HANDOVER MANAGEMENT OPTIMIZATION OVER LTE -A NETWORK USING S1 AND X2 HANDOVER
Published In: 7TH INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, ELECTRONICS AND COMMUNICATION
Author(s): H.A. SAKR , M.A. MOHAMED
Abstract: Handover is one of the essential components in the mobility management of wireless systems. It allows the client equipment (UE) to connect between LTE-A networks. The variables that can influence this handover performance are the kind of interfaces in which the handover exists, either X2 or S1 interface, the mobility of the UE and the QCI (Quality of Service Class Identifiers). S1 interface associates the eNodeB to the EPC. It divided into double interfaces, one for the user plane and the other for the control plane. The mobility within LTE-A/SAE as well as mobility to other systems using both 3GPP and non-3GPP technologies. X2 is a new kind of interfaces introduced by the LTE-A Radio Access Network. Neighboring eNodeBs are linked in a peerto-peer fashion to perform handover and provide a means for the rapid coordination of radio resources. This research looks at the handover parameters (e.g. EPS bearer bit loss, BLER, throughput, SNR, LTE-A delay) on the mobile user and eNodeBs. Perfo
- Publication Date: 19-Aug-2018
- DOI: 10.15224/978-1-63248-157-3-11
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PATTERN IDENTIFICATION ON PROTEIN SEQUENCES OF NEURODEGENERATIVE DISEASES USING ASSOCIATION RULE MINING
Published In: 7TH INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, ELECTRONICS AND COMMUNICATION
Author(s): M SHAHEDUL ISLAM , MD. ABUL KASHEM MIA , MOHAMMAD SHAMSUR RAHMAN , SWAPNIL SAHA
Abstract: Proteins are the integral part of all living beings, which are building blocks of many amino acids. To be functionally active, amino acids chain folds up in a complex way to give each protein an unique 3D shape, where a minor error may cause misfolded structure. Neurodegenerative diseases e.g. Alzheimer, Parkinson, Sickle cell anemia, etc. arise due to misfolding in protein sequences. Thus, identifying the patterns of the amino acids is important for inferring the protein associated genetic diseases. Recent studies in predicting patterns of amino acids focused on only the simple chronic neurodegenerative disease Chromaffin Tumor by applying association rule mining. However, more complex diseases are yet to be attempted. Moreover, the association rules obtained by these studies were not verified by usefulness measuring tools. In this paper, we have analyzed the protein sequences associated with more complex neurodegenerative protein misfolded diseases by association rule mining techniqu
- Publication Date: 19-Aug-2018
- DOI: 10.15224/978-1-63248-157-3-12
- Views: 0
- Downloads: 0