Remote radio head (RRH) deployment in flexible C-RAN under limited fronthaul capacity

Abstract

Cloud radio access networks (C-RAN) has been regarded as a promising solution to the next generation communication system, but the massive fronthaul bandwidth required to aggregate baseband samples from remote radio head (RRH) to the baseband unit (BBU) pool has a significant impact on the performance of C-RAN. Existing baseband compression algorithms can hardly solve this problem. So, in this paper we consider a new flexible C-RAN architecture with two types of RRHs with different degrees of centralization in the network, namely, primitive RRH and RRH with Layer 1 functions. The objective is then to determine where and how many nodes of each type to be deployed in the target service region so that the deployment cost is minimized, under the condition that the fronthaul capacity is limited and the total traffic demand in the system is satisfied. We prove that the problem is NP-hard and propose an efficient algorithm with polynomial time complexity to solve the problem. The simulation results show that the proposed solution is indeed better than existing solutions and also adaptive to different types of traffic distributions and demands.