Distributed Uplink Power Control in Multiservice Wireless Networks via a Game Theoretic Approach with Convex Pricing
Distributed Uplink Power Control in Multiservice Wireless Networks via a Game Theoretic Approach with Convex Pricing
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DOI：
10.1109/tpds.2011.98
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发表时间：
2012
影响因子：
5.3
通讯作者：
E. Tsiropoulou;Georgios K. Katsinis;S. Papavassiliou
中科院分区：
文献类型：
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作者：
E. Tsiropoulou;Georgios K. Katsinis;S. Papavassiliou
在本文中，解决了支持多个服务的CDMA无线网络上链路中用户传输功率的有效分布式电源控制的问题。每个用户都与嵌套的公用事业功能相关联，该功能适当地代表了他对QoS意识的实际上行链路吞吐量和相应功耗之间的预期权衡的满意程度。最初，制定了多功能上行链路电源控制游戏（MSUPC），每个用户在强加的物理限制下自私地旨在最大程度地提高其基于公用事业的性能，并确定其独特的NASH平衡点。然后证明了MSUPC游戏NASH均衡的效率低下，并引入了基于用法的凸定价政策，与文献中已采用的线性定价方案相比，它提供了一种更有效的方法。因此，制定了带有凸定价（MSUPC-CP）的多服务上行链路控制游戏，并确定其独特的帕累托最佳NASH平衡。提出了用于计算MSUPC-CP游戏平衡的分布式迭代算法，而通过建模和仿真来说明总体方法的效率。
In this paper, the problem of efficient distributed power control via convex pricing of users' transmission power in the uplink of CDMA wireless networks supporting multiple services is addressed. Each user is associated with a nested utility function, which appropriately represents his degree of satisfaction in relation to the expected trade-off between his QoS-aware actual uplink throughput performance and the corresponding power consumption. Initially, a Multiservice Uplink Power Control game (MSUPC) is formulated, where each user aims selfishly at maximizing his utility-based performance under the imposed physical limitations and its unique Nash equilibrium point is determined. Then the inefficiency of MSUPC game's Nash equilibrium is proven and a usage-based convex pricing policy of the transmission power is introduced, which offers a more effective approach compared to the linear pricing schemes that have been adopted in the literature. Consequently, a Multiservice Uplink Power Control game with Convex Pricing (MSUPC-CP) is formulated and its unique Pareto optimal Nash equilibrium is determined. A distributed iterative algorithm for computing MSUPC-CP game's equilibrium is proposed, while the overall approach's efficiency is illustrated via modeling and simulation.