Effective Capacity Analysis of STAR-RIS-Assisted NOMA Networks

• Published in: IEEE wireless communications letters Vol. 11; no. 9; pp. 1930 - 1934
• Main Authors: Liu, Huiling, Li, Geng, Li, Xingwang, Liu, Yuanwei, Huang, Gaojian, Ding, Zhiguo
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.09.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Delays; Effective capacity (EC); Mathematical analysis; Measurement; Nakagami distribution; Network latency; NOMA; non-orthogonal multiple access (NOMA); Nonorthogonal multiple access; Protocols; Quality of service; reconfigurable intelligent surface (RIS); Signal to noise ratio; simultaneous transmitting and reflecting (STAR); User requirements
• ISSN: 2162-2337; 2162-2345
• DOI: 10.1109/LWC.2022.3188443

This letter studies the performance of the simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided non-orthogonal multiple access (NOMA) networks in support of ultra-reliable low-latency communications. We adopt effective capacity (EC) as the metric to explore the delay requirements of NOMA users. Specifically, the analytical expressions of the EC are obtained for the network with a pair of NOMA users on the different sides of the STAR-RIS. Furthermore, the high signal-to-noise ratio (SNR) slope and high SNR power offset are invoked to provide asymptotic analysis of the ECs in high SNR. Some insightful conclusions are drawn from the simulations: 1) the EC of near user <inline-formula> <tex-math notation="LaTeX">({U_{n}}) </tex-math></inline-formula> increases linearly while the EC of far user <inline-formula> <tex-math notation="LaTeX">({U_{m}}) </tex-math></inline-formula> tends to be a constant in the high SNR; 2) comparing with STAR-orthogonal multiple access and conventional RIS, the use of STAR-RIS NOMA increases the ECs of <inline-formula> <tex-math notation="LaTeX">{U_{n}} </tex-math></inline-formula> and overall network; 3) increasing the number of STAR-RIS elements is an effective strategy to improve the ECs of both <inline-formula> <tex-math notation="LaTeX">{U_{n}} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">{U_{m}} </tex-math></inline-formula>.