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arXiv 2610.03266cs.ITmath.IT

任意用户数和符号速率下MR-NOMA的性能分析

Performance Analysis of MR-NOMA with Arbitrary Number of Users and Symbol Rates

Zainab Khader, Arafat Al-Dweik, Emad Alsusa

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中文总结 AI 辅助

本文分析MR-NOMA在Nakagami-m信道下任意用户数和符号速率的BER性能,推导精确及近似表达式,并证明其通过符号持续时间分集优于传统SR-NOMA,同时优化功率分配以支持灵活用户配对和QoS需求。

中文摘要 AI 辅助

本文在Nakagami-m衰落信道上,针对任意用户数和符号速率,对下行多速率非正交多址(MR-NOMA)的误码率(BER)性能进行了分析研究。分析首先针对三用户情形展开,随后推广至用户数超过三的系统,在完美串行干扰消除(SIC)假设下,为首个被检测用户推导出精确的BER表达式,并为其余用户推导出精确的闭式近似。这些结果进一步统一为Nakagami-m衰落信道上任意用户数和符号速率配置下的通用平均BER表达式。一种依赖于符号模式的信干噪比(SINR)分析进一步揭示了符号持续时间分集如何实现固有干扰消除,从而解释了MR-NOMA相较于传统单符号速率(SR)-NOMA的BER优势。此外,本文还构建了一个平均BER最小化问题,并通过数值求解优化用户的功率分配,仿真结果验证了分析结论。总体而言,MR-NOMA在保持可靠BER性能并满足多样化服务质量(QoS)需求的同时,在用户配对方面展现出更大的灵活性。

英文摘要

This paper analytically investigates the bit error rate (BER) performance of downlink multi-rate (MR)-non-orthogonal multiple access (NOMA) over Nakagami-m fading channels for an arbitrary number of users and symbol rates. The analysis is first developed for a three-user case, then generalized to systems with more than three users, yielding an exact BER expression for the first detected user and an accurate closed-form approximations for the remaining users under the perfect-successive interference cancellation (SIC) assumption. These results are further unified into a general average-BER expression over Nakagami-m fading for arbitrary user numbers and symbol-rate configurations. A symbol-pattern-dependent signal-to-interference plus noise ratio (SINR) analysis further shows how the symbol-duration diversity enables inherent interference cancellation, explaining the BER advantage of MR-NOMA over conventional single-symbol rate (SR)-NOMA. An average BER minimization problem is also formulated and numerically solved to optimize the users' power allocation, with simulation results corroborating the analytical findings. Overall, MR-NOMA is shown to offer greater flexibility in user pairing while maintaining reliable BER performance and accommodating diverse quality-of-service (QoS) requirements.

发表机构

  • Khalifa University(哈利法大学)
  • The University of Manchester(曼彻斯特大学)

机构由 AI 辅助整理,请以论文原文为准。

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