SMC algorithms for approximate-map equalization of MIMO channels with polynomial complexity

Sequential Monte Carlo (SMC) schemes have been recently proposed in order to perform optimal equalization of multiple input multiple output (MIMO) wireless channels. The main feaures of SMC techniques that make them appealing for the equalization problem are (a) their potential to provide asymptotically optimal performance in terms of bit error rate and (b) their suitability for implementation using parallel hardware. Nevertheless, existing SMC equalizers still exhibit a very high computational complexity, relative to the dimensions of the MIMO channel, which makes them useless in practical situations. In this paper we introduce two new SMC equalizers whose computational load is only of polynomial order with respect to the channel dimensions, and avoid computationally heavy tasks such as matrix inversions. The performance of the proposed techniques is numerically illustrated by means of computer simulations.