| 1. |
- Abdu, Tedros Salih, et al.
(författare)
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Demand-Aware Onboard Payload Processor Management for High Throughput NGSO Satellite Systems
- 2023
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Ingår i: IEEE Transactions on Aerospace and Electronic Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9251. ; , s. 1-18
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Tidskriftsartikel (refereegranskat)abstract
- High-Throughput Satellite (HTS) systems with digital payload technology have been identified as a key enabler to support 5G/6G high-data connectivity with wider coverage area. The satellite community has extensively explored resource allocation methods to achieve this target. Typically, these methods do not consider the intrinsic architecture of the flexible satellite digital payload, which consists of multiple processors responsible for receiving, processing, and transmitting the signals. This paper presents a demand-aware onboard processor management scheme for broadband Non-Geostationary (NGSO) satellites. In this context, we formulate an optimization problem to minimize the number of active on-board processors while meeting the system constraints and user requirements. As the problem is non-convex, we solve it in two steps. First, we transform the problem into demand-driven bandwidth allocation while fixing the number of processors. Second, using the bandwidth allocation solution, we determine the required number of processors with two methods: 1) sequential optimization with the Branch & Bound method and 2) Bin Packing with Next Fit, First Fit, and Best Fit methods. Finally, we demonstrate the proposed methods with extensive numerical results. It is shown that the Branch & Bound, Best Fit, and First Fit methods manage the processors better than the Next Fit method. Furthermore, Branch & Bound requires fewer processors than the above methods.
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| 2. |
- Bui, Van-Phuc, et al.
(författare)
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Robust Congestion Control for Demand-Based Optimization in Precoded Multi-Beam High Throughput Satellite Communications
- 2022
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Ingår i: IEEE Transactions on Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 0090-6778. ; 70:10, s. 6918-6937
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Tidskriftsartikel (refereegranskat)abstract
- 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 ever-increasing 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 multi-objective 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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