Pricing and power control for joint network-centric and user-centric radio resource management

被引:73
作者
Feng, N [1 ]
Mau, SC [1 ]
Mandayam, NB [1 ]
机构
[1] Rutgers State Univ, Dept Elect & Comp Engn, WINLAB, Piscataway, NJ 08854 USA
基金
美国国家科学基金会;
关键词
game theory; power control; pricing; radio resource management (RRM); revenue maximization; utility;
D O I
10.1109/TCOMM.2004.833191
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 ; 0809 ;
摘要
Objectives of most radio resource-management schemes can be classified as either user centric or network centric. User-centric schemes try to maximize the interests of individual users, while network-centric schemes optimize collective metrics for all users. These two types of resource management tend to result in qualitatively different resource allocations (with, sometimes, very different degrees of fairness). In this paper, we consider the joint optimization of both user-centric and network-centric metrics. Specifically, we use a utility function (measured in units of bits per Joule) as the user-centric metric, and for the network-centric counterpart, we consider a function of the sum of the throughputs of users in the network. The user-centric measure reflects the individual user's throughput, as well as the battery energy (transmit power) consumed to achieve it. The network-centric measure reflects the total revenue derived by the usage of network resources. We introduce an explicit pricing mechanism to mediate between the user-centric and network-centric resource-management problems. Users adjust their power in a distributed fashion to maximize the difference between their utilities and their payments (measured as a product of the unit price and throughput). The network adjusts the unit price in order to maximize its revenue (measured as the sum of the individual payments). We show that the distributed user-centric power control results in a unique Nash equilibrium. Our numerical results indicate that there exists a unique unit price that maximizes the revenue of the network. We also derive a semianalytical, computationally simple, and highly accurate approximation to the optimal solution. Our results show that while users with better channels receive better qualities of service, as usual (e.g., as in waterfilling), they also make proportionally higher contributions to the network revenue.
引用
收藏
页码:1547 / 1557
页数:11
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