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In this paper, a new parameter, noise rise factor, that indicates the amount of interference generated by a call is suggested as a basis for setting price. We study the problem of optimal integrated dynamic pricing and radio resource management, in terms of resource allocation and call admission control, in an interference-limited network. The methods of dynamic programming are unsuitable for problems with large state spaces due to the "curse of dimensionality". To overcome this, we solve the problem using the simulation-based methods of neuro-dynamic programming. The results show that the optimal policy suggested provides significant average reward and congestion improvement over conventional policies that charge users based on their load factor.