Social-Aware Content Delivery in Device-to-Device Underlay Networks
Chen Xu
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China
Search for more papers by this authorCaixia Gao
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China
Search for more papers by this authorZhenyu Zhou
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China
Search for more papers by this authorJonathan Rodriguez
Instituto de Telecomunicações, Aveiro, Portugal
University of South Wales, Pontypridd, UK
Search for more papers by this authorChen Xu
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China
Search for more papers by this authorCaixia Gao
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China
Search for more papers by this authorZhenyu Zhou
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China
Search for more papers by this authorJonathan Rodriguez
Instituto de Telecomunicações, Aveiro, Portugal
University of South Wales, Pontypridd, UK
Search for more papers by this authorAbstract
Device-to-device (D2D) communication is one of the key solutions for future 5G system. One main line of works optimizing resource allocation for D2D communications is to maximize the spectrum efficiency (SE). This chapter provides a brief review of the related works. It introduces the system model that consists of physical layer and social layer and the formulation of the social network-based content delivery problem. The chapter describes the three-dimensional matching algorithm with relevant theoretical concepts and analysis. In D2D underlay cellular network, the base station (BS) is the controller of resource management and link establishment, and thus the global channel state information (CSI) should be available at the BS for the matching approach. The chapter analyses the properties involving convergence, stability, optimality, and complexity of the proposed three-dimensional matching algorithm.
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