A Belief Propagation Approach For Caching Strategy Design In D2d Networks

The cache-enabled D2D network supports direct interconnection among users and can help to offload the data traffic through user caching. In this paper, we consider a reasonable caching strategy design in the cache-enabled D2D network to improve its performance. First we formulate an optimization problem aiming to minimize the average file download time of the users. Next we transform the original problem to a max-product form that can be distributed solved. Then we introduce the factor graph and the conventional belief propagation (BP) algorithm. Finally, we show how we design a BP algorithm with Randomized Gaussian Message Passing scheme and Weighting mechanism (BP-RW) to improve its convergence and performance. The distributed BP-RW algorithm can assign almost all computations to each user in the network, which will help to reduce the heavy computational overhead of the central controller. Meanwhile, simulation results show that the BP-RW algorithm performs better than the conventional BP algorithm, and performs very closely to the centralized greedy algorithm with much lower computational complexity.