On the Design of Near-Optimal Generalized Block-Based Spatial Modulation With Low Detection Complexity

IF 2.9 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Yen-Ming Chen;Wei-Lun Lin;Heng Lee;Tsung-Lin Chen
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引用次数: 0

Abstract

Spatial Modulation (SM) and Generalized Spatial Modulation (GSM) have attracted significant attention in the development of spectrally and energy-efficient transmission schemes for multiple-input multiple-output (MIMO) systems. However, independently designing the constellation cardinality and TACs leads to limited performance gains and an exponential increase in complexity, particularly under maximum-likelihood (ML) detection. To address these limitations, the generalized block-based spatial modulation (GBSM) scheme was proposed, enabling greater flexibility by jointly designing GSM signals across a block of time indices. Building on this idea, this paper first proposes a near-optimal codebook search method based on three-dimensional (3-D) mapping, applicable to both fast and slow Rayleigh fading channels. Secondly, a codebook-assisted tree-search detector (CATSD) is introduced, offering a 98% reduction in complexity compared to ML detection while maintaining near-ML error performance. Finally, an alternative codebook search method is presented, accompanied by a complexity analysis that reveals a favorable trade-off between performance and computational cost.
低检测复杂度的近最优广义分块空间调制设计
空间调制(SM)和广义空间调制(GSM)在多输入多输出(MIMO)系统的频谱和节能传输方案的发展中引起了极大的关注。然而,独立设计星座基数和tac会导致有限的性能提升和复杂性的指数增长,特别是在最大似然(ML)检测下。为了解决这些限制,提出了基于广义分块的空间调制(GBSM)方案,通过跨时间指标块联合设计GSM信号,实现了更大的灵活性。在此基础上,本文首先提出了一种基于三维映射的近最优码本搜索方法,该方法适用于快速和慢速瑞利衰落信道。其次,引入了一种码本辅助树搜索检测器(CATSD),与机器学习检测相比,它的复杂性降低了98%,同时保持了接近机器学习的错误性能。最后,提出了一种替代的码本搜索方法,并进行了复杂性分析,揭示了性能和计算成本之间的有利权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.30
自引率
0.00%
发文量
0
审稿时长
22 weeks
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