Power control for wireless data

Power control for wireless data
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DOI:
10.1109/momuc.1999.819473
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发表时间:
1999-11
期刊:
1999 IEEE International Workshop on Mobile Multimedia Communications (MoMuC'99) (Cat. No.99EX384)
影响因子:
--
通讯作者:
D. Goodman;N. Mandayam
D. Goodman;N. Mandayam
中科院分区:
其他
文献类型:
--
作者:
D. Goodman;N. Mandayam

文献摘要

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随着蜂窝电话成为大众消费品,下一个前沿领域是移动的多媒体通信。这种情况提出了对语音以外的信息源进行功率控制的问题。为了探讨这个问题,我们使用微观经济学和博弈论的概念和数学。在本文中,电话呼叫的服务质量被称为“效用”,CDMA电话的分布式功率控制问题是一个“非合作博弈”。功率控制算法对应于具有被称为“纳什均衡”的局部最优操作点的策略。电话功率控制算法在博弈论术语中也是“帕累托有效”的。当我们在无线数据传输中应用相同的方法进行功率控制时,我们发现相应的策略虽然局部最优,但不是帕累托有效的。相对于电话算法,还有其他算法,它们至少对一个终端产生更高的效用,而不降低对任何其他终端的效用。本文提出了一个这样的算法。该算法包括一个价格函数,成比例的发射机功率。价格相当于对传输的效用征税。当终端调整它们的功率水平以最大化净效用(效用价格)时,它们达到比它们单独努力最大化效用时所达到的更低的功率水平和更高的效用。
With cellular phones mass-market consumer items, the next frontier is mobile multimedia communications. This situation raises the question of power control for information sources other than voice. To explore this issue, we use the concepts and mathematics of microeconomics and game theory. In this context, the quality of service of a telephone call is referred to as the "utility" and the distributed power control problem for a CDMA telephone is a "noncooperative game". The power control algorithm corresponds to a strategy that has a locally optimum operating point referred to as a "Nash equilibrium". The telephone power control algorithm is also "Pareto efficient" in the terminology of game theory. When we apply the same approach to power control in wireless data transmissions, we find that the corresponding strategy, while locally optimum, is not Pareto efficient. Relative to the telephone algorithm, there are other algorithms that produce higher utility for at least one terminal, without decreasing the utility for any other terminal. This paper presents one such algorithm. The algorithm includes a price function, proportional to the transmitter power. The price acts as a tax on the utility of a transmission. When terminals adjust their power levels to maximize the net utility (utility price), they arrive at lower power levels and higher utility than they achieve when they individually strive to maximize utility.