This paper presents a novel cross-layer optimization framework to improve the quality of user experience (QoE) and energy efficiency of the heterogeneous wireless multimedia broadcast receivers. This joint optimization is achieved by grouping the users based on their device capabilities and estimated channel conditions experienced by them and broadcasting adaptive content to these groups. The adaptive multimedia content is obtained by using scalable video coding (SVC) with optimal source encoding parameters resulted from an innovative cooperative game. Energy saving at user terminals results from using a layer-aware time slicing approach in the transmission stage. A trade-off between energy saving and QoE is observed, and is incorporated in the definition of a utility function of the players in the formulated heterogeneous user composition and physical channel aware game. An adaptive modulation and coding scheme is also optimally incorporated in order to maximize the reception quality of the broadcast receivers, while maximizing the network broadcast capacity. Compared to the conventional broadcast schemes, the proposed framework shows an appreciable improvement in QoE levels for all users, while achieving higher energy-savings for the energy constrained users.

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There is a massive upsurge in data traffic over the Internet due to multimedia services. The upcoming heterogeneous broadband wireless access networks (BWANs) provide higher data rates, increased capacity, and enhanced network coverage. Since the smart phone usage and multimedia service demand is increasing at a much faster pace as compared to the capacity and resources of the underlying network technology, adaptive multimedia services are essential to provide satisfactory quality of experience (QoE). The focus of this chapter is to discuss the adaptive techniques to provide better multimedia services to heterogeneous users in next-generation networks. These techniques consist of video streaming optimization using MPEG-DASH, video caching schemes, quality aware video transcoding, web optimization of multimedia services, and user-centric cross-layer optimization.

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