Joint Caching and Transmission Design for Delay Minimization in Small Cell Networks

Caching and coordinated multi-point noncoherent joint transmission (JT) has been considered on top of small cell networks (SCNs) to greatly decrease network delay. Unlike existing studies that focus solely on optimizing caching based on specific transmission policies, we investigate the joint design of caching and JT strategies by considering their interactions. Due to the nonconvex nature of the joint optimization problem, we decouple it into a caching optimization subproblem and a transmission optimization subproblem. In SCNs, SBSs are selectively activated according to the transmission strategy to efficiently manage interference and enhance signal quality. In solving the caching optimization subproblem, the activation probabilities of all SBSs are modeled and a closed-form suboptimal caching algorithm is derived based the activation probabilities of all SBSs. Based on the closed-form caching algorithm, a distributed transmission scheme is designed by using the multi-agent reinforcement learning (MARL) method. Simulation results demonstrate that the closed-form caching algorithm achieves nearly optimal performance with significantly reduced complexity. Compared to heuristic schemes, optimization schemes, and MARL schemes, the proposed joint scheme achieves at least 80% reduction of the network delay.