Belief Propagation Based Decoding of Large Non-Orthogonal STBCs

TL;DR

This paper introduces a belief propagation algorithm for decoding large non-orthogonal STBCs from cyclic division algebras, achieving near-capacity performance and close to SISO AWGN benchmarks.

Contribution

It is the first to apply BP decoding to large-dimension non-orthogonal STBCs from CDA, demonstrating significant performance improvements.

Findings

Achieves near-capacity BER performance with large STBCs

Close to SISO AWGN performance as dimensions increase

Decodes 24x24 STBC with 576 real dimensions effectively

Abstract

In this paper, we present a belief propagation (BP) based algorithm for decoding non-orthogonal space-time block codes (STBC) from cyclic division algebras (CDA) having {\em large dimensions}. The proposed approach involves message passing on Markov random field (MRF) representation of the STBC MIMO system. Adoption of BP approach to decode non-orthogonal STBCs of large dimensions has not been reported so far. Our simulation results show that the proposed BP-based decoding achieves increasingly closer to SISO AWGN performance for increased number of dimensions. In addition, it also achieves near-capacity turbo coded BER performance; for e.g., with BP decoding of $24\times 24$ STBC from CDA using BPSK (i.e., 576 real dimensions) and rate-1/2 turbo code (i.e., 12 bps/Hz spectral efficiency), coded BER performance close to within just about 2.5 dB from the theoretical MIMO capacity is achieved.