Joint Scheduling and Power Optimization for Delay Constrained Transmissions in Coded Caching Over Wireless Fading Channels

Abstract

Coded caching has become a hot research topic in recent years. However, existing studies rarely consider the delay constrained transmissions over wireless fading channels. For strict delay constrained content delivery over wireless fading channels, power optimization is usually required to achieve energy-efficient transmissions. Moreover, in coded caching, since the data to different users is transmitted via many coded multicast transmissions, the scheduling of these transmissions over fading channels is also critical for minimizing energy consumption. To this end, a joint scheduling and power optimization problem is formulated to minimize the expected energy consumption over wireless fading channels under strict delay constraints. Causal channel state information (CSI) is considered in this paper for practical cases, which nonetheless makes the optimal solution to this problem hard to achieve due to the uncertain future channel states. Therefore, a heuristic approach is developed to solve this problem. The number of slots for each coded multicast transmission is first determined by obtaining the optimal result of a nonlinear integer programming (NLIP) problem based on statistical channel estimations. Next, a closed-form inverse-waterfilling algorithm is carried out to allocate power for the coded transmissions under delay constraints, and then the one that saves the maximum energy consumption is scheduled for transmission. The heuristic approach is proved to achieve a result that is upper-bounded by a parameter times the optimal result of the original problem under non-causal CSI. Simulation results further show that compared to the benchmark with only slot allocation for each coded transmission, our approach with joint scheduling and power optimization can significantly save energy consumption while ensuring strict delay constraints.