Performances Analysis in Uplink Non-Orthogonal Multiple Access System with Imperfect Successive Interference Cancellation
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摘要: 非正交多址接入(NOMA)技术允许多个发送方共用同一个资源块，接收方通过连续干扰消除(SIC)解码出不同发送方的信息。然而，目前针对NOMA系统的研究大多基于理想SIC的假设，而没有考虑非理想SIC对系统性能带来的影响。针对此问题，该文在非理想SIC的假设下，针对单小区上行NOMA系统提出一套性能分析框架。首先，采用二项式点过程(BPP)对上行NOMA系统中基站和用户设备的空间分布进行建模。基于此模型，采用基于大尺度衰落的干扰消除顺序，对干扰消除的误差情况进行分析。进一步，基于随机几何理论和次序统计理论，推导出距基站由近至远次序为k的用户设备的覆盖概率，并采用平均覆盖概率衡量整个NOMA传输系统的可靠性。理论和仿真结果分析了远近次序、基站半径和发射功率等系统参数对传输可靠性的影响，并验证了理论推导的准确性。Abstract: Non-Orthogonal Multiple Access (NOMA) serves multiple transmitters using the same resource block, and the receiver decodes the information from different transmitters through Successive Interference Cancellation (SIC). However, most of the researches on NOMA systems are based on perfect SIC assumption, in which the impact of imperfect SIC on NOMA system is not considered. Focusing on this problem, a framework is provided to analyze the performance of single-cell uplink NOMA system under the assumption of imperfect SIC. Firstly, the Binomial Point Process (BPP) is used to model the spatial distribution of base station and user equipment in uplink NOMA system. Based on this model, the interference cancellation order which is based on large-scale fading is adopted, and then the error of interference cancellation is analyzed. Then, based on stochastic geometry theory and order statistics theory, the expression of coverage probability of user equipment which is at rank k in terms of the distance from the base station is derived, besides, the average coverage probability is adopted to reflect the reliability of NOMA transmission system. The analytical and simulation results show the influence of system parameters such as distance order and base station radius on transmission reliability. Also, the validity of theoretical deduction is verified.
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ZHANG Zekun, SUN Haijian, and HU R Q. Downlink and uplink non-orthogonal multiple access in a dense wireless network[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(12): 2771–2784. doi: 10.1109/JSAC.2017.2724646 李钊, 戴晓琴, 陈柯宇, 等. 非正交多址接入下行链路用户匹配与功率优化算法[J]. 电子与信息学报, 2017, 39(8): 1804–1811. doi: 10.11999/JEIT161197LI Zhao, DAI Xiaoqin, CHEN Keyu, et al. User matching and power optimization algorithm for downlink NOMA[J]. Journal of Electronics &Information Technology, 2017, 39(8): 1804–1811. doi: 10.11999/JEIT161197 宋康, 韦磊, 冀保峰, 等. 基于干扰消除的异构蜂窝网络中断分析[J]. 电子与信息学报, 2016, 38(2): 255–261. doi: 10.11999/JEIT150532SONG Kang, WEI Lei, JI Baofeng, et al. Outage performance for heterogeneous cellular networks with interference cancellation[J]. Journal of Electronics &Information Technology, 2016, 38(2): 255–261. doi: 10.11999/JEIT150532 YANG Chenchen, WANG Xiaodong, XIA Bin, et al. Joint interference cancellation in cache- and SIC-enabled networks[J]. IEEE Transactions on Communications, 2018, 66(9): 4155–4169. doi: 10.1109/TCOMM.2018.2821125 SHIRVANIMOGHADDAM M, DOHLER M, and JOHNSON S J. Massive non-orthogonal multiple access for cellular IoT: Potentials and limitations[J]. IEEE Communications Magazine, 2017, 55(9): 55–61. doi: 10.1109/MCOM.2017.1600618 TIMOTHEOU S and KRIKIDIS I. Fairness for non-orthogonal multiple access in 5G systems[J]. IEEE Signal Processing Letters, 2015, 22(10): 1647–1651. doi: 10.1109/LSP.2015.2417119 DING Zhiguo, FAN Pingzhi, and POOR H V. Impact of user pairing on 5G nonorthogonal multiple-access downlink transmissions[J]. IEEE Transactions on Vehicular Technology, 2016, 65(8): 6010–6023. doi: 10.1109/TVT.2015.2480766 ZHANG Ningbo, WANG Jing, KANG Guixia, et al. Uplink nonorthogonal multiple access in 5G systems[J]. IEEE Communications Letters, 2016, 20(3): 458–461. doi: 10.1109/LCOMM.2016.2521374 YANG Zheng, DING Zhiguo, FAN Pingzhi, et al. A general power allocation scheme to guarantee quality of service in downlink and uplink NOMA systems[J]. IEEE Transactions on Wireless Communications, 2016, 15(11): 7244–7257. doi: 10.1109/TWC.2016.2599521 TABASSUM H, HOSSAIN E, and HOSSAIN J. Modeling and analysis of uplink non-orthogonal multiple access in large-scale cellular networks using Poisson cluster processes[J]. IEEE Transactions on Communications, 2017, 65(8): 3555–3570. doi: 10.1109/TCOMM.2017.2699180 ZHANG Zekun and HU R Q. Uplink non-orthogonal multiple access with fractional power control[C]. 2017 IEEE Wireless Communications and Networking Conference (WCNC), San Francisco, USA, 2017: 1–6. doi: 10.1109/WCNC.2017.7925935. DING Zhiguo, YANG Zheng, FAN Pingzhi, et al. On the performance of non-orthogonal multiple access in 5G systems with randomly deployed users[J]. IEEE Signal Processing Letters, 2014, 21(12): 1501–1505. doi: 10.1109/LSP.2014.2343971 HE Biao, LIU An, YANG Nan, et al. On the design of secure non-orthogonal multiple access systems[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(10): 2196–2206. doi: 10.1109/JSAC.2017.2725698 ZHANG Shuai, XU Xiaoming, WANG Huiming, et al. Enhancing the physical layer security of uplink non-orthogonal multiple access in cellular internet of things[J]. IEEE Access, 2018, 6: 58405–58417. doi: 10.1109/ACCESS.2018.2875118 GANTI R K and HAENGGI M. Interference and outage in clustered wireless Ad hoc networks[J]. IEEE Transactions on Information Theory, 2009, 55(9): 4067–4086. doi: 10.1109/TIT.2009.2025543 RACHED N B, BOTEV Z, KAMMOUN A, et al. On the sum of order statistics and applications to wireless communication systems performances[J]. IEEE Transactions on Wireless Communications, 2018, 17(11): 7801–7813. doi: 10.1109/TWC.2018.2871201 DAVID H A and NAGARAJA H N. Order Statistics[M], Hoboken: Wiley, 2003. 期刊类型引用(23)
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