Graph-based fair resource allocation scheme combining interference alignment in femtocell networks

The exponential growth of services demands further increase of spectral efficiency which drives the next generation wireless access networks towards deploying femtocells with frequency reuse. However, the interference will be severe especially in dense deployment scenarios. The fair resource allocation problem by joint consideration of sub-channel assignment and interference alignment (IA) is more complicated than the traditional problem. First, not all the users are appropriate for IA since the number of participant users is limited by the feasibility constraint and the interference power levels are different for the path loss. Second, IA can increase the degrees-of-freedoms while occupy additional signal dimensions of participant users, hence more sub-channels are needed by IA compared with the non-participants when each user transmits the same number of streams. This study models the fair resource allocation problem as an optimisation problem, which is a non-deterministic polynomial-time (NP)-hard. To solve it with low complexity, the authors propose a graph-based scheme to give the approximate solution, where the selection criteria of IA group are based on the influence of IA on the interference graph. Simulation results show that the authors scheme can approximate the optimal solution in a small network and improve the fairness in dense deployment scenarios.