Abstract:In this paper, the problem of interference mitigation in a multicell Device to Device (D2D) underlay cellular network is addressed. In this type of network architectures, cellular users and D2D users share common Resource Blocks (RBs). Though such paradigms allow potential increase in the number of supported users, the latter comes at the cost of interference increase that in turn calls for the design of efficient interference mitigation methodologies. To treat this problem efficiently, we propose a two step approach, where the first step concerns the efficient RB allocation to the users and the second one the transmission power allocation. Specifically, the RB allocation problem is formulated as a bilateral symmetric interaction game. This assures the existence of a Nash Equilibrium (NE) point of the game, while a distributed algorithm, which converges to it, is devised. The power allocation problem is formulated as a linear programming problem per RB, and the equivalency between this problem and the total power minimization problem is shown. Finally, the operational effectiveness of the proposed approach is evaluated via numerical simulations, while its superiority against state of the art approaches existing in the recent literature is shown in terms of increased number of supported users, interference reduction and power minimization.

In this paper, the problem of efficient distributed power control via convex pricing of users' transmission power in the uplink of CDMA wireless networks supporting multiple services is addressed. Each user is associated with a nested utility function, which appropriately represents his degree of satisfaction in relation to the expected trade-off between his QoS-aware actual uplink throughput performance and the corresponding power consumption. Initially, a Multiservice Uplink Power Control game (MSUPC) is formulated, where each user aims selfishly at maximizing his utility-based performance under the imposed physical limitations and its unique Nash equilibrium point is determined. Then the inefficiency of MSUPC game's Nash equilibrium is proven and a usage-based convex pricing policy of the transmission power is introduced, which offers a more effective approach compared to the linear pricing schemes that have been adopted in the literature. Consequently, a Multiservice Uplink Power Control game with Convex Pricing (MSUPC-CP) is formulated and its unique Pareto optimal Nash equilibrium is determined. A distributed iterative algorithm for computing MSUPC-CP game's equilibrium is proposed, while the overall approach's efficiency is illustrated via modeling and simulation.

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