Edge Caching and Content Delivery with Minimized Delay for Both High-Speed Train and Local Users

In this paper, we investigate the edge caching and content delivery problem for both high-speed train (HST) passengers and low-mobility cellular users. Under multi-dimensional resources constraints, we formulate an optimization problem to minimize the content retrieval delay of HST passengers and meanwhile guarantee the delay requirements of cellular users. As the formulated problem is a mixed-integer nonconvex optimization problem, which is intractable directly, we propose an efficient iterative algorithm that optimizes the three decision variables (i.e., content placement, subchannel allocation, and transmission power allocation) alternately. In specific, Lagrangian multiplier is introduced to convert the constrained optimization, which transforms the content caching problem into a Lagrangian relaxed knapsack problem. Afterwards, the subchannel assignment problem is solved by the Hungarian algorithm with polynomial time complexity, and the power allocation strategy is obtained by the bisection method. Extensive simulations are carried out and results demonstrate that our proposed caching strategy can reduce the content retrieval delay by up to 25% in comparison with the benchmark strategy.