TY - JOUR

T1 - Adaptive maximum likelihood detection of MPSK signals in frequency nonselective fast rayleigh fading

AU - Adachi, Fumiyuki

PY - 1997/1/1

Y1 - 1997/1/1

N2 - Adaptive maximum likelihood (ML) detection implemented by the Viterbi algorithm (VA) is proposed for the reception of MPSK signals in frequency nonselective fast Rayleigh fading. M-state VA, each state in the VA trellis represents a signal constellation point, is used. Diversity reception is incorporated into the structure of Viterbi decoding. The pilot symbol (unmodulated carrier) is periodically inserted to terminate the trellis so that the phase ambiguity of the detected data sequence is avoided. Applying the per-survivor processing principle (PSPP), adaptive ML detection performs adaptive channel estimation using a simple linear predictor at all trellis states in parallel. The predictor coefficient is stochastically adapted without requiring a priori knowledge of fading channel statistics, based on a recursive least-squares (RLS) adaptation algorithm, to match changes in the statistical properties of the channel (i.e., AWGN or fast/slow fading) using both data and pilot symbols. Simulations of 4PSK signal transmission demonstrate that the proposed adaptive ML detection scheme can track fast fading, thus significantly reducing the irreducible bit error rate (BER) due to Doppler spread in the fading channel. It is also shown that adaptive ML detection provides BER performance close to ideal coherent detection (CD) in AWGN channels.

AB - Adaptive maximum likelihood (ML) detection implemented by the Viterbi algorithm (VA) is proposed for the reception of MPSK signals in frequency nonselective fast Rayleigh fading. M-state VA, each state in the VA trellis represents a signal constellation point, is used. Diversity reception is incorporated into the structure of Viterbi decoding. The pilot symbol (unmodulated carrier) is periodically inserted to terminate the trellis so that the phase ambiguity of the detected data sequence is avoided. Applying the per-survivor processing principle (PSPP), adaptive ML detection performs adaptive channel estimation using a simple linear predictor at all trellis states in parallel. The predictor coefficient is stochastically adapted without requiring a priori knowledge of fading channel statistics, based on a recursive least-squares (RLS) adaptation algorithm, to match changes in the statistical properties of the channel (i.e., AWGN or fast/slow fading) using both data and pilot symbols. Simulations of 4PSK signal transmission demonstrate that the proposed adaptive ML detection scheme can track fast fading, thus significantly reducing the irreducible bit error rate (BER) due to Doppler spread in the fading channel. It is also shown that adaptive ML detection provides BER performance close to ideal coherent detection (CD) in AWGN channels.

KW - Adaptive channel estimation

KW - Maximum likelihood detection

KW - Rayleigh fading

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M3 - Article

AN - SCOPUS:0031188246

VL - E80-B

SP - 1045

EP - 1054

JO - IEICE Transactions on Communications

JF - IEICE Transactions on Communications

SN - 0916-8516

IS - 7

ER -