Abstract:Low earth orbit (LEO) satellite systems with sensing functionality is envisioned to facilitate global-coverage service and emerging applications in 6G. Currently, two fundamental challenges, namely, inter-beam interference among users and power limitation at the LEO satellites, limit the full potential of the joint design of sensing and communication. To effectively control the interference, rate-splitting multiple access (RSMA) scheme is employed as the interference management strategy in the system design. On the other hand, to address the limited power supply at the LEO satellites, we consider low-resolution quantization digital-to-analog converters (DACs) at the transmitter to reduce power consumption, which grows exponentially with the number of quantization bits. Additionally, optimizing the total energy efficiency (EE) of the system is a common practice to save the power. However, this metric lacks fairness among users. To ensure this fairness and further enhance EE, we investigate the max-min fairness EE of the RSMA-assisted integrated sensing and communications (ISAC)-LEO satellite system. In this system, the satellite transmits a quantized dual-functional signal serving downlink users while detecting a target. Specifically, we optimize the precoders for maximizing the minimal EE among all users, considering the power consumption of each radio frequency (RF) chain under communication and sensing constraints. To tackle this optimization problem, we proposed an iterative algorithm based on successive convex approximation (SCA) and Dinkelbach's method. Numerical results illustrate that the proposed design outperforms the strategies that aim to maximize the total EE of the system and conventional space-division multiple access (SDMA) in terms of max-min fairness EE and the communication-sensing trade-off.
Abstract:Future wireless networks, in particular, 5G and beyond, are anticipated to deploy dense Low Earth Orbit (LEO) satellites to provide global coverage and broadband connectivity with reliable data services. However, new challenges for interference management have to be tackled due to the large scale of dense LEO satellite networks. Rate-Splitting Multiple Access (RSMA), widely studied in terrestrial communication systems and Geostationary Orbit (GEO) satellite networks, has emerged as a novel, general, and powerful framework for interference management and multiple access strategies for future wireless networks. In this paper, we propose a multilayer interference management scheme for spectrum sharing in heterogeneous GEO and LEO satellite networks, where RSMA is implemented distributedly at GEO and LEO satellites, namely Distributed-RSMA (D-RSMA), to mitigate the interference and boost the user fairness of the system. We study the problem of jointly optimizing the GEO/LEO precoders and message splits to maximize the minimum rate among User Terminals (UTs) subject to a transmit power constraint at all satellites. A Semi-Definite Programming (SDP)-based algorithm is proposed to solve the original non-convex optimization problem. Numerical results demonstrate the effectiveness and network load robustness of our proposed D-RSMA scheme for multilayer satellite networks. Because of the data sharing and the interference management capability, D-RSMA provides significant max-min fairness performance gains when compared to several benchmark schemes.
Abstract:In this paper, we initiate the study of rate-splitting multiple access (RSMA) for a mono-static integrated sensing and communication (ISAC) system, where the dual-functional base station (BS) simultaneously communicates with multiple users and detects multiple moving targets. We aim at optimizing the ISAC waveform to jointly maximize the max-min fairness (MMF) rate of the communication users and minimize the largest eigenvalue of the Cram\'er-Rao bound (CRB) matrix for unbiased estimation. The CRB matrix considered in this work is general as it involves the estimation of angular direction, complex reflection coefficient, and Doppler frequency for multiple moving targets. Simulation results demonstrate that RSMA maintains a larger communication and sensing trade-off than conventional space-division multiple access (SDMA) and it is capable of detecting multiple targets with a high detection accuracy. The finding highlights the potential of RSMA as an effective and powerful strategy for interference management in the general multi-user multi-target ISAC systems.
Abstract:Extreme crowding of electromagnetic spectrum in recent years has led to the emergence of complex challenges in designing sensing and communications systems. Both systems need wide bandwidth to provide a designated quality-of-service thus resulting in competing interests in exploiting the spectrum. Efficient spectrum utilization has led to the emergence of Integrated Sensing and Communications (ISAC) systems, an approach listed for beyond 5G networks. Several seminal works focusing on the physical and medium-access layer as well as system aspects of ISAC have appeared in the literature already. These works largely focus on terrestrial communications and the use of near-earth objects like Unmanned Aerial Vehicles (UAV)s. The focus of this work is to explore the ISAC in the emerging massive Low Earth Orbit (LEO) satellite systems, leveraging on their low latency, density, ubiquitous coverage and ease of integration. In particular, two aspects of the ISAC: opportunistic and optimized will be highlighted in this work through the use of LEO satellites for positioning as well as the use of Rate-Splitting Multiple Access (RSMA) technique optimized to address sensing and communication requirements.
Abstract:Energy efficiency (EE) problem has become an important and major issue in satellite communications. In this paper, we study the beamforming design strategy to maximize the EE of rate-splitting multiple access (RSMA) for the multibeam satellite communications by considering imperfect channel state information at the transmitter (CSIT). We propose an expectation-based robust beamforming algorithm against the imperfect CSIT scenario. By combining the successive convex approximation (SCA) with the penalty function transformation, the nonconvex EE maximization problem can be solved in an iterative manner. The simulation results demonstrate the effectiveness and superiority of RSMA over traditional space division multiple access (SDMA). Moreover, our proposed beamforming algorithm can achieve better EE performance than the conventional beamforming algorithm.
Abstract:This letter is the second part of a three-part tutorial focusing on rate-splitting multiple access (RSMA) for 6G. As Part II of the tutorial, this letter addresses the interplay between RSMA and integrated radar sensing and communications (ISAC). In particular, we introduce a general RSMAassisted ISAC architecture, where the ISAC platform has a dual capability to simultaneously communicate with downlink users and probe detection signals to a moving target. Then, the metrics of radar sensing and communications are respectively introduced, followed by a RSMA-assisted ISAC waveform design example which jointly minimizes the Cramer-Rao bound (CRB) of target estimation and maximizes the minimum fairness rate (MFR) amongst communication users subject to the per-antenna power constraint. The superiority of RSMA-assisted ISAC is verifed through simulation results in both terrestrial and satellite scenarios. RSMA is demonstrated to be a powerful multiple access and interference management strategy for ISAC, and provides a better communication-sensing trade-off compared with the conventional benchmark strategies. Consequently, RSMA is a promising technology for next generation multiple access (NGMA) and future networks such as 6G and beyond.
Abstract:In this paper, we consider a multi-antenna dual-functional radar-communication (DFRC) satellite system, where the satellite has a dual capability to simultaneously communicate with downlink satellite users (SUs) and probe detection signals to a moving target. To design an appropriate DFRC waveform, we investigate the rate-splitting multiple access (RSMA)-assisted DFRC beamfoming, and employ the Cramer-Rao bound (CRB) as a radar performance metric, which represents a lower bound on the variance of unbiased estimators. The beamforming is optimized to minimize the CRB subject to quality of service (QoS) constraints of SUs and a per-feed transmit power budget. Satellite communication and detecting ground/ sea objects in a bistatic mode are accomplished simultaneously using the DFRC waveform we designed. Simulation results demonstrate that the proposed RSMA-assisted DFRC beamforming outperforms the conventional space-division multiple access (SDMA) strategy in terms of the communication-sensing trade-off and target estimation performance in a multibeam satellite system.
Abstract:This work studies the joint beamforming design problem of achieving max-min rate fairness in a satellite-terrestrial integrated network (STIN) where the satellite provides wide coverage to multibeam multicast satellite users (SUs), and the terrestrial base station (BS) serves multiple cellular users (CUs) in a densely populated area. Both the satellite and BS operate in the same frequency band. Since rate-splitting multiple access (RSMA) has recently emerged as a promising strategy for non-orthogonal transmission and robust interference management in multi-antenna wireless networks, we present two RSMA-based STIN schemes, namely the coordinated scheme relying on channel state information (CSI) sharing and the cooperative scheme relying on CSI and data sharing. Our objective is to maximize the minimum fairness rate amongst all SUs and CUs subject to transmit power constraints at the satellite and the BS. A joint beamforming algorithm is proposed to reformulate the original problem into an approximately equivalent convex one which can be iteratively solved. Moreover, an expectation-based robust joint beamforming algorithm is proposed against the practical environment when satellite channel phase uncertainties are considered. Simulation results demonstrate the effectiveness and robustness of our proposed RSMA schemes for STIN, and exhibit significant performance gains compared with various traditional transmission strategies.
Abstract:Rate-splitting multiple access (RSMA) is a promising technique for downlink multi-antenna communications owning to its capability of enhancing the system performance in a wide range of network loads, user deployments and channel state information at the transmitter (CSIT) inaccuracies. In this paper, we investigate the achievable rate performance of RSMA in a multi-user multiple-input single-output (MU-MISO) network where only slow-varying statistical channel state information (CSI) is available at the transmitter. RSMA-based statistical beamforming and the split of the common stream is optimized with the objective of maximizing the minimum user rate subject to a sum power budget of the transmitter. Two statistical CSIT scenarios are investigated, namely the Rayleigh fading channels with only spatial correlations known at the transmitter, and the uniform linear array (ULA) deployment with only channel amplitudes and mean of phase known at the transmitter. Numerical results demonstrate the explicit max min fairness (MMF) rate gain of RSMA over space division multiple access (SDMA) in both scenarios. Moreover, we demonstrate that RSMA is more robust to the inaccuracy of statistical CSIT.
Abstract:Rate-splitting multiple access (RSMA), relying on linearly precoded rate-splitting (RS) at the transmitter and successive interference cancellation (SIC) at the receivers has emerged as a powerful and flexible multiple access strategy for downlink multi-user multi-antenna systems. Through message splitting and the transmission of both common and private messages, RSMA has been demonstrated to be a robust interference management strategy which enables partially decoding interference and partially treating interference as noise. In this work, we consider the application of RSMA in a multigroup multicast scenario, where each message is intended to a group of users. By leveraging the recent results on the max-min fair (MMF) optimization problem of RSMA-based multigroup multicast beamforming with imperfect channel state information at the transmitter (CSIT), we investigate the design of the physical (PHY) layer including finite length polar coding, finite alphabet modulation, adaptive modulation and coding (AMC) algorithm, and SIC receivers, etc. Link-level simulation (LLS) results verify the superiority of RSMA-based multigroup multicast transmission compared with space-division multiple access (SDMA)-based strategy in both cellular systems and multibeam satellite systems.