peer reviewed

Satellite communications (SatComs) have recently been through a renaissance, both technologically and entrepreneurially. Ambitious plans have already come into fruition with the operation of low-Earth orbit (LEO) constellations including thousands of satellites and supported by state of the art but proprietary technologies, such as active antenna arrays and intersatellite links (ISLs). In this context, this article aims to provide a forward-looking vision of use cases and a deep dive into technological enablers that will be prominent in space communications beyond 2030. In parallel, it motivates how open standards can play a role in delivering affordable communication services in space. Starting from the 5G plans for nonterrestrial networks, we provide a survey and roadmap toward artificial intelligence (AI)-supported satellite systems, space-enabled quantum networks, and joint communications and positioning (JCAP) for space missions and interplanetary exploration.

This paper investigates downlink transmission in 5G Integrated Satellite-Terrestrial Networks (ISTNs) supporting automotive users (UEs) in urban environments, where base stations (BSs) and Low Earth Orbit (LEO) satellites (LSats) cooperate to serve moving UEs over shared C-band frequency carriers. Urban settings, characterized by dense obstructions, together with UE mobility, and the dynamic movement and coverage of LSats pose significant challenges to user association and resource allocation. To address these challenges, we formulate a multi-objective optimization problem designed to improve both throughput and seamless handover (HO). Particularly, the formulated problem balances sum-rate (SR) maximization and connection change (CC) minimization through a weighted trade-off by jointly optimizing power allocation and BS-UE/LSat-UE associations over a given time window. This is a mixed-integer and non-convex problem which is inherently difficult to solve. To solve this problem efficiently, we propose an iterative algorithm based on the Successive Convex Approximation (SCA) technique. Furthermore, we introduce a practical prediction-based algorithm capable of providing efficient solutions in real-world implementations. Especially, the simulations use arealistic 3D map of Londonand UE routes obtained from the Google Navigator application to ensure practical examination. Thanks to these realistic data, the simulation results can show valuable insights into the link budget assessment in urban areas due to the impact of buildings on transmission links under the blockage, reflection, and diffraction effects. Furthermore, the numerical results demonstrate the effectiveness of our proposed algorithms in terms of SR and the CC-number compared to the greedy and benchmark algorithms.

High capacity satellite networks utilize beamforming as a critical pillar to ensure efficient and reliable communication. This paper presents a scalable and constrained clustering algorithm for downlink MEO beamforming with detailed attention to load balancing. We propose a three-step approach to address the challenges of grouping users under minimum load constraints as well as antenna requirements. The low-complexity algorithm operates by first sampling available user-traffic-data while respecting Must-Link (ML) and Cannot-Link (CL) constraints such that the sampled subset is representative of the entire dataset. In the second step, a Bivariate Gaussian Mixture Model (BGMM) is applied to cluster the sampled data, incorporating the ML/CL constraints directly into an expectation-maximization (EM) process. The user/beam assignments are computed by considering both spatial proximity and operator linkage constraints to address beams compliance with the defined relationships between users. The final step involves populating these clusters with the remaining data points using a modified stable marriage algorithm, ensuring each component meets the minimum load requirements. Critical iterative refinements are performed to optimize the cluster assignments while guaranteeing convergence to a balanced and efficient beamforming solution. The effectiveness of the proposed solution is tested against a payload system with/without power flexibility, which is often hard to parameterize optimally.

This paper examines integrated satellite-terrestrial networks (ISTNs) in urban environments, where terrestrial networks (TNs) and non-terrestrial networks (NTNs) share the same frequency band in the C-band which is considered the promising band for both systems. The dynamic issues in ISTNs, arising from the movement of low Earth orbit satellites (LEOSats) and the mobility of users (UEs), are addressed. The goal is to maximize the sum rate by optimizing link selection for UEs over time. To tackle this challenge, an efficient iterative algorithm is developed. Simulations using a realistic 3D map provide valuable insights into the impact of urban environments on ISTNs and also demonstrates the effectiveness of the proposed algorithm.

The advent of Satellite as a Service (SaaS) platforms has empowered satellite service providers (SPs) to rent portions of satellite capacity from infrastructure providers (IPs) to cater to the diverse demands of their users across multiple satellite services. To effectively manage costs and maintain a high Quality of Experience (QoE) for numerous concurrent connections, SPs should secure flexible capacity from IPs. However, the irregular and unpredictable nature of traffic demands from various applications complicates the capacity-renting framework. This study presents a dynamic capacity allocation framework that efficiently handles diverse traffic flows with varying arrival rates, aiming to minimize rental costs while meeting blocking probability and QoE requirements. Utilizing theMt/Mt/1 queuing model and a continuous-time Markov chain, the technical designs are framed as a statistical optimization problem. In this context, the system waiting-queue lengths are estimated using the transient probabilities of Kolmogorov equations. Subsequently, cumulative distribution functions are employed to re-formulate this stochastic optimization problem into a convex form, which can be tackled through the Lagrangian duality method.Through extensive simulations and numerical assessments, we illustrate our method’s efficacy, with the proposed algorithm outperforming benchmarks by reducing costs by up to 9.85% and 3.1%.

This paper investigates the uplink transmission of an integrated satellite-terrestrial network, wherein the low-earth-orbit (LEO) satellites provide backhaul services to isolated cellular base stations (BSs) for forwarding mobile user (UE) data to the core network. In this integrated system, the high mobility of LEO satellites (LEOSats) introduces significant challenges in managing radio resource allocation (RA), as well as the associations between UEs, BSs, and LEOSats for supporting users’ demands efficiently, while also dynamically balancing the capacity of UE-BS access and BS-LEO backhaul links. Regarding these critical issues, the paper aims to jointly optimize the two-tier UE-BS and BS-LEOSat association, sub-channel assignment, bandwidth allocation, and power control to meet users’ demands in the shortest transmission time. This optimization problem, however, falls into the category of mixed-integer non-convex programming, making it very challenging and requiring advanced solution techniques to find optimal solutions. To tackle this complex problem efficiently, we first develop an iterative centralized algorithm by utilizing convex approximation and compressed-sensing-based methods to deal with binary variables. Furthermore, for practical implementation and to offload computation from the central processing node, we propose a Dec-Alg that can be implemented in parallel at local controllers and achieve efficient solutions. Numerical results are also illustrated to strengthen the effectiveness of our proposed algorithms compared to traditional greedy and benchmark algorithms.

The next generation multibeam satellites open up a new way to design satellite communication channels with the full flexibility in bandwidth, transmit power and beam coverage management. In this paper, we exploit the flexible multibeam satellite capabilities and the geographical distribution of users to improve the performance of satellite-assisted edge caching systems. Our aim is to jointly optimize the bandwidth allocation in multibeam and caching decisions at the edge nodes to address two important problems: i) cache feeding time minimization and ii) cache hits maximization. To tackle the non-convexity of the joint optimization problem, we transform the original problem into a difference-of-convex (DC) form, which is then solved by the proposed iterative algorithm whose convergence to at least a local optimum is theoretically guaranteed. Furthermore, the effectiveness of the proposed design is evaluated under the realistic beams coverage of the satellite SES-14 and Movielens data set. Numerical results show that our proposed joint design can reduce the caching feeding time by 50% and increase the cache hit ratio (CHR) by 10% to 20% compared to existing solutions. Furthermore, we examine the impact of multispot beams and multicarrier wide-beam on the joint design and discuss potential research directions.

Efficiently utilizing the network resources to minimize the operation costs while satisfying customer’s Quality-of-Experience (QoE) related requirement as well as dynamic demands is a challenging task of all network operators. This paper aims to develop a stationary capacity allocation method that anticipates time-varying demand and keeps the network operating under constraints on a stochastic blocking probability. Queuing delay requirement is also regarded as an QoE-oriented practical design. Employing an approximation of time-varying queuing model and continuous time Markov chain (CTMC) for queue length, the technical designs are stated as a convex stochastic optimization based on which a dynamic capacity allocation is proposed by using Lagrangian and gradient descent searching method. Numerical studies confirm that our proposed framework can efficiently and dynamically allocate optimal capacity for a blocking probability of less than 1% and the probability of violating the queuing-delay requirement is less than 5%.

High-throughput satellite communication systems are growing in strategic importance thanks to their role in delivering broadband services to mobile platforms and residences and/or businesses in rural and remote regions globally. Although precoding has emerged as a prominent technique to meet ever-increasing user demands, there is a lack of studies dealing with congestion control. This paper enhances the performance of multi-beam high throughput geostationary satellite systems under congestion, where the users’ quality of service (QoS) demands cannot be fully satisfied with limited resources. In particular, we propose congestion control strategies, relying on simple power control schemes. We formulate a multi-objective optimization framework balancing the system sum-rate and the number of users satisfying their QoS requirements. Next, we propose two novel approaches that effectively handle the proposed multi-objective optimization problem. The former is a model-based approach that relies on the weighted sum method to enrich the number of satisfied users by solving a series of the sum-rate optimization problems in an iterative manner. The latter is a data-driven approach that offers a low-cost solution by utilizing supervised learning and exploiting the optimization structures as continuous mappings. The proposed general framework is evaluated for different linear precoding techniques, for which the low computational complexity algorithms are designed. Numerical results manifest that our proposed framework effectively handles the congestion issue and brings superior improvements of rate satisfaction to many users than previous works. Furthermore, the proposed algorithms show low run-time and make them realistic for practical systems.

This paper designs dynamic onboard signal processing schemes in a multiple gateway multi-beam satellite system where full frequency reuse pattern is considered among the beams and feeds. In particular, we deploy on-board Joint Precoding, Feed selection and Signal switching mechanism (JPFS) so that the following advantages are realized, I) No need of Channel State Information (CSI) exchange among the gateways and satellite, since the performance of precoding is highly sensitive to the quality of CSI, II) In case one gateway fails, rerouting signals through other gateways can be applied without any extra signal processing, III) Properly selecting on-board feed/s to serve each user which generates maximum gain toward corresponding user, IV) Flexibly switching the signals received from the gateways to requested users where each user can dynamically request traffic from any gateway, and V) Multiple users with multiple traffic streams can be dynamically served at each beam. However, deploying such JPFS architecture imposes high complexity to the satellite payload. To tackle this issue, this study aims at deploying JPFS that can provide affordable complexity at the payload. In addition, while increasing the data demand imposes extensive bandwidth resources requirement in the feeder link, the proposed JPFS design works efficiently with available feeder link resources even if the data demand increases. The proposed design is evaluated with a close-to-real beam pattern and the latest broadband communication standard for satellite communications.

This paper presents designing precoding technique at the gateway of a multibeam mobile satellite systems, enabling full frequency reuse pattern among the beams. Such a system brings in two critical challenges to overcome. The inter-beam interference makes applying interference mitigation techniques necessary. Further, when the user terminals are mobile the Channel State Information (CSI) becomes time-varying which is another challenge to overcome. Therefore, the gateway has only access to an outdated CSI, which can eventually limit the precoding gains. In this way, employing a proper CSI estimation mechanism at the gateway can improve the performance of the precoding scheme. In this context, the objectives of this paper are two folds. First, we present different CSI feedback mechanisms which aim at preserving a lower CSI variations at the gateway. Then, we develop the corresponding precoding schemes which are adapted with the proposed CSI feedback mechanisms. To keep the complexity of the proposed precoding schemes affordable, we consider a maritime communication scenario so that the signals received by mobile user terminals suffer from a lower pathloss compared to the Land Mobile communication. Finally, we provide several simulations results in order to evaluate the performance of the proposed precoding techniques.

This paper aims to design joint precoding and onboard beamforming at a multiple gateway multibeam satellite system. Full frequency reuse pattern is considered among the beams and each gateway serves a cluster of adjacent beams such that multiple clusters are served through a set of gateways. However, two issues are required to be addressed. First, the interference in both user and feeder links is the bottleneck of the whole system and employing interference mitigation techniques is essential. Second, as the data demand increases, the ground and space segments should employ extensive bandwidth resources in the feeder link accordingly. This entails embedding an extra number of gateways aiming to support a fair balance between the increasing demand and the corresponding required feeder link resources. To tackle these problems, this paper studies the impact of employing a joint multiple gateway architecture and on-board beamforming scheme. It is shown that by properly designing the on-board beamforming scheme, the number of gateways can be kept affordable even if the data demand increases. The proposed beamforming scheme can partially mitigate the interference in the user link. While the user and feeder link channels vary over time, this paper focuses on designing fixed beamforming which is sufficiently robust to the variations in both channels, leading to keep payload complexity low. Moreover, Zero Forcing precoding technique is employed at the gateways to reject the interference in the feeder links as well as it helps the proposed fixed on-board beamforming by partially equalizing the interference in user link.

This paper present On-Board Precoding (OBP) for a multiple gateway multibeam satellite system where full frequency reuse pattern is employed at both user and feeder links. By reducing the Channel State Information (CSI) round-trip delay to half, OBP offers significant benefits in the emerging multiple gateway scenario in terms of lower gateways coordination. However, two critical issues need to be addressed: (a) interference in both user and feeder links is the bottleneck of the whole system and employing interference mitigation techniques is essential, (b) clear push towards non-adaptive (fixed) payload implementation, leading to low computationally complex satellite architectures. In order to fulfill requirements (a) and (b), this paper studies the impact of employing a fixed OBP technique at the payload which is sufficiently robust to the variations in both user and feeder link channels. In addition to (a) and (b), the provided simulation results depict the performance gain obtained by our proposed OBP with respect to the conventional interference mitigation techniques in multiple gateway multibeam systems.

This paper aims to design joint on-ground precoding and on-board beamforming of a multiple gateway multibeam satellite system in a hybrid space-ground mode where full frequency reuse pattern is considered among the beams. In such an architecture, each gateway serves a cluster of adjacent beams such that the adjacent clusters are served through a set of gateways that are located at different geographical areas. However, such a system brings in two challenges to overcome. First, the inter-beam interference is the bottleneck of the whole system and applying interference mitigation techniques becomes necessary. Second, as the data demand increases, the ground and space segments should employ extensive bandwidth resources in the feeder link accordingly. This entails embedding an extra number of gateways aiming to support a fair balance between the increasing demand and the corresponding required feeder link resources. To solve these problems, this study investigates the impact of employing a joint multiple gateway architecture and onboard beamforming scheme. It is shown that by properly designing the on-board beamforming scheme, the number of gateways can be kept affordable even if the data demand increases. Moreover, Zero Forcing (ZF) precoding technique is considered to cope with the inter-beam interference where each gateway constructs a part of block ZF precoding matrix. The conceived designs are evaluated with a close-to-real beam pattern and the latest broadband communication standard for satellite communications.

Herein, we study the spectral coexistence of Geostationary (GEO) Fixed Satellite Services (FSS) downlink and Broadcasting Satellite Services (BSS) feeder links in the Ka-band (17.3 – 18.1 GHz) which is primarily allocated for BSS feeder links. Firstly, a novel cognitive spectrum exploitation framework is proposed in order to utilize the available band efficiently. Subsequently, based on the interference analysis carried out between these systems, two cognitive approaches, namely Carrier Allocation (CA) and Beamforming (BF), are investigated under the considered framework assuming the availability of an accurate Radio Environment Map (REM). The employed techniques allow the flexibility of using additional shared carriers for the FSS downlink system along with the already available exclusive carriers (19.7 – 20.2 GHz), thus increasing the overall system throughput. It is shown that a significant improvement in the per beam throughput as well as in the beam availability can be achieved by applying CA and BF approaches in the considered scenario.

Satellite communication (SatCom) is facing a spectrum scarcity problem due to the limited available exclusive spectrum and the high demand of the broadband satellite services. In this context, there has been an increasing interest in the satellite community to exploit the non- exclusive Ka-band spectrum in order to enhance the spectral efficiency of future broadband satellite systems. Herein, we propose a novel concept of enabling the spectral coexistence of satellite and terrestrial networks using three dimensional (3D) beamforming, which exploits the elevation dimension in addition to the commonly used azimuth dimension. The proposed beamforming solution is employed in a Multiple-Input Low Noise Block Downconverter (MLNB) based Feed Array Reflector (FAR) in contrast to the widely used Uniform Linear Array (ULA) structure. Within the employed antenna structure, the performance of the proposed beamforming solution is evaluated considering different feed arrangements. Finally, a database-assisted approach and two blind approaches are suggested for the effective implementation of the proposed solutions.

We address fixed satellite broadcast reception with the goal of decreasing the aperture of the receiving antenna. The front-end antenna size is commonly determined by the presence of interference from adjacent satellites. A small antenna aperture leads to interference from neighboring satellites utilizing the same frequency bands. We propose a reception system with M multiple input elements and with subsequent joint detection of desired and interfering signals that provides reliable communication in the presence of multiple interfering signals. An iterative least squares technique is adopted combining spatial and temporal processing and achieving robustness against pointing errors. Simulation results show how the proposed joint spatial and temporal adapted mechanism outperforms the simple combination of existing techniques under interference overloaded conditions. Also, we demonstrate how to accurately synchronize the signals as part of the detection procedure. The technique is evaluated in a realistic simulation study representing the conditions encountered in a DVB-S2 broadcast scenario.

The problem of adjacent satellite interference (ACI) within the direct-to-home (DTH) satellite broadcast reception scenario is considered. The use of small DTH front-end reception systems results inevitably in a higher interference level from adjacent satellites using the same frequency band. The growth in satellite communication and the trend to small dishes increases the ACI problem. The general problem of interference limited DTH reception has been studied in recent work. This paper extends the work of (J. Grotz et al., 2005) by considering additionally an MMSE based method based on the proposal by Beidas and Gamal (2002). The interference channel model and the iterative interference cancellation algorithm are introduced and applied to the DTH digital broadcast case. Simulations of the interesting scenarios are conducted and discussed. It is shown, that the algorithm works well over large ranges of the considered scenarios of frequency offset and signal power levels.

Spectral efficiency is of great concern in the return channel of satellite based broadband systems. In (Beidas, 2002) the feasibility of increased efficiency by reducing channel spacing below the symbol rate was demonstrated using joint detection and decoding for a synchronized system. We extend this work by addressing the critical synchronization problem in the presence of adjacent channel interference (ACI) which limits performance as carrier spacing is reduced. A pilot sequence aided joint synchronization scheme for a multi-frequency time division multiple access (MF-TDMA) system is proposed. Based on a maximum likelihood (ML) criterion, the channel parameters, including frequency, time and phase are jointly estimated for the channel of interest and the adjacent channels. The impact of ACI on the synchronization and detection performance is investigated. It is shown that joint channel parameter estimation outperforms single carrier synchronization with reasonable additional computational complexity in the receiver. Based on the proposed synchronization scheme in conjunction with an appropriate joint detection mechanism, see (Beidas, 2002), carrier spacing can be reduced significantly compared to current systems providing a substantial increase in spectral efficiency.