Cache-Aware Cooperative Multicast Beamforming in Dynamic Satellite-Terrestrial Networks

TL;DR

This paper tackles backhaul congestion and QoS degradation in cache-aided satellite-terrestrial networks by formulating a mixed-timescale optimization that jointly optimizes cache placement (long-term) and short-term content delivery, including satellite beam direction and cooperative multicast beamforming. A two-stage solution framework is developed: an improved Whale Optimization Algorithm for beam direction control and a successive convex approximation method for multicast beamforming, paired with a history-driven cache placement strategy. The approach is shown to converge and reduce network costs, with savings in transmission power and backhaul traffic reaching up to 52% under various scenarios and parameter settings. The work demonstrates that jointly optimizing edge caching with dynamic beam scheduling and multicast coordination yields substantial gains for energy-efficient, scalable content delivery in dynamic STNs, highlighting the practical impact for future non-terrestrial networks.

Abstract

With the burgeoning demand for data-intensive services, satellite-terrestrial networks (STNs) face increasing backhaul link congestion, deteriorating user quality of service (QoS), and escalating power consumption. Cache-aided STNs are acknowledged as a promising paradigm for accelerating content delivery to users and alleviating the load of backhaul links. However, the dynamic nature of low earth orbit (LEO) satellites and the complex interference among satellite beams and terrestrial base stations pose challenges in effectively managing limited edge resources. To address these issues, this paper proposes a method for dynamically scheduling caching and communication resources, aiming to reduce network costs in terms of transmission power consumption and backhaul traffic, while meeting user QoS demands and resource constraints. We formulate a mixed timescale problem to jointly optimize cache placement, LEO satellite beam direction, and cooperative multicast beamforming among satellite beams and base stations. To tackle this intricate problem, we propose a two-stage solution framework, where the primary problem is decoupled into a short-term content delivery subproblem and a long-term cache placement subproblem. The former subproblem is solved by designing an alternating optimization approach with whale optimization and successive convex approximation methods according to the cache placement state, while cache content in STNs is updated using an iterative algorithm that utilizes historical information. Simulation results demonstrate the effectiveness of our proposed algorithms, showcasing their convergence and significantly reducing transmission power consumption and backhaul traffic by up to 52%.

Figures (8)

• Figure 1: Illustration of the studied satellite-terrestrial network topology.
• Figure 2: Overview of the proposed content caching and delivery solution.
• Figure 3: The network topology at the fifth time slot. Dots represent users, hexagons denote base stations, and a diamond signifies the sub-satellite point.
• Figure 4: Convergence behavior of our proposal.
• Figure 5: Trade-offs between power cost and backhaul traffic with different $\rho$.