Reduced-Complexity Turbo Equalization for Turbo Coded MIMO/OFDM Systems

摘要

This paper derives a law-complexity turbo equalization algorithm for turbo coded multiple input multiple output/orthogonal frequency division multiplexing systems. This algorithm consists of soft-output decision-feedback equalization with a probabilistic data association algorithm and a soft-input soft-output turbo channel decoder using iterative operations. In each iteration, extrinsic information extracted from the probabilistic data association algorithm detector and from the channel decoder is used as the prior information for the next iteration to realize iterative channel equalization and channel decoding. Our simulation results show that the algorithm improves the signal noise ratio around 1 dB xvith bit error rate reaching 10~(-6) when the E_b/N_0 = 4 dB compared to minimum mean square error and match filter, and can greatly reduce the intersymbol interference at a low overall complexity of O(N~3) after 2 iterations.