Minimization of n th Order Rate Matching in Satellite Networks with One to Many Pairings

Anargyros J. Roumeliotis, Christos N. Efrem and Athanasios D. Panagopoulos ()
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Anargyros J. Roumeliotis: School of Electrical and Computer Engineering, National Technical University of Athens, GR-157 80 Athens, Greece
Christos N. Efrem: School of Electrical and Computer Engineering, National Technical University of Athens, GR-157 80 Athens, Greece
Athanasios D. Panagopoulos: School of Electrical and Computer Engineering, National Technical University of Athens, GR-157 80 Athens, Greece

Future Internet, 2022, vol. 14, issue 10, 1-11

Abstract: This paper studies the minimization of n th (positive integer) order rate matching in high-throughput multi-beam satellite systems, based on one-to-many capacity allocation pairings, for the first time in the literature. The offered and requested capacities of gateways and users’ beams are exploited, respectively. Due to the high complexity of the binary optimization problem, its solution is approached with a two-step heuristic scheme. Firstly, the corresponding continuous, in [0, 1], pairing problem is solved applying the difference of convex optimization theory, and then, a transformation from continuous to binary feasible allocation is provided to extract the pairings among gateways and users’ beams. Comparing with the exponential-time optimal exhaustive mechanism that investigates all possible pairs to extract the best matching for minimizing the rate matching, extended simulations show that the presented approximation for the solution of the non-convex optimization problem has fast convergence and achieves a generally low relative error for lower value of n . Finally, the simulation results show the importance of n in the examined problem. Specifically, pairings originated by the minimization of rate matching with larger n result in more fair rate matching among users’ beams, which is a valuable result for satellite and generally wireless systems operators.

Keywords: high-throughput satellite systems; dynamic resource allocation; difference of convex optimization; quadratic optimization; heuristic minimization (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2022
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