Exploiting Reconfigurable Intelligent Surfaces in Edge Caching: Joint Hybrid Beamforming and Content Placement Optimization

TL;DR

This paper introduces a novel RIS-assisted edge caching system that jointly optimizes content placement, active beamforming, and passive phase shifts to reduce network costs and improve wireless edge performance.

Contribution

It proposes an integrated optimization framework combining content placement and hybrid beamforming with RIS phase shifts, including new algorithms for non-convex problems.

Findings

Significant reduction in backhaul capacity usage.

Decreased power consumption at the network edge.

Effective joint optimization improves overall system performance.

Abstract

Edge caching can effectively reduce backhaul burden at core network and increase quality-ofservice at wireless edge nodes. However, the beneficial role of edge caching cannot be fully realized when the offloading link is in deep fade. Fortunately, the impairments induced by wireless propagation environments could be renovated by a reconfigurable intelligent surface (RIS). In this paper, a new RIS-aided edge caching system is proposed, where a network cost minimization problem is formulated to optimize content placement at cache units, active beamforming at base station and passive phase shifting at RIS. After decoupling the content placement subproblem with hybrid beamforming design, we propose an alternating optimization algorithm to tackle the active beamforming and passive phase shifting. For active beamforming, we transform the problem into a semidefinite programming (SDP) and prove that the optimal solution of SDP is always rank-1. For passive phase shifting, we introduce block coordinate descent method to alternately optimize the auxiliary variables and the RIS phase shifts. Further, a conjugate gradient algorithm based on manifold optimization is proposed to deal with the non-convex unit-modulus constraints. Numerical results show that our RIS-aided edge caching design can effectively decrease the network cost in terms of backhaul capacity and power consumption.