Massive Connectivity and Massive Content Distribution for Future Wireless Access

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The unprecedented growth of wireless communications in the past decade is about to undergo another technological revolution. Future wireless cellular network will not only enable ultra-high-speed wireless access anytime, anywhere, but also provide connectivity through millions of devices, in particular, sensors and actuators that will help realize the visions of smart homes, smart cars, and smart cities. The proposed research program will tackle the technological challenges of future wireless access driven by the multiple diverging requirements for enhanced broadband and massive connectivity. ***The proposal will investigate fundamental limits of massive content distribution, particularly in recognition of the opportunities to take advantage of storage and caching capabilities at the network edge in order to break the fundamental barrier of multicell interference in wireless cellular networks. The opportunities to cache user content at both the base-stations (BSs) and remote terminals lead to a content-centric view of the network, in which the interactions between parameters such as file popularity, user association strategy, and cooperation and interference mitigation techniques give rise to challenging system optimization problems that the proposed research program will aim to solve. Further, the opportunities for wireless multicast leads to the possibility of coded caching, which gives rise to new content delivery strategies that can significantly reduce the network backhaul requirement. The proposed research will carefully model these new transmission modes that are enabled by cloud computing and caching capabilities, and will bring caching, BS cooperation and interference cancellation opportunity into the wireless interference channel model in order to arrive at a new understanding of the content delivery capacity of cellular networks. ***Future wireless networks will not only significantly enhance broadband access, but also offer connectivity across massive number of devices for environmental monitoring, sensing, and control applications. These novel modes of communications present significant new challenges in system design, especially for device identification, channel estimation, and for short-packet transmission in delay sensitive applications. The proposed research will recognize the sporadic nature of device transmissions and examine the theoretical foundation of massive connectivity by casting active device identification as a sparse recovery problem. The proposed study will investigate the interplay between compressed sensing and information theory in order to illustrate the roles of physical layer technologies such as massive MIMO, cloud processing, and cooperative communication in massive device communication, and to understand how cellular networks should be engineered to meet the diverse user requirements for future wireless access.