Multi-beam Satellite Communication Systems Research Articles

Dynamic Resource Allocation for Multi-Beam Satellite Communication Systems

Dynamic Resource Allocation for Multi-Beam Satellite Communication Systems

Energy-Efficient RSMA for Multigroup Multicast and Multibeam Satellite Communications

This letter studies energy-efficient rate-splitting multiple access (RSMA) for multigroup multicast and multibeam satellite communication systems. Specifically, we minimize the unmet system capacity, which means the rate difference between the requested user rate and the effective achieved rate, and communication energy consumption by optimizing the power allocation and rate allocation under the per-feed power and sum radiated power constraints. To solve the non-convex optimization problem, auxiliary variables and epigraph method are introduced to transform the original problem into a difference of convex functions programming. Then, the successive convex approximation (SCA) technique is used to obtain a suboptimal solution. Numerical results verify the superiority of our proposed solution compared to the benchmark methods.

The Next Generation of Beam Hopping Satellite Systems: Dynamic Beam Illumination With Selective Precoding

Beam Hopping (BH) is a popular technique considered for next-generation multi-beam satellite communication system which allows a satellite focusing its resources on where they are needed by selectively illuminating beams. While beam illumination plan can be adjusted according to its needs, the main limitation of convectional BH is the adjacent beam avoidance requirement needed to maintain acceptable levels of interference. With the recent maturity of precoding technique, a natural way forward is to consider a dynamic beam illumination scheme with selective precoding, where large areas with high-demand can be covered by multiple active precoded beams. In this paper, we mathematically model such beam illumination design problem employing an interference-based penalty function whose goal is to avoid precoding whenever possible subject to beam demand satisfaction constraints. The problem can be written as a binary quadratic programming (BQP). Next, two convexification frameworks are considered namely: (i) A Semi-Definition Programming (SDP) approach particularly targeting BQP type of problems, and (ii) Multiplier Penalty and Majorization-Minimization (MPMM) based method which guarantees to converge to a local optimum. Finally, a greedy algorithm is proposed to alleviate complexity with minimal impact on the final performance. Supporting results based on numerical simulations show that the proposed schemes outperform the relevant benchmarks in terms of demand matching performance while minimizing the use of precoding.

Fair multigroup multicast precoding design based on traffic demands for multibeam satellite systems

Onboard resources are limited for multibeam satellite communication systems, while differences exist in traffic demands among users. Since conventional multigroup multicast precoding methods do not take traffic demands for users into consideration, it is difficult to flexibly adjust the offered throughput to users’ demands. Users with higher demand may obtain lower throughput while users with lower demand may be over-satisfied, which results in the requested-offered throughput mismatch and resource waste. This paper proposes a fair multigroup multicast precoding design based on traffic demands. To obtain the precoding design, the optimization problem aimed at maximizing the minimum throughput satisfaction ratio, which is defined as the ratio of the offered throughput to the traffic demand, is formulated, so as to provide fair service for all users while satisfying per-feed power constraints and traffic demand constraints. To address this problem, an auxiliary variable is first introduced to equivalently simplify it. Then, the semidefinite relaxation and the bisection search strategies are adopted to further handle the problem. Finally, the optimal precoding vectors are obtained by employing eigenvalue decomposition or Gaussian randomization. Simulation results indicate the effectiveness of the proposed precoding algorithm and demonstrate that it can better adapt to the scenarios with different traffic demands.

Channel capacity limit of multi-beam satellite system

The requests of broadband coverage area and the expected user demand is satisfied by the satellite industry by using multiple spot beams of high throughput satellites with fixed multi-beam pattern and footprint planning. The technology core of high-throughput satellite is multi-beam technology, and the means to efficiently reuse spectrum is a full-frequency reuse scheme. In order to study the channel capacity limit of multi-beam satellite systems, the Wiener-Gaussian access model of terrestrial cellular systems is analyzed in this paper. This paper analyzes the Wiener-Gaussian access model of terrestrial cellular systems, then considers the difference between the spatial characteristics and gain characteristics of the multi-beam satellite system compared with the terrestrial cellular system, and proposes a Wiener model suitable for the multi-beam satellite communication system. On this basis, the channel capacity limit of multi-beam satellites under different fading conditions is deduced when using optimal linear precoding and minimum mean square error precoding. It provides theoretical support for the in-depth study of the channel capacity mechanism and system performance of multi-beam satellites.

User-level scheduling and resource allocation for multi-beam satellite systems with full frequency reuse

Multi-beam satellite communication systems can improve the resource utilization and system capacity effectively. However, the inter-beam interference, especially for the satellite system with full frequency reuse, will degrade the system performance greatly due to the characteristics of multi-beam satellite antennas. In this article, the user scheduling and resource allocation of a multi-beam satellite system with full frequency reuse are jointly studied, in which all beams can use the full bandwidth. With the strong inter-beam interference, we aim to minimize the system latency experienced by the users during the process of data downloading. To solve this problem, deep reinforcement learning is used to schedule users and allocate bandwidth and power resources to mitigate the inter-beam interference. The simulation results are compared with other reference algorithms to verify the effectiveness of the proposed algorithm.

Rate-Splitting Multiple Access for Multigateway Multibeam Satellite Systems With Feeder Link Interference

This paper studies the precoder design problem of achieving max-min fairness (MMF) amongst users in multigateway multibeam satellite communication systems with feeder link interference. We propose a beamforming strategy based on a newly introduced transmission scheme known as rate-splitting multiple access (RSMA). RSMA relies on multi-antenna rate-splitting at the transmitter and successive interference cancellation (SIC) at the receivers, such that the intended message for a user is split into a common part and a private part and the interference is partially decoded and partially treated as noise. In this paper, we formulate the MMF problem subject to per-antenna power constraints at the satellite for the system with imperfect channel state information at the transmitter (CSIT). We also consider the case of two-stage precoding which is assisted by on- board processing (OBP) at the satellite. Numerical results obtained through simulations for RSMA and the conventional linear precoding method are compared. When RSMA is used, MMF rate gain is promised and this gain increases when OBP is used. RSMA is proven to be promising for multigateway multibeam satellite systems whereby there are various practical challenges such as feeder link interference, CSIT uncertainty, per-antenna power constraints, uneven user distribution per beam and frame-based processing.

A Multi-Beam Satellite Cooperative Transmission Scheme Based on Resources Optimization and Packets Segmentation

Multi-beam satellite communication systems are promising architectures in the future. A packet is transmitted by multi-satellite and multi-beam cooperatively, which can provide efficient spectrum utilization, improve system throughput, and guarantee Quality of Services (QoS). In multi-beam satellite communication systems, multi-layer and multi-dimensional radio resources change dynamically, which leads to the discontinuity of optimal resources and the lack of mapping balance between packets and radio resources. To deal with these problems, we propose a cross-layer and cross-dimension radio resources optimization model based on the weighted discrete firefly algorithm and an adaptive packet segmentation scheme based on the irregular gradient algorithm. The cross-layer and cross-dimension radio resources optimization model based on the weighted discrete firefly algorithm simulates cross-layer and cross-dimension optimization for the high-dynamic and multi-dimensional radio resources by considering the channel state information (CSI) and QoS in the multi-beam satellite communication system. The optimal resources are taken as the weight of irregular gradient algorithm to segment packets and map packets to radio resources, which can realize the mapping balance between packets and radio resources and ensure the efficiency and reliability of communication. The simulations show that the new transmission scheme improves the normalized system throughput and user satisfaction index by 18.7% and 6.2%, respectively.

Precoding With Received-Interference Power Control for Multibeam Satellite Communication Systems

Zero-Forcing (ZF) and Regularized Zero-Forcing (RZF) precoding are low-complexity sub-optimal solutions widely accepted in the satellite communications community to mitigate the resulting co-channel interference caused by aggressive frequency reuse. However, both are sensitive to the conditioning of the channel matrix, which can greatly reduce the achievable gains. This paper brings the attention to the benefits of a design that allows some residual received interference power at the co-channel users. The motivation behind this approach is to relax the dependence on the matrix inversion procedure involved in conventional precoding schemes. In particular, the proposed scheme aims to be less sensitive to the user scheduling, which is one of the key limiting factors for the practical implementation of precoding. Furthermore, the proposed technique can also cope with more users than satellite beams. In fact, the proposed precoder can be tuned to control the interference towards the co-channel beams, which is a desirable feature that is not met by the existing RZF solutions. The design is formulated as a non-convex optimization and we study various algorithms in order to obtain a practical solution. Supporting results based on numerical simulations show that the proposed precoding implementations are able to outperform the conventional ZF and RZF schemes.

Fairness-Based Beam Bandwidth Allocation for Multi-Beam Satellite Communication System

Fairness-Based Beam Bandwidth Allocation for Multi-Beam Satellite Communication System

MILP formulation improvement with k-means clustering for the beam layout optimization in multibeam satellite systems

This paper addresses an NP-hard design optimization problem in a multibeam satellite communication system. This problem consists in designing irregular beam layouts to satisfy non-uniform user traffic demands over the satellite service area, under antenna constraints, satellite payload constraints and a telecommunication mission criterion. Efficiently solving this problem is of crucial importance due to its impact on the system performance and cost. We compare three mixed-integer linear programming formulations. The first one, issued from previous work, is based on a linearization of both convex and non-convex Euclidean distance constraints. The two other aim at reducing the solution space size and at breaking symmetry inherent to the first formulation. For that purpose, we introduce a new process to interface k-means clustering with mixed-integer linear programming. We examine an exact and a heuristic approach for exploiting these principles that yield two new formulations. The heuristic approach outperforms the others based on our tests on a set of large-scale realistic problem instances, allowing to use mixed-integer linear programming in the industrial context.

Multi-Agent Deep Reinforcement Learning-Based Flexible Satellite Payload for Mobile Terminals

Information dissemination in mobile networks turns out to be a problem when the network is sparse. Mobile networks begin to establish a separate cluster attributable to the limited communication range of terminals. The multi-beam satellite communication systems can play a significant role in providing direct-to-user satellite mobile services and connecting the separated clusters. This paper focuses on how to efficiently schedule limited satellite-based radio resources to enhance transmission efficiency and meet the requested traffic with low complexity. Taking the inter-beam interference and resource utilization variance into consideration, we build a game-theoretic based model for bandwidth allocation in the forward link. As the size of satellite beams increases, the size of the action space for deep reinforcement learning based on a single agent becomes large, resulting in high time complexity. Thus, we extend the single-agent deep reinforcement learning to the multi-agent context and then propose a cooperative multi-agent deep reinforcement learning method to achieve the optimal bandwidth allocation strategy. Each beam works as a player who is willing to satisfy the request traffic with flexible payloads. We built a multi-beam satellite platform using real historical data. The experimental results show that this approach is capable of enhancing transmission efficiency and can be flexible to achieve the desired goal with low complexity.

Interbeam Interference Constrained Resource Allocation for Shared Spectrum Multibeam Satellite Communication Systems

Future Internet of Things should contain space segment and terrestrial segment. In addition, the multibeam satellite communication systems, especially working in S shared band, have gained more attention, which plays a significant role in providing direct-to-user satellite mobile services. Besides, due to the limited on-board resources, it is increasingly urgent to improve resource utilization. Taking the interbeam interference, channel conditions, delay factor, capacity, bandwidth utilization variance into consideration, a novel joint resource allocation algorithm is proposed in this paper. Interbeam interference coefficient matrix derived from frequency reuse is established to measure the level of co-channel interference. Moreover, the proposed algorithm can allocate resources flexibly according to specific traffic requirements and channel conditions. A novel joint power and bandwidth allocation algorithm is proposed by optimizing throughput and approximation problem of actual requirement. The optimal solution to this optimization problem can be obtained by golden section theory and subgradient iteration. The evaluation results demonstrate that the proposed algorithm can maximize the capacity, minimize the bandwidth utilization variance, and it can also allocate resource intelligently adapting to the user requirements and channel conditions.

Outage Constrained Robust Multigroup Multicast Beamforming for Multi-Beam Satellite Communication Systems

We investigate outage constrained robust multigroup multicast beamforming for multi-beam satellite communication systems with full frequency reuse. Based on a satellite downlink beam domain channel model with channel phase uncertainty taken into account, we first investigate robust multigroup multicast beamforming with the aim to maximize the worst-case outage signal-to-interference-plus-noise ratio under the outage and the per-beam power constraints. We then cast the outage constrained robust beamforming design into the convex optimization framework with some approximation techniques. Simulation results show that the proposed robust multigroup multicast beamformer can provide significant performance gains in terms of multicast rate and outage probability over the conventional approach.

Spectrum Access and Power Control for Cognitive Satellite Communications: A Game-Theoretical Learning Approach

With the increasing scarcity of spectrum resources in satellite and terrestrial communications, spectrum sharing becomes a promising option. In this paper, we investigate the spectrum access and power control problem in multibeam-based cognitive satellite communication network. Differ from the most existing spectrum access problems in terrestrial networks, we consider not only the interference between cognitive users, but also the co-channel interference from multi-beam satellite communication system to cognitive users. We formulate a spectrum access and power control game, and it is proved to be an ordinal potential game. The sufficient conditions for cognitive users not to interfere with each other are given, and the upper bound of the aggregation interference experienced by all cognitive users is deduced theoretically. Then, based on the trial and error (TE) algorithm, we propose a learning-based distributed spectrum access algorithm, which statistically converges to the best Nash equilibrium(NE). Furthermore, to simplify the coefficients design and improve the convergence performance, we propose an improved learning-based distributed spectrum access algorithm. Simulation results show that the average network throughput of the proposed game is close to the best, which validates the game-theoretic solution. Simulation results also show that the improved learning-based distributed spectrum access algorithm is superior to the original algorithm in terms of convergence speed, throughput performance, and practicability, which confirms the effectiveness of the improved algorithm.

Robust Multigroup Multicast Transmission for Frame-Based Multi-Beam Satellite Systems

We investigate robust multigroup multicast transmission for frame-based multi-beam satellite communication systems with full frequency reuse. To mitigate the effect of outdated channel state information (CSI), we first investigate robust multigroup multicast precoding that maximizes the minimum average signal to interference plus noise ratio (SINR) under the per-beam power constraints. We show the relationship between the robust max-min fair problem and the robust power minimization problem with partial CSI and propose a low complexity precoder for the robust power minimization problem. We then investigate user clustering which only requires partial CSI. We show that the approximated average SINR can be maximized provided that the estimated channel vectors of the users in the same cluster are linearly dependent while those in different clusters are mutually orthogonal. Motivated by this user clustering condition, we further propose a low-complexity user clustering algorithm. Simulation results demonstrate that the proposed robust approach can provide substantial performance gains over the conventional approach in multi-beam satellite communication systems.

A Multi-reference Extended Variable Step-size LMS Algorithm for Solving Dynamic Weighting Coefficients of the Satellite Beam-forming Networks

A Multi-beam satellite communication system can form beam by coherently superimposing the beams generated by multiple feeds in space. In order to form the beam based on dynamic user, a multi-reference extended variable step-size LMS algorithm is introduced in this paper to solve the dynamic weighting coefficients. According to the simulation result, when the mean square error of the synthesized beam is small, this algorithm can effectively improve the beamforming convergence rate.

A Non-adjacent Feed Selection Method for Beamforming Performance Enhancement for Multi-beam Satellite Antenna

In recent years, user-centered beamforming systems have attracted increasing interest in the study of multi-beam satellite communication systems. In order to ensure service quality, the beam directivity of targets should have enough flexibility to bear the randomness of user locations. In this paper, a non-adjacent feed selection method is proposed to minimize the mean square error of beamforming and provide enough flexibility of the beam directivity at the same time.

Adaptive scheduling for millimeter wave multi-beam satellite communication systems

Adaptive scheduling for millimeter wave multi-beam satellite communication systems

Multiple Gateway Transmit Diversity in Q/V Band Feeder Links

Design of high bandwidth and reliable feeder links are central toward provisioning new services on the user link of a multibeam satellite communication system. Toward this, utilization of the Q/V band and an exploitation of multiple gateways (GWs) as a transmit diversity measure for overcoming severe propagation effects are being considered. In this context, this contribution deals with the design of a feeder link comprising <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">$N+P$</tex-math></inline-formula> GWs ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">$N$</tex-math></inline-formula> active and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">$P$</tex-math></inline-formula> redundant GWs). Toward provisioning the desired availability, a novel switching scheme is analyzed and practical aspects such as prediction-based switching and switching rate are discussed. Unlike most relevant works, a dynamic rain attenuation model is used to analytically derive average outage probability in the fundamental <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">$1+1$</tex-math></inline-formula> GW case. Building on this result, an analysis for the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">$N+P$</tex-math></inline-formula> scenario leading to a quantification of the end-to-end performance is provided. This analysis aids system sizing by illustrating the interplay between the number of active and redundant GWs on the chosen metrics: average outage and average switching rate.