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论文类型： 期刊论文

发表时间： 2019-12-01

发表刊物： IEEE COMMUNICATIONS LETTERS

收录刊物： SCIE

卷号： 23

期号： 12

页面范围： 2187-2191

ISSN号： 1089-7798

关键字： Probabilistic logic; Detectors; MIMO communication; Transmitting antennas; Bayes methods; Channel estimation; Massive GSSK-MIMO systems; equality constraint; augmented model; weighting parameter; probabilistic approach

摘要： In this letter, we propose an equality-constrained detector using probabilistic approaches for massive multiple-input multiple-output (MIMO) systems with generalized space shift keying (GSSK) modulation. Probabilistic approaches derived from the Bayesian iteration can provide the soft decision for achieving the near-optimal performance and some other benefits such as combination of detection and channel decoding. However, these methods cannot be directly adopted to GSSK modulated MIMO systems without considering the equality-constraint of GSSK signals. To address this problem, we develop an augmented system model with a weighting parameter. Moreover, the relation between the augmented model and the quadratic penalty function is also derived to determine the value of weighting parameter. Consequently, probabilistic approaches based on the augmented system model can be directly used to solve the equality-constrained problems. Simulation results substantiate the high-performance and extensibility of the proposed detector.