In the near future, the 5th generation (5G) of wireless systems will be well established. They will consist of an integration of different techniques, including distributed antenna systems and massive multiple-input multiple-output (MIMO) systems, and the overall performance will highly depend on the channel coding techniques employed. Due to the nature of future wireless networks, space–time codes are no longer merely an object of choice, but will often appear naturally in the communications setting. However, as the involved communication devices often exhibit a modest computational power, the complexity of the codes to be utilised should be reasonably low for possible practical implementation. Fast-decodable codes enjoy reduced complexity of maximum-likelihood (ML) decoding due to a smart inner structure allowing for parallelisation in the ML search. The complexity reductions considered in this chapter are entirely owing to the algebraic structure of the considered codes, and could be further improved by employing non-ML decoding methods, however yielding suboptimal performance. The aim of this chapter is twofold. First, we provide a tutorial introduction to space–time coding and study powerful algebraic tools for their design and construction. Secondly, we revisit algebraic techniques used for reducing the worst-case decoding complexity of both single-user and multiuser space-time codes, alongside with general code families and illustrative examples.
|Title of host publication||Number Theory Meets Wireless Communications|
|Editors||Victor Beresnevich, Alister Burr, Bobak Nazer, Sanju Velani|
|Place of Publication||Cham|
|Number of pages||43|
|Publication status||Published - 22 Sep 2020|
|MoE publication type||A3 Part of a book or another research book|