A near optimum joint detection and decoding algorithm for MIMO-OFDM channels

In this paper, a joint detection and decoding algorithm is proposed for the spatial multiplex multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) channels. In the spatial multiplexed MIMO-OFDM channels, if enough cyclic prefix (CP) at least equal to the channel length is used, inter symbol interference is completely canceled and consequently spatial multiplexing interference (SMI) is the main limiting factor on the performance [4]. Optimum SMI cancellation is more complex for practically usage. In this paper, a novel technique is proposed to approach to the performance of the optimum algorithm in much lower complexity. The proposed algorithm is based on a modified soft partially parallel interference cancellation (SPPIC) technique where, in each iteration, a part of the SMI proportional to the probability of the correct estimation in the last iteration, is cancelled. The output of this soft joint detector is fed to a turbo decoder. In the first iteration of the decoding, the probability of the correctness is calculated approximately assuming the correct estimation for other sub-streams in the last iteration and in the next iterations, it is updated using the output LLR of the turbo decoder. The proposed modified SPPIC algorithm is simulated and compared to the minimum mean square of error (MMSE), interference free case (lower bound), and SPPIC algorithms for 4 states frac12 turbo code in 4times4 MIMO OFDM channel assuming Micro cell Winner channel model considering 64 and 512 sub-carriers. Bit error rate (BER) and frame error rate (FER) are considered as comparison criteria and it is shown that the performance of the new algorithm is much better than MMSE algorithm and is very close to the interference-free lower bound.