To satisfy the explosive access demands of Internet-of-Things (IoT) devices, various kinds of multiple access techniques have received much attention. In this article, we investigate the multicast communication of a satellite and aerial-integrated network (SAIN) with rate-splitting multiple access (RSMA), where both satellite and unmanned aerial vehicle (UAV) components are controlled by network management center and operate in the same frequency band. Considering a content delivery scenario, the UAV subnetwork adopts the RSMA to support massive access of IoT devices (IoTDs) and achieve desired performances of interference suppression, spectral efficiency, and hardware complexity. We first formulate an optimization problem to maximize the sum rate of the considered system subject to the signal-interference-plus-noise-ratio requirements of IoTDs and per-antenna power constraints at the UAV and satellite. To solve this nonconvex optimization problem, we exploit the sequential convex approximation and the first-order Taylor expansion to convert the original optimization problem into a solvable one with the rank-one constraint, and then propose an iterative penalty function-based algorithm to solve it. Finally, simulation results verify that the proposed method can effectively suppress the mutual interference and improve the system sum rate compared to the benchmark schemes.

In this paper, we investigate secrecy-energy efficient hybrid beamforming (BF) schemes for a satellite-terrestrial integrated network, wherein a multibeam satellite system shares the millimeter wave spectrum with a cellular system. Under the assumption of imperfect angles of departure for the wiretap channels, the hybrid beamformer at the base station and digital beamformers at the satellite are jointly designed to maximize the achievable secrecy-energy efficiency, while satisfying signal-to-interference-plus-noise ratio constraints of both the earth stations (ESs) and cellular users. Since the formulated optimization problem is nonconvex and mathematically intractable, we propose two robust BF schemes to obtain approximate solutions with low complexity. Specifically, for the case of a single ES, we integrate the Charnes-Cooper approach with an iterative search algorithm to convert the original nonconvex problem into a solvable one and obtain the BF weight vectors. In the case of multiple ESs, by exploiting the sequential convex approximation method, we convert the original problem into a linear one with multiple matrix inequalities and second-order cone constraints, for which we obtain a solution with satisfactory performance. The effectiveness and superiority of the proposed robust BF design schemes are validated via simulations using realistic satellite and terrestrial downlink channel models.

Rate-splitting multiple access (RSMA) has recently received considerable attention due to its high efficiency in both spectral utilization and energy consumption. Inspired by this emerging technique, this paper presents a secure beamforming (BF) scheme for RSMA-based cognitive satellite terrestrial networks in the presence of multiple eavesdroppers. Assuming that the system operates in the millimeter wave band and only imperfect wiretap channel state information is available at the satellite and terrestrial base station, our objective is to maximize the secrecy-energy efficiency of the earth station (ES) while meeting the constraints on the ES secrecy rate, the cellular users’ rate requirements, and transmit power budgets of the satellite and base station. As the formulated optimization problem is mathematically intractable, by applying successive convex approximation and Taylor expansion methods, we propose a robust BF scheme to convert the nonconvex objective and constraints into convex ones, which can be iteratively solved. The effectiveness and superiority of the proposed scheme are confirmed through simulation results.

This paper investigates the massive access for a satellite-aerial-terrestrial network (SATN), where a high-altitude platform (HAP) is deployed as a relay to assist the uplink transmission from terrestrial user equipment (UE) to satellite. Unlike previous works, we adopt radio frequency (RF) and free space optical for the aerial-terrestrial and satellite-aerial links, respectively. Specifically, by assuming that imperfect angular information (IAI) of each UE is known at the HAP, we develop a space division multiple access (SDMA) scheme to maximize the ergodic sum rate (ESR). To this end, we first exploit the IAI to calculate the analytical expression of channel correlation matrix. Then, by considering the limitation of array freedom, we propose a subspace-based UE grouping and scheduling scheme to cluster all UEs into groups. Next, we present a computationally effective beamforming (BF) scheme for each UE at HAP to efficiently implement SDMA in the RF link. Furthermore, a closed-form expression for the ESR of the SATN is derived to validate the proposed BF and SDMA schemes. Finally, simulation results corroborate the derived theoretical formulas and reveal the impacts of array size, angular estimation error, the number of UEs and scheduling threshold on the system performance.

This letter investigates the multiuser downlink transmission performance of an asymmetric free space optical (FSO)/radio frequency (RF) link. Here, the satellite delivers signal to the unmanned aerial vehicle (UAV) through a FSO link subject to Gamma-Gamma distributed turbulence, while the UAV forwards the decoded signal to multiple users through RF links characterzied by the correlated Rayleigh fading channel. By adopting that the selective decode-and-forward (DF) protocol at the UAV, we derive a closed-form expression for ergodic capacity (EC) of the considered system, where the RF link exploits transmit beamforming (BF) based on statistical channel state information (CSI) to obtain better performance than single antenna scenarios in existing works. Then, with the help of the derived EC and the available statistical CSI, a novel proportional fair scheduling (PFS) scheme is proposed. Finally, numerical results are conducted to verify the correctness of the theoretical analysis and the superiorty of the proposed scheduling scheme.