Resource Allocation for Beam-hopping User Downlinks in Multi-beam Satellite System

Wang, Lin; Zhang, Chen; Qu, Dexin; Zhang, Gengxin

doi:10.1109/iwcmc.2019.8766489

Cited by 18 publications

(9 citation statements)

References 8 publications

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“…For fixed super-user parameters, changing ω b alters how the radiated power is dispersed across the coverage area, resulting in a change to the maximum gain (and therefore EIRP) at the center of a beam. Assuming that each beam uses a constant BW, the spectral efficiency (η b ) relating to the selected MODCOD defines the beam capacity (Γ) as per Equation (9). Therefore, as users are iteratively allocated to a beam and the super-user parameters updated, the achievable CNR and Γ will be a function of ω b .…”

Section: Modified User Demands and Beam Capacity Estimationsmentioning

confidence: 99%

“…Recall that after MoCHA or WkFRI, we have an initial BLP, with the beam locations and beam widths known; the modified demands of a user with respect to its distance from the beam centers and the beam capacities can be estimated using Equations ( 7) and (9), respectively; the optimization problem of allocating users to beams in order to maximize the total demand covered or total number of users served, subject to constraints on beam capacity and number of users each beam can serve, is a CCKP. We used IBM ILOG CPLEX Optimization Studio Version 22.1 for solving the following binary ILP model, using StaticLex that maximizes, in the first instance, the covered demand, and in the second instance, maximize the number of users covered with this optimized covered demand.…”

Section: Cckp and Ipmentioning

confidence: 99%

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FlexBeamOpt: Hybrid solution methodologies for high‐throughput GEO satellite beam laydown and resource allocation

Gaudry

Mak‐Hau

2023

Satell Commun Network

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SummaryModern satellite communication systems are required to serve heterogeneous and geographically dispersed user demands with limited resources. In this paper, we investigate methodologies for dynamic resource allocation in Geosynchronous Earth Orbit (GEO) High‐throughput Satellite (HTS) systems. We designed three solution approaches FlexBeamOpt v1, FlexBeamOpt v2, and FlexBeamOpt v3, each as a hybridization of custom heuristics, integer linear programming, and/or constraint programming. We test the performance of the three approaches on 12 test instances that vary in user distribution (realistic, random, and clustered), user numbers (500 vs. 5000 users), and demand distribution (uniform vs. random). We observed that FlexBeamOpt v1 consistently outperformed FlexBeamOpt v2 and FlexBeamOpt v3 in terms of demand coverage and number of users covered for realistic and random user distribution test instances but at the cost of computation time. FlexBeamOpt v3 is the fastest in these instances. For clustered user distribution instances, FlexBeamOpt v3 performed better in terms of demand coverage and number of users covered, at the cost of using more beams. For these test instances, FlexBeamOpt v2 is the fastest in terms of computation time while providing a comparable solution quality.

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Section: Modified User Demands and Beam Capacity Estimationsmentioning

confidence: 99%

Section: Cckp and Ipmentioning

confidence: 99%

FlexBeamOpt: Hybrid solution methodologies for high‐throughput GEO satellite beam laydown and resource allocation

Gaudry

Mak‐Hau

2023

Satell Commun Network

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“…[ 8 ] investigated the advantages of beam hopping and showed the performance and capacity improvement over non-hopped systems. Scholars have also proposed a new generation of high-throughput satellite communication system architecture based on beam hopping, and the hopping pattern design is jointly optimized by a convex optimization algorithm [ 9 , 10 , 11 ]. Li Guangxia’s team also sorted out the existing algorithms for satellite beam hopping resource allocation, and verified the good applicability of beam hopping in high-throughput systems [ 12 ].…”

Section: Related Workmentioning

confidence: 99%

An Efficient Multi-Dimensional Resource Allocation Mechanism for Beam-Hopping in LEO Satellite Network

Guo

Han

Gong

et al. 2022

Sensors

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Low Earth Orbit (LEO) satellite communication networks have become an important means to provide internet access services for areas with limited infrastructure. Compared with the Geostationary Earth Orbit (GEO) satellites, the LEO satellites have limited on-board communication caching and calculating resources. Furthermore, the distribution of traffic requests is dynamically changing and uneven due to the relative movement between the LEO satellites and the ground. Therefore, how to schedule the multi-dimensional resources is an important issue for the LEO satellite communication networks. Beam-hopping is an efficient approach to improve the resource utilization by dynamically allocating time, power, and frequency according to the traffic requests. This paper proposes an efficient multi-dimensional resource allocation mechanism for beam-hopping in LEO satellite networks, which simultaneously satisfies the GEO interference avoidance. First, we construct the beam-hopping model of LEO satellites, and formulate the resource optimization problem. Second, we provide the weighted greedy strategy to determine the illumination pattern. In order to reduce the search space, the cells are clustered to non-interference clusters. Then, an improved genetic algorithm is provided to jointly allocate the communication resources. Finally, we construct various simulations to evaluate our proposed mechanism. Compared with the random-BH, polling-BH and traditional genetic algorithm, our algorithm achieves better performance in terms of both system throughput, access success rate, average delay and fairness between cells. The performance improvement is more significant in scenarios where traffic demand is unevenly distributed.

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“…Song et al [30] first analyzed the influence of satellite distance on resource scheduling and proposed an algorithm that combines an improved genetic algorithm and a local search method to rapidly improve the quality of the scheduling scheme. Reference [31] first used the heuristic-based optimization method to coarsely search the feasible region space where the optimal solution is most likely to appear. However, due to the diversity of services and the high dynamics of satellites, the time slot preallocation will not be able to meet the real-time and changeable service requirements well.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Beam Scheduling of Multibeam Low Earth Orbit Satellites Based on an Enhanced Artificial Bee Colony Algorithm

et al. 2022

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The application of beam-hopping technology to low earth orbit satellites can effectively achieve flexible allocation and efficient utilization of on-board resources. Considering that the power resources on low earth orbit satellites are limited, the electromagnetic environment is complex and changeable, and the terminal distribution and service requirements are highly dynamic. We established the service model, service priority model and multibeam resource scheduling model under the constraints of beam bandwidth, on-board power, service priorities, etc. To solve the catastrophic problem of a large solution space in the resource scheduling model and to improve the convergence of the algorithm, we propose an enhanced artificial bee colony algorithm. The optimization strategy improves the process of population initialization, solution updates, and search for the global optimal solution. The simulation results show that under the constraints of cochannel interference and on-board resource utilization, the algorithm always converges to the objective function at the fastest speed, which proves that the algorithm has high applicability to the high dynamic characteristics of LEO satellites. In addition, the algorithm can obtain the global optimal solution, and thus, it can ensure the fairness of resource allocation and the effectiveness of service completion.

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Resource Allocation for Beam-hopping User Downlinks in Multi-beam Satellite System

Cited by 18 publications

References 8 publications

FlexBeamOpt: Hybrid solution methodologies for high‐throughput GEO satellite beam laydown and resource allocation

FlexBeamOpt: Hybrid solution methodologies for high‐throughput GEO satellite beam laydown and resource allocation

An Efficient Multi-Dimensional Resource Allocation Mechanism for Beam-Hopping in LEO Satellite Network

Dynamic Beam Scheduling of Multibeam Low Earth Orbit Satellites Based on an Enhanced Artificial Bee Colony Algorithm

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