Graph‐based low complexity detection algorithms in multiple‐input–multiple‐out systems: an edge selection approach. Issue 12 (1st August 2013)

• Record Type: Journal Article
• Authors: Lv, Tiejun; Long, Feichi
• Is Part Of: IET communications. Volume 7:Issue 12(2013)
• Page Start: 1202
• Page End: 1210
• Publication Date: 2013-08-01
• Subjects: belief maintenance -- computational complexity -- filtering theory -- graph theory -- mean square error methods -- message passing -- MIMO communication -- modulation -- signal detection -- telecommunication computing; graph‐based low complexity detection algorithms -- low complexity multiple‐input‐multiple‐out signal detection problem -- edge selection approach -- belief propagation -- factor graph model -- BP algorithm -- message passing -- factor nodes -- variable nodes -- mean feedback method -- information loss compensation -- binary modulations -- high‐order modulations -- bit soft output symbols -- bit soft modulation symbols -- minimum mean‐square error filter initialised algorithm -- asymptotic optimality -- multi input‐multi out systems; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2012.0644
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In this study, the problem of low complexity multiple‐input–multiple‐out signal detection based on belief propagation (BP) is addressed. The authors propose an edge selection approach that works on factor graph model to cut down the number of circles and high complexity of standard BP algorithm. The message passing from factor nodes to variable nodes is updated by only partial edges, and the mean feedback method is designed to compensate the information loss brought by the edge selection. Both binary and high‐order modulations are considered, and the scheme of mapping between bit soft output and modulation symbols when computing the feedback information is discussed. In addition, a minimum mean‐square error filter initialised algorithm is proposed, in which the initial message of BP detection is exploited. Both binary and high‐order modulations are discussed as well when the authors design this initial message. Simulation results along with convergence and complexity analyses verify that the proposed edge selection approach can achieve good performance with low complexity, and significantly outperform the existing methods with comparative complexity. Moreover, our approach has asymptotic optimality and is a self‐adapting scheme, which can achieve the trade‐off between performance and complexity by varying the number of selected edges.