Resource Allocation in Cellular Communication Systems

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This is a joint project between Dimitri Bertsekas, MIT and Andrea Goldsmith, Caltech. The scarcity of channel capacity to support emerging multimedia wireless applications requires efficient strategies for using the available bandwidth. Any system using fixed frequency reuse and base station assignment must be designed relative to worst-case interference assumptions. Dynamic resource allocation is a more efficient strategy, where frequencies, base stations, data rates, and power levels are dynamically assigned relative to current and potential system conditions. In this work, we propose to formulate the general resource allocation problem as an optimization problem subject to interference constraints. The cost function is very general. It can incorporate most of the practical systems complexity in the optimization framework, including cell handoff due to user mobility, multiple classes of traffic, and channel variation. We consider both FDMA and CDMA methods of dividing up the available systems band width. We will apply linear programming to minimize the instantaneous cost function, and dynamic programming techniques to minimize the cost function over the infinite horizon. The dynamic problem formulation will utilize recent developments in neuro-dynamic programming techniques.