On Optimal Turbo Decoding of Wideband MIMO-OFDM Systems Under Imperfect Channel State Information

TL;DR

This paper proposes a robust decoding metric for BICM in wideband MIMO-OFDM systems that accounts for noisy channel estimates, significantly improving bit error rates without added complexity.

Contribution

It introduces a Bayesian-based decoding metric that enhances robustness to channel estimation errors in MIMO-OFDM systems.

Findings

Significant BER improvement over mismatched decoding.

Robust decoding without additional computational complexity.

Effective in both UWB and Rayleigh fading channels.

Abstract

We consider the decoding of bit interleaved coded modulation (BICM) applied to both multiband and MIMO OFDM systems for typical scenarios where only a noisy (possibly very bad) estimate of the channel is provided by sending a limited number of pilot symbols. First, by using a Bayesian framework involving the channel a posteriori density, we adopt a practical decoding metric that is robust to the presence of channel estimation errors. Then this metric is used in the demapping part of BICM multiband and MIMO OFDM receivers. We also compare our results with the performance of a mismatched decoder that replaces the channel by its estimate in the decoding metric. Numerical results over both realistic UWB and theoretical Rayleigh fading channels show that the proposed method provides significant gain in terms of bit error rate compared to the classical mismatched detector, without introducing any additional complexity.