An improving energy efficiency cooperation algorithm based on Nash bargaining solution in selfish user cooperative networks

A bandwidth-exchange cooperation algorithm based on the Nash bargaining solution （NBS） is proposed to encourage the selfish users to participate with more cooperation so as to improve the users＇ energy efficiency. As a result, two key problems, i.e. , when to cooperate and how to cooperate, are solved. For the first problem, a proposed cooperation condition that can decide when to cooperate and guarantee users＇ energy efficiency achieved through cooperation is not lower than that achieved without cooperation. For the second problem, the cooperation bandwidth allocations （CBAs） based on the NBS solve the problem how to cooperate when cooperation takes place. Simulation results show that, as the modulation order of quadrature amplitude modulation （QAM） increases, the cooperation between both users only occurs with a large signal-to-noise ratio （SNR）. Meanwhile, the energy efficiency decreases as the modulation order increases. Despite all this, the proposed algorithm can obviously improve the energy efficiency measured in bits-per-Joule compared with non-cooperation.

Optimal Time and Bandwidth Allocation Based on Nash Bargaining Solution for Cooperative Cognitive Systems

In this paper,we propose a cooperative spectrum sharing strategy based on the Nash bargaining solution.Specifically,the primary system leases a fraction of its transmission time to the secondary system in exchange for cooperation to improve its transmission performance.To gain access to the spectrum of the primary system,the secondary system needs to split a fraction of its transmission bandwidth to help to forward the primary signal.As a reward,the secondary system can use the remaining bandwidth to transmit its own signal.We find a unique solution for this time and bandwidth allocation using the Nash bargaining solution.Simulation results demonstrate that the performance of the primary and secondary systems can both be improved by the proposed spectrum sharing strategy.

Multi-user Symmetric Cooperation Based on Nash Bargaining Solution in Cooperative Relay Networks

This paper presents a symmetric cooperation strategy for cooperative relay networks with multiple users. The multi-user symmetric cooperation model and the relay selection algorithm are proposed. Then, the time slot allocation problem is cast into a bargaining problem, and the optimal time slot allocation solution is obtained by Nash bargaining solution （NBS）. Moreover, we also consider the implementations of the cooperation strategy, i.e., the grouping and admission control algorithm. Simulation results show that users can obtain larger rates under the symmetric cooperation strategy than the non-cooperative case.

Nash bargaining solution based multi-cell and multi-user interference alignment scheme for cellular networks

In wireless cellular networks, the interference alignment （IA） is a promising technique for interference management. A new IA scheme for downlink cellular network with multi-cell and multi-user was proposed, in the proposed scheme, the interference in the networks is divided into inter-cell interference （ICI） among cells and inter-user interference （IUI） in each cell. The ICI is aligned onto a multi-dimensional subspace by multiplying the ICI alignment precoding matrix which is designed by the singular value decomposition （SVD） scheme at the base station （BS） side. The aligned ICI is eliminated by timing the interference suppression matrix which is designed by zero-forcing （ZF） scheme at the user equipment （UE） side. Meanwhile, the IUI is aligned by multiplying the IUI alignment precoding matrix which is designed based on Nash bargaining solution （NBS） in game theory. The NBS is solved by the particle swarm optimization （PSO） method. Simulations show that, compared with the traditional ZF IA scheme, the proposed scheme can obtain higher data rate and guarantee the data rate fairness of UEs with little additional complexity.

Bargaining Game Theoretic Power Control in Selfish Cooperative Relay Networks

Wireless cooperative communications require appropriate power allocation （PA） between the source and relay nodes. In selfish cooperative communication networks, two partner user nodes could help relaying information for each other, but each user node has the incentive to consume his power solely to decrease its own symbol error rate （SER） at the receiver. In this paper, we propose a fair and efficient PA scheme for the decode-and-forward cooperation protocol in selfish cooperative relay networks. We formulate this PA problem as a two-user cooperative bargaining game, and use Nash bargaining solution （NBS） to achieve a win-win strategy for both partner users. Simulation results indicate that the NBS is fair in that the degree of cooperation of a user only depends on how much contribution its partner can make to decrease its SER at the receiver, and efficient in the sense that the SER performance of both users could be improved through the game.

Bandwidth Allocation with Minimum Rate Constraints in Cluster-based Femtocell Networks

Inter-femtocell interference becomes serious when femtocells are densely deployed. To mitigate the inter-femtocell interference, this paper proposes a cluster-based bandwidth allocation algorithm. We create femtocell clusters by constructing a weighted interference graph and allocate bandwidth to each cluster based on a Nash bargaining solution(NBS). Simulation results show that the cluster-based bandwidth allocation algorithm can reduce the inter-femtocell interference and meet the minimum rate constraint of each cluster.

Game Theoretic Subcarrier and Power Allocation for Wireless OFDMA Networks

This paper proposes a bargaining game theoretic resource(including the subcarrier and the power) allocation scheme for wireless orthogonal frequency division multiple access(OFDMA) networks.We define a wireless user s payoff as a function of the achieved data-rate.The fairness resource allocation problem can then be modeled as a cooperative bargaining game.The objective of the game is to maximize the aggregate payoffs for the users.To search for the Nash bargaining solution(NBS) of the game,a suboptimal subcarrier allocation is performed by assuming an equal power allocation.Thereafter,an optimal power allocation is performed to maximize the sum payoff for the users.By comparing with the max-rate and the max-min algorithms,simulation results show that the proposed game could achieve a good tradeoff between the user fairness and the overall system performance.