1. 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

2. 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
Toshiaki Koike-Akino
Linear Block Precoding for Distributed Antenna

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

4. 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
Toshiaki Koike-Akino
Linear Block Precoding for Distributed Antenna

5. 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
Toshiaki Koike-Akino
Linear Block Precoding for Distributed Antenna

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

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

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

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

10. 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:
Toshiaki Koike-Akino
Linear Block Precoding for Distributed Antenna

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

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

13. 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
Toshiaki Koike-Akino
Linear Block Precoding for Distributed Antenna

14. 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
Toshiaki Koike-Akino
Linear Block Precoding for Distributed Antenna

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