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Power Allocation for Energy Efficient Multiple Antenna Systems With Joint Total and Per-Antenna Power Constraints

机译:具有联合总和每个天线功率约束的高能效多天线系统的功率分配

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摘要

An energy efficiency (EE) maximization problem with multiple transmit antennas (multiple-input-single-output or distributed antennas setups) is considered in this paper. Besides the constraint on the total transmit power, per-antenna transmit power constraints, and a total weighted power constraint are jointly considered. Moreover, a quality-of-service constraint is also considered. Both linear and nonlinear high power amplifier (HPA) cases are studied. Because the original problem for the linear HPA case is a fractional convex problem, Dinkelbach's algorithm is implemented to reformulate the problem. By investigating the Karush-Kuhn-Tucker conditions, the mathematical properties of the globally optimal solution are studied and proved, which provides a deeper understanding of the structure of power allocation among antennas. These properties also lead to a reduction of the complexity of the algorithms proposed to find the global optimum. For the nonlinear HPA cases, the reformulated problem after successive convex approximation is shown to be exactly in the same form as that of the previous problem with linear HPA with different weights of power consumption at each antenna. On the basis of numerical results comparing our EE maximization algorithms against different benchmarks, the efficiency and the superiority of our algorithms can be concluded.
机译:本文考虑了多发射天线(多输入单输出或分布式天线设置)的能量效率(EE)最大化问题。除了对总发射功率的约束之外,还共同考虑了每个天线的发射功率约束和总加权功率约束。此外,还考虑了服务质量约束。研究了线性和非线性高功率放大器(HPA)的情况。由于线性HPA案例的原始问题是分数凸问题,因此实现了Dinkelbach算法重新表述该问题。通过研究Karush-Kuhn-Tucker条件,研究并证明了全局最优解的数学性质,从而提供了对天线间功率分配结构的更深刻理解。这些特性还导致为找到全局最优而提出的算法的复杂性降低。对于非线性HPA情况,连续凸逼近后的重构问题显示为与线性HPA先前问题的形式完全相同,每个天线的功耗权重不同。根据将EE最大化算法与不同基准进行比较的数值结果,可以得出我们算法的效率和优越性。

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