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While 5G wireless networks are expected to handle ever growing data avalanche, classical deployment/optimization approaches such as hyper- dense deployment of base stations or having more bandwidth are cost-inefficient, therefore seen as stopgaps. In this regard, context-aware approaches which exploits human predictability, recent advances in storage, edge/cloud computing and big data analytics are...
Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into...
With the constant increase in wireless handheld devices and the prospect of billions of connected machines one of the problems for future mobile networks, usually overlooked by the research community, is that more connected devices require proportionally more signalling overhead. Particularly, acquiring users' channel state information is necessary in order for the base station to assign frequency...
Locally caching contents at the network edge constitutes one of the most disruptive approaches in 5G wireless networks. Reaping the benefits of edge caching hinges on solving a myriad of challenges such as how, what and when to strategically cache contents subject to storage constraints, traffic load, unknown spatio-temporal traffic demands and data sparsity. Motivated by this, we propose a novel...
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