Rate Splitting Multiple Access for Next Generation Cognitive Radio Enabled LEO Satellite Networks

This paper proposes a cognitive radio enabled LEO SatCom using RSMA radio access technique with the coexistence of GEO SatCom network. In particular, this work aims to maximize the sum rate of LEO SatCom by simultaneously optimizing the power budget over different beams, RSMA power allocation for users over each beam, and subcarrier user assignment while restricting the interference temperature to GEO SatCom. The problem of sum rate maximization is formulated as non-convex, where the global optimal solution is challenging to obtain. Thus, an efficient solution can be obtained in three steps: first we employ a successive convex approximation technique to reduce the complexity and make the problem more tractable. Second, for any given resource block user assignment, we adopt KKT conditions to calculate the transmit power over different beams and RSMA power allocation of users over each beam. Third, using the allocated power, we design an efficient algorithm based on the greedy approach for resource block user assignment. Numerical results demonstrate the benefits of the proposed optimization scheme compared to the benchmark schemes.

Rate Splitting Multiple Access for Cognitive Radio GEO-LEO Co-Existing Satellite Networks

LEO satellite communication has drawn particular attention recently due to its high data rate services and low round-trip latency. It is low-cost to launch and can provide global coverage. However, the spectrum scarcity might be one of the critical challenges in the growth of LEO satellites, impacting severe restrictions on the development of ground-space integrated networks. To address this issue, we propose RSMA for CR enabled GEO-LEO coexisting satellite network. In particular, this work aims to maximize the system's sum rate by simultaneously optimizing the power allocation and subcarrier beam assignment of LEO satellite communication while restricting the interference temperature to GEO satellite users. The problem of sum rate maximization is formulated as non-convex and a Global optimal solution is challenging to obtain. Therefore, we first employ the successive convex approximation technique to reduce the complexity and make the problem more tractable. Then for the power allocation, we exploit KKT condition and adopt an efficient algorithm based on the greedy approach for subcarrier beam assignment. We also propose two suboptimal schemes with fixed power allocation and random subcarrier beam assignment as the benchmark. Results demonstrate the benefits of the proposed scheme compared to the benchmark schemes.

Joint Beam Placement and Load Balancing Optimization for Non-Geostationary Satellite Systems

Non-geostationary (Non-GSO) satellite constellations have emerged as a promising solution to enable ubiquitous high-speed low-latency broadband services by generating multiple spot-beams placed on the ground according to the user locations. However, there is an inherent trade-off between the number of active beams and the complexity of generating a large number of beams. This paper formulates and solves a joint beam placement and load balancing problem to carefully optimize the satellite beam and enhance the link budgets with a minimal number of active beams. We propose a two-stage algorithm design to overcome the combinatorial structure of the considered optimization problem providing a solution in polynomial time. The first stage minimizes the number of active beams, while the second stage performs a load balancing to distribute users in the coverage area of the active beams. Numerical results confirm the benefits of the proposed methodology both in carrier-to-noise ratio and multiplexed users per beam over other benchmarks.

Joint Beam Hopping and Carrier Aggregation in High Throughput Multi-Beam Satellite Systems

Beam hopping (BH) and carrier aggregation (CA) are two promising technologies for the next generation satellite communication systems to achieve several orders of magnitude increase in system capacity and to significantly improve the spectral efficiency. While BH allows a great flexibility in adapting the offered capacity to the heterogeneous demand, CA further enhances the user quality-of-service (QoS) by allowing it to pool resources from multiple adjacent beams. In this paper, we consider a multi-beam high throughput satellite (HTS) system that employs BH in conjunction with CA to capitalize on the mutual interplay between both techniques. Particularly, an innovative joint BH-CA scheme is proposed and analyzed in this work to utilize their individual competencies. This includes designing an efficient joint time-space beam illumination pattern for BH and multi-user aggregation strategy for CA. Through this, user-carrier assignment, transponder filling-rates, beams hopping pattern, and illumination duration are all simultaneously optimized by formulating a joint optimization problem as a multi-objective mixed integer linear programming problem (MINLP). Simulation results are provided to corroborate our analysis, demonstrate the design tradeoffs, and point out the potentials of the proposed joint BH-CA concept. Advantages of our BH-CA scheme versus the conventional BH method without employing CA are investigated and presented under the same system circumstances.

Massive MIMO Hybrid Precoding for LEO Satellite Communications With Twin-Resolution Phase Shifters and Nonlinear Power Amplifiers

The massive multiple-input multiple-output (MIMO) transmission technology has recently attracted much attention in the non-geostationary, e.g., low earth orbit (LEO) satellite communication (SATCOM) systems since it can significantly improve the energy efficiency (EE) and spectral efficiency. In this work, we develop a hybrid analog/digital precoding technique in the massive MIMO LEO SATCOM downlink, which reduces the onboard hardware complexity and power consumption. In the proposed scheme, the analog precoder is implemented via a more practical twin-resolution phase shifting (TRPS) network to make a meticulous tradeoff between the power consumption and array gain. In addition, we consider and study the impact of the distortion effect of the nonlinear power amplifiers (NPAs) in the system design. By jointly considering all the above factors, we propose an efficient algorithmic approach for the TRPS-based hybrid precoding problem with NPAs. Numerical results show the EE gains considering the nonlinear distortion and the performance superiority of the proposed TRPS-based hybrid precoding scheme over the baselines.

Integration of NOMA with Reflecting Intelligent Surfaces: A Multi-cell Optimization with SIC Decoding Errors

Reflecting intelligent surfaces (RIS) has recently emerged as one of the promising technologies for achieving high energy and spectral efficiency in next-generation wireless networks. By using low-cost passive reflecting elements, RIS can smartly reconfigure the signal propagation to extend the wireless communication coverage. On the other side, Non-orthogonal multiple access (NOMA) has been proved as a key air interface technique for supporting massive connections over limited resources. This letter proposes a new optimization framework for the multicell RIS-NOMA network. In particular, we address the system spectral efficiency maximization with successive interference cancellation (SIC) decoding errors. The closed-form expressions of transmit power at the base station and power allocation coefficients of users are derived using Karush-Kuhn-Tucker conditions. Moreover, an efficient reflection matrix for RIS in each cell is designed using successive convex approximation and DC programming. Simulation results are provided to demonstrate the benefits of the proposed optimization in the multi-cell RISNOMA network.

Opportunities for Physical Layer Security in UAV Communication Enhanced with Intelligent Reflective Surfaces

Unmanned Aerial Vehicles (UAVs) are an important component of next-generation wireless networks that can assist in high data rate communications and provide enhanced coverage.Their high mobility and aerial nature offer deployment flexibility and low-cost infrastructure support to existing cellular networks and provide many applications that rely on mobile wireless communications. However, security is a major challenge in UAV communications, and Physical Layer Security (PLS) is an important technique to improve the reliability and security of data shared with the assistance of UAVs. Recently, Intelligent Reflecting Surfaces (IRS) have emerged as a novel technology to extend and/or enhance wireless coverage by re-configuring the propagation environment of communications. This paper provides an overview of how IRS can improve the PLS of UAV networks. We discuss different use cases of PLS for IRS enhanced UAV communications and briefly review the recent advances in this area. Then based on the recent advances, we also present a case study that utilizes alternate optimization to maximize the secrecy capacity for IRS enhanced UAV scenario in the presence of multiple eavesdroppers. Finally, we highlight several open issues and research challenges to realize PLS in IRS enhanced UAV communications.

Beam Squint-Aware Integrated Sensing and Communications for Hybrid Massive MIMO LEO Satellite Systems

The space-air-ground-sea integrated network (SAGSIN) plays an important role in offering global coverage. To improve the efficient utilization of spectral and hardware resources in the SAGSIN, integrated sensing and communications (ISAC) has drawn extensive attention. Most existing ISAC works focus on terrestrial networks and can not be straightforwardly applied in satellite systems due to the significantly different electromagnetic wave propagation properties. In this work, we investigate the application of ISAC in massive multiple-input multiple-output (MIMO) low earth orbit (LEO) satellite systems. We first characterize the statistical wave propagation properties by considering beam squint effects. Based on this analysis, we propose a beam squint-aware ISAC technique for hybrid analog/digital massive MIMO LEO satellite systems exploiting statistical channel state information. Simulation results demonstrate that the proposed scheme can operate both the wireless communications and the target sensing simultaneously with satisfactory performance, and the beam-squint effects can be efficiently mitigated with the proposed method in typical LEO satellite systems.

On the Impacts of Phase Shifting Design and Eavesdropping Uncertainty on Secrecy Metrics of RIS-aided Systems

This paper investigates the secrecy outage probability (SOP), the lower bound of SOP, and the probability of non-zero secrecy capacity (PNZ) of reconfigurable intelligent surface (RIS)-assisted systems from an information-theoretic perspective. In particular, we consider the impacts of eavesdroppers' location uncertainty and the phase adjustment uncertainty, namely imperfect coherent phase shifting and discrete phase shifting on RIS. More specifically, analytical and simulation results are presented to show that (i) the SOP gain due to the increase of the RIS reflecting elements number gradually decreases; and (ii) both phase shifting designs demonstrate the same PNZ secrecy performance, in other words, the random discrete phase shifting outperforms the imperfect coherent phase shifting design with reduced complexity.

Hybrid Analog/Digital Precoding for Downlink Massive MIMO LEO Satellite Communications

Massive multiple-input multiple-output (MIMO) is promising for low earth orbit (LEO) satellite communications due to the potential in enhancing the spectral efficiency. However, the conventional fully digital precoding architectures might lead to high implementation complexity and energy consumption. In this paper, hybrid analog/digital precoding solutions are developed for the downlink operation in LEO massive MIMO satellite communications, by exploiting the slow-varying statistical channel state information (CSI) at the transmitter. First, we formulate the hybrid precoder design as an energy efficiency (EE) maximization problem by considering both the continuous and discrete phase shift networks for implementing the analog precoder. The cases of both the fully and the partially connected architectures are considered. Since the EE optimization problem is nonconvex, it is in general difficult to solve. To make the EE maximization problem tractable, we apply a closed-form tight upper bound to approximate the ergodic rate. Then, we develop an efficient algorithm to obtain the fully digital precoders. Based on which, we further develop two different efficient algorithmic solutions to compute the hybrid precoders for the fully and the partially connected architectures, respectively. Simulation results show that the proposed approaches achieve significant EE performance gains over the existing baselines, especially when the discrete phase shift network is employed for analog precoding.