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Sökning: (swepub) pers:(Ottersten Björn 1961) pers:(Grotz Joel) lar1:(kth) > Robust Congestion C...

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

Bui, Van-Phuc (författare)
Van Chien, Trinh (författare)
Lagunas, Eva (författare)
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Grotz, Joel (författare)
Chatzinotas, Symeon (författare)
Ottersten, Björn, 1961- (författare)
University of Luxembourg, Interdisciplinary Centre for Security, Reliability and Trust (SnT), Luxembourg, 1855, Luxembourg
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 (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2022
2022
Engelska.
Ingår i: IEEE Transactions on Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 0090-6778. ; 70:10, s. 6918-6937
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • 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.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Nyckelord

Multi-beam high throughput satellite communications
multi-objective optimization
neural networks
quality of service requirements

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