 0.1 PEP (Simulated), r = PEP (Analytical), r = 0.5 PEP (Simulated), r = 0.9 PEP (Analytical), r = SNR (db) Figure: PEP performance of the proposed SM MIMO-STBC based selective DF cooperative scheme over correlated Rayleigh fading links.

21 Simulation Result III: PEP Performance 10 0 Pair wise Error Probability (PEP) Uniform Power Scenario I Optimal Power Scenario I 10 6 Uniform Power = Optimal Power Scenario II Uniform Power Scenario III Optimal Power Scenario III SNR(dB) Figure: PEP Performance of the cooperative SM MIMO-STBC system using optimal/equal power allocation for various channel conditions. Scenario I: δ 2 sr =δ2 sd =δ2 rd =1, Scenario II: δ 2 sr =100,δ2 sd =δ2 rd =1, Scenario III: δ 2 sr=δ 2 sd =1,δ2 rd =100.

22 Closed form analytical expressions have been derived for the end-to-end PEP, diversity order and optimal power allocation for a selective DF based SM MIMO-STBC cooperative system considering receive/transmit antenna correlation. It has been observed that the end-to-end performance of selective DF based SM MIMO-STBC cooperative systems is superior in comparison to that of STBC, STBC-SM and STBC based cooperative systems.

23 Thank You

Performance Analysis of MIMO-OSTBC based Selective DF Cooperative Wireless System with Node Mobility and Channel Estimation Errors

Performance Analysis of MIMO-OSTBC based Selective DF Cooperative Wireless System with Node Mobility and Channel Estimation Errors System Model Performance Analysis of MIMO-OSTBC based Selective DF Cooperative Wireless System with Node Mobility and Channel Estimation Errors Multimedia Wireless Networks (MWN) Group, Indian Institute

More information

Advanced Spatial Modulation Techniques for MIMO Systems

Advanced Spatial Modulation Techniques for MIMO Systems Advanced Spatial Modulation Techniques for MIMO Systems Ertugrul Basar Princeton University, Department of Electrical Engineering, Princeton, NJ, USA November 2011 Outline 1 Introduction 2 Spatial Modulation

More information

Lecture 5: Antenna Diversity and MIMO Capacity Theoretical Foundations of Wireless Communications 1. Overview. CommTh/EES/KTH

Lecture 5: Antenna Diversity and MIMO Capacity Theoretical Foundations of Wireless Communications 1. Overview. CommTh/EES/KTH : Antenna Diversity and Theoretical Foundations of Wireless Communications Wednesday, May 4, 206 9:00-2:00, Conference Room SIP Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless Communication

More information

Capacity Region of the Two-Way Multi-Antenna Relay Channel with Analog Tx-Rx Beamforming

Capacity Region of the Two-Way Multi-Antenna Relay Channel with Analog Tx-Rx Beamforming Capacity Region of the Two-Way Multi-Antenna Relay Channel with Analog Tx-Rx Beamforming Authors: Christian Lameiro, Alfredo Nazábal, Fouad Gholam, Javier Vía and Ignacio Santamaría University of Cantabria,

More information

Orthogonal Frequency Division Multiplexing with Index Modulation

Orthogonal Frequency Division Multiplexing with Index Modulation Globecom 2012 - Wireless Communications Symposium Orthogonal Frequency Division Multiplexing with Index Modulation Ertuğrul Başar, Ümit Aygölü, Erdal Panayırcı and H. Vincent Poor Istanbul Technical University,

More information

Differential spatial modulation for high-rate transmission systems

Differential spatial modulation for high-rate transmission systems Nguyen et al. EURASIP Journal on Wireless Communications and Networking (2018) 2018:6 DOI 10.1186/s13638-017-1013-1 RESEARCH Open Access Differential spatial modulation for high-rate transmission systems

More information

Reliability of Radio-mobile systems considering fading and shadowing channels

Reliability of Radio-mobile systems considering fading and shadowing channels Reliability of Radio-mobile systems considering fading and shadowing channels Philippe Mary ETIS UMR 8051 CNRS, ENSEA, Univ. Cergy-Pontoise, 6 avenue du Ponceau, 95014 Cergy, France Philippe Mary 1 / 32

More information

On the Performance of. Golden Space-Time Trellis Coded Modulation over MIMO Block Fading Channels

On the Performance of. Golden Space-Time Trellis Coded Modulation over MIMO Block Fading Channels On the Performance of 1 Golden Space-Time Trellis Coded Modulation over MIMO Block Fading Channels arxiv:0711.1295v1 [cs.it] 8 Nov 2007 Emanuele Viterbo and Yi Hong Abstract The Golden space-time trellis

More information

SAGE-based Estimation Algorithms for Time-varying Channels in Amplify-and-Forward Cooperative Networks

SAGE-based Estimation Algorithms for Time-varying Channels in Amplify-and-Forward Cooperative Networks SAGE-based Estimation Algorithms for Time-varying Channels in Amplify-and-Forward Cooperative Networks Nico Aerts and Marc Moeneclaey Department of Telecommunications and Information Processing Ghent University

More information

Multi-Antenna Cooperative Wireless Systems: A Diversity-Multiplexing Tradeoff Perspective

Multi-Antenna Cooperative Wireless Systems: A Diversity-Multiplexing Tradeoff Perspective IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. X, NO. X, DECEMBER 007 Multi-Antenna Cooperative Wireless Systems: A Diversity-Multiplexing Tradeoff Perspective Melda Yuksel, Student Member, IEEE, and Elza

More information

Multiple Antennas in Wireless Communications

Multiple Antennas in Wireless Communications Multiple Antennas in Wireless Communications Luca Sanguinetti Department of Information Engineering Pisa University luca.sanguinetti@iet.unipi.it April, 2009 Luca Sanguinetti (IET) MIMO April, 2009 1 /

More information

Lecture 9: Diversity-Multiplexing Tradeoff Theoretical Foundations of Wireless Communications 1

Lecture 9: Diversity-Multiplexing Tradeoff Theoretical Foundations of Wireless Communications 1 : Diversity-Multiplexing Tradeoff Theoretical Foundations of Wireless Communications 1 Rayleigh Friday, May 25, 2018 09:00-11:30, Kansliet 1 Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless

More information

Lecture 9: Diversity-Multiplexing Tradeoff Theoretical Foundations of Wireless Communications 1. Overview. Ragnar Thobaben CommTh/EES/KTH

Lecture 9: Diversity-Multiplexing Tradeoff Theoretical Foundations of Wireless Communications 1. Overview. Ragnar Thobaben CommTh/EES/KTH : Diversity-Multiplexing Tradeoff Theoretical Foundations of Wireless Communications 1 Rayleigh Wednesday, June 1, 2016 09:15-12:00, SIP 1 Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless Communication

More information

A robust transmit CSI framework with applications in MIMO wireless precoding

A robust transmit CSI framework with applications in MIMO wireless precoding A robust transmit CSI framework with applications in MIMO wireless precoding Mai Vu, and Arogyaswami Paulraj Information Systems Laboratory, Department of Electrical Engineering Stanford University, Stanford,

More information

A Precoding Method for Multiple Antenna System on the Riemannian Manifold

A Precoding Method for Multiple Antenna System on the Riemannian Manifold Journal of Communications Vol. 9, No. 2, February 2014 A Precoding Method for Multiple Antenna System on the Riemannian Manifold Lin Zhang1 and S. H. Leung2 1 Department of Electronic Engineering, City

More information

Schur-convexity of the Symbol Error Rate in Correlated MIMO Systems with Precoding and Space-time Coding

Schur-convexity of the Symbol Error Rate in Correlated MIMO Systems with Precoding and Space-time Coding Schur-convexity of the Symbol Error Rate in Correlated MIMO Systems with Precoding and Space-time Coding RadioVetenskap och Kommunikation (RVK 08) Proceedings of the twentieth Nordic Conference on Radio

More information

Half-Duplex Gaussian Relay Networks with Interference Processing Relays

Half-Duplex Gaussian Relay Networks with Interference Processing Relays Half-Duplex Gaussian Relay Networks with Interference Processing Relays Bama Muthuramalingam Srikrishna Bhashyam Andrew Thangaraj Department of Electrical Engineering Indian Institute of Technology Madras

More information

Differential Full Diversity Spatial Modulation using Amplitude Phase Shift Keying

Differential Full Diversity Spatial Modulation using Amplitude Phase Shift Keying RADIOENGINEERING, VOL 7, NO 1, APRIL 018 151 Differential ull Diversity Spatial Modulation using Amplitude Phase Shift Keying Kavishaur DWARIKA 1, Hongjun XU 1, 1 School of Engineering, University of KwaZulu-Natal,

More information

Secrecy Outage Performance of Cooperative Relay Network With Diversity Combining

Secrecy Outage Performance of Cooperative Relay Network With Diversity Combining Secrecy Outage erformance of Cooperative Relay Network With Diversity Combining Khyati Chopra Dept. of lectrical ngineering Indian Institute of Technology, Delhi New Delhi-110016, India mail: eez148071@ee.iitd.ac.in

More information

Random Matrices and Wireless Communications

Random Matrices and Wireless Communications Random Matrices and Wireless Communications Jamie Evans Centre for Ultra-Broadband Information Networks (CUBIN) Department of Electrical and Electronic Engineering University of Melbourne 3.5 1 3 0.8 2.5

More information

2318 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 54, NO. 6, JUNE Mai Vu, Student Member, IEEE, and Arogyaswami Paulraj, Fellow, IEEE

2318 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 54, NO. 6, JUNE Mai Vu, Student Member, IEEE, and Arogyaswami Paulraj, Fellow, IEEE 2318 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 54, NO. 6, JUNE 2006 Optimal Linear Precoders for MIMO Wireless Correlated Channels With Nonzero Mean in Space Time Coded Systems Mai Vu, Student Member,

More information

Single-Symbol ML Decodable Distributed STBCs for Partially-Coherent Cooperative Networks

Single-Symbol ML Decodable Distributed STBCs for Partially-Coherent Cooperative Networks This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the ICC 2008 proceedings Single-Symbol ML Decodable Distributed STBCs for

More information

Trust Degree Based Beamforming for Multi-Antenna Cooperative Communication Systems

Trust Degree Based Beamforming for Multi-Antenna Cooperative Communication Systems Introduction Main Results Simulation Conclusions Trust Degree Based Beamforming for Multi-Antenna Cooperative Communication Systems Mojtaba Vaezi joint work with H. Inaltekin, W. Shin, H. V. Poor, and

More information

Performance Analysis of a Threshold-Based Relay Selection Algorithm in Wireless Networks

Performance Analysis of a Threshold-Based Relay Selection Algorithm in Wireless Networks Communications and Networ, 2010, 2, 87-92 doi:10.4236/cn.2010.22014 Published Online May 2010 (http://www.scirp.org/journal/cn Performance Analysis of a Threshold-Based Relay Selection Algorithm in Wireless

More information

A Coding Strategy for Wireless Networks with no Channel Information

A Coding Strategy for Wireless Networks with no Channel Information A Coding Strategy for Wireless Networks with no Channel Information Frédérique Oggier and Babak Hassibi Abstract In this paper, we present a coding strategy for wireless relay networks, where we assume

More information

ABSTRACT. Cooperative Detection and Network Coding in Wireless Networks. Mohammed W. Baidas, Master of Science, 2009

ABSTRACT. Cooperative Detection and Network Coding in Wireless Networks. Mohammed W. Baidas, Master of Science, 2009 ABSTRACT Title of Thesis: Cooperative Detection and Network Coding in Wireless Networks Mohammed W. Baidas, Master of Science, 2009 Thesis directed by: Professor K. J. Ray Liu Department of Electrical

More information

Training-Symbol Embedded, High-Rate Complex Orthogonal Designs for Relay Networks

Training-Symbol Embedded, High-Rate Complex Orthogonal Designs for Relay Networks Training-Symbol Embedded, High-Rate Complex Orthogonal Designs for Relay Networks J Harshan Dept of ECE, Indian Institute of Science Bangalore 56001, India Email: harshan@eceiiscernetin B Sundar Rajan

More information

Ergodic and Outage Capacity of Narrowband MIMO Gaussian Channels

Ergodic and Outage Capacity of Narrowband MIMO Gaussian Channels Ergodic and Outage Capacity of Narrowband MIMO Gaussian Channels Yang Wen Liang Department of Electrical and Computer Engineering The University of British Columbia April 19th, 005 Outline of Presentation

More information

TX Diversity with Array-Interference Gain Date:

TX Diversity with Array-Interference Gain Date: TX Diversity with Array-Interference Gain Date: 2013-09-18 Name Company Address Phone email Gabriel Villardi NICT 3-4 Hikarion-Oka, Yokosuka, Japan +81-46-847-5438 gpvillardi@nict.go.jp Pin-Hsun Lin NICT

More information

Tight Lower Bounds on the Ergodic Capacity of Rayleigh Fading MIMO Channels

Tight Lower Bounds on the Ergodic Capacity of Rayleigh Fading MIMO Channels Tight Lower Bounds on the Ergodic Capacity of Rayleigh Fading MIMO Channels Özgür Oyman ), Rohit U. Nabar ), Helmut Bölcskei 2), and Arogyaswami J. Paulraj ) ) Information Systems Laboratory, Stanford

More information

Soft-Decision-and-Forward Protocol for Cooperative Communication Networks with Multiple Antennas

Soft-Decision-and-Forward Protocol for Cooperative Communication Networks with Multiple Antennas Soft-Decision-and-Forward Protocol for Cooperative Communication Networks with Multiple Antenn Jae-Dong Yang, Kyoung-Young Song Department of EECS, INMC Seoul National University Email: {yjdong, sky6174}@ccl.snu.ac.kr

More information

Exploiting Partial Channel Knowledge at the Transmitter in MISO and MIMO Wireless

Exploiting Partial Channel Knowledge at the Transmitter in MISO and MIMO Wireless Exploiting Partial Channel Knowledge at the Transmitter in MISO and MIMO Wireless SPAWC 2003 Rome, Italy June 18, 2003 E. Yoon, M. Vu and Arogyaswami Paulraj Stanford University Page 1 Outline Introduction

More information

Optimization of relay placement and power allocation for decode-and-forward cooperative relaying over correlated shadowed fading channels

Optimization of relay placement and power allocation for decode-and-forward cooperative relaying over correlated shadowed fading channels Han et al. EURASIP Journal on Wireless Communications and Networking 4, 4:4 RESEARCH Open Access Optimization of relay placement and power allocation for decode-and-forwa cooperative relaying over correlated

More information

Single-User MIMO systems: Introduction, capacity results, and MIMO beamforming

Single-User MIMO systems: Introduction, capacity results, and MIMO beamforming Single-User MIMO systems: Introduction, capacity results, and MIMO beamforming Master Universitario en Ingeniería de Telecomunicación I. Santamaría Universidad de Cantabria Contents Introduction Multiplexing,

More information

Diversity Performance of a Practical Non-Coherent Detect-and-Forward Receiver

Diversity Performance of a Practical Non-Coherent Detect-and-Forward Receiver Diversity Performance of a Practical Non-Coherent Detect-and-Forward Receiver Michael R. Souryal and Huiqing You National Institute of Standards and Technology Advanced Network Technologies Division Gaithersburg,

More information

Variable-Rate Two-Phase Collaborative Communication Protocols for Wireless Networks

Variable-Rate Two-Phase Collaborative Communication Protocols for Wireless Networks Variable-Rate Two-Phase Collaborative Communication Protocols for Wireless Networks Hideki Ochiai Department of Electrical and Computer Engineering, Yokohama National University 79-5 Tokiwadai, Hodogaya-ku,

More information

Unifying Analysis of Ergodic MIMO Capacity in Correlated Rayleigh Fading Environments

Unifying Analysis of Ergodic MIMO Capacity in Correlated Rayleigh Fading Environments Unifying Analysis of Ergodic MIMO Capacity in Correlated Rayleigh Fading Environments Mario Kiessling,, Joachim Speidel, Markus Reinhar Institute of elecommunications, University of Stuttgart, Germany

More information

Asymptotic SER and Outage Probability of MIMO MRC in Correlated Fading

Asymptotic SER and Outage Probability of MIMO MRC in Correlated Fading Asymptotic SER and Outage Probability of MIMO MRC in Correlated Fading Shi Jin, Student Member, IEEE, Matthew R. McKay, Student Member, IEEE, Xiqi Gao, Member, IEEE, and Iain B. Collings, Senior Member,

More information

Quantifying the Performance Gain of Direction Feedback in a MISO System

Quantifying the Performance Gain of Direction Feedback in a MISO System Quantifying the Performance Gain of Direction Feedback in a ISO System Shengli Zhou, Jinhong Wu, Zhengdao Wang 3, and ilos Doroslovacki Dept. of Electrical and Computer Engineering, University of Connecticut

More information

Maximum Achievable Diversity for MIMO-OFDM Systems with Arbitrary. Spatial Correlation

Maximum Achievable Diversity for MIMO-OFDM Systems with Arbitrary. Spatial Correlation Maximum Achievable Diversity for MIMO-OFDM Systems with Arbitrary Spatial Correlation Ahmed K Sadek, Weifeng Su, and K J Ray Liu Department of Electrical and Computer Engineering, and Institute for Systems

More information

Limited Feedback in Wireless Communication Systems

Limited Feedback in Wireless Communication Systems Limited Feedback in Wireless Communication Systems - Summary of An Overview of Limited Feedback in Wireless Communication Systems Gwanmo Ku May 14, 17, and 21, 2013 Outline Transmitter Ant. 1 Channel N

More information

Diversity-Multiplexing Tradeoff of Asynchronous Cooperative Diversity in Wireless Networks

Diversity-Multiplexing Tradeoff of Asynchronous Cooperative Diversity in Wireless Networks Diversity-Multiplexing Tradeoff of Asynchronous Cooperative Diversity in Wireless Networks Shuangqing Wei Abstract Synchronization of relay nodes is an important and critical issue in exploiting cooperative

More information

Blind Channel Identification in (2 1) Alamouti Coded Systems Based on Maximizing the Eigenvalue Spread of Cumulant Matrices

Blind Channel Identification in (2 1) Alamouti Coded Systems Based on Maximizing the Eigenvalue Spread of Cumulant Matrices Blind Channel Identification in (2 1) Alamouti Coded Systems Based on Maximizing the Eigenvalue Spread of Cumulant Matrices Héctor J. Pérez-Iglesias 1, Daniel Iglesia 1, Adriana Dapena 1, and Vicente Zarzoso

More information

Transmit Directions and Optimality of Beamforming in MIMO-MAC with Partial CSI at the Transmitters 1

Transmit Directions and Optimality of Beamforming in MIMO-MAC with Partial CSI at the Transmitters 1 2005 Conference on Information Sciences and Systems, The Johns Hopkins University, March 6 8, 2005 Transmit Directions and Optimality of Beamforming in MIMO-MAC with Partial CSI at the Transmitters Alkan

More information

Optimum Power Allocation in Fading MIMO Multiple Access Channels with Partial CSI at the Transmitters

Optimum Power Allocation in Fading MIMO Multiple Access Channels with Partial CSI at the Transmitters Optimum Power Allocation in Fading MIMO Multiple Access Channels with Partial CSI at the Transmitters Alkan Soysal Sennur Ulukus Department of Electrical and Computer Engineering University of Maryland,

More information

Space-Time Diversity Enhancements Using Collaborative Communications

Space-Time Diversity Enhancements Using Collaborative Communications IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. XX, NO. YY, MONTH 2005 1 Space-Time Diversity Enhancements Using Collaborative Communications Patrick Mitran, Student Member, IEEE, Hideki Ochiai, Member,

More information

Algebraic Methods for Wireless Coding

Algebraic Methods for Wireless Coding Algebraic Methods for Wireless Coding Frédérique Oggier frederique@systems.caltech.edu California Institute of Technology UC Davis, Mathematics Department, January 31st 2007 Outline The Rayleigh fading

More information

Lecture 8: MIMO Architectures (II) Theoretical Foundations of Wireless Communications 1. Overview. Ragnar Thobaben CommTh/EES/KTH

Lecture 8: MIMO Architectures (II) Theoretical Foundations of Wireless Communications 1. Overview. Ragnar Thobaben CommTh/EES/KTH MIMO : MIMO Theoretical Foundations of Wireless Communications 1 Wednesday, May 25, 2016 09:15-12:00, SIP 1 Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless Communication 1 / 20 Overview MIMO

More information

Lecture 7 MIMO Communica2ons

Lecture 7 MIMO Communica2ons Wireless Communications Lecture 7 MIMO Communica2ons Prof. Chun-Hung Liu Dept. of Electrical and Computer Engineering National Chiao Tung University Fall 2014 1 Outline MIMO Communications (Chapter 10

More information

Transmit Diversity for Arrays in Correlated Rayleigh Fading

Transmit Diversity for Arrays in Correlated Rayleigh Fading 1 Transmit Diversity for Arrays in Correlated Rayleigh Fading Cornelius van Rensburg and Benjamin Friedlander C van Rensburg is with Samsung Telecommunications America. E-mail: cdvanren@ece.ucdavis.edu

More information

12.4 Known Channel (Water-Filling Solution)

12.4 Known Channel (Water-Filling Solution) ECEn 665: Antennas and Propagation for Wireless Communications 54 2.4 Known Channel (Water-Filling Solution) The channel scenarios we have looed at above represent special cases for which the capacity

More information

When does vectored Multiple Access Channels (MAC) optimal power allocation converge to an FDMA solution?

When does vectored Multiple Access Channels (MAC) optimal power allocation converge to an FDMA solution? When does vectored Multiple Access Channels MAC optimal power allocation converge to an FDMA solution? Vincent Le Nir, Marc Moonen, Jan Verlinden, Mamoun Guenach Abstract Vectored Multiple Access Channels

More information

Dirty Paper Coding vs. TDMA for MIMO Broadcast Channels

Dirty Paper Coding vs. TDMA for MIMO Broadcast Channels TO APPEAR IEEE INTERNATIONAL CONFERENCE ON COUNICATIONS, JUNE 004 1 Dirty Paper Coding vs. TDA for IO Broadcast Channels Nihar Jindal & Andrea Goldsmith Dept. of Electrical Engineering, Stanford University

More information

Ergodic and Outage Capacity of Narrowband MIMO Gaussian Channels

Ergodic and Outage Capacity of Narrowband MIMO Gaussian Channels Ergodic and Outage Capacity of Narrowband MIMO Gaussian Channels Yang Wen Liang Department of Electrical and Computer Engineering The University of British Columbia, Vancouver, British Columbia Email:

More information

Generalized Spatial Modulation Aided MmWave MIMO with Sub-Connected Hybrid Precoding Scheme

Generalized Spatial Modulation Aided MmWave MIMO with Sub-Connected Hybrid Precoding Scheme Generalized Spatial Modulation Aided MmWave MIMO with Sub-Connected Hybrid Precoding Scheme Longzhuang He, Jintao Wang, and Jian Song Department of Electronic Engineering, Tsinghua University, Beijing,

More information

Title. Author(s)Tsai, Shang-Ho. Issue Date Doc URL. Type. Note. File Information. Equal Gain Beamforming in Rayleigh Fading Channels

Title. Author(s)Tsai, Shang-Ho. Issue Date Doc URL. Type. Note. File Information. Equal Gain Beamforming in Rayleigh Fading Channels Title Equal Gain Beamforming in Rayleigh Fading Channels Author(s)Tsai, Shang-Ho Proceedings : APSIPA ASC 29 : Asia-Pacific Signal Citationand Conference: 688-691 Issue Date 29-1-4 Doc URL http://hdl.handle.net/2115/39789

More information

Wireless Communications Lecture 10

Wireless Communications Lecture 10 Wireless Communications Lecture 1 [SNR per symbol and SNR per bit] SNR = P R N B = E s N BT s = E b N BT b For BPSK: T b = T s, E b = E s, and T s = 1/B. Raised cosine pulse shaper for other pulses. T

More information

Achieving the Full MIMO Diversity-Multiplexing Frontier with Rotation-Based Space-Time Codes

Achieving the Full MIMO Diversity-Multiplexing Frontier with Rotation-Based Space-Time Codes Achieving the Full MIMO Diversity-Multiplexing Frontier with Rotation-Based Space-Time Codes Huan Yao Lincoln Laboratory Massachusetts Institute of Technology Lexington, MA 02420 yaohuan@ll.mit.edu Gregory

More information

Multiple Antennas for MIMO Communications - Basic Theory

Multiple Antennas for MIMO Communications - Basic Theory Multiple Antennas for MIMO Communications - Basic Theory 1 Introduction The multiple-input multiple-output (MIMO) technology (Fig. 1) is a breakthrough in wireless communication system design. It uses

More information

On the Robustness of Algebraic STBCs to Coefficient Quantization

On the Robustness of Algebraic STBCs to Coefficient Quantization 212 Australian Communications Theory Workshop (AusCTW) On the Robustness of Algebraic STBCs to Coefficient Quantization J. Harshan Dept. of Electrical and Computer Systems Engg., Monash University Clayton,

More information

Optimal Power Allocation for Energy Recycling Assisted Cooperative Communications

Optimal Power Allocation for Energy Recycling Assisted Cooperative Communications Optimal Power llocation for Energy Recycling ssisted Cooperative Communications George. Ropokis, M. Majid Butt, Nicola Marchetti and Luiz. DaSilva CONNECT Centre, Trinity College, University of Dublin,

More information

Degrees-of-Freedom for the 4-User SISO Interference Channel with Improper Signaling

Degrees-of-Freedom for the 4-User SISO Interference Channel with Improper Signaling Degrees-of-Freedom for the -User SISO Interference Channel with Improper Signaling C Lameiro and I Santamaría Dept of Communications Engineering University of Cantabria 9005 Santander Cantabria Spain Email:

More information

Achievable Rates and Optimal Resource Allocation for Imperfectly-Known Fading Relay Channels

Achievable Rates and Optimal Resource Allocation for Imperfectly-Known Fading Relay Channels Achievable Rates and Optimal Resource Allocation for Imperfectly-Known Fading Relay hannels Junwei Zhang, Mustafa enk Gursoy Department of Electrical Engineering University of Nebraska-Lincoln, Lincoln,

More information

Capacity of multiple-input multiple-output (MIMO) systems in wireless communications

Capacity of multiple-input multiple-output (MIMO) systems in wireless communications 15/11/02 Capacity of multiple-input multiple-output (MIMO) systems in wireless communications Bengt Holter Department of Telecommunications Norwegian University of Science and Technology 1 Outline 15/11/02

More information

Lecture 4. Capacity of Fading Channels

Lecture 4. Capacity of Fading Channels 1 Lecture 4. Capacity of Fading Channels Capacity of AWGN Channels Capacity of Fading Channels Ergodic Capacity Outage Capacity Shannon and Information Theory Claude Elwood Shannon (April 3, 1916 February

More information

Analysis of Cooperative Communication and Link Layer. Performance under Imperfectly Known Fading Channel. Gains

Analysis of Cooperative Communication and Link Layer. Performance under Imperfectly Known Fading Channel. Gains Analysis of Cooperative Communication and Link Layer Performance under Imperfectly Known Fading Channel Gains by Ali Zarei Ghanavati M.Sc., Sharif University of Technology, 009 B.Sc., University of Tehran,

More information

Lattices and Lattice Codes

Lattices and Lattice Codes Lattices and Lattice Codes Trivandrum School on Communication, Coding & Networking January 27 30, 2017 Lakshmi Prasad Natarajan Dept. of Electrical Engineering Indian Institute of Technology Hyderabad

More information

FULL rate and full diversity codes for the coherent

FULL rate and full diversity codes for the coherent 1432 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, NO. 4, APRIL 2005 The Golden Code: A 2 2 Full-Rate Space Time Code With Nonvanishing Determinants Jean-Claude Belfiore, Member, IEEE, Ghaya Rekaya,

More information

On the Use of Division Algebras for Wireless Communication

On the Use of Division Algebras for Wireless Communication On the Use of Division Algebras for Wireless Communication frederique@systems.caltech.edu California Institute of Technology AMS meeting, Davidson, March 3rd 2007 Outline A few wireless coding problems

More information

Design of Space Time Spreading Matrices

Design of Space Time Spreading Matrices Design of Space Time Spreading Matrices Yibo Jiang, Ralf Koetter, and Andrew Singer Coordinated Science Laboratory Dept. of Electrical and Computer Engineering Univ. of Illinois at Urbana-Champaign Urbana,

More information

Multi-Input Multi-Output Systems (MIMO) Channel Model for MIMO MIMO Decoding MIMO Gains Multi-User MIMO Systems

Multi-Input Multi-Output Systems (MIMO) Channel Model for MIMO MIMO Decoding MIMO Gains Multi-User MIMO Systems Multi-Input Multi-Output Systems (MIMO) Channel Model for MIMO MIMO Decoding MIMO Gains Multi-User MIMO Systems Multi-Input Multi-Output Systems (MIMO) Channel Model for MIMO MIMO Decoding MIMO Gains Multi-User

More information

SOS-BASED BLIND CHANNEL ESTIMATION IN MULTIUSER SPACE-TIME BLOCK CODED SYSTEMS

SOS-BASED BLIND CHANNEL ESTIMATION IN MULTIUSER SPACE-TIME BLOCK CODED SYSTEMS SOS-BASED BLIND CHANNEL ESTIMATION IN MULTIUSER SPACE-TIME BLOCK CODED SYSTEMS Javier Vía, Ignacio Santamaría Dept. of Communications Engineering University of Cantabria, Spain e-mail:jvia,nacho}@gtas.dicom.unican.es

More information

Asymptotic Distortion Performance of Source-Channel Diversity Schemes over Relay Channels

Asymptotic Distortion Performance of Source-Channel Diversity Schemes over Relay Channels Asymptotic istortion Performance of Source-Channel iversity Schemes over Relay Channels Karim G. Seddik 1, Andres Kwasinski 2, and K. J. Ray Liu 1 1 epartment of Electrical and Computer Engineering, 2

More information

Adaptive Space-Time Shift Keying Based Multiple-Input Multiple-Output Systems

Adaptive Space-Time Shift Keying Based Multiple-Input Multiple-Output Systems ACSTSK Adaptive Space-Time Shift Keying Based Multiple-Input Multiple-Output Systems Professor Sheng Chen Electronics and Computer Science University of Southampton Southampton SO7 BJ, UK E-mail: sqc@ecs.soton.ac.uk

More information

Algebraic Multiuser Space Time Block Codes for 2 2 MIMO

Algebraic Multiuser Space Time Block Codes for 2 2 MIMO Algebraic Multiuser Space Time Bloc Codes for 2 2 MIMO Yi Hong Institute of Advanced Telecom. University of Wales, Swansea, UK y.hong@swansea.ac.u Emanuele Viterbo DEIS - Università della Calabria via

More information

WIRELESS COMMUNICATIONS AND COGNITIVE RADIO TRANSMISSIONS UNDER QUALITY OF SERVICE CONSTRAINTS AND CHANNEL UNCERTAINTY

WIRELESS COMMUNICATIONS AND COGNITIVE RADIO TRANSMISSIONS UNDER QUALITY OF SERVICE CONSTRAINTS AND CHANNEL UNCERTAINTY University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Theses, Dissertations, and Student Research from Electrical & Computer Engineering Electrical & Computer Engineering, Department

More information

Approximately achieving the feedback interference channel capacity with point-to-point codes

Approximately achieving the feedback interference channel capacity with point-to-point codes Approximately achieving the feedback interference channel capacity with point-to-point codes Joyson Sebastian*, Can Karakus*, Suhas Diggavi* Abstract Superposition codes with rate-splitting have been used

More information

INVERSE EIGENVALUE STATISTICS FOR RAYLEIGH AND RICIAN MIMO CHANNELS

INVERSE EIGENVALUE STATISTICS FOR RAYLEIGH AND RICIAN MIMO CHANNELS INVERSE EIGENVALUE STATISTICS FOR RAYLEIGH AND RICIAN MIMO CHANNELS E. Jorswieck, G. Wunder, V. Jungnickel, T. Haustein Abstract Recently reclaimed importance of the empirical distribution function of

More information

Fast-Decodable MIMO HARQ Systems

Fast-Decodable MIMO HARQ Systems 1 Fast-Decodable MIMO HARQ Systems Seyyed Saleh Hosseini, Student Member, IEEE, Jamshid Abouei, Senior Member, IEEE, and Murat Uysal, Senior Member, IEEE Abstract This paper presents a comprehensive study

More information

Non Orthogonal Multiple Access for 5G and beyond

Non Orthogonal Multiple Access for 5G and beyond Non Orthogonal Multiple Access for 5G and beyond DIET- Sapienza University of Rome mai.le.it@ieee.org November 23, 2018 Outline 1 5G Era Concept of NOMA Classification of NOMA CDM-NOMA in 5G-NR Low-density

More information

BER Performance Analysis of Cooperative DaF Relay Networks and a New Optimal DaF Strategy

BER Performance Analysis of Cooperative DaF Relay Networks and a New Optimal DaF Strategy 144 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 1, NO. 4, APRIL 11 BER Performance Analysis of Cooperative DaF Relay Networks and a New Optimal DaF Strategy George A. Ropokis, Athanasios A. Rontogiannis,

More information

A Comparison of Cooperative Transmission Schemes for the Multiple Access Relay Channel

A Comparison of Cooperative Transmission Schemes for the Multiple Access Relay Channel A Comparison of Cooperative Transmission Schemes for the ultiple Access elay Channel André Angierski andre.angierski@uni-rostock.de 0/03/7 UNIVESITY OF OSTOCK FACULTY OF COPUTE SCIENCE AND ELECTICAL ENGINEEING

More information

Rate-Optimum Beamforming Transmission in MIMO Rician Fading Channels

Rate-Optimum Beamforming Transmission in MIMO Rician Fading Channels Rate-Optimum Beamforming Transmission in MIMO Rician Fading Channels Dimitrios E. Kontaxis National and Kapodistrian University of Athens Department of Informatics and telecommunications Abstract In this

More information

arxiv:cs/ v1 [cs.it] 11 Sep 2006

arxiv:cs/ v1 [cs.it] 11 Sep 2006 0 High Date-Rate Single-Symbol ML Decodable Distributed STBCs for Cooperative Networks arxiv:cs/0609054v1 [cs.it] 11 Sep 2006 Zhihang Yi and Il-Min Kim Department of Electrical and Computer Engineering

More information

ELEC E7210: Communication Theory. Lecture 10: MIMO systems

ELEC E7210: Communication Theory. Lecture 10: MIMO systems ELEC E7210: Communication Theory Lecture 10: MIMO systems Matrix Definitions, Operations, and Properties (1) NxM matrix a rectangular array of elements a A. an 11 1....... a a 1M. NM B D C E ermitian transpose

More information

Interactive Interference Alignment

Interactive Interference Alignment Interactive Interference Alignment Quan Geng, Sreeram annan, and Pramod Viswanath Coordinated Science Laboratory and Dept. of ECE University of Illinois, Urbana-Champaign, IL 61801 Email: {geng5, kannan1,

More information

IEEE TRANSACTIONS ON COMMUNICATIONS (ACCEPTED TO APPEAR) 1. Diversity-Multiplexing Tradeoff in Selective Cooperation for Cognitive Radio

IEEE TRANSACTIONS ON COMMUNICATIONS (ACCEPTED TO APPEAR) 1. Diversity-Multiplexing Tradeoff in Selective Cooperation for Cognitive Radio IEEE TRANSACTIONS ON COMMUNICATIONS (ACCEPTED TO APPEAR) Diversity-Multiplexing Tradeoff in Selective Cooperation for Cognitive Radio Yulong Zou, Member, IEEE, Yu-Dong Yao, Fellow, IEEE, and Baoyu Zheng,

More information

REPORT DOCUMENTATION PAGE

REPORT DOCUMENTATION PAGE REPORT DOCUMENTATION PAGE Form Approved OMB No. 74-188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions,

More information

Game Theoretic Approach to Power Control in Cellular CDMA

Game Theoretic Approach to Power Control in Cellular CDMA Game Theoretic Approach to Power Control in Cellular CDMA Sarma Gunturi Texas Instruments(India) Bangalore - 56 7, INDIA Email : gssarma@ticom Fernando Paganini Electrical Engineering Department University

More information

Applications of Lattices in Telecommunications

Applications of Lattices in Telecommunications Applications of Lattices in Telecommunications Dept of Electrical and Computer Systems Engineering Monash University amin.sakzad@monash.edu Oct. 2013 1 Sphere Decoder Algorithm Rotated Signal Constellations

More information

Optimum Relay Position for Differential Amplify-and-Forward Cooperative Communications

Optimum Relay Position for Differential Amplify-and-Forward Cooperative Communications Optimum Relay Position for Differential Amplify-and-Forard Cooperative Communications Kazunori Hayashi #1, Kengo Shirai #, Thanongsak Himsoon 1, W Pam Siriongpairat, Ahmed K Sadek 3,KJRayLiu 4, and Hideaki

More information

Design of MMSE Multiuser Detectors using Random Matrix Techniques

Design of MMSE Multiuser Detectors using Random Matrix Techniques Design of MMSE Multiuser Detectors using Random Matrix Techniques Linbo Li and Antonia M Tulino and Sergio Verdú Department of Electrical Engineering Princeton University Princeton, New Jersey 08544 Email:

More information

Sub-modularity and Antenna Selection in MIMO systems

Sub-modularity and Antenna Selection in MIMO systems Sub-modularity and Antenna Selection in MIMO systems Rahul Vaze Harish Ganapathy Point-to-Point MIMO Channel 1 1 Tx H Rx N t N r Point-to-Point MIMO Channel 1 1 Tx H Rx N t N r Antenna Selection Transmit

More information

MULTI-INPUT multi-output (MIMO) channels, usually

MULTI-INPUT multi-output (MIMO) channels, usually 3086 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 57, NO. 8, AUGUST 2009 Worst-Case Robust MIMO Transmission With Imperfect Channel Knowledge Jiaheng Wang, Student Member, IEEE, and Daniel P. Palomar,

More information

The Optimality of Beamforming: A Unified View

The Optimality of Beamforming: A Unified View The Optimality of Beamforming: A Unified View Sudhir Srinivasa and Syed Ali Jafar Electrical Engineering and Computer Science University of California Irvine, Irvine, CA 92697-2625 Email: sudhirs@uciedu,

More information

Finite-SNR Analysis of Partial Relaying with Relay Selection in Channel-coded Cooperative Networks

Finite-SNR Analysis of Partial Relaying with Relay Selection in Channel-coded Cooperative Networks SUBMITTED TO IEEE TRANS WIRELESS COMMUN MAY 205 Finite-SNR Analysis of Partial Relaying with Relay Selection in Channel-coded Cooperative Networks Thang X Vu Member IEEE and Pierre Duhamel Fellow IEEE

More information

Characterizing the Capacity for MIMO Wireless Channels with Non-zero Mean and Transmit Covariance

Characterizing the Capacity for MIMO Wireless Channels with Non-zero Mean and Transmit Covariance Characterizing the Capacity for MIMO Wireless Channels with Non-zero Mean and Transmit Covariance Mai Vu and Arogyaswami Paulraj Information Systems Laboratory, Department of Electrical Engineering Stanford

More information

Homework 5 Solutions. Problem 1

Homework 5 Solutions. Problem 1 Homework 5 Solutions Problem 1 (a Closed form Chernoff upper-bound for the uncoded 4-QAM average symbol error rate over Rayleigh flat fading MISO channel with = 4, assuming transmit-mrc The vector channel

More information

Golden Space-Time Block Coded Modulation

Golden Space-Time Block Coded Modulation Golden Space-Time Block Coded Modulation Laura Luzzi Ghaya Rekaya-Ben Othman Jean-Claude Belfiore and Emanuele Viterbo Télécom ParisTech- École Nationale Supérieure des Télécommunications 46 Rue Barrault

More information