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Online spectrum allocation for cognitive cellular network supporting scalable demands

机译:支持可扩展需求的认知蜂窝网络的在线频谱分配

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We advocate an online spectrum allocation system for cognitive cellular network supporting scalable demands. Our system's demands processing model is online model, which means that allocation result is returned immediately. To solve the tough issues of online spectrum allocation, we try to balance the spectrum utilization and future coming demands. A state machine is introduced to allocate spectrum efficiently, and at different state system have different procedures to provide service to customers. To make good use of scalable property of demand and to increase fairness among customers, the concept of satisfaction degree is introduced. We also analyze our system's state and its transition theoretically and give the derivation of every parameter of system and the method to calculate them. Enough work is done to evaluate the system with real data evaluation and results show that the system is efficient and robust under different cases in which the customers' arrival rate and service time are varied.
机译:我们提倡一种用于支持可扩展需求的认知蜂窝网络的在线频谱分配系统。我们系统的需求处理模型是在线模型,这意味着分配结果会立即返回。为了解决在线频谱分配的难题,我们尝试在频谱利用率和未来需求之间取得平衡。引入状态机以有效地分配频谱,并且在不同的状态系统具有不同的过程来向客户提供服务。为了充分利用需求的可扩展性并提高客户之间的公平性,引入了满意度的概念。我们还从理论上分析了系统的状态及其转换,并推导了系统的每个参数及其计算方法。经过充分的工作,对系统进行了真实的数据评估,结果表明,该系统在客户到达率和服务时间变化的不同情况下是有效且健壮的。

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