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AN EFFICIENT CROSS-LAYER AWARE MAPPING OF VOIP CALLS IN WIRELESS OFDMA SYSTEMS Part II. Mapping Algorithms and their Performance

AN EFFICIENT CROSS-LAYER AWARE MAPPING OF VOIP CALLS IN WIRELESS OFDMA SYSTEMS Part II. Mapping Algorithms and their Performance

AN EFFICIENT CROSS-LAYER AWARE MAPPING OF VOIP CALLS IN WIRELESS OFDMA SYSTEMS Part II. Mapping Algorithms and their Performance

Purpose: This work address and solve the problem of efficient broadcasting of resource allocations descriptors for VoIP traffic in mobile OFDMA-based wireless systems. Methods: We show that the mapping overhead is substantially reduced by using semi-persistent allocations and that by taking advantage of the periodicity of VoIP frames, generated by a multiphase vocoder. To handle the impact of mobility on the characteristics of the wireless channel we utilize a cross-layer decision approach to track the channel conditions and predict the expected mobile user behavior such that the system may under-react to channel changes in some cases. Results: The development efforts in this paper were directed towards developing efficient heuristic solutions since the problem is NP hard. Two heuristic algorithms with low computational complexity of O(n2) are presented and their performance gains are compared against a simple persistent allocation approach. Extensive simulations show that these mapping algorithms reduce the allocation overhead substantially in OFDMA-based systems such as WiMAX and LTE. The main advantage of the proposed algorithms is their ability to support multiple codecs, or a single codec with different operational modes, that result in different packet sizes and different periods. In addition, our proposed algorithms cluster the assignments together hence enabling the BS to allocate unused resources to other traffic types. Practical relevance: The proposed algorithmic solutions are simple enough to be implemented in practical OFDMA systems such as WiMAX and LTE to allow an efficient use of bandwidth for high quality VoIP sessions in of mobile users.

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