Abstract-Slot allocation in a CDMA/TDD cellular network, which decomposes a frame into uplink and downlink slots, is a multi-dimensional optimization problem involving all the cells in the system due to interference between cells. However, the complexity of the problem makes it computationally too expensive to solve simultaneously for all the cells in a system of reasonable size. In this paper, we propose a novel predictive and distributed slot allocation scheme for transporting multimedia traffic over CDMA/TDD cellular networks with multiple cells, designed to maximize a general utility function that is (strictly) concave increasing. We formulate the utility-maximizing slot allocation problem as a nonlinear integer programming problem, and provide a solution that can be realized efficiently in a distributed manner. Also, we derive sufficient conditions for a real-number solution to be optimal and develop an efficient algorithm to find a near-optimal integer solution. The effectiveness of the integer solution is demonstrated by showing that its gap with the optimal solution is small. We show by experiments that the proposed predictive method has a sufficient accuracy when there are many active users in cells. Extensive simulation results show that the proposed distributed slot allocation method performs very well in comparison to an existing method.

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Abstract.A performance of an experiment to analyze the relationship between weight value and map complexity. That means there is a trial to find which weight value performs the best on maps with different complexity. And then in this article there is an application of hierarchical and dynamic weight method into Theta* path-finding algorithm. The dynamic weight value is picked from the first experiment. For different abstract map, a weight value is changed base on the complexity of the abstract map. This article contains a re-test of new implementation of Theta* and compare to the Mr. Nash's Theta* to collect the positive outcome. And by applying the dynamic weight method with different weight based on map complexity, the dynamic weight theta* perform better in time costing