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Energy-Efficient Joint Scheduling and Power Control in Multi-Cell Wireless Networks

机译:多小区无线网络中的节能联合调度和功率控制

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Traditional design of wireless networks mainly focuses on system capacity and spectral efficiency. As green networking is an inevitable trend, energy-efficient design for future wireless networks becomes paramount. In this paper, we address energy-efficient resource management in downlink orthogonal frequency division multiple access networks. The focus is targeted toward multi-cell networks, which are composed of multiple base stations (BSs) sharing the available radio resources. Consequently, greater emphasis is given to techniques that take inter-cell interference into account. Resource management in our context refers to the task of allocating the radio resources in order to maximize energy efficiency. We devise resource management techniques that jointly tackle the problems of scheduling and power control. Accordingly, we adopt two different approaches: a centralized approach, where BSs coordinate in order to reach a globally optimal energy-efficient solution, and a distributed approach, where BSs selfishly strive to maximize their own energy efficiency. We portray the centralized approach as a convex optimization problem, whereas we have recourse to non-cooperative game theory to model the distributed approach. In particular, we show that the non-cooperative game converges to a unique Nash equilibrium in low- and high-interference scenarios. We perform thorough numerical simulations to quantify the discrepancy between the centralized and distributed approaches, and identify the conditions where they have precedence over the state of the art. Moreover, the simulation results highlight the fast convergence of our algorithms, which is a precious asset for realistic deployments.
机译:无线网络的传统设计主要集中在系统容量和频谱效率上。由于绿色联网是必然趋势,因此面向未来无线网络的节能设计变得至关重要。在本文中,我们解决了下行链路正交频分多址网络中的节能资源管理问题。重点针对多小区网络,它由共享可用无线电资源的多个基站(BS)组成。因此,更加重视考虑小区间干扰的技术。在我们的上下文中,资源管理是指分配无线电资源以最大程度地提高能源效率的任务。我们设计资源管理技术,共同解决调度和电源控制问题。因此,我们采用两种不同的方法:集中式方法(其中BS协调以达成全球最佳的节能解决方案)和分布式方法(其中BS自私地努力最大化自身的能源效率)。我们将集中式方法描述为凸优化问题,而我们采用非合作博弈理论来对分布式方法进行建模。特别是,我们证明了在低干扰和高干扰情况下,非合作博弈收敛到唯一的纳什均衡。我们进行全面的数值模拟,以量化集中式方法和分布式方法之间的差异,并确定条件优先于现有技术的条件。此外,仿真结果突出了我们算法的快速收敛性,这对于实际部署而言是宝贵的资产。

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