Adaptive differential detection using linear prediction for M-aryDPSK

This paper proposes a novel adaptive differential detection scheme (adaptive DD), which can significantly reduce the irreducible bit-error rate (BER) of M-ary DPSK due to Doppler spread by the adaptive linear prediction of the reference signal. The predictor coefficient is adapted to changing channel conditions by using the recursive least-square (RLS) algorithm. A phase sequence estimation based on the M-state Viterbi algorithm (VA) and another based on the decision feedback algorithm (DFA) are presented. A theoretical BER analysis is presented for adaptive DD-DFA. BER performances of 2 and 4DPSK in Rayleigh fading channels are evaluated by computer simulations. When the RLS forgetting factor of β=1 is used, simulation results show that the irreducible BER of 4DPSK can be reduced to 7.2×10^-5 (3.9×10 ^-4) for VA (DFA) while conventional DD offers 3.9×10 ^-3 when f_DT_b (maximum Doppler frequency times bit duration)=0.01 and average E_b/N₀ (signal energy per bit-to-additive white Gaussian noise (AWGN) power spectrum density ratio)=60 dB, where most errors are produced by Doppler spread. Adaptive DD is also effective in AWGN channels-simulations show that for the case of 4DPSK, a performance gain of 1.2 (0.7) dB is achieved over conventional DD for VA (DFA) at BER=10^-3