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On the Power Allocation Problem in the Gaussian Interference Channel with Proportional Rate Constraints

机译:具有比例速率约束的高斯干扰信道中的功率分配问题

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This paper takes an analytical approach to solving the optimization problem of finding the power allocation that maximizes the sum-rate of the Gaussian interference channel with any linear power (interference) constraint and proportional rate constraints. It is proved that the sum-rate of the Gaussian interference channel restricted to proportional rate constraints does not have a critical point and the maximum sum-rate subject to said constraints occurs at the boundary of the domain formed by the plane representing the linear power constraint. This is accomplished by using analytic geometry in higher dimensions to show that the curve of intersection of the sum-rate and the proportional rate constraints is always increasing, and intersects the boundary plane representing the linear power constraint at a unique point. A polynomial time (in the number of users) centralized algorithm that finds this point of optimal power allocation is proposed. This is a significant improvement over existing algorithms for related power allocation problems which have exponential time complexity in the number of users. Two distributed algorithms with linear and constant complexities are also presented. Simulation results supporting the analysis and demonstrating the performances of the algorithms are presented.
机译:本文采用一种分析方法来解决寻找功率分配的优化问题,该功率分配可以在任何线性功率(干扰)约束和比例率约束条件下最大化高斯干扰信道的总和。证明了受限于比例速率约束的高斯干扰信道的总速率没有临界点,并且受到所述约束的最大总速率出现在由代表线性功率约束的平面形成的区域的边界处。这是通过在更高维度上使用解析几何来完成的,以显示总和比率与比例比率约束的交点曲线始终在增加,并且在唯一点处与代表线性功率约束的边界平面相交。提出了一种多项式时间(用户数量)集中式算法,该算法可以找到最佳功率分配的这一点。这是对相关功率分配问题的现有算法的一项重大改进,该算法在用户数量上具有指数级的时间复杂度。还提出了具有线性和恒定复杂度的两种分布式算法。给出了支持分析并论证算法性能的仿真结果。

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