Total Delay Optimization in Cache-Enabled C-RANs With Hierarchical Rate Splitting

Abstract

This paper proposes a Hierarchical Rate Splitting (HRS)-based and Macro Base Station (MBS)-assisted cooperative content delivery scheme for Cache-enabled Cloud Radio Access Networks (C <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula> -RANs). In this scheme, a user is served by a cluster of Small Base Stations (SBSs) that cache contents. If the user-requested content is missing in its cache, the SBS retrieves it from the central processor (backhaul link) and the MBS (wireless broadcast). We minimize the total delay of this system. We thus optimize user grouping, decoding order, RS variables, BS clustering, and beamforming subject to the transmit power and backhaul capacity constraints. This process formulates a non-convex problem, which we decouple into three subproblems. First, we must pair users to reduce intra-group interference. We thus develop a Low-Complexity User Pairing (LCUP) algorithm. Second, we optimize the decoding order to minimize the broadcast link delay. We, therefore, propose a Dynamic Delay-based Decoding Order Update (D <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{3}$</tex-math></inline-formula> OU) algorithm. Third, we jointly design the RS variables, beamforming, and BS clustering. We use surrogate optimization via the Quadratic Transform (QT), Woodbury matrix identity, and Taylor expansion. We then recast this problem to a Two-Tier Alternating (TTA) problem, which we solve with closed-form (outer tier) and convex (inner tier) formulations. We integrate these algorithms to propose an overall algorithm. It achieves significant performance gains and a 3-fold reduction in time-complexity over the standard Semi-Definite Relaxation (SDR)-based algorithm and several benchmark schemes.