Resource Allocation for Green Cloud Radio Access Networks Powered by Renewable Energy

In this paper, we investigate the sustainable resource allocation for green Cloud Radio Access Networks (C-RAN) powered by renewable energy. Specifically, the Base Station pool (BS pool) in the C-RAN distributes data to a set of remote radio heads (RRHs) with energy harvesting (EH) capability, and allocates sub-carriers to the selected RRHs for downlink transmissions, by jointly considering the user throughput and energy sustainability performance of RRHs. To this end, we formulate a utility optimization problem, characterizing the stochastic process of energy harvesting (EH) and wireless fading channel. Based on Lyapunov optimization techniques, we decompose the formulated problem into three sub-problems, including energy harvesting, data scheduling, and sub-carrier allocation. We then propose an efficient online algorithm to obtain the maximal aggregate user utility while ensuring the stability of the data buffers and sustainability of the energy buffers. Performance analysis demonstrates that the proposed algorithm can achieve a suboptimal performance with guaranteed upper bounds on data queue and energy queue lengths. Extensive simulations validate the effectiveness and efficiency of the proposed algorithm.