Multimedia broadcast and multicast services (MBMS) in mobile networks has been widely addressed, however an investigation of such a technology in emerging, multi-tier, scenarios is still lacking. Notably, user clustering and resource allocation are extremely challenging in multi-tier networks, and imperative to maximize system capacity and improve quality of user-experience (QoE) in MBMS. Thus, in this paper we propose a clustering and resource allocation approach, named EMB, which specifically addresses heterogeneous networks and accounts for the fact that multimedia content is adaptively encoded into scalable layers depending on the QoE requirements and channel conditions of the heterogeneous users. Importantly, we prove that our clustering algorithm yields Pareto efficient broadcasting areas, multimedia encoding parameters, and re- source allocation, in a way that is also fair to the users. Fur- thermore, numerical results obtained under realistic conditions and using real-world video content, show that the proposed EMB results in lower churn count (i.e., higher number of served users), higher throughput, and increased QoE, while using fewer network resources.
EMB: Efficient Multimedia Broadcast in Multi-tier Mobile Networks / Singhal, Chetna; Chiasserini, Carla Fabiana; Casetti, CLAUDIO ETTORE. - In: IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY. - ISSN 0018-9545. - STAMPA. - 68:11(2019), pp. 11186-11199. [10.1109/TVT.2019.2938406]
EMB: Efficient Multimedia Broadcast in Multi-tier Mobile Networks
Carla Fabiana Chiasserini;Claudio Ettore Casetti
2019
Abstract
Multimedia broadcast and multicast services (MBMS) in mobile networks has been widely addressed, however an investigation of such a technology in emerging, multi-tier, scenarios is still lacking. Notably, user clustering and resource allocation are extremely challenging in multi-tier networks, and imperative to maximize system capacity and improve quality of user-experience (QoE) in MBMS. Thus, in this paper we propose a clustering and resource allocation approach, named EMB, which specifically addresses heterogeneous networks and accounts for the fact that multimedia content is adaptively encoded into scalable layers depending on the QoE requirements and channel conditions of the heterogeneous users. Importantly, we prove that our clustering algorithm yields Pareto efficient broadcasting areas, multimedia encoding parameters, and re- source allocation, in a way that is also fair to the users. Fur- thermore, numerical results obtained under realistic conditions and using real-world video content, show that the proposed EMB results in lower churn count (i.e., higher number of served users), higher throughput, and increased QoE, while using fewer network resources.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2748655
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