摘要翻译：
由于具有支持大规模连接和高频谱效率的潜力，NOMA是未来无线接入网(FRA)的有力候选。然而，NOMA最大的缺点是由于用户间的干扰，在实现连续干扰抵消(SIC)时会产生误差。本文推导了Nakagami-m衰落信道中存在SIC错误时下行链路(NOMA)误码率的闭式精确表达式。通过计算机仿真验证了推导公式的正确性。结果表明，m参数仍然像OMA系统一样代表分集顺序。另外，NOMA的用户误码率性能在很大程度上取决于功率分配系数。
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英文标题：
《Derivation of the closed-form BER expressions for DL-NOMA over
  Nakagami-m fading channels》
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作者：
Ferdi Kara, Hakan Kaya
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最新提交年份：
2018
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Information Theory        信息论
分类描述：Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
涵盖信息论和编码的理论和实验方面。包括ACM学科类E.4中的材料，并与H.1.1有交集。
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一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Mathematics        数学
二级分类：Information Theory        信息论
分类描述：math.IT is an alias for cs.IT. Covers theoretical and experimental aspects of information theory and coding.
它是cs.it的别名。涵盖信息论和编码的理论和实验方面。
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英文摘要：
  NOMA is as a strong candidate for the Future Radio Access Network (FRA) due to its potential to support massive connectivity and high spectral efficiency. However, the most important drawback of NOMA is the error during Successive Interference Canceller (SIC) is implemented because of the inter-user interferences. In this paper, we derive closed-form exact Bit-Error Rate expressions for Downlink(DL) NOMA over Nakagami-m fading channels in the presence of SIC errors. The derived expressions are validated by the computer simulations. It is shown that the m parameter still represents the diversity order like as OMA systems. Besides, the BER performances of users for NOMA have substantially depended on the power allocation coefficient.
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PDF链接：
https://arxiv.org/pdf/1807.04577