Abstract

In this paper, the joint design of energy-efficient multicast beamforming and in-network caching in Internet of Things is investigated. We propose the fractional in-network caching scheme. Specifically, parts of the sensed data resources are cached in the helpers, such as small-cell base stations and device-to-device equipments, and the caching fraction for a certain resource is the same among the helpers. The remaining data resources are kept in the sensor nodes. Employing multicast transmission at the helpers, the cached data can be cooperatively transmitted to the clients belonging to multiple multicast groups, where the data requests are identical among the clients in the same multicast group. Based on the proposed fractional caching and multicast transmission protocols, the power consumption model is established, and then we formulate the energy efficiency (EE) optimization problem, which is challenging to solve due to its non-convexity. Thereafter, by exploiting the Dinkelbach ’ s method, semi-definite relaxation, successive convex approximation and other approximation techniques, the original problem is converted into a second-order cone programming problem, which is convex and can be efficiently solved by off-the-shelf CVX solvers. Numerical results exhibit the fast convergence of the proposed algorithm, and demonstrate the superior EE performance of the proposed fractional caching scheme, compared to the benchmark strategies.

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