Dynamic spectrum access for D2D networks: A hypergraph game approach

Abstract

In this paper the spectrum access problem in dynamic D2D networks is researched based on the hypergraph game solution. The traditional binary graph based interference model cannot describe the cumulative interference relations, which are common in D2D networks. Therefore, we use the hypergraph model to depict the complex interference among the low powered and densely located D2D pairs. Consider the dynamic nature of the D2D communication, each D2D pair may frequently change between the active and silent state. Therefore, the network topology changes dynamically according to the combination of active D2D pairs. In order to reduce the cost and the delay caused by frequently updating access policies, we make the allocation of spectrum access aiming at optimizing the expectation of long-term network performance. We formulate the spectrum access problem as a local congestion game to minimize the expectation of the MAC layer interference level, which can consequently optimize the network performance. Afterwards, a distributed learning algorithm was used to search the pure strategy Nash equilibrium of the game. The simulation results validate the superiority of the hypergraph game solution.