Simultaneous Unicast and Multicast Transmissions in Stacked Intelligent Metasurfaces-assisted HAPS Wireless Networks: Performance Analysis and Optimization

TL;DR

This paper explores the use of stacked intelligent metasurfaces in HAPS wireless networks for simultaneous unicast and multicast transmissions, focusing on energy efficiency and optimization techniques.

Contribution

It introduces a novel SIM-based beamforming approach and develops two optimization methods, including a deep neural network, for energy-efficient HAPS communications.

Findings

Closed-form outage probability expressions derived for Rician channels.

Two optimization methods compared: AO framework and unsupervised DNN.

Simulation shows improved energy efficiency with proposed methods.

Abstract

In this paper, we investigate high-altitude platform station (HAPS) wireless networks for simultaneous non-orthogonal unicast and multicast transmissions. Specifically, stacked intelligent metasurface (SIM)-based wave-domain beamforming is proposed to enable efficient HAPS-to-ground communications. Also, the system performance is investigated from an energy-efficiency (EE) perspective, which is a crucial for HAPS operations. For performance analysis, we derive approximate closed-form expressions for the outage probability over Rician fading channels. For EE optimization, we jointly optimize the transmit power and the SIM phase-shifts for the maximal EE. Two methods are proposed to solve this non-convex optimization problem. The first method develops an efficient alternating optimization (AO) framework based on golden-section search and projected gradient ascent (PGA) for transmit power and phase-shift optimization, respectively. The second method uses unsupervised deep neural network (DNN) that does not require labeling. Performance comparison between the two methods, as well as with other benchmarks schemes are examined. Additionally, the impacts of the number of SIM elements per layers, the number of SIM layers, the maximum transmit power on the EE performance are evaluated. Simulation results are provided to demonstrate the performance of the proposed systems.