Abstract-In this paper, we study the effects of social interactions among nodes on the capacity of wireless networks. We consider three scenarios. In the first scenario, the size of the social group for all nodes is fixed while the frequency of communication within members of a social group follows power law distribution. In the second scenario, scale free networks are studied where the size of the social group differs from node to node, and the destination in each group is selected uniformly among the members of that group. Further investigation in the second scenario reveals that traditional transport capacity definition provides misleading conclusions for such network models. We show that nodes with different social status impact the capacity differently. By separating nodes with different social status and allocating separate bandwidth to them, it is shown that majority of nodes scale in this network. In the third scenario, both the size of the social groups and the destination in each group are selected according to power law distributions. Our simulation results corroborate the analytical results. Further, we observe consistently that social interaction improves the capacity of wireless networks which implies that the Gupta-Kumar results were pessimistic for practical networks.
Abstract-The capacity of next generation of cellular networks using femtocaches is studied when multihop communications and decentralized cache placement are considered. We show that the storage capability of future network User Terminals (UT) can be effectively used to increase the capacity in random decentralized uncoded caching. We further propose a random decentralized coded caching scheme which achieves higher capacity results than the random decentralized uncoded caching. The result shows that coded caching which is suitable for systems with limited storage capabilities can improve the capacity of cellular networks by a factor of log(n) where n is the number of nodes served by the femtocache.
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