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Energy Efficiency Maximization for Multi-Cell Multi-Carrier NOMA Networks

机译:多电池多载波NOMA网络的能效最大化

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摘要

As energy efficiency (EE) is a key performance indicator for the future wireless network, it has become a significant research field in communication networks. In this paper, we consider multi-cell multi-carrier non-orthogonal multiple access (MCMC-NOMA) networks and investigate the EE maximization problem. As the EE maximization is a mixed-integer nonlinear programming NP-hard problem, it is difficult to solve directly by traditional optimization such as convex optimization. To handle the EE maximization problem, we decouple it into two subproblems. The first subproblem is user association, where we design a matching-based framework to perform the user association and the subcarriers’ assignment. The second subproblem is the power allocation problem for each user to maximize the EE of the systems. Since the EE maximization problem is still non-convex with respect to the power domain, we propose a two stage quadratic transform with both a single ratio quadratic and multidimensional quadratic transform to convert it into an equivalent convex optimization problem. The power allocation is obtained by iteratively solving the convex problem. Finally, the numerical results demonstrate that the proposed method could achieve better EE compared to existing approaches for non-orthogonal multiple access (NOMA) and considerably outperforms the fractional transmit power control (FTPC) scheme for orthogonal multiple access (OMA).
机译:随着能源效率(EE)是未来无线网络的关键性能指标,它已成为通信网络中的重要研究领域。在本文中,我们考虑多小区多载波非正交多次访问(MCMC-NOMA)网络并调查EE最大化问题。随着EE最大化是一个混合整数非线性编程NP难题,难以通过传统优化直接解决,例如凸优化。为了处理EE最大化问题,我们将其分成两个子问题。第一个子问题是用户协会,我们设计了一种基于匹配的框架来执行用户关联和子载波的分配。第二个子问题是每个用户最大化系统EE的功率分配问题。由于EE最大化问题仍然是非凸出的电源域,因此我们提出了一种双级二次变换,单个比率二次和多维二次变换都将其转换为等效的凸优化问题。通过迭代解决凸面问题而获得功率分配。最后,数值结果表明,与现有的非正交多通道(NOMA)的现有方法相比,该方法可以实现更好的EE,并且相当胜过用于正交多次访问(OMA)的分数传输功率控制(FTPC)方案。

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