dc.contributor.author |
Ammar, Hussein Ali, |
dc.date.accessioned |
2017-12-12T08:04:01Z |
dc.date.available |
2017-12-12T08:04:01Z |
dc.date.copyright |
2018-09 |
dc.date.issued |
2017 |
dc.date.submitted |
2017 |
dc.identifier.other |
b20547328 |
dc.identifier.uri |
http://hdl.handle.net/10938/21051 |
dc.description |
Thesis. M.E. American University of Beirut. Department of Electrical and Computer Engineering, 2017. ET:6678 |
dc.description |
Advisor : Dr. Youssef Nasser, senior lecturer, Electrical and Computer Engineering ; Co-Advisor : Dr. Hassan Artail, Professor, Electrical and Computer Engineering ; Committee members : Dr. Karim Kabalan, professor, Electrical and Computer Engineering ; Dr. Ibrahim Abo Faycal, associate professor, Electrical and Computer Engineering. |
dc.description |
Includes bibliographical references (leaves 112-114) . |
dc.description.abstract |
In-Band Full-Duplex (IBFD) has emerged as a technology to increase throughput and spectral efficiency for the users. It is a key potential technology expected to be a part of the future enhancements on the next generation cellular networks. Nodes operating at IBFD can transmit and receive simultaneously at the same time-frequency resource blocks, without the need to orthogonalize the Uplink-Downlink (UL-DL) frequency bands. Transceivers of such users implement Self-Interference Cancellation (SIC) techniques, and are able to route incoming and outgoing signals while transmitting at the same network resources, thus potentially doubling the capacity of the wireless channel. Stochastic geometry, a field focusing on the study of random spatial patterns, provides an elegant way of analyzing the performance of wireless networks and its technologies. In view of that, we develop approaches using this tool to derive network performance metrics. We use stochastic geometry to study the performance of a possible deployment scheme of IBFD in cellular networks. Mainly, we make use of the mathematical tools used in stochastic geometry to tackle two topics. At first, we study the Base Stations (BSs) locations in real cellular networks. We use data for the Evolved NodeB (eNB) locations from real deployed LTE networks in specific urban areas. We start our analysis by obtaining the spatial density distribution of these eNBs. Then, we try to fit this distribution with some candidate distributions, in which we determine the distribution that best fits with the actual density and gives the lowest Root Mean Square Error (RMSE). The aim from this procedure is to use this fitted density distribution in a framework that derives general performance metrics for the whole studied network. Henceforth, these metrics give a general idea about how the spatial density distribution can affect the network in general. Among these metrics, we show that the exact closed form expressions for the interference power PDF can be obtained for some cases. Th |
dc.format.extent |
1 online resource (xiv, 114 leaves) : color illustrations |
dc.language.iso |
eng |
dc.relation.ispartof |
Theses, Dissertations, and Projects |
dc.subject.classification |
ET:006678 |
dc.subject.lcsh |
Stochastic geometry. |
dc.subject.lcsh |
Wireless communication systems. |
dc.title |
Modified stochastic geometry models for the analysis of dense networks in 5G - |
dc.type |
Thesis |
dc.contributor.department |
Faculty of Engineering and Architecture. |
dc.contributor.department |
Department of Electrical and Computer Engineering, |
dc.contributor.institution |
American University of Beirut. |