Search: onr:"swepub:oai:DiVA.org:kth-286888" >
Beam Illumination P...
Beam Illumination Pattern Design in Satellite Networks : Learning and Optimization for Efficient Beam Hopping
-
Lei, L. (author)
-
Lagunas, E. (author)
-
Yuan, Y. (author)
-
show more...
-
Kibria, M. G. (author)
-
Chatzinotas, S. (author)
-
- Ottersten, Björn, 1961- (author)
- Interdisciplinary Centre for Security, Reliability and Trust, Luxembourg University, Luxembourg, Luxembourg
-
show less...
-
(creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2020
- 2020
- English.
-
In: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 8, s. 136655-136667
- Related links:
-
https://doi.org/10.1...
-
show more...
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
show less...
Abstract
Subject headings
Close
- Beam hopping (BH) is considered to provide a high level of flexibility to manage irregular and time-varying traffic requests in future multi-beam satellite systems. In BH optimization, adopting conventional iterative heuristics may have their own limitations in providing timely solutions, and directly using data-driven technique to approximate optimization variables may lead to constraint violation and degraded performance. In this paper, we explore a combined learning-and-optimization (LO) approach to provide an efficient, feasible, and near-optimal solution. The investigations are from the following aspects: 1) Integration of BH optimization and learning techniques; 2) Features to be learned in BH design; 3) How to address the feasibility issue incurred by machine learning. We provide numerical results and analysis to show that the learning component in LO significantly accelerates the procedure of identifying promising BH patterns, resulting in reduced computing time from seconds/minutes to milliseconds level. The identified learning feature enables high accuracy in predictions. In addition, the optimization component in LO guarantees the solution's feasibility and improves the overall performance with around 5% gap to the optimum.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
Keyword
- Beam hopping
- machine learning
- neural network
- optimization
- satellite communications
Publication and Content Type
- ref (subject category)
- art (subject category)
Find in a library
To the university's database