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Device-to-device (D2D) cache placement and content delivery is a recent technology that exploits idle memory capacity of mobile devices and promises to fulfill users' content needs with very low delay and without using the scarce cellular network capacity. Recent literature on D2D caching mostly concentrated on optimal cache placement and mostly disregarded the required discovery mechanisms and the accompanying overhead. In this work we propose a clustering-based procedure that is used to cache content at the helper nodes along with advertisement and discovery procedures for content delivery. We implement a Long Term Evolution (LTE)-based simulation setup to evaluate the proposed schemes. Numerical results reveal that the clustering-based user and content discovery significantly improves cellular offloading and reduces the discovery overhead with a minimal sacrifice from delay.

Abstract:We consider an orthogonal frequency division multiple access (OFDMA)-based multicast system where multiple base stations transmit a multicast session to a multicast group. The goal is to maximize the multicast rate (i.e. the minimum achievable user rate) subject to a total power constraint. We assume the use of an erasure code (e.g., a Reed-Solomon code) or rateless code (e.g., Luby transform code). This facilitates each user to accumulate rates from their best subchannels, so that the achievable multicast rate is not limited to the worst user. The resource allocation problem involves determining the transmitting base station at each OFDMA subchannel, the number of bits to be transmitted at each subchannel, and the set of nodes to decode the bits at each subchannel. We formulate the problem as a mixed binary integer linear programming and find the optimal solution as a benchmark. We also propose a greedy subchannel and bit allocation algorithm that is close to optimal.