# RLS-Based Detection for Massive Spatial Modulation MIMO

Source: [RLS-Based Detection for Massive Spatial Modulation MIMO](<https://www.sota2.com/research/paper/68fa55de1e209131ce997db9>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T13:49:44.067Z

Authors: Ali Bereyhi, Saba Asaad, Bernhard G\\"ade, Ralf R. M\\"uller

Published: 2019-05-13T18:14:47.000Z

## Abstract

Most detection algorithms in spatial modulation (SM) are formulated as linear regression via the regularized least-squares (RLS) method. In this method, the transmit signal is estimated by minimizing the residual sum of squares penalized with some regularization. This paper studies the asymptotic performance of a generic RLS-based detection algorithm employed for recovery of SM signals. We derive analytically the asymptotic average mean squared error and the error rate for the class of bi-unitarily invariant channel matrices.   The analytic results are employed to study the performance of SM detection via the box-LASSO. The analysis demonstrates that the performance characterization for i.i.d. Gaussian channel matrices is valid for matrices with non-Gaussian entries, as well. This justifies the partially approved conjecture given in \[1\]. The derivations further extend the former studies to scenarios with non-i.i.d. channel matrices. Numerical investigations validate the analysis, even for practical system dimensions.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1905.05223>)

[PDF](<https://arxiv.org/pdf/1905.05223.pdf>)