Resource allocation optimisation for delay‐sensitive traffic in energy harvesting cloud radio access network

In this study, the authors study a sustainable resource allocation scheme for delay‐sensitive applications in an energy harvesting (EH)‐cloud radio access network (CRAN). The authors formulate an optimisation problem to maximise the user equipment (UE) utility and provide them with strong delay‐guarantee by jointly considering the stochastic EH process, dynamic wireless channel state. By using the Lyapunov stochastic network optimisation technique combined with virtual queues, the authors decompose the formulated problem into four sub‐problems, including channel allocation, data dropping, UE request scheduling and energy management. Based on the solutions of these sub‐problems, a UE optimal resource allocation algorithm is proposed to maximise UE utility while guaranteeing the delay bound and the sustainability of remote radio heads. Furthermore, this algorithm does not require any prior statistical information of the system, e.g. EH process and channel state. Both theoretical analyses and simulation results demonstrate that the proposed algorithm can achieve close‐to‐optimal UE utility, bounded data buffer, delay‐guarantee, and required battery capacity for the operation of the CRAN.