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In this study, new mathematical formulations and algorithms for joint scheduling and hybrid resource allocation are derived and investigated for a multi-user downlink orthogonal frequency division multiple access system. A three-sectored multi-cellular heterogeneous traffic environment is considered where users are randomly distributed and categorised under different priority levels. Traffic consists of time delay-sensitive and time delay-insensitive services. Three practical scheduling and resource allocation methods are proposed to address the balance between throughput, outage probability and resource efficiency under varying channel conditions. The proposed methods are based on the Lagrangian duality framework, and are formulated as mixed integer programming problems constrained by the total power of the base station and users' data rate while maintaining the quality of service for each user. Both dynamic and fixed resource allocation approaches are included in the main problem formulation. The complexity of the resource allocation problem is minimised by approximating the well-known water level. Simulation results show that the total system throughput is penalised for the method that aims to minimise the outage probability of the highest priority level. This is because of the severe channel conditions experienced by some users, whereas the alternatively proposed methods maintain system efficiency under a similar amount of constrained resources and required traffic.