Improper Gaussian Signaling for Downlink NOMA Systems With Imperfect Successive Interference Cancellation

被引:17
作者
Cheng, Hao [1 ,2 ]
Xia, Yili [1 ]
Huang, Yongming [3 ]
Yang, Luxi [1 ]
机构
[1] Southeast Univ, Sch Informat Sci & Engn, Nanjing 210096, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Sch Internet Things, Nanjing 210003, Peoples R China
[3] Southeast Univ, Sch Informat Sci & Engn, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
基金
中国国家自然科学基金;
关键词
NOMA; Interference cancellation; Quality of service; Downlink; MIMO communication; Throughput; Receivers; Non-orthogonal multiple access (NOMA); imperfect SIC; improper Gaussian signaling; impropriety degree; Q-learning; NONORTHOGONAL MULTIPLE-ACCESS; PERFORMANCE; OPTIMIZATION; CONVERGENCE; CHALLENGES; BOUNDS;
D O I
10.1109/TWC.2022.3161379
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Non-orthogonal multiple access (NOMA) exhibits superiority in spectrum efficiency which is particularly essential in the Internet of Things (IoT) system involving massive number of device connections. This paper addresses the achievable rate improvement for the downlink NOMA system, in the context of imperfect successive interference cancellation (SIC), by means of the improper Gaussian signaling (IGS) technique. We investigate a basic scenario where the strong user transmits the conventional proper data, while the weak user adopts an improper signaling scheme. The users' data rates are first formulated in terms of the impropriety degree of the IGS, under residual interference introduced by the imperfect SIC. In this way, analytical expressions for the best improper transmission can be characterized by jointly optimizing the user's power and the impropriety degree, where their sufficient and necessary conditions are provided. When the strong user transmits with its maximum power, the IGS scheme always increases the achievable rate of the strong user while the weak user may also benefit. When the weak user transmits with its maximum power, such a scheme enables us optimize the achievable rate of the strong user under various levels of channel-to-noise ratios (CNR) and imperfect SIC. Finally, when both the users are imposed by quality of service (QoS) constraints, a Q-learning based solution is proposed to maximize their sum rate. Simulations on the downlink NOMA system support the analysis.
引用
收藏
页码:7753 / 7763
页数:11
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