Interference management for Small Cell (SC) networks has drawn great attention from both academia and industry due to its importance in Long-Term Evolution (LTE) and emerging 5G networks. Although various approaches have been proposed in the literature, many of them face practical limitations such as showing gains only in specific scenarios, relying on ideal fronthaul, or becoming computationally intractable as the network size increases. In this paper, a novel framework is proposed for interference management in centralized SC networks by jointly utilizing graph theory and optimization theory. It extends the classic center-edge frequency reuse schemes into a more fine-grained scale, thus capturing the complex interference relationships in SC networks. The cell-level resource partition can be semi-statically updated according to the traffic dynamics while existing Medium Access Control (MAC) schedulers can be used for subframe-level resource allocation, not requiring fiber fronthaul. LTE system-level simulation results show that the proposed scheme can significantly improve both cell edge and mean user throughput with practical complexity.

We consider decentralized medium-access control in which many pairwise interactions occur between randomly selected users that belong to a large population. In each local interaction, the users involved compete over an access opportunity. A given user has a fixed number of access attempts and a fixed budget for buying different priority levels. In each time-slot, the access is attributed to the user with the largest priority level. We analyze this problem under both cooperative as well as competitive frameworks. We show that unlike many standard team problems, optimal pure policies do not exist in the team framework, but both an optimal solution as well as equilibria exist within the class of mixed policies. We establish structural properties as well as explicit characterization of these: We show that the optimal policy requires only three priority levels, whereas the noncooperative game possesses a unique symmetric equilibrium point that uses at most two priority levels. Our analysis is applied to power control over wireless capture channels, where the budget constraint corresponds to the battery lifetime.