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We consider the problem of providing inter-access-point (AP) fairness guarantee in dense AP deployments where starvation can occur. In particular, we develop a framework for providing robust minimum throughput guarantee for each AP under the uncertainty of user distributions. Our framework consists of an AP throughput provisioning scheme and a distributed CSMA algorithm. The throughput provisioning scheme computes a robust feasible minimum AP throughput vector based on a random AP-level conflict graph and chance-constrained optimization. By incorporating the minimum throughput vector, we develop a distributed CSMA algorithm that fulfills the minimum requirement for each AP and is compatible with the IEEE 802.11 standard. We show through extensive simulations that our framework addresses the AP starvation problem by guaranteeing minimum throughput for each AP. [ABSTRACT FROM PUBLISHER]

We study the coordinated transmission problem in cooperative cellular networks where a cluster of base stations forms a virtual cell to serve a mobile station (MS). The performance of such an MS-centric virtual cell network is dictated by the beamformer that enables to suppress interference; however, designing a beamformer is highly challenging due to the coupled nature of interference and desired signals under arbitrarily formed virtual cells. We develop a new formulation of the beamforming problem for sum-rate maximization in virtual cell networks and analyze the structure of its optimal solutions. Based on this analysis, we develop a beamforming algorithm that can balance between desired signal maximization and interference minimization, so as to maximize the sum-rate. We show through extensive simulations that our balanced beamforming algorithm mitigates edge user effect and outperforms existing algorithms in various scenarios where virtual cells are allowed to overlap. [ABSTRACT FROM PUBLISHER]

Due to the tradeoff between capacity and fairness in a wide variety of networks, increasing one objective may deteriorate the other. This paper investigates the possibility of improving capacity and fairness at the same time, specifically in two-hop cellular networks. First, we prove that an achievable capacity region can be enlarged by using relay, i.e., the capacity and fairness tradeoff relationship is alleviated. To achieve the Pareto-efficient boundary of this enlarged capacity region, an appropriate scheduling algorithm should be developed. Thus, second, we propose a generalized opportunistic scheduling algorithm for relaying mode that can improve both capacity and fairness. Furthermore, we propose a heuristic algorithm with low complexity and signaling overhead for relaying mode. Extensive simulations under various configurations demonstrate that the proposed algorithm not only increases the throughput of each user but also effectively alleviates unfairness among users. [ABSTRACT FROM PUBLISHER]