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In uplink orthogonal frequency division multiplexing access(OFDMA) systems,efficient resource allocation can greatly improve system performance.Therefore,in this paper,we present a game-theoretical approach to achieve a joint subcarrier and power allocation in a distributed way.Particularly,the subcarrier allocation problem is modeled as a multi-player discrete,stochastic and finite strategy game,where each of the subcarriers is viewed as a player to choose the most satisfying user.The subcarriers of each user are allocated with equal power.For the proposed game model,on the one hand,we exploit the support and programming methods to obtain the Nash equilibriums,and analyze their theoretical properties.On the other hand,we propose a lowcomplexity algorithm based on the linear reward-inaction(L R-I) algorithm to search for the Nash equilibriums.And the relationship between the convergence results of this algorithm and the Nash equilibriums is discussed.Extensive simulation results demonstrate the effectiveness of the resource allocation game model and algorithm.
In uplink orthogonal frequency division multiplexing access (OFDMA) systems, efficient resource allocation can greatly improve system performance. Herefore, in this paper, we present a game-theoretical approach to achieve a joint subcarrier and power allocation in a distributed way. Partlyly, the subcarrier allocation problem is modeled as a multi-player discrete, stochastic and finite strategy game, where each of the subcarriers is viewed as a player to choose the most satisfying user. subcarrier of each user are allocated with equal power. For the proposed game model, on the one hand, we exploit the support and programming methods to obtain the Nash equilibriums, and analyze their theoretical properties. On the other hand, we propose a low complexity algorithm based on the linear reward-inaction (L RI) algorithm to search for the Nash equilibriums.And the relationship between the convergence results of this algorithm and the Nash equilibriums is discussed. Expensive simulation results demons trate the effectiveness of the resource allocation game model and algorithm.