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In this paper we propose a new architecture for applications of Cognitive Radio Network (CRN) system based on network selection issue in which secondary users (SU) is able to connect to heterogeneous Cognitive Radio system and selects a network to perform a single transport control protocol (TCP) connection. We use a cross-layer design approach to consider jointly the spectrum sensing, access decision, physical-layer Adaptive Modulation and Coding scheme, and data-link layer frame size in each Cognitive Radio network to maximize the TCP throughput of SUs. Specifically, we formulate the Cognitive Radio Network as a Markov Decision Process, where the finite-state Markov model is used to characterize the time-varying channel states in each network. Then, we maximize Expected end-to-end TCP throughput in long-term by using Iteration method. This is illustrated by simulation results.