Distributed Uplink Power Control for Optimal SIR Assignment in Cellular Data Networks
Distributed Uplink Power Control for Optimal SIR Assignment in Cellular Data Networks
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DOI：
10.1109/tnet.2008.918070
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发表时间：
2008-12
期刊：
影响因子：
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通讯作者：
P. Hande;S. Rangan;M. Chiang;Xinzhou Wu
中科院分区：
文献类型：
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作者：
P. Hande;S. Rangan;M. Chiang;Xinzhou Wu
本文通过分布式算法解决了多蜂窝无线网络上行链路的联合功率控制和信干比分配问题。1993年Foschini-Miljanic分布式功率控制可以达到给定的固定的和可行的SIR目标。然而，在数据网络中，SIR需要与无线数据网络中的发射功率联合优化。自20世纪90年代中期以来，在大量的研究文献中，这个联合优化问题的解决方案要么是分布式的，但次优，或最佳的，但集中。对于这个问题的凸公式，我们报告了一个分布式的最优算法。一直是研究瓶颈的主要问题是复杂的，耦合约束集，我们解决它通过重新参数化通过左Perron Frobenius特征向量，其次是本地可计算的上升方向的发展。一个关键的步骤是一个新的表征的可行的SIR区域在基站上的负载，并从移动的站，我们的术语溢出的潜在干扰的指示。基于此负载溢出特性，我们首先开发了一个分布式算法，可以实现任何帕累托最优SIR分配，然后一个分布式算法，挑选出一个特定的帕累托最优SIR分配和相关的权力，通过效用最大化。扩展到功率约束和干扰约束的情况下进行。该算法在理论上是合理的，实际上是可实现的：我们提出了收敛性和最优性证明，以及使用3GPP网络和路径损耗模型的模拟。
This paper solves the joint power control and SIR assignment problem through distributed algorithms in the uplink of multi-cellular wireless networks. The 1993 Foschini-Miljanic distributed power control can attain a given fixed and feasible SIR target. In data networks, however, SIR needs to be jointly optimized with transmit powers in wireless data networks. In the vast research literature since the mid-1990s, solutions to this joint optimization problem are either distributed but suboptimal, or optimal but centralized. For convex formulations of this problem, we report a distributed and optimal algorithm. The main issue that has been the research bottleneck is the complicated, coupled constraint set, and we resolve it through a re-parametrization via the left Perron Frobenius eigenvectors, followed by development of a locally computable ascent direction. A key step is a new characterization of the feasible SIR region in terms of the loads on the base stations, and an indication of the potential interference from mobile stations, which we term spillage. Based on this load-spillage characterization, we first develop a distributed algorithm that can achieve any Pareto-optimal SIR assignment, then a distributed algorithm that picks out a particular Pareto-optimal SIR assignment and the associated powers through utility maximization. Extensions to power-constrained and interference-constrained cases are carried out. The algorithms are theoretically sound and practically implementable: we present convergence and optimality proofs as well as simulations using 3GPP network and path loss models.