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Energy efficiency maximisation in downlink multi-cell networks via coordinated resource allocation

机译:通过协调资源分配最大化下行链路多小区网络中的能效

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There is a great interest in considering the energy efficiency (EE) as an important performance evaluation recently for its contribution to both energy saving and environmental conservation. In this study, the authors focus on the optimal energy-efficient design for downlink multi-cell environment with coordinated scheduling and beamforming. The EE is defined as bit-per-joule capacity to indicate how efficiently energy is consumed for transmitting information. They set up the optimum model for maximising the EE of coordinated cells subject to a total power constraint at each base station and study the resource allocation (RA) for it, including user selection, power allocation and beamforming vectors optimisation. They consider an equivalent non-fractional form of the original problem and propose an iterative algorithm to optimise the spectrum RA and beamforming vectors alternatively. In each iteration, the beamforming vectors are updated by the iterative algorithm based on the first-order optimality conditions, while the user scheduling policy is updated by the enhanced greedy algorithm. Performance studies show that the proposed algorithm has a rapid speed of convergence and achieves significant performance gain in EE for cellular networks.
机译:最近,人们将能效(EE)视为一项重要的性能评估,因为它对节能和环境保护都做出了很大的贡献。在这项研究中,作者集中于具有协调调度和波束成形的下行链路多小区环境的最佳节能设计。 EE被定义为每焦耳比特容量,以指示能量传输信息的效率如何。他们建立了一个最佳模型,以最大化每个基站受总功率约束的协作小区的EE,并研究其资源分配(RA),包括用户选择,功率分配和波束成形矢量优化。他们考虑了原始问题的等价非分数形式,并提出了一种迭代算法来交替优化频谱RA和波束成形向量。在每次迭代中,基于一阶最优性条件,通过迭代算法更新波束成形向量,而通过增强型贪婪算法,更新用户调度策略。性能研究表明,所提出的算法具有快速的收敛速度,并且在蜂窝网络的EE中获得了显着的性能提升。

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