Channel Equalization for STBC-Encoded Cooperative Transmissions with Asynchronous Transmitters

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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_at_binghamton.edu
• http//ucesp.ws.binghamton.edu/xli

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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

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Contents

• Introduction
• Cooperative transmissions with asynchronous
  transmitters
• Viterbi equalizer
• Linear equalizers linear prediction
• Simulations
• Conclusions

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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

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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

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

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3. Viterbi equalizer

• Consider J2 and Alamouti STBC for simplicity
• Receiver adjust d short channel, strong h2(0)

Odd delay d
Even delay d between transmitters
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• 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

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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

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• Linear prediction
• Proposition

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• Properties
• Symbols estimated from linear prediction error
  y(2n) and y(2n1)
• Efficient adaptive implementation complexity
  O(N), track residue carrier induced
  time-variation
• Robust most ill channel conditions avoided by
  selecting proper d

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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

QPSK, J2. d1. VA has 128 states.
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Viterbi equalizer with decision feedback. 4
trellis states.
VA with DF, delay d10. VA with DF, delay d2. VA
without DF, delay d2.
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Linear equalizers QPSK. d10. Equalizer length
N20.

• 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

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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)