Resource Allocation in Heterogeneous Cloud Radio Access Networks: A Workload Balancing Perspective

Heterogeneous cloud radio access networks (H-CRANs) have been proposed as a promising architecture for providing high energy efficiency, high spectral efficiency and high data rate at low cost. In this paper, we develop a novel resource allocation scheme among macro base stations (BSs) and remote radio heads (RRHs) for the H-CRANs. The key idea of our proposal is that we design the coverage regions of macro BSs in a seamless and balanced way. Secondly, we calculate the areas that can not rely on macro BSs for reliable high speed data transmission and allocate resources in these areas among RRHs in the balanced way to alleviate the high transmission pressure on fronthauls between RRHs and the centralized baseband unit (BBU) pool. The proposed resource allocation scheme is triggered when severe disbalance is detected. Numerical results show that our proposal can perform quite well for the data traffic distribution in a real city environment. It provides QoS guaranteed performance with lower capital expenditure (CAPEX) and operating expenditure (OPEX).