Flexible Resource Optimization for GEO Multibeam Satellite Communication System

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 everincreasing 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 multiobjective 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.

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“…Combining the power solution and the limited power budget constraint in (45), we obtain the second condition as shown in the theorem.…”

Section: B Proof Of Theoremmentioning

confidence: 99%

“…Even though ( 11) is a single-objective problem, it is still nonconvex due to a hybrid between the continuous and discrete feasible domains of the optimization variables. We, therefore, make an assumption follow the trends in QoS satisfaction in future satellite communications [45].…”

Section: A Model-based Approachmentioning

confidence: 99%

Robust Congestion Control for Demand-Based Optimization in Precoded Multi-Beam High Throughput Satellite Communications

Bui

Chien

Lagunas

et al. 2022

IEEE Trans. Commun.

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“…This fact is also common in precoded HTS systems [22], which in addition necessitate a channel estimation procedure. Subsequently, different suboptimal paradigms with different degrees of flexibilities arise; see for example [24] and references therein.…”

Section: A Related Workmentioning

confidence: 99%

“…This way the weights are inversely proportional to each superuser's traffic demand. Furthermore, to satisfy the TPC, the elements of w are scaled by a corresponding scalar z k > 0, ∀k ∈ K as seen in (24).…”

Section: ) Wp-mmsementioning

confidence: 99%

Matching Traffic Demand in GEO Multibeam Satellites: The Joint Use of Dynamic Beamforming and Precoding Under Practical Constraints

Chaker

Chougrani

Martins

et al. 2022

IEEE Trans. on Broadcast.

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To adjust for the non-uniform spatiotemporal nature of traffic patterns, next-generation high throughput satellite (HTS) systems can benefit from recent technological advancements in the space-segment in order to dynamically design traffic-adaptive beam layout plans (ABLPs). In this work, we propose a framework for dynamic beamforming (DBF) optimization and adaptation in dynamic environments. Given realistic traffic patterns and a limited power budget, we propose a feasible DBF operation for a geostationary multibeam HTS network. The goal is to minimize the mismatch between the traffic demand and the offered capacity under practical constraints. These constraints are dictated by the traffic-aware design requirements, the on-board antenna system limitations, and the signaling considerations in the K-band. Noting that the ABLP is agnostic about the inherent inter-beam interference (IBI), we construct an interference simulation environment using irregularly shaped beams for a large-scale multibeam HTS system. To cope with IBI, the combination of on-board DBF and on-ground precoding is considered. For precoded and non-precoded HTS configurations, the proposed design shows better traffic-matching capabilities in comparison to a regular beam layout plan. Lastly, we provide trade-off analyses between system-level key performance indicators for different realistic non-uniform traffic patterns.

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“…Through the use of multibeam and frequency reuse technology, high-throughput satellites can provide a total throughput that is dozens of times higher than traditional fixed communication service satellites, [1][2][3][4] greatly reducing the cost of unit bandwidth. In the face of a large number of application scenarios in various industries, the establishment of a three-dimensional "5G+" network of sea, land and air requires the use of satellite communications, which is more advantageous in wide-area coverage schemes.…”

mentioning

confidence: 99%

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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Flexible Resource Optimization for GEO Multibeam Satellite Communication System

Cited by 88 publications

References 35 publications

Robust Congestion Control for Demand-Based Optimization in Precoded Multi-Beam High Throughput Satellite Communications

Robust Congestion Control for Demand-Based Optimization in Precoded Multi-Beam High Throughput Satellite Communications

Matching Traffic Demand in GEO Multibeam Satellites: The Joint Use of Dynamic Beamforming and Precoding Under Practical Constraints

Multiaperture multibeam antenna design method for high‐throughput satellite applications

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