Power control by geometric programming

被引:648
作者
Chiang, Mung [1 ]
Tan, Chee Wei
Palomar, Daniel P.
O'Neill, Daniel
Julian, David
机构
[1] Princeton Univ, Dept Elect Engn, Princeton, NJ 08544 USA
[2] Sun Microsyst Inc, Santa Clara, CA 95054 USA
[3] Qualcomm, San Diego, CA 92121 USA
基金
美国国家科学基金会;
关键词
convex optimization; CDMA power control; distributed algorithms;
D O I
10.1109/TWC.2007.05960
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 [电气工程]; 0809 [电子科学与技术];
摘要
In wireless cellular or ad hoc networks where Quality of Service (QoS) is interference-limited, a variety of power control problems can be formulated as nonlinear optimization with a system-wide objective, e.g., maximizing the total system throughput or the worst user throughput, subject to QoS constraints from individual users, e.g., on data rate, delay, and outage probability. We show that in the high Signal-to-Interference Ratios (SIR) regime, these nonlinear and apparently difficult, nonconvex optimization problems can be transformed into convex optimization problems in the form of geometric programming; hence they can be very efficiently solved for global optimality even with a large number of users. In the medium to low SIR regime, some of these constrained nonlinear optimization of power control cannot be turned into tractable convex formulations, but a heuristic can be used to compute in most cases the optimal solution by solving a series of geometric programs through the approach of successive convex approximation. While efficient and robust algorithms have been extensively studied for centralized solutions of geometric programs, distributed algorithms have not been explored before. We present a systematic method of distributed algorithms for power control that is geometric-programming-based. These techniques for power control, together with their implications to admission control and pricing in wireless networks, are illustrated through several numerical examples.
引用
收藏
页码:2640 / 2651
页数:12
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