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首页> 外文期刊>International journal of communication systems >Pricing and power control for energy-efficient radio resource management in cognitive femtocell networks
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Pricing and power control for energy-efficient radio resource management in cognitive femtocell networks

机译:认知毫微微小区网络中节能无线资源管理的定价和功率控制

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摘要

Cognitive femtocell has been considered as a promising technique that can improve the capacity and the utilization of spectrum efficiency in wireless networks because of the short transmission distance and low transmit power. In this paper, we study the win-win solution of energy-efficient radio resource management in cognitive femtocell networks, where the macrocell tries to maximize its revenue by adjusting spectrum utilization price while the femtocells try to maximize their revenues by dynamically adjusting the transmit power. When the spectrum utilization price is given by macrocell, we formulate the power control problem of standalone femtocells as an optimization problem and introduce a low-complexity iteration algorithm based on gradient-assisted binary search algorithm to solve it. Besides, non-cooperative game is used to formulate the power control problem between collocated femtocells in a collocated femtocell set, and then low complexity and widely used gradient-based iteration algorithm is applied to obtain the Nash-equilibrium solution. Specially, asymptotic analysis is applied to find the approximate spectrum utilization price in macrocell, which can greatly reduce the computational complexity of the proposed energy-efficient radio resource management scheme. Finally, extensive simulation results are presented to verify our theoretical analysis and demonstrate the performance of the proposed scheme. Copyright (c) 2013 John Wiley & Sons, Ltd.
机译:认知毫微微小区由于传输距离短,发射功率低而被认为是一种有前途的技术,可以提高无线网络的容量和频谱效率的利用率。在本文中,我们研究了认知型毫微微小区网络中节能无线资源管理的双赢解决方案,其中宏小区试图通过调整频谱利用价格来最大化其收入,而毫微微小区试图通过动态地调整发射功率来最大化其收入。 。当宏小区给出频谱利用价格时,我们将独立的毫微微小区的功率控制问题表述为一个优化问题,并提出一种基于梯度辅助二分查找算法的低复杂度迭代算法来解决。此外,利用非合作博弈来制定并置毫微微小区集中并置毫微微小区之间的功率控制问题,然后采用低复杂度和广泛使用的基于梯度的迭代算法来获得纳什均衡解。特别地,通过渐进分析来找到宏小区中的近似频谱利用价格,这可以大大降低所提出的节能无线电资源管理方案的计算复杂度。最后,给出了广泛的仿真结果,以验证我们的理论分析并证明了该方案的性能。版权所有(c)2013 John Wiley&Sons,Ltd.

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