Adaptive MBSFN subframe allocation scheme for VBR video streaming over LTE‐A networks. Issue 12 (24th September 2018)

• Record Type: Journal Article
• Authors: Ghandri, Abdennaceur; Boujelben, Yassine; Ben Jemaa, Maher
• Is Part Of: Transactions on emerging telecommunications technologies. Volume 29:Issue 12(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-09-24
• Subjects: Telecommunication -- Periodicals; 384.05
• DOI: 10.1002/ett.3518
• Languages: English
• ISSNs: 2161-5748

Abstract

Abstract: Meeting the growing demand for multimedia services is still the main challenge for the current mobile network technologies. The 3rd Generation Partnership Project has proposed an emerging technology called multimedia broadcast/multicast service (MBMS). This service is gaining traction as a method of efficiently using the scarce wireless resources for multicasting the same content to a large number of users belonging to the same area. In the multicast broadcast single frequency network (MBSFN) context, the conventional approach specified by the 3rd Generation Partnership Project standard adopts a semistatic resource allocation mechanism for MBMS services according to their quality‐of‐service parameters. More precisely, the resources assigned to all MBMS service flows remain unchanged along the transmission period and reallocation may take place only when a new multicast session is admitted for transmission or a current session ends. This approach is inefficient and not suitable, especially for services with variable bit rate such as live video streaming. In this paper, we propose a proactive resource allocation algorithm that can dynamically adjust the subframe allocation within an MBSFN area in order to keep pace with the variable bit rate traffics' fluctuations. The basic idea of the proposed solution is to periodically reallocate the MBSFN subframes, in case of persistent over or under allocations, based on a linear prediction model of the resources actually consumed and the traffic behavior. The simulation results show that our proposed algorithm can reduce the waste of MBSFN resources, which could be used for other multicast or unicast transmissions, without violating the quality‐of‐service and fairness constraints. Abstract : In this paper, Ghandri et al, propose an Adaptive MBSFN Subframe Allocation (AMSA) approach which can dynamically adjust the subframe allocation within an MBSFN area in order to keep pace with the fluctuations of the VBR traffics. The basic idea of the AMSA scheme is to periodically reallocate the MBSFN subframes, in case of persistent over‐ or under allocations, based on a linear prediction model of the resources consumption and the traffic behavior. The simulation results show that AMSA strategy can reduce clearly the waste of MBSFN resources which could be used for other multicast or unicast transmissions, without violating the QoS and fairness constraints.