Projection-based list detection in Generalized Spatial Modulation MIMO systems

TL;DR

This paper introduces a new multi-stage detection method for Generalized Spatial Modulation MIMO systems that improves detection accuracy and reduces computational complexity by generating and selecting from a list of candidate signals.

Contribution

It proposes a projection-based list detection strategy that enhances performance close to maximum likelihood detection with lower computational cost.

Findings

Significantly reduces the performance gap to optimal detection.

Maintains lower computational complexity compared to maximum likelihood detection.

Effective in Generalized Spatial Modulation MIMO systems.

Abstract

This letter presents a novel detection strategy for Spatially-Multiplexed Generalized Spatial Modulation systems. It is a multi-stage detection that produces a list of candidates of the transmitted signal vector, sorted according to the proximity of the data vector to one of the possible vector subspaces. The quality metric and list-length metric selects the best candidate and manages the list length, respectively. Performance results show that it significantly reduces the performance gap to the optimal maximum likelihood detector, while maintaining significant computational cost reduction.