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Queue-Aware STAR-RIS Assisted NOMA Communication Systems
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DOI：10.1109/TWC.2023.3322381.png)
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摘要
En 中文
Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) are gaining great attention for their ability to achieve full-space coverage. In this paper, the queue-aware STAR-RIS assisted non-orthogonal multiple access (NOMA) communication system is investigated to ensure system stability. To tackle the challenge of infinite time periods for stability, the long-term stability-oriented problem is reformulated as a per-slot queue-weighted sum rate (QWSR) maximization problem using Lyapunov drift theory. Particularly, the allocated rate weight for each user is determined by the corresponding data queue at the base station (BS). By jointly optimizing the NOMA decoding order, the active beamforming coefficients at the BS, and the passive transmission and reflection coefficients at the STAR-RIS, three STAR-RIS operating protocols are considered, namely energy splitting (ES), mode switching (MS), and time switching (TS). An equivalent-combined channel gain based scheme is proposed to obtain the desired decoding order. For ES, the highly coupled and non-convex problem is solved iteratively and alternatively by invoking the blocked coordinate descent and the successive convex approximation methods. This approach is further expanded to a penalty-based two-loop algorithm to solve the binary amplitude constrained problem for MS. For TS, the problem is decomposed into two subproblems, each of which is solved similarly as ES. Simulation results show that: i) our proposed STAR-RIS assisted NOMA communication achieves superior performance to the conventional schemes; ii) the reformulated QWSR maximization problem is proven to ensure the system stability; and iii) TS performs best in both the QWSR and the average queue length.
Keyword:
NOMA
Protocols
Wireless communication
Array signal processing
Communication systems
Resource management
Downlink
Lyapunov drift theory
queue stability
STAR-RISs
期刊
IF:
10.7
论文数:
1.3W
被引数:
5.3W
机构
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