Low-Complexity Linear Diversity-Combining Detector for MIMO-OTFS

TL;DR

This paper introduces a low-complexity MIMO-OTFS detector that employs linear diversity combining with optimized weights, enhancing performance and reducing complexity compared to existing methods.

Contribution

It proposes a novel linear diversity-combining detector for MIMO-OTFS that uses estimated spatial correlation to optimize combining weights, improving performance and complexity.

Findings

Outperforms LMMSE and MP detectors in MIMO-OTFS

Reduces computational complexity

Effectively mitigates spatial correlation effects

Abstract

This paper presents a low complexity detector for multiple-input multiple-output (MIMO) systems based on the recently proposed orthogonal time frequency space (OTFS) modulation. In the proposed detector, the copies of the transmitted symbol-vectors received through the different diversity branches (propagation paths and receive antennas) are linearly combined using the maximum ratio combining (MRC) technique to iteratively improve the signal to interference plus noise ratio (SINR) at the output of the combiner. To alleviate the performance degradation due to spatial correlation at the receiver antennas, we present a sample-based method to estimate such correlation and find the optimized combining weights for MRC from the estimated correlation matrix. The detector performance and complexity improve over the linear minimum mean square error (LMMSE) and message passing (MP) detectors proposed in the literature for MIMO-OTFS.