QoS-aware Joint RRH activation and clustering in cloud-RANs

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Abstract
Cloud Radio Access Networks (Cloud-RAN) promise to leverage cloud computing capabilities to enhance the quality and coverage of wireless networks. A dense network of remote radio heads (RRHs) ensures less attenuation at the receiver side. However, two drawbacks are associated with such dense network: the first is the high energy consumption associated with such a large number of RRHs; the second is the interference experienced by the receiver due to close proximity of the transmitters. To address these challenges, we study the problem of joint activation and clustering of RRHs. Since the problem is NP-hard, we provide a two-step algorithm that can find an efficient solution. The first step uses linear-programming relaxation to find a feasible solution. The second step is a greedy approach to improve the utility function through gradual activation-clustering of RRHs. Our simulation results demonstrate the benefit in the joint design of activation and clustering over existing activation only approaches.

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