Throughput Maximization & Power Optimization Analysis in Non-Orthogonal Multiple Access System

Mohamed Gaballa, M. Abbod, Ahmed J. Jameel, Nirvana Khaled
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引用次数: 2

Abstract

Currently, non-orthogonal multiple access (NOMA) has been considered as a key authorizing multiple access scheme for 5G & beyond (B5G) cellular systems. In NOMA, by utilizing the variations in channels gain, multiple users can be multiplexed in power domain and then non-orthogonally organized for communication on the same spectrum resources. Practical successive interference cancellation (SIC) technique needs to be used at the receivers to decode the desired information signals. In this research, we formulate a downlink NOMA sum- throughput maximization problem in a cellular system such that power allocations for devices in NOMA cell can be optimized based on the transmitted power budget and Quality of service (QoS) constraints. Analysis for the objective function with the constraints to demonstrate the convexity of the optimization problem is presented. Lagrange multipliers and Karush-Kuhn-Tucker (KKT) optimality conditions are applied to derive the optimal power allocations. Simulations are conducted using Genetic algorithm (GA) solver to investigate the improvement achieved in power allocation using power optimization compared to the users with fixed power scenario in terms of bit error rate (BER), sum-rate, outage probability and SIC error.
非正交多址系统的吞吐量最大化与功率优化分析
目前,非正交多址(NOMA)已被认为是5G及以上(B5G)蜂窝系统的关键授权多址方案。在NOMA中,利用信道增益的变化,可以在功率域中实现多用户复用,然后在同一频谱资源上进行非正交组织通信。实际的连续干扰消除(SIC)技术需要在接收机上用于解码所需的信息信号。在本研究中,我们在蜂窝系统中提出了一个下行链路NOMA和吞吐量最大化问题,使得NOMA小区中设备的功率分配可以基于传输功率预算和服务质量(QoS)约束进行优化。给出了带约束的目标函数分析,证明了优化问题的凸性。应用拉格朗日乘子和KKT最优性条件推导出最优功率分配。利用遗传算法(GA)求解器进行了仿真,从误码率(BER)、和率、中断概率和SIC误差等方面研究了功率优化与固定功率场景下的用户相比在功率分配方面所取得的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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