Mode Selection and Power Allocation in Multi-Level Cache-Enabled Networks

Abstract

Moving contents proximity to the network edge and proactively caching popular contents at multiple infrastructures are promising directions for solving the backhaul congestion problem. This letter proposes and evaluates a multi-level cache-enabled network, where cache-hit users can fetch their data from the available cache at either small base-stations, unmanned aerial vehicles, or cache-enabled mobile device-to-device users. Cache-miss users, on the other hand, fetch their data from the central cloud via limited capacity backhaul links. This letter considers the problem of maximizing the network weighted-sum rate by jointly determining the users' mode of operation and their transmit powers, subject to backhaul capacity and transmit power constraints. After showing how the association problem can be formulated as a generalized assignment problem, the letter solves the transmit power problem using an iterative function evaluation apprach. The resulting mode-selection and power-allocation (MSPA) iterative algorithm is then tested through numerical simulations, which suggest that, while being easily implementable, the proposed multi-level caching can substantially relieve the backhaul congestion, especially in dense-networks, and at low-backhaul capacity regimes.