Sept. 2009 Best Paper Award Unified Analysis of Linear Block Precoding for Distributed Antenna Systems Toshiaki Koike-Akino1 Andreas F. Molisch2 Zhifeng Tao3, Philip Orlik3 Toshiyuki Kuze4 1 Harvard University 2 University of Southern California 3 Mitsubishi Electric Research Laboratories 4 Mitsubishi Electric Corporation

Base Station Cooperation Cooperative transmission using distributed base station to achieve diversity gains Increasing coverage Spectrum efficiency Improving security Physical-layer secrecy BS1 Data Rate Control for Intended User Interference Level Control at Unintended Users MS BS2 BS3 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Block Transmission with Cyclic Prefix M transmitting BSs N receiving MSs Frequency-selective fading Precoding Matrix Channel Noise 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Time Reversal (TR) Precoding Intended User BS 1 Reversal Filter BS 2 Unintended User Filter Mismatch BS requires no channel state information available at the other BSs 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Most Existing Precoding Schemes Optimum precoding (OFDM) Unitary precoding (Single Carrier) Time-reversal precoding (MRC, EGC, SLC) Zero-forcing precoding (ZF) Minimum MSE precoding (MMSE) Fourier transform Power/Phase allocation 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Linear Block Precoding for Distributed Antenna Performance Measures Channel capacity Mean-square error (MSE) Achievable secrecy rate Tx power constraint Interference limitation 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Optimum Precoding (OFDM) Optimal power allocation differs from traditional water filling  modified water filling Maximizing capacity Minimizing MSE Maximizing secrecy rate 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Performance Comparison 1-dB decaying 16-path Rayleigh fading channels 1 BS or 5 BSs 1 MS, 2 MSs, or 5 MSs 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Capacity Comparison (1 BS or 5 BSs) 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Scaling Law with Increased BS Capacity of MRC-TR can increase logarithmically with BS compared by unitary precoding for high SNR: Capacity of MRC-TR can increase linearly with BS compared to unitary precoding for low SNR: 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Scaling Law with Increased BS 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Secrecy Rate Comparison (5 BSs, 2 MSs) 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Linear Block Precoding for Distributed Antenna Summary We analyzed linear block precoding for distributed base station systems We derived optimal precoding for maximizing channel capacity, minimizing MSE, and maximizing secrecy rate We compared most existing precoders (TR, OFDM, MMSE, ZF, unitary) We showed the impact of the number of cooperative base stations TR precoding is promising for distributed antennas 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Linear Block Precoding for Distributed Antenna Why Secure? We want to protect private information Cryptography heavily relies on the assumption that any unintended user does not use any powerful computers Information-theoretical security can be important to protect our information because there is no complexity assumption Crypto. Secrecy Powerful Privacy Normal 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna

Optimization Problems 2009.12 Toshiaki Koike-Akino Linear Block Precoding for Distributed Antenna