Early Acceptance Matching Game for User Association in 5G Cellular HetNets

We examine the use of matching theory for user association in millimeter wave (mmWave)-enabled cellular heterogeneous networks. In a mmWave system, the channel variations can be fast and unpredictable, rendering centralized user association potentially inefficient. We propose an efficient distributed matching algorithm, called early acceptance (EA), tailored for user association in 5G HetNets. The effectiveness of the proposed algorithm is assessed by comparing with the well-known deferred acceptance (DA) matching algorithm, in which user association is delayed until the algorithm terminates. Numerical results show that the proposed distributed EA matching algorithm reaches a near-optimal solution compared to a centralized algorithm, and leads to a more power-efficient and much faster user association process compared to the distributed DA algorithm.