Adaptive resource allocation in NOMA-enabled backscatter communications systems

Deepa Das, Rajendra Kumar Khadanga, D. K. Rout
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Abstract

The integration of NOMA with Backscatter communication (BackCom) is a promising solution for developing a green future wireless network. However, system performance degrades with the deployment of multiple backscatter devices (BDs) in a network. Hence, energy efficiency (EE) maximization with proper resource allocation is among the primary concerns. In this regard, this paper proposes an adaptive resource allocation method for maximizing EE by simultaneously optimizing the transmission power from the base station (BS), power allocation coefficients, and reflection coefficients under the constraints of maximum allowable transmission power and minimum achievable data rate. Specifically, an iterative method based on a parametric transformation approach is adopted for maximizing EE by jointly optimizing the coefficients, in which the power allocation problem to the BDs is solved by an adaptive method that is based on improved proportionate normalized least mean square (IPNLMS) algorithm. Then, the system performance is evaluated, and the impact of different parameters is also studied it is observed that EE is significantly improved as compared to the existing scheme, and maximum at η=-0.5.
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支持 NOMA 的反向散射通信系统中的自适应资源分配
NOMA 与后向散射通信(BackCom)的集成是开发未来绿色无线网络的一个前景广阔的解决方案。然而,系统性能会随着网络中多个反向散射设备(BD)的部署而降低。因此,通过合理的资源分配实现能源效率(EE)最大化是首要关注的问题之一。为此,本文提出了一种自适应资源分配方法,在最大允许传输功率和最小可实现数据速率的约束条件下,同时优化基站(BS)的传输功率、功率分配系数和反射系数,从而实现 EE 最大化。具体来说,采用了一种基于参数变换方法的迭代法,通过联合优化系数来实现 EE 最大化,其中基站的功率分配问题由一种基于改进比例归一化最小均方(IPNLMS)算法的自适应方法来解决。然后,对系统性能进行了评估,并研究了不同参数的影响,结果表明,与现有方案相比,EE 得到了显著改善,并在η=-0.5 时达到最大值。
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