A Low-Complexity Graph-Based LMMSE Receiver for MIMO ISI Channels with M-QAM Modulation

TL;DR

This paper introduces a low-complexity, graph-based LMMSE equalizer for MIMO ISI channels with M-QAM modulation, achieving near-optimal performance with reduced computational complexity.

Contribution

It presents a novel state space graph representation for LMMSE equalization that scales linearly with block length and is independent of modulation size, along with an efficient LLR computation method.

Findings

Performs close to genie-aided bounds in simulations.

Complexity scales linearly with block length, independent of modulation size.

Outperforms existing methods in high-order M-QAM scenarios.

Abstract

In this paper, we propose a low complexity graph-based linear minimum mean square error (LMMSE) equalizer in order to remove inter-symbol and inter-stream interference in multiple input multiple output (MIMO) communication. The proposed state space representation inflicted on the graph provides linearly increasing computational complexity with block length. Also, owing to the Gaussian assumption used in the presented cycle-free factor graph, the complexity of the suggested equalizer structure is not affected by the size of the signalling space. In addition, we introduce an efficient way of computing extrinsic bit log-likelihood ratio (LLR) values for LMMSE estimation compatible with higher order alphabets which is shown to perform better than the other methods in the literature. Overall, we provide an efficient receiver structure reaching high data rates in frequency selective MIMO systems whose performance is shown to be very close to a genie-aided matched filter bound through extensive simulations.