Low-Complexity MAP-Based Successive Data Detection for Coded OFDM Systems Over Highly Mobile Wireless Channels
作者： Erdal Panayirci , Hakan Dogan , H. Vincent Poor
关键词: Sampling (statistics) 、 Maximum likelihood 、 Markov chain 、 Frequency domain 、 Bit error rate 、 Algorithm 、 Electronic engineering 、 Markov chain Monte Carlo 、 Communication channel 、 Equalization (audio) 、 Maximum a posteriori estimation 、 Multiplexing 、 Orthogonal frequency-division multiplexing 、 Computer science 、 Communication complexity
摘要: This paper is concerned with the challenging and timely problem of data detection for coded orthogonal frequency-division multiplexing (OFDM) systems in presence frequency-selective very rapidly time varying channels. New low-complexity maximum a posteriori probability (MAP) algorithms are proposed based on sequential optimal ordering (SDOO) successive cancellation (SDSC). The received signal vector optimally decomposed into reduced dimensional subobservations by exploiting banded structure frequency-domain channel matrix whose bandwidth parameter to be adjusted according speed mobile terminal. symbols then detected computationally efficient way means Markov chain Monte Carlo (MCMC) technique Gibbs sampling. impact imperfect state information (CSI) bit error rate (BER) performance these investigated analytically computer simulations. A detailed computational complexity investigation simulation results indicate that, particularly, algorithm SDSC has significant advantages robust against estimation errors compared existing suboptimal equalization earlier literature.
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