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- W4368227709 abstract "Now days cellular users are expecting seamless connectivity and better quality of experience from service providers. In cellular networks, user mobility is crucial since it raises a number of significant concerns such as handover, location updating and resource allocation etc. It is necessary to study the mobility patterns of user and predict the user's moving direction in order to offer handover and resource management in an efficient manner. Hence the mobility prediction is one of the most important parameter cellular networks and gaining the attention of many researchers. In this paper an extensive survey of mobility prediction is presented wherein a brief overview of various prediction outputs along with evaluation metrics is discussed. Specifically, an overview of applications of mobility prediction and different cutting-edge strategies, such as hidden markov models, markov chains, and machine learning and deep learning are discussed. At last the current research obstacles because the advancement of next generation networks are explored." @default.
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- W4368227709 date "2023-02-10" @default.
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- W4368227709 title "Mobility Prediction in Cellular Networks: A Survey" @default.
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