期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2014
卷号：2014
DOI：10.1155/2014/138032
出版社：Hindawi Publishing Corporation
摘要：This paper investigates the traffic pattern prediction based on seasonal deviation and spectrum reallocation with multiple channel width in cognitive cellular networks. Compared to the existing approaches based on time series or classical statistic method, the binary exponential deviation offset prediction proposed in this paper focuses on the increment or decrement on every sampling point during an exponential offset period. Then the deviations will be revised at different levels in the next prediction process. The proposed approach is validated with some real end-user data from a WiFi network and simulation experiments. Based on such a precise prediction, we allocate the channels with different bandwidth to end-users according to diverse quality-of-service (QoS), which increases both the system’s profits and actual spectrum utilization. The multidimensional bounded knapsack problem is introduced to divide channels, to which the proposed balance between value density and request probability strategy gets the approximate solution. The simulation experiment results show its good performance in not only utility but also spectrum utilization of the base-stations, especially when the resources are deficient.
