Please use this identifier to cite or link to this item: https://idr.l4.nitk.ac.in/jspui/handle/123456789/8556
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dc.contributor.authorGhosh, J.
dc.contributor.authorBachhar, S.
dc.contributor.authorNandi, U.K.
dc.contributor.authorRai, A.
dc.contributor.authorRoy, S.D.
dc.date.accessioned2020-03-30T10:22:25Z-
dc.date.available2020-03-30T10:22:25Z-
dc.date.issued2016
dc.identifier.citationAdvances in Intelligent Systems and Computing, 2016, Vol.385, , pp.159-169en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8556-
dc.description.abstractThis research focuses on the problem of cell edge user�s coverage in the context of femtocell networks operating within the locality of macrocell border where pathloss, shadowing, Rayleigh fading have been included into the environment. As macro cell edge users are located far-away from the macro base station (MBS), so that, the underprivileged users (cell edge users) get assisted by the cognitive-femto base station (FBS) to provide consistent quality of service (QoS). Considering various environment factors such as wall structure, number of walls, distance between MBS and users, interference effect (i.e., co-tier and crosstier), we compute downlink (DL) throughput of femto user (FU) for single input single output (SISO) system over a particular sub-channel, but also based on spectrum allocation and power adaptation, performance of two tier network is analyzed considering network coverage as the performance metric. Finally, the effectiveness of the scheme is verified by extensive matlab simulation. � Springer International Publishing Switzerland 2016.en_US
dc.titleNetwork optimization using femtocell deployment at macrocell edge in cognitive environmenten_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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