Demand-based Scheduling for Precoded Multibeam High-Throughput Satellite Systems

Honnaiah, Puneeth Jubba; Lagunas, Eva; Spano, Danilo; Maturo, Nicola; Chatzinotas, Symeon

doi:10.1109/wcnc49053.2021.9417300

Cited by 13 publications

(21 citation statements)

References 16 publications

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“…Note that this study focuses on the demand-matching at the beam level. The task to distribute the beam capacity to the different end-users of that beam is known as user scheduling (Guidotti and Vanelli-Coralli, 2020;Honnaiah et al, 2021).…”

Section: Objectivementioning

confidence: 99%

Precoded Cluster Hopping for Multibeam GEO Satellite Communication Systems

Lagunas

Kibria²,

Al-Hraishawi

et al. 2021

Front. Signal Process.

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Beam hopping (BH) and precoding are two trending technologies for high-throughput satellite (HTS) systems. While BH enables the flexible adaptation of the offered capacity to the heterogeneous demand, precoding aims at boosting the spectral efficiency. In this study, we consider an HTS system that employs BH in conjunction with precoding in an attempt to bring the benefits of both in one. In particular, we propose the concept of cluster hopping (CH), where a set of adjacent beams are simultaneously illuminated with the same frequency resource. On this line, we propose an efficient time–space illumination pattern design, where we determine the set of clusters that shall be illuminated simultaneously at each hopping event along with the dwelling time. The CH time–space illumination pattern design formulation is shown to be theoretically intractable due to the combinatorial nature of the problem and the impact of the actual illumination design on the resulting interference. For this, we make some design decisions on the beam–cluster design that open the door to a less complex still well-performing solution. Supporting results based on numerical simulations are provided which validate the effectiveness of the proposed CH concept and a time–space illumination pattern design with respect to benchmark schemes.

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Section: Objectivementioning

confidence: 99%

Precoded Cluster Hopping for Multibeam GEO Satellite Communication Systems

Lagunas

Kibria²,

Al-Hraishawi

et al. 2021

Front. Signal Process.

Self Cite

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“…We stress that problem (11) is non-convex as a consequence of the discrete feasible domain and the non-convex objective function. Particularly, the discrete feasible domain makes (11) a combinatorial problem, where the global optimum can only be obtained for a small scale network with few users and small number of beams since an exhaustive search of the parameter space is required. Nevertheless, the exhaustive search has the computational complexity scaling up exponentially with the number of available users.…”

Section: A Problem Formulationmentioning

confidence: 99%

“…Remark 1. Problem (11) is a generalized version of the previous works [5], [11] and references therein since the N users are scheduled over different time slots and since we also take the QoS requirements into account. In other words, problem (11) ensures the scheduled users always satisfied their throughput demands.…”

Section: A Problem Formulationmentioning

confidence: 99%

“…Problem (11) is a generalized version of the previous works [5], [11] and references therein since the N users are scheduled over different time slots and since we also take the QoS requirements into account. In other words, problem (11) ensures the scheduled users always satisfied their throughput demands. Furthermore, an effective RZF precoding matrix constructed from a good scheduling scheme not only reduces mutual interference but also ameliorates the received signal strength that boosts the system performance.…”

Section: A Problem Formulationmentioning

confidence: 99%

“…At the t-th outer iteration (1 ≤ t ≤ T ), if the number of scheduled users from the previous time slot, which have not been satisfied their QoS requirements yet, is less than the number of beams, i.e., |K(t − 1)| < M , there is room for scheduling new users to join the system in case of all the constraints of problem (11) satisfied. For such, an inner loop is implemented to testify whether or not at most the M − |K(t − 1)| + 1 potential users can be scheduled.…”

Section: B Proposed Heuristic Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

User Scheduling for Precoded Satellite Systems with Individual Quality of Service Constraints

Chien¹,

Lagunas²,

Ta³

et al. 2021

Preprint

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Multibeam high throughput satellite (MB-HTS) systems will play a key role in delivering broadband services to a large number of users with diverse Quality of Service (QoS) requirements. This paper focuses on MB-HTS where the same spectrum is re-used by all user links and, in particular, we propose a novel user scheduling design capable to provide guarantees in terms of individual QoS requirements while maximizing the system throughput. This is achieved by precoding to mitigate mutual interference. The combinatorial optimization structure requires an extremely high cost to obtain the global optimum even with a reduced number of users. We, therefore, propose a heuristic algorithm yielding a good local solution and tolerable computational complexity, applicable for large-scale networks. Numerical results demonstrate the effectiveness of our proposed algorithm on scheduling many users with better sum throughput than the other benchmarks. Besides, the QoS requirements for all scheduled users are guaranteed.

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Multiaperture multibeam antenna design method for high‐throughput satellite applications

Tao

Ding

Zhang

et al. 2022

Int J RF Mic Comp-Aid Eng

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As the core technology of high‐throughput satellite payloads, multibeam antennas have received high attention and rapid development in recent years. Because of the characteristics of high gain and high beam isolation, multiaperture multibeam antennas is an important technical approach to meet the high‐performance requirements of high‐throughput satellites. This article proposes a mathematical modeling method based on the mutual coupling parameters of the reflector. This method takes capacity requirements and satellite structure design boundary conditions as input condition, and adopts an adaptive evolutionary multiobjective optimization algorithm to perform joint optimization and solution of multiple parameters, which can complete the optimization efficiently. This method does not need to perform a large number of antenna parameter simulation, reduces the number of iterations and structural layout design, greatly reduces the design cost. This article takes the demand of the AP‐6D satellite as an example, applies the above method to the multibeam antenna design of the satellite, and completes the simulation verification, structural design, physical manufacturing, and various tests of the antenna to verify the correctness of the design method.

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Demand-based Scheduling for Precoded Multibeam High-Throughput Satellite Systems

Cited by 13 publications

References 16 publications

Precoded Cluster Hopping for Multibeam GEO Satellite Communication Systems

Precoded Cluster Hopping for Multibeam GEO Satellite Communication Systems

User Scheduling for Precoded Satellite Systems with Individual Quality of Service Constraints

Multiaperture multibeam antenna design method for high‐throughput satellite applications

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