4.7 Article

Performance Analysis of STAR-IRS Aided NOMA Short-Packet Communications With Statistical CSI

期刊

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 72, 期 9, 页码 12385-12390

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2023.3266830

关键词

Diversity order; non-orthogonal multiple access; short-packet communication; simultaneous transmitting and reflecting intelligent reflecting surfaces

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This paper analyzes the benefits of simultaneous transmitting and reflecting intelligent reflecting surfaces (STAR-IRSs) in short-packet communications (SPC) with non-orthogonal multiple access (NOMA) and statistical channel state information. By considering Rician fading and energy splitting protocol, the performance of STAR-IRS aided NOMA SPC systems with continuous and discrete phase shifts is analyzed. The relationship among average block error rate (BLER), power allocation, blocklength, and transmission and reflection coefficients is determined. Monte Carlo simulations are used to verify the theoretical analysis and examine the optimal transmission and reflection coefficients.
We analyze the benefits of simultaneous transmitting and reflecting intelligent reflecting surfaces (STAR-IRSs) for short-packet communications (SPC) with non-orthogonal multiple access (NOMA) and statistical channel state information towards ultra-reliable and low-latency communications. Considering Rician fading and energy splitting protocol, we analyze the performance of STAR-IRS aided NOMA SPC systems with continuous and discrete phase shifts. We first derive new closed-form expressions for the average block error rate (BLER) and diversity order in the finite signal-to-noise ratio (SNR) regime. We then determine the relationship among the average BLER, power allocation, blocklength, and transmission and reflection coefficients. Finally, Monte Carlo simulations are used to verify our theoretical analysis and examine the optimal transmission and reflection coefficients that minimize the common blocklength in the considered system under reliability constraints.

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