SM and NOMA Joint Assisted Indoor Multi-User VLC Downlink

IF 5.3 2区 计算机科学 Q1 TELECOMMUNICATIONS
Fasong Wang;Ting Zuo;Jiankang Zhang;Shijie Shi;Yitong Li
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引用次数: 0

Abstract

In this paper, a novel spatial modulation (SM) assisted successive interference cancelation (SIC) free non-orthogonal multiple access (NOMA) scheme is proposed for indoor multi-user visible light communications (VLC) downlink. In the proposed scheme, all users are grouped according to channel gains. The data information of users in each group is then mapped to the spatial domain and constellation symbol domain according to their bit error rate requirements. In addition, due to the inherent sparsity of SM modulated signals, the compressed sensing (CS) sparse reconstruction algorithm is revoked for demodulating signals at the receiver. In this process, the information carried by the activated light emitting diode index is demodulated using the CS aided sparsity reconstruction algorithm, while the constellation symbol information is demodulated using the maximum likelihood (ML) algorithm. Additionally, by combining the greedy algorithm with the ML algorithm, a new method for sparse signal reconstruction detection is proposed. Compared with traditional NOMA technology, at the receiver side, both the error propagation caused by SIC and intra-group interference can be eliminated. Furthermore, the computational complexity of demodulation is reduced by utilizing the proposed joint signal detection procedure. The effectiveness of the proposed indoor multi-user SM NOMA VLC architecture is validated through Monte Carlo simulations.
SM和NOMA联合辅助室内多用户VLC下行链路
提出了一种用于室内多用户可见光通信下行链路的空间调制(SM)辅助连续干扰消除(SIC)自由非正交多址(NOMA)方案。该方案根据信道增益对所有用户进行分组。然后根据用户误码率要求,将每组用户的数据信息映射到空间域和星座符号域。此外,由于SM调制信号固有的稀疏性,在接收端解调信号时取消了压缩感知(CS)稀疏重建算法。在此过程中,激活发光二极管索引所携带的信息使用CS辅助稀疏度重构算法解调,星座符号信息使用最大似然(ML)算法解调。此外,将贪心算法与ML算法相结合,提出了一种稀疏信号重构检测的新方法。与传统的NOMA技术相比,在接收端可以消除由SIC引起的误差传播和组内干扰。此外,利用所提出的联合信号检测方法降低了解调的计算复杂度。通过蒙特卡罗仿真验证了所提出的室内多用户SM NOMA VLC体系结构的有效性。
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
IEEE Transactions on Green Communications and Networking
IEEE Transactions on Green Communications and Networking Computer Science-Computer Networks and Communications
CiteScore
9.30
自引率
6.20%
发文量
181
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