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Energy-Efficient Joint Congestion Control and Resource Optimization in Heterogeneous Cloud Radio Access Networks

机译:异构云无线接入网中的节能联合拥塞控制和资源优化

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摘要

The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm that integrates the advantages of cloud radio access networks and heterogeneous networks. In this paper, we study joint congestion control and resource optimization to explore the energy efficiency (EE)-guaranteed trade-off between throughput utility and delay performance in a downlink slotted H-CRAN. We formulate the considered problem as a stochastic optimization problem, which maximizes the utility of average throughput and maintains the network stability subject to the required EE constraint and transmit power consumption constraints by traffic admission control, user association, resource block allocation, and power allocation. Leveraging on the Lyapunov optimization technique, the stochastic optimization problem can be transformed and decomposed into three separate subproblems that can be concurrently solved at each slot. The third mixed-integer nonconvex subproblem is efficiently solved by utilizing the continuity relaxation of binary variables and the Lagrange dual decomposition method. Theoretical analysis shows that the proposal can quantitatively control the throughput-delay performance trade-off with the required EE performance. Simulation results consolidate the theoretical analysis and demonstrate the advantages of the proposal from the prospective of queue stability and power consumption. © 2016 IEEE.
机译:异构云无线电接入网络(H-CRAN)是一种有前途的范例,它融合了云无线电接入网络和异构网络的优势。在本文中,我们研究联合拥塞控制和资源优化,以探索在下行时隙H-CRAN中吞吐量效用和延迟性能之间的能效(EE)保证权衡。我们将考虑的问题表述为随机优化问题,该问题可以最大程度地提高平均吞吐量,并根据所需的EE约束保持网络稳定性,并通过流量准入控制,用户关联,资源块分配和功率分配来传输功耗约束。利用Lyapunov优化技术,可以将随机优化问题转换并分解为三个独立的子问题,这些子问题可以在每个时隙同时解决。通过利用二进制变量的连续松弛和拉格朗日对偶分解方法,可以有效地解决第三个混合整数非凸子问题。理论分析表明,该方案可以定量地控制吞吐量-延迟性能与所需的EE性能之间的折衷。仿真结果巩固了理论分析,并从队列稳定性和功耗的角度证明了该方案的优势。 ©2016 IEEE。

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