An analytical framework in LEO mobile satellite systems servicing batched Poisson traffic. Issue 1 (12th December 2017)

• Record Type: Journal Article
• Authors: Moscholios, Ioannis D.; Vassilakis, Vassilios G.; Sarigiannidis, Panagiotis G.; Sagias, Nikos C.; Logothetis, Michael D.
• Is Part Of: IET communications. Volume 12:Issue 1(2018)
• Page Start: 18
• Page End: 25
• Publication Date: 2017-12-12
• Subjects: probability -- Markov processes -- wireless channels -- telecommunication network reliability -- celestial mechanics -- mobility management (mobile radio) -- telecommunication traffic -- mobile satellite communication -- cellular radio; low earth orbit mobile satellite system -- Poisson traffic -- batched Poisson process -- multirate loss system -- satellite‐fixed cell -- multidimensional Markov chain -- product form solution -- PFS -- steady‐state distribution -- channel occupancy distribution determination -- handover failure probability -- software‐defined LEO‐MSS; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2017.0220
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : The authors consider a low earth orbit (LEO) mobile satellite system (MSS) that accepts new and handover calls of multirate service‐classes. New calls arrive in the system as batches, following the batched Poisson process. A batch has a generally distributed number of calls. Each call is treated separately from the others and its acceptance is decided according to the availability of the requested number of channels. Handover calls follow also a batched Poisson process. All calls compete for the available channels under the complete sharing policy. By considering the LEO‐MSS as a multirate loss system with 'satellite‐fixed' cells, it can be analysed via a multi‐dimensional Markov chain, which yields to a product form solution (PFS) for the steady‐state distribution. Based on the PFS, they propose a recursive and yet efficient formula for the determination of the channel occupancy distribution, and consequently, for the calculation of various performance measures including call blocking and handover failure probabilities. The latter are much higher compared to the corresponding probabilities in the case of the classical (and less bursty) Poisson process. Simulation results verify the accuracy of the proposed formulas. Furthermore, they discuss the applicability of the proposed model in software‐defined LEO‐MSS.