Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Citation - Scopus: 2Resource Allocation for User-Relay Assisted Miso-Ofdma Networks(Institute of Electrical and Electronics Engineers Inc., 2015) Baştürk, İlhan; Özbek, BernaThe next generation cellular networks request higher capacity and coverage that user-relay assisted Orthogonal Frequency Division Multiple Access (OFDMA) networks are costeffective solutions to meet these demands. These networks can be enriched with multiple antennas in order to obtain a diversity gain to combat signal fading and to achieve more capacity gain without increasing the bandwidth or transmit power. However, radio resource management (RRM) such as relay selection and resource allocation (RA) is important in such a multi-user, multirelay and multi-antenna environment to fully take advantage of multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. Thus, we propose a RA algorithm for these networks to reveal the benefits of the combination of userrelaying and multiple antennas technologies and compare the proposed scheme with existing schemes in terms of percentage of satisfied users and cell-edge users' data rate.Conference Object Citation - WoS: 23Citation - Scopus: 31A Dominating Set Based Clustering Algorithm for Mobile Ad Hoc Networks(Springer Verlag, 2006) Çokuslu, Deniz; Erciyeş, Kayhan; Dağdeviren, OrhanWe propose a new Connected Dominating Set (CDS) based algorithm for clustering in Mobile Ad hoc Networks (MANETs). Our algorithm is based on Wu and Li's [14] algorithm, however we provide significant modifications by considering the degrees of the nodes during marking process and also provide further heuristics to determine the color of a node in the initial phase. We describe, analyze and measure performance of this new algorithm by simulation and show that it performs better than Wu and Li's [14] algorithm especially in the case of dense networks.Conference Object Citation - WoS: 7Citation - Scopus: 16A Hierarchical Connected Dominating Set Based Clustering Algorithm for Mobile Ad Hoc Networks(Institute of Electrical and Electronics Engineers Inc., 2007) Çokuslu, Deniz; Erciyeş, KayhanWe propose a hierarchical Connected Dominating Set (CDS) based algorithm for clustering in Mobile Ad hoc Networks (MANETs). Our algorithm is an extension of our previous Connected Dominating Set Based Clustering (CDSC) Algorithm [1]. We extended the levels of the CDS to two levels and improved functionality at each level by providing additional rules to make sure that every node belongs to a single cluster. In the first level of the algorithm, the elements of the CDS are formed, based on CDSC Algorithm heuristics with improved functionality. The second level of the algorithm is executed among the CDS elements to find the second level CDS where each element belonging to the set represents a group of CDS elements, therefore a group of clusters. We show that this approach is more scalable and simpler to implement than a single level algorithm and that it also provides more balanced two level clusters due to its distributed nature. We also show that the number of levels of the algorithm can be extended to more than two layers providing more populated clusters, therefore providing a level of cluster and group membership structure within the MANET. This hierarchical groups can be used for different application needs at each level such as multi-cast communication or security purposes in MANETs.Conference Object Citation - WoS: 4Citation - Scopus: 4Merging Clustering Algorithms in Mobile Ad Hoc Networks(Springer Verlag, 2005) Dağdeviren, Orhan; Erciyeş, Kayhan; Çokuslu, DenizClustering is a widely used approach to ease implementation of various problems such as routing and resource management in mobile ad hoc networks (MANET)s. We first look at minimum spanning tree(MST) based algorithms and then propose a new algorithm for clustering in MANETs. The algorithm we propose merges clusters to form higher level clusters by increasing their levels. We show the operation of the algorithm and analyze its time and message complexities.