Fully distributed joint resource allocation in ultra-dense D2D networks: a utility-based learning approach

Fully distributed joint resource allocation in ultra-dense D2D networks: a utility-based learning approach

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In this study, the authors address the problem of joint resource block and power allocation in ultra-dense device-to-device (D2D) networks underlaying cellular networks. They propose a fully distributed scalable scheme that ensures quality-of-service (QoS) of the cellular user equipments (CUEs) while maximising the sum rate of the D2D tier. The resource allocation problem is modelled as a Stackelberg game with pricing. The base station as the leader decides prices to be paid by the D2D users for reusing the resources of the CUEs, based on the QoS requirements of the CUEs, and broadcasts the prices. D2D pairs as followers use the pricing information and a completely uncoupled learning algorithm that guarantees Pareto optimal solution. Analytical proof is provided to establish the convergence of the learning algorithm. Simulation results show superior performance compared to two other existing schemes.


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