基于神经网络的PSO预测蜂窝通信量的繁忙时间,并利用认知无线电将其分配给电视空闲频道

W. Ojenge, T. Afullo, P. Ogao, William OkelloOdongo
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PSO of Neural Networks to Predict Busy Times of Cellular Traffic for Assignment to TV Idle Channels by Cognitive Radio
Kenya has identified radio spectrum as a keydriver in its development. Yet, globally, radio spectrum is inefficiently utilized due to ITU's static spectrum allocation.In Kenya, mobile operators are running short of bandwidth due to deployment of 4G services, which enable super fast mobile broadband/internet. In the USA and UK, FCC and Ofcom, respectively, have made effort to allow opportunistic 'poaching' of licensed spectrum as long as communication of licensed user is not interfered with. This has focused research on use of cognitive radio, which would use its sensor networks to establish which TV channels are idle in order to allocate them temporarily to cellular networks.Enabling the cognitive radio to predict which channels shall lie idle at what times introduces better planning and more temporally-efficient allocation. This study explores the viability of predicting the times of mobile telephony traffic jam for a mobile service operator with poor QoS rating within a cell of perennial mobile traffic jam in order to explore whether those times can map well with the TV spectrum holes. The times of the TV spectrum holes shall be determined in a later study.
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