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Cube-Split: A Structured Grassmannian Constellation for Non-Coherent SIMO Communications

2019/05/21 by Khac–Hoang Ngo, Khac-Hoang Ngo, Alexis Decurninge +6 · 3 citations
Computer Science · Engineering · Mathematics · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Techniques #Algorithm #Channel (broadcasting) #Combinatorics #Computer science #Constellation #Cooperative Communication and Network Coding #Decoding methods #Discrete mathematics #FOS: Computer and information sciences #Fading #Grassmannian #Hypercube #Information Theory (cs.IT) #MIMO #Mathematics #Rayleigh fading #Telecommunications #Theoretical computer science #Topology (electrical circuits) #cs.IT #math.IT

paper · pdf · doi:10.48550/arxiv.1905.08745

published in arXiv (Cornell University) (Cornell University) · appeared in the IEEE Transactions on Wireless Communications

openalex publication_date 2019/05/21 · openalex created_date 2019/05/29 · arxiv created 2020/06/04 · arxiv updated 2020/06/05 · openalex updated_date 2026/08/08

Abstract

In this paper, we propose a practical structured constellation for non-coherent communication with a single transmit antenna over Rayleigh flat and block fading channel without instantaneous channel state information. The constellation symbols belong to the Grassmannian of lines and are defined up to a complex scaling. The constellation is generated by partitioning the Grassmannian of lines into a collection of bent hypercubes and defining a mapping onto each of these bent hypercubes such that the resulting symbols are approximately uniformly distributed on the Grassmannian. With a reasonable choice of parameters, this so-called cube-split constellation has higher packing efficiency, represented by the minimum distance, than the existing structured constellations. Furthermore, exploiting the constellation structure, we propose low-complexity greedy symbol decoder and log-likelihood ratio computation, as well as an efficient way to associate it to a multilevel code with multistage decoding. Numerical results show that the performance of the cube-split constellation is close to that of a numerically optimized constellation and better than other structured constellations. It also outperforms a coherent pilot-based scheme in terms of error probability and achievable data rate in the regime of short coherence time and large constellation size.

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