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Energy and Spectral Efficiency Tradeoff for Massive MIMO Systems With Transmit Antenna Selection

机译:具有发射天线选择的大规模MIMO系统的能量和频谱效率权衡

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摘要

This correspondence investigates the fundamental tradeoff between the spectral efficiency (SE) and energy efficiency (EE) for massive multiple-input multiple-output (MIMO) systems with linear precoding and transmit antenna selection, where both the circuit power consumption and the large-scale fading are considered. The EE and SE are optimized with respect to the number of transmit antennas and transmit power, and consequently, we formulate the EE–SE tradeoff as a mixed-integer-continuous-variable multiobjective optimization (MOO) problem. Using the derived EE–SE relations, the properties of the Pareto front for the EE–SE tradeoff are analyzed. To solve the complicated MOO problem, we develop two algorithms: the weighted-sum particle swarm optimization (WS-PSO) algorithm and the normal-boundary-intersection particle swarm optimization (NBI-PSO) algorithm. Simulation results show that the two algorithms can achieve the Pareto optimal EE-SE tradeoff, and NBI-PSO provides more evenly distributed solutions than WS-PSO.
机译:该对应关系研究了具有线性预编码和发射天线选择的大规模多输入多输出(MIMO)系统的频谱效率(SE)和能量效率(EE)之间的基本权衡,其中电路功耗和大规模考虑衰落。针对发射天线的数量和发射功率对EE和SE进行了优化,因此,我们将EE–SE的权衡公式化为混合整数连续可变多目标优化(MOO)问题。使用导出的EE-SE关系,分析EE-SE权衡的Pareto前沿的属性。为了解决复杂的MOO问题,我们开发了两种算法:加权和粒子群优化算法(WS-PSO)和法向边界相交粒子群优化算法(NBI-PSO)。仿真结果表明,两种算法都能实现帕累托最优的EE-SE折衷,并且NBI-PSO提供的解决方案比WS-PSO更均匀。

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