標題: Performance-Complexity Analysis for MAC ML-Based Decoding With User Selection
作者: Lu, Hsiao-feng
Elia, Petros
Singh, Arun Kumar
電機學院
College of Electrical and Computer Engineering
關鍵字: Complexity exponent;diversity-multiplexing tradeoff;multiple access channel;performance-complexity tradeoff;user selection
公開日期: 1-Apr-2016
摘要: The rate-reliability-complexity limits of a quasi-static -user multiple access channel (MAC), with or without feedback, are explored in this paper. Using high-SNR asymptotics, bounds on the computational resources required to achieve near-optimal (ML-based) decoding performance are first derived. They, in turn, yield bounds on the (reduced) complexity needed to achieve any (including suboptimal) diversity-multiplexing tradeoff (DMT) performance. Similar complexity-bounds in the presence of feedback-aided user selection are also given. This latter effort reveals the ability of a few bits of feedback not only to improve performance, but also to reduce complexity. In this context, our analysis reveals the interesting finding that a proper calibration of user selection can allow for near-optimal ML-based decoding, with complexity that need not scale exponentially in the total number of codeword bits. The derived bounds constitute the best known performance-versus-complexity behavior to date for ML-based MAC decoding, as well as a first exploration of the complexity-feedback-performance interdependencies in multiuser settings.
URI: http://dx.doi.org/10.1109/TSP.2015.2508788
http://hdl.handle.net/11536/133455
ISSN: 1053-587X
DOI: 10.1109/TSP.2015.2508788
期刊: IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume: 64
Issue: 7
起始頁: 1867
結束頁: 1880
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