Rate-splitting multiple access for non-terrestrial communication and sensing networks

Rate-splitting multiple access (RSMA) has emerged as a powerful and flexible non-orthogonal transmission, multiple access (MA) and interference management scheme for future wireless networks. This thesis is concerned with the application of RSMA to non-terrestrial communication and sensing networks. Various scenarios and algorithms are presented and evaluated. First, we investigate a novel multigroup/multibeam multicast beamforming strategy based on RSMA in both terrestrial multigroup multicast and multibeam satellite systems with imperfect channel state information at the transmitter (CSIT). The max-min fairness (MMF)-degree of freedom (DoF) of RSMA is derived and shown to provide gains compared with the conventional strategy. The MMF beamforming optimization problem is formulated and solved using the weighted minimum mean square error (WMMSE) algorithm. Physical layer design and link-level simulations are also investigated. RSMA is demonstrated to be very promising for multigroup multicast and multibeam satellite systems taking into account CSIT uncertainty and practical challenges in multibeam satellite systems. Next, we extend the scope of research from multibeam satellite systems to satellite- terrestrial integrated networks (STINs). Two RSMA-based STIN schemes are investigated, namely the coordinated scheme relying on CSI sharing and the co- operative scheme relying on CSI and data sharing. Joint beamforming algorithms are proposed based on the successive convex approximation (SCA) approach to optimize the beamforming to achieve MMF amongst all users. The effectiveness and robustness of the proposed RSMA schemes for STINs are demonstrated. Finally, we consider RSMA for a multi-antenna integrated sensing and communications (ISAC) system, which simultaneously serves multiple communication users and estimates the parameters of a moving target. Simulation results demonstrate that RSMA is beneficial to both terrestrial and multibeam satellite ISAC systems by evaluating the trade-off between communication MMF rate and sensing Cramer-Rao bound (CRB).Open Acces

Throughput Enhancement and Power Optimization in NOMA-based Multiuser Multicast Systems

In recent years, Non-Orthogonal Multiple Access (NOMA) has emerged as a promising technique for enhancing the capacity and throughput of wireless communication systems. This thesis investigates the potential of NOMA in improving the performance of multiuser multicast systems, focusing on multibeam satellite communication systems in the forward link, throughput enhancement, and power optimization. We propose a novel framework that combines a NOMA scheme with multibeam architecture and frequency reuse in multicast transmission. The proposed framework enhances system throughput by optimizing power allocation. First, we present a comprehensive review of the principles and techniques related to NOMA and multibeam multicast systems, highlighting their unique challenges and potential benefits. Next, we introduce our proposed framework in 4-color frequency reuse satellite systems. In 4-color frequency reuse, each user receives signals from other co-channel beams. However, the level of isolation is such that the interbeam interference can be treated as background noise without significant performance degradation. This means that there is no collaboration between beams, and each beam can be isolated from the rest. Therefore, NOMA is considered in single-beam multicast satellite communication systems. The optimum power allocation to maximize the minimum fairness rate and sum-rate is derived for a given user clustering in a single beam. Moreover, an optimum user clustering is derived, which improves the system throughput. Next, we investigate our proposed framework in full frequency reuse satellite systems under perfect channel state information at the transmitter (CSIT). The proposed framework integrates the NOMA scheme in multicast multibeam architecture. Linear precoding techniques, such as zero-forcing (ZF) and minimum mean square error (MMSE), are used to cancel interbeam interference while NOMA is applied on a beam basis. NOMA and linear precoding are adopted for the proposed framework in multicast transmission. A low-complexity user scheduling is proposed to deal with the trade-offs between optimum user scheduling for linear precoding and the NOMA scheme. Moreover, a low-complexity linear precoding in multicast transmission is proposed based on unicast linear precoding methods and a mapper which deals with the lack of spatial degrees of freedom. To improve the performance of linear precoding, we present three mappers, where the proposed singular-value-decomposition (SVD) mapper demonstrates the best performance. To improve system throughput, power allocation should be optimized. In this thesis, we consider two objective functions: max-min fairness rate (MMF) and sum-rate. This thesis introduces a technique for addressing the non-convex MMF optimization issue in the proposed framework by employing auxiliary variables to convert it into a semi-definite programming problem, which can then be resolved using linear programming solvers. This thesis also suggests an approach to tackle the non-convex sum-rate maximization goal function in MB-MC-NOMA systems by constructing Lagrangian multipliers concerning the constraints. By employing quadratic transformations on the sum-of-ratios, the problem is restructured within an iterative sum-rate power optimization algorithm. This thesis considers a realistic scenario with imperfect CSIT. To combat the effect of imperfect CSIT in multibeam multicast satellite communication systems, a rate-splitting approach is proposed. An averaging rate (AR) framework for MMF rate and sum-rate optimization considering ICST is proposed. To render the formulated MMF and sum-rate problems convex, we utilize the Weighted Minimum Mean Square Error (WMMSE) method. We first derive a rate-WMMSE relationship and then, using this relationship along with a low-complexity solution based on Alternating Optimization (AO), we transform the problems into equivalent convex ones. To validate the effectiveness of our proposed frameworks, we conduct extensive simulations and comparisons with state-of-the-art schemes. The results demonstrate significant improvements in throughput and power efficiency, confirming the potential of NOMA-based multiuser multicast systems for future wireless communication networks. Finally, we discuss potential future research directions, including the integration of the proposed frameworks in the cellular networks, calculating the transmitter and receiver complexity of the proposed techniques, considering higher layers of RS. This thesis contributes to the ongoing development of next-generation wireless communication systems, paving the way for more efficient and reliable data transmission in multiuser multicast environments

Multigroup Multicast Precoding for Energy Optimization in SWIPT Systems with Heterogeneous Users

The key to developing future generations of wireless communication systems lies in the expansion of extant methodologies, which ensures the coexistence of a variety of devices within a system. In this paper, we assume several multicasting (MC) groups comprising three types of heterogeneous users including Information Decoding (ID), Energy Harvesting (EH) and both ID and EH. We present a novel framework to investigate the multi-group (MG) - MC precoder designs for three different scenarios, namely, Separate Multicast and Energy Precoding Design (SMEP), Joint Multicast and Energy Precoding Design (JMEP), and Per-User Information and/or Energy Precoding Design (PIEP). In the considered system, a multi-antenna source transmits the relevant information and/or energy to the groups of corresponding receivers using more than one MC streams. The data processing users employ the conventional ID receiver architectures, the EH users make use of a non-linear EH module for energy acquisition, while the users capable of performing both ID and EH utilize the separated architecture with disparate ID and non-linear EH units. Our contribution is threefold. Firstly, we propose an optimization framework to i) minimize the total transmit power and ii) to maximize the sum harvested energy, the two key performance metrics of MG-MC systems. The proposed framework allows the analysis of the system under arbitrary given quality of service and harvested energy requirements. Secondly, to deal with the non-convexity of the formulated problems, we transform the original problems respectively into equivalent forms, which can be effectively solved by semi-definite relaxation (SDR) and alternating optimization. The convergence of the proposed algorithms is analytically guaranteed. Thirdly, a comparative study between the proposed schemes is conducted via extensive numerical results, wherein the benefits of adopting SMEP over JMEP and PIEP models are discusse

Symbol-level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-art, Classification and Challenges

Precoding has been conventionally considered as an effective means of mitigating or exploiting the interference in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: i) transmitting distinct data streams to groups of users and ii) applying precoding on a symbol-per-symbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: i) the switching rate of the precoding weights, leading to the classes of block-level and symbol-level precoding, ii) the number of users that each stream is addressed to, hence unicast, multicast, and broadcast precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area

Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting

Recently, interest on the utilization of unmanned aerial vehicles (UAVs) has aroused. Specifically, UAVs can be used in cellular networks as aerial users for delivery, surveillance, rescue search, or as an aerial base station (aBS) for communication with ground users in remote uncovered areas or in dense environments requiring prompt high capacity. Aiming to satisfy the high requirements of wireless aerial networks, several multiple access techniques have been investigated. In particular, space-division multiple access(SDMA) and power-domain non-orthogonal multiple access (NOMA) present promising multiplexing gains for aerial downlink and uplink. Nevertheless, these gains are limited as they depend on the conditions of the environment. Hence, a generalized scheme has been recently proposed, called rate-splitting multiple access (RSMA), which is capable of achieving better spectral efficiency gains compared to SDMA and NOMA. In this paper, we present a comprehensive survey of key multiple access technologies adopted for aerial networks, where aBSs are deployed to serve ground users. Since there have been only sporadic results reported on the use of RSMA in aerial systems, we aim to extend the discussion on this topic by modelling and analyzing the weighted sum-rate performance of a two-user downlink network served by an RSMA-based aBS. Finally, related open issues and future research directions are exposed.Comment: 16 pages, 6 figures, submitted to IEEE Journa

Evaluation of multi-user multiple-input multiple-output digital beamforming algorithms in B5G/6G low Earth orbit satellite systems

Satellite communication systems will be a key component of 5G and 6G networks to achieve the goal of providing unlimited and ubiquitous communications and deploying smart and sustainable networks. To meet the ever-increasing demand for higher throughput in 5G and beyond, aggressive frequency reuse schemes (i.e., full frequency reuse), combined with digital beamforming techniques to cope with the massive co-channel interference, are recognized as a key solution. Aimed at (i) eliminating the joint optimization problem among the beamforming vectors of all users, (ii) splitting it into distinct ones, and (iii) finding a closed-form solution, we propose a beamforming algorithm based on maximizing the users' signal-to-leakage-and-noise ratio served by a low Earth orbit satellite. We investigate and assess the performance of several beamforming algorithms, including both those based on channel state information at the transmitter, that is, minimum mean square error and zero forcing, and those only requiring the users' locations, that is, switchable multi-beam. Through a detailed numerical analysis, we provide a thorough comparison of the performance in terms of per-user achievable spectral efficiency of the aforementioned beamforming schemes, and we show that the proposed signal to-leakage-plus-noise ratio beamforming technique is able to outperform both minimum mean square error and multi-beam schemes in the presented satellite communication scenario