Optimizing Air-borne Network-in-a-box Deployment for Efficient Remote Coverage

TL;DR

This paper proposes a novel deployment of low-altitude platform stations with network-in-a-box units and high-altitude backhaul to improve remote wireless coverage efficiently, emphasizing system planning and resource optimization.

Contribution

It introduces a new airborne network-in-a-box deployment framework utilizing HAPS backhaul and advanced coding techniques for enhanced remote coverage.

Findings

Optimized placement and resource allocation improve coverage.

System planning significantly enhances performance under limited resources.

Superposition coding and SIC effectively manage interference.

Abstract

Among many envisaged drivers for the sixth generation, one is from the United Nations Sustainability Development Goals 2030 to eliminate digital inequality. Remote coverage in sparsely populated areas, difficult terrains, or emergency scenarios requires on-demand access and flexible deployment with minimal capex and opex. In this context, network-in-a-box (NIB) is an exciting solution that packs the whole wireless network into a single portable and re-configurable box to support multiple access technologies such as WiFi/2G/3G/4G/5G etc. In this paper, we propose low-altitude platform stations (LAPS) based NIBs with stratospheric high-altitude platform station (HAPS) as backhaul. Specifically, backhaul employs non-orthogonal multiple access (NOMA) with superposition coding at the transmitting HAPS and successive interference cancellation (SIC) at the receiving NIBs, whereas the access link (AL) employs superposition coding along with the regularized zero-forcing (RZF) precoding at the NIB in order to elevate the computational overhead from the ground users. The required number of airborne NIBs to serve a desired coverage area, their optimal placement, user association, beam optimization, and resource allocation are optimized by maximizing the sum rate of the AL while maintaining the quality of service. Our findings reveal the significance of thorough system planning and communication parameters optimization for enhanced system performance and best coverage under limited resources.