Satellite- and Cache-assisted UAV: A Joint Cache Placement, Resource Allocation, and Trajectory Optimization for 6G Aerial Networks

TL;DR

This paper proposes a joint optimization framework for cache placement, resource allocation, and trajectory planning in satellite-assisted UAV networks to maximize user throughput in 6G terrestrial communications.

Contribution

It introduces a novel joint optimization approach using BCD and SCA methods for UAV cache placement, resource management, and trajectory design in satellite-assisted networks.

Findings

Proposed algorithm significantly improves max-min throughput.

Joint optimization outperforms benchmark schemes.

Enhanced total achievable throughput in simulations.

Abstract

This paper considers LEO satellite- and cache-assisted UAV communications for content delivery in terrestrial networks, which shows great potential for next-generation systems to provide ubiquitous connectivity and high capacity. Specifically, caching is provided by the UAV to reduce backhaul congestion, and the LEO satellite supports the UAV's backhaul link. In this context, we aim to maximize the minimum achievable throughput per ground user (GU) by jointly optimizing cache placement, the UAV's resource allocation, and trajectory while cache capacity and flight time are limited. The formulated problem is challenging to solve directly due to its non-convexity and combinatorial nature. To find a solution, the problem is decomposed into three sub-problems: (1) cache placement optimization with fixed UAV resources and trajectory, followed by (2) the UAV resources optimization with fixed cache placement vector and trajectory, and finally, (3) we optimize the UAV trajectory with fixed cache placement and UAV resources. Based on the solutions of sub-problems, an efficient alternating algorithm is proposed utilizing the block coordinate descent (BCD) and successive convex approximation (SCA) methods. Simulation results show that the max-min throughput and total achievable throughput enhancement can be achieved by applying our proposed algorithm instead of other benchmark schemes.