Channel Equalization for STBC-Encoded Cooperative Transmissions with Asynchronous Transmitters

1. 1 Channel Equalization for STBC-Encoded Cooperative Transmissions with Asynchronous Transmitters Xiaohua (Edward) Li, Fan Ng, Juite Hwu, Mo Chen Department of Electrical and Computer Engineering State University of New York at Binghamton {xli, fanng1,jhuw1,mchen0}@binghamton.edu http://ucesp.ws.binghamton.edu/~xli

2. 2 Summary Equalization for STBC-encoded cooperative transmissions Asynchronous transmitters create ISI even in flat-fading environment ISI channels adjustable by receiver Viterbi equalizer for near-optimal performance Efficient linear-prediction-based equalizer Performance of cooperative transmission studied by simulations

3. 3 Contents Introduction Cooperative transmissions with asynchronous transmitters Viterbi equalizer Linear equalizers: linear prediction Simulations Conclusions

4. 4 Introduction Cooperative transmissions Use STBC for diversity, power efficiency Challenges: Imperfect synchronization among transmitters: conventional STBC receiver not applicable Performance degradation: compromise advantage of cooperative transmissions Objectives: New receiver equalization techniques Performance comparison: asynchronous cooperative, or non-cooperative transmissions

5. 5 2. Cooperative transmissions with asynchronous transmitters Assume Transmit nodes 1 to J transmit symbols {s(n)} with STBC No perfect synchronization in time (local clock, transmission delay, propagation delay) Frequency synchronization not addressed, dealt with by adaptive equalizer

6. 6 Channel model (J transmitter, a single receiver, flat fading)

7. 7 3. Viterbi equalizer Consider J=2 and Alamouti STBC for simplicity Receiver adjust d: short channel, strong h2(0)

8. 8 Channel model with uncoded symbols Even delay d. Even/odd samples are Odd delay d, similarly available Viterbi equalizer available Complexity: With decision feedback: Complexity reduced by adjusting d

9. 9 4. Linear-prediction-based equalizer Choose proper d to make h1(0) dominating Construct vector model Special structure: H has dominating diagonal , Good for linear prediction Example:

10. 10 Linear prediction: Proposition:

11. 11 Properties Symbols estimated from linear prediction error y(2n) and y(2n+1) Efficient adaptive implementation: complexity O(N), track residue carrier induced time-variation Robust: most ill channel conditions avoided by selecting proper d

12. 12 Simulations Color codes: Convention STBC decoder used in asynchronous coop transmission. Non-cooperative transmission, flat fading channel Proposed Viterbi equalizer with asynchronous coop transmission Optimal STBC with perfect synchronization

13. 13

14. 14 Conventional STBC decoder used in asynchronous coop transmission MMSE equalizer used in asynchronous coop transmission Non-cooperative transmission, dispersive channel Proposed linear-prediction-based equalizer Conventional STBC with dispersive channel

15. 15 Conclusions Equalizers for STBC cooperative transmissions when transmitters are not synchronized Viterbi equalizer: performance near conventional STBC, high complexity Viterbi equalizer with feedback: slight performance loss, extremely reduced complexity Linear prediction-based equalizer: linear complexity, performance better than non-cooperation, much worse than conventional STBC (all in dispersive channel)