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

Li, Jian and Peng, M. and Yu, Y. and Ding, Z. (2016) Energy-Efficient Joint Congestion Control and Resource Optimization in Heterogeneous Cloud Radio Access Networks. IEEE Transactions on Vehicular Technology, 65 (12). pp. 9873-9887. ISSN 0018-9545

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Abstract

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.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Transactions on Vehicular Technology
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200/2202
Subjects:
ID Code:
84958
Deposited By:
Deposited On:
28 Feb 2017 16:04
Refereed?:
Yes
Published?:
Published
Last Modified:
23 Sep 2020 03:23