Remote Radio Head Activation and User Association in Dense C-RANs

Cloud radio access networks (C-RANs) is a promising technology for improving the performance of future mobile networks. In this paper, we focus on the joint remote radio head (RRH) activation and user association problem in dense C-RANs. Considering that a certain required minimum data rate may not...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 69; no. 10; pp. 12216 - 12228
Main Authors: Wu, Zhikun, Fei, Zesong, Zheng, Zhong, Li, Bin, Han, Zhu
Format: Journal Article
Language:English
Published: New York IEEE 01.10.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0018-9545, 1939-9359
Online Access:Get full text
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Summary:Cloud radio access networks (C-RANs) is a promising technology for improving the performance of future mobile networks. In this paper, we focus on the joint remote radio head (RRH) activation and user association problem in dense C-RANs. Considering that a certain required minimum data rate may not be satisfied universally for all users in some situation, we aim to first maximize the number of users whose minimum data rate constraints can be guaranteed, and then maximize the system profit, which is a combination of the system throughput and the total power consumption. Due to the NP-hard feature of the problem, the conventional algorithms are impractical when the network size is large due to large computational complexity. Therefore, we adopt the max-sum algorithm to efficiently solve the joint RRH activation and user association problem, which can be implemented efficiently in a distributed manner. The signaling overhead of the max-sum algorithm can be reduced further by simplifying message updating rules and by shortening messages exchanged between nodes. Considering the fact that the high density of RRH deployment may hinder the convergence rate of the max-sum algorithm, we also propose a simplified algorithm by decomposing the original problem into two sub-problems, and each can be solved by the max-sum algorithm individually. Simulation results prove the efficiencies of the proposed algorithms.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2020.3016188