An adaptive coded modulation with multi-levels QoS analysis in multimedia environment
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We propose a framework for network-assisted radio resource management in wireless data networks. This type of radio resource management techniques offer implementation and capacity benefits compared to conventional, interference-measurement based, dynamic channel assignment (DCA) algorithms. The basic idea is to use interbase signaling to shift most of the burden of the resource allocation from the air interface to the backbone infrastructure. By exchanging channel assignment as well as other relevant information in real time through the backbone network, each base can calculate the impact of a resource assignment on the system. As a result, rapid interference measurements, which are typically needed to implement DCA schemes, are replaced by a limited amount of path loss measurements and the computation of interference conditions by the base stations. This significantly reduces the measurement and over-the-air signaling requirements, and can also provide an opportunity for a better optimization of the system performance. We focus on two specific algorithms: network-assisted least-interference-based dynamic packet assignment (NA-LI-DPA) and network-assisted dynamic packet assignment with throughput optimization (NA-DPA). NA-LI-DPA closely resembles a least-interference-based dynamic channel assignment algorithm, and NA-DPA attempts to further improve the overall system throughput. The algorithms, as defined, are appropriate for a best-effort data service, where the primary goal is to provide a higher throughput. However, it will be clear from the discussion that it is also feasible to alter the algorithms to optimize performance metrics other than throughput, e.g., to ensure a certain quality of service. We show through simulation that, for a system like enhanced general packet radio service (EGPRS) system, NA-DPA can provide a throughput that is 50% higher than random packet assignment, and 25% higher than that obtained by conventional DCA algorithms