A Simple Variational Bayes Detector for Orthogonal Time Frequency Space (OTFS) Modulation

TL;DR

This paper introduces a variational Bayes detector for OTFS modulation that offers a low-complexity alternative to MAP detection, with guaranteed convergence and improved performance over message passing algorithms.

Contribution

It proposes a novel variational Bayes approach for OTFS detection that guarantees convergence to the global optimum, reducing complexity compared to MAP detection.

Findings

Fast convergence of the VB detector demonstrated

Performance gain over message passing algorithms shown

Effective in mitigating inter-symbol interference

Abstract

The emerging orthogonal time frequency space (OTFS) modulation technique has shown its superiority to the current orthogonal frequency division multiplexing (OFDM) scheme, in terms of its capabilities of exploiting full time-frequency diversity and coping with channel dynamics. The optimal maximum a posteriori (MAP) detection is capable of eliminating the negative impacts of the inter-symbol interference in the delay-Doppler (DD) domain at the expense of a prohibitively high complexity. To reduce the receiver complexity for OTFS scheme, this paper proposes a variational Bayes (VB) approach as an approximation of the optimal MAP detection. Compared to the widely used message passing algorithm, we prove that the proposed iterative algorithm is guaranteed to converge to the global optimum of the approximated MAP detector regardless the resulting factor graph is loopy or not. Simulation results validate the fast convergence of the proposed VB receiver and also show its promising performance gain compared to the conventional message passing algorithm.