An Adaptive Conditional Zero-Forcing Decoder with Full-diversity, Least Complexity and Essentially-ML Performance for STBCs
Lakshmi Prasad Natarajan, B. Sundar Rajan

TL;DR
This paper introduces adaptive low-complexity decoders for space-time block codes that achieve full-diversity and near-ML performance, outperforming existing codes in complexity and error rates for multiple antenna configurations.
Contribution
The paper proposes two new adaptive decoders, ACZF and ACZF-SIC, which achieve full-diversity with lower complexity than ML decoders for several well-known STBCs.
Findings
Decoders achieve full-diversity with less complexity than ML decoding.
Simulations confirm performance matches ML decoding for tested codes.
Proposed decoders outperform existing codes in complexity and error performance.
Abstract
A low complexity, essentially-ML decoding technique for the Golden code and the 3 antenna Perfect code was introduced by Sirianunpiboon, Howard and Calderbank. Though no theoretical analysis of the decoder was given, the simulations showed that this decoding technique has almost maximum-likelihood (ML) performance. Inspired by this technique, in this paper we introduce two new low complexity decoders for Space-Time Block Codes (STBCs) - the Adaptive Conditional Zero-Forcing (ACZF) decoder and the ACZF decoder with successive interference cancellation (ACZF-SIC), which include as a special case the decoding technique of Sirianunpiboon et al. We show that both ACZF and ACZF-SIC decoders are capable of achieving full-diversity, and we give sufficient conditions for an STBC to give full-diversity with these decoders. We then show that the Golden code, the 3 and 4 antenna Perfect codes, the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
