Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.

Satellite Communications with 5G, B5G, and 6G: Challenges and Prospects

Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity communication, yet it is not without its challenges. Paramount concerns encompass spectrum allocation, the harmonization of network architectures, and inherent latency issues in satellite transmissions. Potential mitigations, such as dynamic spectrum sharing and the deployment of edge computing, are explored as viable solutions. Looking ahead, the advent of quantum communications within satellite frameworks and the integration of AI spotlight promising research trajectories. These advancements aim to foster a seamless and synergistic coexistence between satellite communications and next-gen mobile networks.

Coded Multicasting for Content Delivery over Predictable Time-Varying Satellite Communication Networks

With the development of astronautic technology, communication satellites now have a tremendous gain in both quantity and quality, and have already shown their capability on multi-functional converged communication other than telecommunication. Under this circumstance, increasing the transmission efficiency of satellite communication network becomes a top priority. In this paper, we focus on content delivery service on satellite networks, where each ground station may have prefetched some file fragments. We cast this problem into a coded caching framework so as to exploit the coded multicast gain for minimizing the satellite communication load. We first propose an optimization-based coded multicast scheme by considering the special property that the satellite network topology is predictable and timevariant. Then, a greedy based fast algorithm is proposed, which can tremendously reduce the computation complexity with a small loss in optimality. Simulation experiments conducted on two Walker constellation satellite networks show that our proposed coded multicast method can efficiently reduce the communication load of satellite networks.

Robust or nonrobust: On MC-DS-CDMA acquisition in LEO satellite communications

Low Earth Orbit(LEO)satellite communications can provide global coverage in the sixth generation communication(6G)networks.To combat the strong Partial Band Interferences(PBIs)and multipath fading in LEO satellite communication systems,the Multicarrier Direct Sequence Code Division Multiple Access(MC-DS-CDMA)technique is a promising alternative to the traditional Single-carrier Direct Sequence Code Division Multiple Access(SC-DS-CDMA)system for its advantages of high bandwidth efficiency,superior interference rejection capability,and low complexity of parallel signal processing.However,limited studies have been conducted on the performance analysis of MC-DS-CDMA acquisition systems in the presence of a large Doppler shift,a unique characteristic of LEO satellite communications.To bridge this gap,we investigate the performance of MC-DS-CDMA systems with two-dimensional acquisition and noncoherent equal gain combining over Rician fading channel in the presence of the Doppler shift and PBIs.The performance metrics are detection probability and Mean Square Error(MSE)of the Doppler factor and delay.Specifically,we derive the closed-form expressions for the MSE and the Probability Density Function(PDF)of the acquisition decision variable and obtain the detection probability.We conduct extensive numerical experiments to verify the theoretical analysis and performance gain of MC-DSCDMA over the SC-DS-CDMA.The results show that MC-DS-CDMA with two-dimensional acquisition is more robust to multipath Rician fading than SC-DS-CDMA.Moreover,MC-DS-CDMA outperforms SC-DS-CDMA regarding the detection probability and MSE when combating the strong PBIs.

Low Altitude Satellite Constellation for Futuristic Aerial-Ground Communications

This paper discusses the significance and prospects of low altitude small satellite aerial vehicles to ensure smooth aerial-ground communications for next-generation broadband networks.To achieve the generic goals of fifthgeneration and beyondwireless networks,the existing aerial network architecture needs to be revisited.The detailed architecture of low altitude aerial networks and the challenges in resource management have been illustrated in this paper.Moreover,we have studied the coordination between promising communication technologies and low altitude aerial networks to provide robust network coverage.We talk about the techniques that can ensure userfriendly control and monitoring of the low altitude aerial networks to bring forth wireless broadband connectivity to a new dimension.In the end,we highlight the future research directions of aerial-ground communications in terms of access technologies,machine learning,compressed sensing,and quantum communications.

Beam Position and Beam Hopping Design for LEO Satellite Communications

The numbers of beam positions(BPs)and time slots for beam hopping(BH)dominate the latency of LEO satellite communications.Aiming at minimizing the number of BPs subject to a predefined requirement on the radius of BP,a low-complexity user density-based BP design scheme is proposed,where the original problem is decomposed into two subproblems,with the first one to find the sparsest user and the second one to determine the corresponding best BP.In particular,for the second subproblem,a user selection and smallest BP radius algorithm is proposed,where the nearby users are sequentially selected until the constraint of the given BP radius is no longer satisfied.These two subproblems are iteratively solved until all the users are selected.To further reduce the BP radius,a duplicated user removal algorithm is proposed to decrease the number of the users covered by two or more BPs.Aiming at minimizing the number of time slots subject to the no co-channel interference(CCI)constraint and the traffic demand constraint,a low-complexity CCI-free BH design scheme is proposed,where the BPs having difficulty in satisfying the constraints are considered to be illuminated in priory.Simulation results verify the effectiveness of the proposed schemes.

Learning-Based Admission Control for Low-Earth-Orbit Satellite Communication Networks

Satellite communications has been regarded as an indispensable technology for future mobile networks to provide extremely high data rates,ultra-reliability,and ubiquitous coverage.However,the high dynamics caused by the fast movement of low-earth-orbit(LEO)satellites bring huge challenges in designing and optimizing satellite communication systems.Especially,admission control,deciding which users with diversified service requirements are allowed to access the network with limited resources,is of paramount importance to improve network resource utilization and meet the service quality requirements of users.In this paper,we propose a dynamic channel reservation strategy based on the Actor-Critic algorithm(AC-DCRS)to perform intelligent admission control in satellite networks.By carefully designing the longterm reward function and dynamically adjusting the reserved channel threshold,AC-DCRS reaches a long-run optimal access policy for both new calls and handover calls with different service priorities.Numerical results show that our proposed AC-DCRS outperforms traditional channel reservation strategies in terms of overall access failure probability,the average call success rate,and channel utilization under various dynamic traffic conditions.

The Impact of Satellite Communications on Environmental Hazard Control: Tool for the Realization of African Union Agenda 2063 Aspirations

Africa is a developing economy and as such, emphasis has been placed on the achievement of revolutionary goals that will place her on a similar rank as the developed economies. Pertaining to this objective, Heads of States and government all over Africa instigated the African Union (AU) Agenda 2063, which is a framework put in place to achieve a continental transformation over the next 40 years. The use of satellites has been proven to be a major influence on economic growth since it facilitates the exchange of information. Environmental hazards such as climate changes, pollution, and inefficient waste management can be classified as one of the drawbacks to achieving this economic growth we hope to accomplish. The purpose of this paper is to analyze and examine satellite communication as a tool for the attainment of an integrated, prosperous and peaceful Africa by means of combatting environmental hazards in the continent.

Blockchain-Based MCS Detection Framework of Abnormal Spectrum Usage for Satellite Spectrum Sharing Scenario

In this paper, the problem of abnormal spectrum usage between satellite spectrum sharing systems is investigated to support multi-satellite spectrum coexistence. Given the cost of monitoring, the mobility of low-orbit satellites, and the directional nature of their signals, traditional monitoring methods are no longer suitable, especially in the case of multiple power level. Mobile crowdsensing(MCS), as a new technology, can make full use of idle resources to complete a variety of perceptual tasks. However, traditional MCS heavily relies on a centralized server and is vulnerable to single point of failure attacks. Therefore, we replace the original centralized server with a blockchain-based distributed service provider to enable its security. Therefore, in this work, we propose a blockchain-based MCS framework, in which we explain in detail how this framework can achieve abnormal frequency behavior monitoring in an inter-satellite spectrum sharing system. Then, under certain false alarm probability, we propose an abnormal spectrum detection algorithm based on mixed hypothesis test to maximize detection probability in single power level and multiple power level scenarios, respectively. Finally, a Bad out of Good(BooG) detector is proposed to ease the computational pressure on the blockchain nodes. Simulation results show the effectiveness of the proposed framework.

For LEO Satellite Networks: Intelligent Interference Sensing and Signal Reconstruction Based on Blind Separation Technology

In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.

System Integration of Terrestrial Mobile Communication and Satellite Communication——The Trends, Challenges and Key Technologies in B5G and 6G

Mobile communication standards have been developed into a new era of B5G and 6G.In recent years,low earth orbit(LEO)satellites and space Internet have become hot topics.The integrated satellite and terrestrial systems have been widely discussed by industries and academics,and even are expected to be applied in those huge constellations in construction.This paper points out the trends of two stages towards system integration of the terrestrial mobile communication and the satellite communications:to be compatible with 5G,and to be integrated within 6G.Based on analysis of the challenges of both stages,key technologies are thereafter analyzed in detail,covering both air interface currently discussed in 3GPP for B5G and also novel network architecture and related transmission technologies toward future 6G.

A Positioning System based on Communication Satellites and the Chinese Area Positioning System(CAPS)

The Chinese Area Positioning System （CAPS） is a positioning system based on satellite communication that is fundamentally different from the 3＂G＂ （GPS, GLONASS and GALILEO） systems. The latter use special-purpose navigation satellites to broadcast navigation information generated on-board to users, while the CAPS transfers ground-generated navigation information to users via the communication satellite. In order to achieve accurate Positioning, Velocity and Time （PVT）, the CAPS employs the following strategies to over- come the three main obstacles caused by using the communication satellite： （a） by real-time following-up frequency stabilization to achieve stable frequency; （b） by using a single carrier in the transponder with 36 MHz band-width to gain sufficient power; （c） by incorporating Decommissioned Geostationary Orbit communication satellite （DGEO）, barometric pressure and Inclined Geostationary Orbit communication satellite （IGSO） to achieve the 3-D posi- tioning. Furthermore, the abundant transponders available on DGEO can be used to realize the large capacity of communication as well as the integrated navigation and communication. With the communication functions incorporated, five new functions appear in the CAPS： （1） combination of navigation and communication; （2） combination of navigation and high accu- racy orbit measurement; （3） combination of navigation message and wide/local area differen- tial processing; （4） combination of the switching of satellites, frequencies and codes; and （5） combination of the navigation message and the barometric altimetry. The CAPS is thereby labelled a PVT5C system of high accuracy. In order to validate the working principle and the performance of the CAPS, a trial system was established in the course of two years at a cost of about 20 million dollars. The trial constellation consists of two GEO satellites located at E87.5° and E110.5°, two DGEOs located at E130° and E142°, as well as barometric altimetry as a virtual satellite. Static and dynamic performance tests were completed for the Eastern, the Western, the Northern, the Southern and the Middle regions of China. The evaluation results are as follows： （1） land static test, plane accuracy range： C/A code, 15-25 m; P code, 5-10 meters; altitude accuracy range, 1- m; （2） land dynamic test, plane accuracy range, C/A code, 15-25 m; P code, 8-10m; （3） velocity accuracy, C/A code, 0.13-0.3 m s-1, P code, 0.15-0.17 m s- 1; （4） timing accuracy, C/A code, 160 ns, P code, 13 ns; （5） timing compared accuracy of Two Way Satellite Time and Frequency Transfer （TWSTFT）, average accuracy, 0.068 ns; （6） random error of the satellite ranging, 10.7 mm; （7） orbit determination accuracy, better than 2 m. The above stated random error is 1σ error. At present, this system is used as a preliminary operational system and a complete system with 3 GEO, 3 DGEO and 3 IGSO is being established.

Joint Computing and Communication Resource Allocation for Satellite Communication Networks with Edge Computing

Benefit from the enhanced onboard processing capacities and high-speed satellite-terrestrial links,satellite edge computing has been regarded as a promising technique to facilitate the execution of the computation-intensive applications for satellite communication networks(SCNs).By deploying edge computing servers in satellite and gateway stations,SCNs can achieve significant performance gains of the computing capacities at the expense of extending the dimensions and complexity of resource management.Therefore,in this paper,we investigate the joint computing and communication resource management problem for SCNs to minimize the execution latency of the computation-intensive applications,while two different satellite edge computing scenarios and local execution are considered.Furthermore,the joint computing and communication resource allocation problem for the computation-intensive services is formulated as a mixed-integer programming problem.A game-theoretic and many-to-one matching theorybased scheme(JCCRA-GM)is proposed to achieve an approximate optimal solution.Numerical results show that the proposed method with low complexity can achieve almost the same weight-sum latency as the Brute-force method.

Dual loop feedback pre-distortion in satellite communication

Since the satellite communication goes in the trend of high-frequency and fast speed, the coefficients updating and the precision of the traditional pre-distortion feedback methods need to be further improved. On this basis, this paper proposes dual loop feedback pre-distortion, which uses two first-order Volterra filter models to reduce the computing complexity and a dynamic error adjustment model to construct a revised feedback to ensure a better pre-distortion performance. The computation complexity, iterative convergence speed and precision of the proposed method are theoretically analyzed. Simulation results show that this dual loop feedback pre-distortion can speed the updating of coefficients and ensure the linearity of the amplifier output.

Edge Intelligence Assisted Resource Management for Satellite Communication

Satellite communication has been seen as a vital part of the sixth generation communication,which greatly extends network coverage.In satellite communication,resource management is a key problem attracting many research interests.However,previous study mainly focuses on throughput improvement via power allocation and spectrum assignment and the proposed approaches are mostly model-based and dedicated to specific problem structures.Fortunately,with the trend of edge intelligence,complex resource management problems can be efficiently resolved in a model-free manner.In this paper,a joint beam activation,user-beam association and time resource allocation approach is proposed.The core idea is using stochastic learning at the ground station to identify active user-link beams to meet user rate demand.In addition,the convergence,optimality and complexity of our proposal are rigorously discussed.By simulation,it is shown that the rate goal of most of the users can be met and meanwhile satellite energy is saved owing to much less active beams.

Reliability Evaluation of All-User Terminals in LEO Satellite Communication Network Based on Modular Reduction

LEO satellite communication network has a large number of satellites distributed in low orbits,which leads to multiple coverage of many areas on the ground.It is hard work to describe and evaluate the reliability of LEO satellite communication network.To solve this problem,the reliability of all-user terminals in LEO satellite communication network is defined,and the corresponding reliability evaluation method is proposed in the paper.Due to the large scale of the interstellar network,a modular reduction algorithm using the modular network instead of the original network for state decomposition is proposed in this paper.Case study shows that the calculation time of the proposed method is equivalent to 6.28%of the original state space decomposition algorithm.On this basis,the reliability of LEO satellite communication network is further analyzed.It is found that the reliability of LEO satellite network was more sensitive to the reliability of Inter-Satellite link and the satisfaction of global coverage in the early stage,and it is more sensitive to the reliability of the satellite in the later stage.The satellite-ground link has a relatively constant impact on of LEO satellite network.

A Satellite Communication System Transmission Scheme Based on Probabilistic Shaping

In this paper, A transmission scheme based on probabilistic shaping applied to satellite communication systems is proposed. 16QAM is taken as an example to establish a 1GBaud ROF experimental system working in Ka-band. The experiment results show that the PS-16QAM signal has better performance in terms of bit error rate than the uniform 16QAM, and its performance is close to the uniform 8QAM scheme.

Multi-Objective Deep Reinforcement Learning Based Time-Frequency Resource Allocation for Multi-Beam Satellite Communications

Resource allocation is an important problem influencing the service quality of multi-beam satellite communications.In multi-beam satellite communications, the available frequency bandwidth is limited, users requirements vary rapidly, high service quality and joint allocation of multi-dimensional resources such as time and frequency are required. It is a difficult problem needs to be researched urgently for multi-beam satellite communications, how to obtain a higher comprehensive utilization rate of multidimensional resources, maximize the number of users and system throughput, and meet the demand of rapid allocation adapting dynamic changed the number of users under the condition of limited resources, with using an efficient and fast resource allocation algorithm.In order to solve the multi-dimensional resource allocation problem of multi-beam satellite communications, this paper establishes a multi-objective optimization model based on the maximum the number of users and system throughput joint optimization goal, and proposes a multi-objective deep reinforcement learning based time-frequency two-dimensional resource allocation(MODRL-TF) algorithm to adapt dynamic changed the number of users and the timeliness requirements. Simulation results show that the proposed algorithm could provide higher comprehensive utilization rate of multi-dimensional resources,and could achieve multi-objective joint optimization,and could obtain better timeliness than traditional heuristic algorithms, such as genetic algorithm(GA)and ant colony optimization algorithm(ACO).

Distributed cooperative task planning algorithm for multiple satellites in delayed communication environment

Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.

Study of High-Temperature Superconductor Diplexers for Satellite Communications

The high-temperature superconductor （HTSC） resonator and diplexer are simulated by full-wave tools. A newly developed miniature HTSC diplexer is designed and fabricated on double sided YBa2Cu3O7 （YBCO） film （YBCO/LaAlO3/YBCO）, the thickness of which is 400 nm for YBCO and 0.5 mm for the LaAlO3. The measured results show a good agreement with the simulation. The volume and mass of the diplexers are greatly reduced by miniaturized configuration.