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This work addresses the problem of radio access congestion control and resource allocation in scenarios where multiple available radio access technologies (RATs) support a wide range of services over a given coverage area. A key issue in these networks is selecting the most appropriate RAT at a call/session establishment according to some specified user/operator criteria. In this sense, a wide range of high-level policies can be defined, providing the most favorable resource allocation. Regardless of having efficient RAT selection policies, which may ensure some initial quality of service (QoS) requirements, intrinsic network dynamics (e.g., mobility, user activity, and interference rise) can cause potential QoS failures, leading to a degraded network performance and, hence, radio access congestion. This work is devoted to the study of the impact of radio access congestion on a number of RAT-selection policies. Consequently, a congestion probability (CP) model is developed to capture the statistical behavior of radio access congestion events. In addition, a general Markovian framework is adopted to evaluate the allocation of multiple services into multiple RATs by means of high-level policy definitions. Specific RAT-selection policies are defined according to several criteria, and their performances are evaluated in a time-division multiple-access (TDMA)/wideband code-division multiple-access (WCDMA) multi-RAT scenario supporting voice and data services. Moreover, the use of CP information as a possible allocation principle for RAT selection is also evaluated, which, in the assumed scenario, results in the most favorable allocation policy.