Relevant bibliographies by topics / Mobile communication systems Cluster analysis

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Mobile communication systems Cluster analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Mobile communication systems Cluster analysis"

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Zhao, Jing, Nan Wei, Hui Li, and Yue Ling Liu. "Analysis of Communication Enterprises' Customers Segmentation Based on Data Mining." Applied Mechanics and Materials 543-547 (March 2014): 4464–67. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.4464.

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Application of data mining in mobile communication enterprises can help the enterprises conduct customers subdivision, understand characteristics of consumer behavior and develop appropriate product service systems based on different subdivided groups to occupy more market shares and provide better services for customers. By applying cluster analysis method in data mining and using k-means algorithm, this paper analyzes the collected mobile service consumption data with college students as samples, concludes behavioral characteristics of the mobile service consumption of three type college students and makes proposals from the perspective of operators.
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Wang, Chao, Jianhua Zhang, and Guangzhong Yu. "Cluster Analysis of Pedestrian Mobile Channels in Measurements and Simulations." Applied Sciences 9, no. 5 (2019): 886. http://dx.doi.org/10.3390/app9050886.

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In wireless communication systems, channels evolve when user terminals move. To further understand channel variation, and especially the evolution of clusters in mobile channels, a set of experiments was designed. First, we performed pedestrian mobile measurements in an urban macro (UMa) scenario at 3.5 GHz, and the K-power means-Kalman filter (KPMKF) algorithm was used for clustering and tracking. By this process, the trajectory of different clusters could clearly be described during measurement. The birth and death rate of clusters per snapshot show that the change of one or two clusters in each snapshot takes more probabilities. In addition, the differences of the cluster lifetime between the clustering process with and without the Kalman filter (KF) algorithm are given to show the effect from the KF. Second, channel simulations were implemented based on the above observed results. The spatial-consistency feature was introduced to get closer to the measured channels, which is based on the primary module of International Mobile Telecommunications-2020 (IMT-2020) channel model. Comparisons among measurements and simulations with and without this feature show that adding this feature improves simulation accuracy. To explore a novel method to characterize clusters during linear movement, a gradient boosted decision-tree (GBDT) algorithm is introduced. It uses the above characteristics of clusters and channel impulse responses (CIRs) as the training and validating dataset. The root mean square error (RMSE) shows that this is promising.
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Jia, Guohui, and Jie Zhou. "Effectiveness Evaluation Method of Application of Mobile Communication System Based on Factor Analysis." Sensors 21, no. 16 (2021): 5414. http://dx.doi.org/10.3390/s21165414.

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The application mode of army mobile communication networks is closely related to combat mission and application environment. Different combat missions and application environments result in different network structures and different service priorities, which requires a semi-automatic system to support the network scheme design. Therefore, evaluating the efficiency of network schemes generated by automatic planning is a problem that needs to be urgently addressed. In the past, researchers have proposed a variety of methods to evaluate the effectiveness of mobile communication systems, most of which are based on simulation methods and ignore the historical data of network usage. This paper studies an effectiveness evaluation method of mobile communication network design schemes and proposes a design scheme for the evaluation and optimization of network plans. Furthermore, the improved method of effectiveness evaluation based on factor analysis is discussed in detail. The method not only effectively uses historical data but also reduces the amount of data collection and calculation. In order to adapt to the preference requirements of different task scenarios, a decision preference setting method based on cluster analysis is proposed, which can render the output optimization result more reasonable and feasible.
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Liu, Yutao, Yue Li, Yimeng Zhao, and Chunhui Zhang. "Research on MAC Protocols in Cluster-Based Ad Hoc Networks." Wireless Communications and Mobile Computing 2021 (March 29, 2021): 1–12. http://dx.doi.org/10.1155/2021/5513469.

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Mobile ad hoc networks can be widely used in many scenes, for example, military communication, emergency communication, and 5G wide area coverage as well as ultradense network scenes. A cluster-based network can decrease network overhead effectively and then constitute a large-scale network through extending network scale by clustering and cascading. In view of multiservice simultaneous transmission demand for small-scale dense networking scene and large-scale extended networking scene, a MAC protocol based on scheduling of cluster head is proposed, which can avoid collision and retransmission between nodes effectively, and then the network synchronizing in intercluster and intracluster as well as the time-slot scheduling is solved fast and efficiently. A network synchronization algorithm based on clock spread of the sponsorship node is proposed to achieve network self-synchronizing, and a modified schedule-tree algorithm based on cluster head and exactly sponsorship node is proposed to decrease network overhead and to increase network fairness, then MAC protocol based on scheduling of cluster head is verified by simulated analysis. Finally, a dynamic gateway selection algorithm based on link stability is proposed in this paper to decrease intercluster communication control overhead and improve intercluster communication reliability.
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Chen, Yanyan, Zheng Zhang, and Tianwen Liang. "Assessing Urban Travel Patterns: An Analysis of Traffic Analysis Zone-Based Mobility Patterns." Sustainability 11, no. 19 (2019): 5452. http://dx.doi.org/10.3390/su11195452.

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Information and communication technology development has yielded large-scale spatiotemporal datasets, such as mobile phone, automatic collection system, and car-hailing data, which have resulted in new opportunities to investigate urban transportation systems. However, few studies have focused on regional mobility patterns. This study presents a multistep method for exploring traffic analysis zone (TAZ)-based mobility patterns and the corresponding relations with local land use characteristics. Based on a large-scale mobile phone dataset from a major mobile phone operator in Beijing, we applied the K-means clustering algorithm to the hourly aggregated trip data to create clusters of TAZs with similar temporal mobility patterns. Land use characteristics were then derived and correlated with the temporal TAZ-based mobility patterns. Four clusters of TAZs with the similar patterns and intensities of urban activities during given time windows were identified. Land use indicators, such as residence and commercial and business area indicators, were correlated with specific temporal TAZ-based mobility patterns. The proposed multistep method could be applied in other cities to enrich relevant analyses and improve urban design and transportation planning.
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Huang, Xinyu, Yunzhe Tian, Yifei He, et al. "Exposing Spoofing Attack on Flocking-Based Unmanned Aerial Vehicle Cluster: A Threat to Swarm Intelligence." Security and Communication Networks 2020 (December 9, 2020): 1–15. http://dx.doi.org/10.1155/2020/8889122.

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With the rapid development of wireless communication technology and intelligent mobile devices, unmanned aerial vehicle (UAV) cluster is becoming increasingly popular in both civilian and military applications. Recently, a swarm intelligence-based UAV cluster study, aiming to enable efficient and autonomous collaboration, has drawn lots of interest. However, new security problems may be introduced with such swarm intelligence. In this work, we perform the first detailed security analysis to a kind of flocking-based UAV cluster with 5 policies, an upgrade version of the well-known Boids model. Targeting a realistic threat in a source-to-destination flying task, we design a data spoofing strategy and further perform complete vulnerability analysis. We reveal that such design and implementation are highly vulnerable. After breaking through the authentication of ad hoc on-demand distance vector (AODV) routing protocol by rushing attack, an attacker can masquerade as the first-arrival UAV within a specific scope of destination and generate data spoofing of arrival status to the following UAVs, so as to interfere with their normal flying paths of destination arrival and cause unexpected arrival delays amid urgent tasks. Experiments with detailed analysis from the 5-UAV cluster to the 10-UAV cluster are conducted to show specific feature composition-based attack effect and corresponding average delay. We also discuss promising defense suggestions leveraging the insights from our analysis.
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Chen, Ruibiao, Fangxing Shu, Kai Lei, Jianping Wang, and Liangjie Zhang. "User Clustering and Power Allocation for Energy Efficiency Maximization in Downlink Non-Orthogonal Multiple Access Systems." Applied Sciences 11, no. 2 (2021): 716. http://dx.doi.org/10.3390/app11020716.

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Non-orthogonal multiple access (NOMA) has been considered a promising technique for the fifth generation (5G) mobile communication networks because of its high spectrum efficiency. In NOMA, by using successive interference cancellation (SIC) techniques at the receivers, multiple users with different channel gain can be multiplexed together in the same subchannel for concurrent transmission in the same spectrum. The simultaneously multiple transmission achieves high system throughput in NOMA. However, it also leads to more energy consumption, limiting its application in many energy-constrained scenarios. As a result, the enhancement of energy efficiency becomes a critical issue in NOMA systems. This paper focuses on efficient user clustering strategy and power allocation design of downlink NOMA systems. The energy efficiency maximization of downlink NOMA systems is formulated as an NP-hard optimization problem under maximum transmission power, minimum data transmission rate requirement, and SIC requirement. For the approximate solution with much lower complexity, we first exploit a quick suboptimal clustering method to assign each user to a subchannel. Given the user clustering result, the optimal power allocation problem is solved in two steps. By employing the Lagrangian multiplier method with Karush–Kuhn–Tucker optimality conditions, the optimal power allocation is calculated for each subchannel. In addition, then, an inter-cluster dynamic programming model is further developed to achieve the overall maximum energy efficiency. The theoretical analysis and simulations show that the proposed schemes achieve a significant energy efficiency gain compared with existing methods.
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Wang, Qiao, Jianjun Wang, and Shenlin Ye. "Decision-Making Optimization Design of Enterprise Standardization Management Planning Based on Mobile Network System." Wireless Communications and Mobile Computing 2021 (May 31, 2021): 1–11. http://dx.doi.org/10.1155/2021/5548522.

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With the continuous deepening of enterprise management and market competition, the pressure of production and operation of enterprises is increasing, and it is urgent to improve the management level of enterprises. This paper mainly studies the decision optimization design of enterprise standardization management planning based on mobile network system. In this paper, the idea of clustering is used to integrate the customers into a customer clustering mode, which will greatly reduce the number of customers studied in the model and simplify the optimization process of the model. Through online and offline processes, these can achieve dynamic and rapid processing of data flow and can well meet the needs of users for data flow analysis. In the construction of enterprise standardization strategic performance evaluation index system, it is necessary to decompose, combine, and converge the index system. According to the construction principles and methods discussed above, the influencing factors of standardized strategic performance evaluation indicators of construction enterprises are preliminarily stratified by using the expert survey method and cluster analysis method, so as to construct the initial evaluation system. For the mobile network system testing, we use the black box test and white box test. The test content mainly includes two modules: area calculation and label calculation. Experimental data show that when the time threshold Ts is set to 1 hour, the prediction accuracy of TBM increases from 46.9% to 47.7%. The results show that the mobile network system realizes the whole life cycle management of enterprise standards and improves the management level of enterprise standardization work.
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Urquiza Villalonga, David Alejandro, Felip Riera-Palou, M. Julia Fernández-Getino García, and Guillem Femenias. "Deployment of Clustered-Based Small Cells in Interference-Limited Dense Scenarios: Analysis, Design, and Trade-Offs." Wireless Communications and Mobile Computing 2021 (July 31, 2021): 1–15. http://dx.doi.org/10.1155/2021/9914456.

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Network densification is one of the most promising solutions to address the high data rate demands in 5G and beyond (B5G) wireless networks while ensuring an overall adequate quality of service. In this scenario, most users experience significant interference levels from neighbouring mobile stations (MSs) and access points (APs) making the use of advanced interference management techniques mandatory. Clustered interference alignment (IA) has been widely proposed to manage the interference in densely deployed scenarios with a large number of users. Nonetheless, the setups considered in previous works are still far from the densification levels envisaged for 5G/B5G networks that are considered in this paper. Moreover, prior designs of clustered-IA systems relied on oversimplified channel models and/or enforced single-stream transmission. In this paper, we explore an ultradense deployment of small cells (SCs) to provide coverage in 5G/B5G wireless networks. A novel cluster design based on a size-restricted k -means algorithm to divide the SCs into different clusters is proposed taking into account path loss and shadowing effects, thus providing a more realistic solution than those available in the current literature. Unlike previous works, this clustering method can also cater for spatial multiplexing scenarios. Also, several design parameters such as the number of transmit antennas, multiplexed data streams, and deployed APs are analyzed in order to identify trade-offs between performance and complexity. The relationship between density of network elements per area unit and performance is investigated, thus allowing to illustrate that there is an optimal coverage area value over which the network resources should be distributed. Moreover, it is shown that the spectral-efficiency degradation due to the intercluster interference in ultradense networks (UDNs) points to the need of designing an interference management algorithm that accounts for both intracluster and intercluster interferences. Simulation results provide key insights for the deployment of small cells in interference-limited dense scenarios.
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Okaie, Yutaka. "Cluster Formation by Mobile Molecular Communication Systems." IEEE Transactions on Molecular, Biological and Multi-Scale Communications 5, no. 2 (2019): 153–57. http://dx.doi.org/10.1109/tmbmc.2020.2981662.

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Dissertations / Theses on the topic "Mobile communication systems Cluster analysis"

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Dağdeviren, Orhan Erciyeş Kayhan. "A cluster based communication architecture for distributed applications in mobile ad hoc networks/." [s.l.]: [s.n.], 2006. http://library.iyte.edu.tr/tezler/master/bilgisayaryazilimi/T000525.pdf.

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Thesis (Master)--İzmir Institute of Technology, İzmir, 2006.<br>Keywords: Cluster method, mobile communication, distruted systems, software architecture, communication networks. Includes bibliographical references (leaves. 63-69).
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Wang, Yong. "Clustering, grouping, and process over networks." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Dissertations/Fall2007/Y_Wang_120707.pdf.

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Zapata, Augusto J. "Analysis of maritime mobile satellite communication systems." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/22890.

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Woo, Kam Tim. "Applications of clustering techniques on communication systems /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202004%20WOO.

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Lee, Kok Thong. "Performance analysis of Mobile Ad Hoc Networking routing protocols /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Dec%5FLee%5Kok.pdf.

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Tang, Seok Yee. "Performance analysis of scalable resource allocation for future mobile communication systems." Thesis, University of Surrey, 2004. http://epubs.surrey.ac.uk/844410/.

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The mobile communications industry has undergone rapid developments in the last decade. Consumers and businesses have become increasingly technology savvy and are likely to expect creative wireless access to many services. Consequently, future mobile systems are envisioned to support a wide variety of applications. The support of these diverse services (e.g. data and multimedia) has led to different bandwidth requirements, inevitably rendering many of the traditional radio resource management (RRM) mechanisms deficient. For one, the present radio resource dimensioning strategy that dimensions radio resource based on "busy hour" traffic does not allow operators to efficiently utilised the radio resource, which is scarce and limited. In line with the future demand driven resource allocation, two novel Scalable Resource Allocation (ScRA) techniques are proposed in this thesis to optimise the utilisation of radio resources within multiple services. The proposed novel ScRA techniques performances are evaluated on a typical GSM/GPRS mobile network through our developed dynamic system level simulator. Based on the simulation results, significant radio resource utilization gain, higher data throughput, lesser delay for data connections can be achieved with the use of our ScRA technique over the conventional StRA technique. For example, when the WWW arrival rate reaches approximate 35 Kbits/sec, ScRA technique can attain the throughput difference as high as 27.663%. On the other hand, the system throughput gain can yield as high as 27.44% when the Email arrival rate reached 1769 bits/sec for ScRA technique. Above all, we have also verified that the ScRA techniques perform well within the consideration of desirable voice QoSs at all times. The better performance of this technique is credited to its flexible and adaptive radio channel allocation (or re-allocation) between the multiple services during each sampled time. Key words; Radio Resource Management, Call Admission Control, Scalable Resource Allocation.
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Thong, Lee Kok. "Performance analysis of mobile ad hoc networking routing protocols." Thesis, Monterey, California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1225.

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Approved for public release, distribution is unlimited<br>This thesis presents a simulation and performance evaluation analysis of the various routing protocols that have been proposed for the Mobile Ad Hoc Network (MANET) environment using the Network Simulator-2 (NS-2) tool. Many routing protocols have been proposed by the academic communities for possible practical implementation of a MANET in military, governmental and commercial environments. Four (4) such routing protocols were chosen for analysis and evaluation: Ad Hoc On-demand Distance Vector routing (AODV), Dynamic Source Routing (DSR), Destination-Sequenced Distance Vector routing (DSDV) and Optimized Link State Routing (OLSR). NS-2 is developed and maintained by the University of Southern California's Information Sciences Institute (ISI). Leveraging on NS-2's simulation capabilities, the key performance indicators of the routing protocols were analyzed such as data network throughput, routing overhead generation, data delivery delay as well as energy efficiency or optimization. The last metric is explored, especially due to its relevance to the mobile environment. Energy is a scare commodity in a mobile ad hoc environment. Any routing software that attempts to minimize energy usage will prolong the livelihood of the devices used in the battlefield. Three important mobility models are considered, namely, Random Waypoint, Manhattan Grid, and Reference Point Group Mobility. The application of these three models will enhance the realism of simulation to actual real life mobility in an urban or military setup scenario. The performance of the routing protocols in varied node density, mobility speed as well as loading conditions have been studied. The results of the simulation will provide invaluable insights to the performance of the selected routing protocols. This can serve as a deciding factor for the U.S. Department of Defense (DoD) in their selection of the most suitable routing protocols tailored to their specific needs.<br>Civilian, Defence Science Technology Agency, Singapore
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Wang, Xiaodong. "Mobile communications in China an analysis of the diffusion process /." The Ohio State University, 1994. http://catalog.hathitrust.org/api/volumes/oclc/34639588.html.

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Alam, Muhammad Tanvir. "Design and analysis for the 3G IP multimedia subsytem /." Gold Coast, QLD : Bond University, 2007. http://epublications.bond.edu.au/theses/alam.

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Thesis (PhD.) -- Bond University, 2007.<br>"A dissertation submitted in fulfillment of the requirements for the degree of Doctor of Philosophy"-- t.p. Bibliography: leaves 219-242. Also available via the World Wide Web.
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Alparslan, Denizhan N. Sohraby Khosrow. "Modeling and analysis of generalized random mobility models for wireless ad hoc networks." Diss., UMK access, 2005.

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Thesis (Ph. D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2005.<br>"A dissertation in telecommunication networking and computer networking." Advisor: Khosrow Sohraby. Typescript. Vita. Title from "catalog record" of the print edition Description based on contents viewed May 30, 2006. Includes bibliographical references (leaves 119-123). Online version of the print edition.
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Books on the topic "Mobile communication systems Cluster analysis"

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Zapata, Augusto J. Analysis of maritime mobile satellite communication systems. Naval Postgraduate School, 1988.

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Bhaumick, Asesh. A strategic analysis of demand for mobile telecommunications services. iimt University Press, 2007.

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Deal, Tim. Mobile broadband services: 2007 competitive analysis & strategic outlook. Pike & Fischer, 2007.

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Dickinger, Astrid. Perceived Quality of Mobile Services: A Segment-Specific Analysis. Peter Lang International Academic Publishers, 2008.

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Perceived quality of mobile services: A segment-specific analysis. P. Lang, 2007.

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Dickinger, Astrid. Perceived quality of mobile services: A segment-specific analysis. P. Lang, 2007.

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Azzedine, Boukerche, Lin Jason Yi-Bing, and ACM SIGMOBILE, eds. Proceedings of the 2nd ACM International Workshop on Modeling, Analysis and Simulation of Wireless and Mobile Systems ; August 20th, 1999, Seatle, WA. Association for Computing Machinery, 1999.

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Ryu, Hokyoung. Mobile user interface analysis and design: A practitioner's guide to designing user interfaces for mobile devices. Nova Science Publishers, 2009.

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Decreusefond, Laurent. Stochastic modeling and analysis of telecom networks. ISTE, 2011.

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ACM, International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems (6th 2003 San Diego Calif ). ACM MSWiM: Proceedings of the Sixth ACM International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems : September 19, 2003. ACM Press, 2003.

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Book chapters on the topic "Mobile communication systems Cluster analysis"

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Sethi, Tegjyot Singh, CH V. M. K. Hari, B. S. S. Kaushal, and Abhishek Sharma. "Cluster Analysis & Pso for Software Cost Estimation." In Information Technology and Mobile Communication. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20573-6_47.

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Paireekreng, Worapat, Kok Wai Wong, and Chun Che Fung. "Cluster Analysis for Personalised Mobile Entertainment Content." In IFIP Advances in Information and Communication Technology. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15214-6_4.

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Kumari, Parveen, Sugandha Singh, and Gaurav Aggarwal. "Energy Efficiency Analysis of Cluster Based Routing in MANET." In Intelligent Communication Technologies and Virtual Mobile Networks. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28364-3_46.

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Venet, Arnaud. "Automatic Determination of Communication Topologies in Mobile Systems." In Static Analysis. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-49727-7_9.

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Ait Rahou, Meriem, and Abderrahim Hasbi. "Toward Cluster Head Selection Criterions in Mobile Ad Hoc Network." In International Conference on Information Technology and Communication Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64719-7_16.

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Pei, Daming. "Interference Analysis of Mobile Communication Multi-system." In Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019). Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1468-5_85.

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Zhang, Andong, Shuowen Zhang, Pengcheng Zhu, and Xiaohu You. "Power Consumption Analysis and Modeling of Mobile Communication Architecture." In Advances in Intelligent Systems and Computing. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1759-6_28.

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Nakano, K., K. Saita, M. Sengoku, Y. Yamada, and S. Shinoda. "Mobile communication traffic analysis on a road systems model." In Performance and Management of Complex Communication Networks. Springer US, 1998. http://dx.doi.org/10.1007/978-0-387-35360-9_1.

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Rajpurohit, Vijay S., and M. M. Manohara Pai. "Performance Analysis of a Multi Window Stereo Algorithm on Small Scale Distributed Systems: A Message Passing Environment." In Information Technology and Mobile Communication. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20573-6_59.

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Wang, Chunli, and Quanyu Wang. "Analysis and Research on Speech Enhancement Algorithms for Mobile Communication." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15235-2_138.

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Conference papers on the topic "Mobile communication systems Cluster analysis"

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Singh, Vinay, and Alok Aggarwal. "Performance analysis of middleware distributed and clustered systems (PAMS) concept in mobile communication devices using Android operating system." In 2014 International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2014. http://dx.doi.org/10.1109/pdgc.2014.7030768.

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Kumar, Rahul, Abhineet Anand, and Rajeev Tiwari. "Cluster analysis for pollution density." In The International Conference on Communication and Computing Systems (ICCCS-2016). CRC Press, 2016. http://dx.doi.org/10.1201/9781315364094-150.

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Jehangir, Assed, and Sonia M. Heemstra de Groot. "Securing inter-cluster communication in Personal Networks." In 2007 Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services (MobiQuitous). IEEE, 2007. http://dx.doi.org/10.1109/mobiq.2007.4451053.

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Yahya, Harith, Yaarob Al-Nidawi, and Andrew H. Kemp. "A dynamic cluster head election protocol for mobile wireless sensor networks." In 2015 International Symposium on Wireless Communication Systems. IEEE, 2015. http://dx.doi.org/10.1109/iswcs.2015.7454362.

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Rekha, S. Bhanu, S. Muthukumarasamy, and K. Thanigaivelu. "Balanced clustering in mobile ad hoc networks using route cluster." In 2016 International Conference on Information Communication and Embedded Systems (ICICES). IEEE, 2016. http://dx.doi.org/10.1109/icices.2016.7518941.

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Novo, David, Alejandro Nocua, Florent Bruguier, Abdoulaye Gamatie, and Gillies Sassatelli. "Evaluation of Heterogeneous Multicore Cluster Architectures Designed for Mobile Computing." In 2018 13th International Symposium on Reconfigurable Communication-centric Systems-on-Chip (ReCoSoC). IEEE, 2018. http://dx.doi.org/10.1109/recosoc.2018.8449376.

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Chin-Chen Chang, Keng-Chu Lin, and Jung-San Lee. "DH-based communication method for cluster-based ad hoc networks." In IEE Mobility Conference 2005. The Second International Conference on Mobile Technology, Applications and Systems. IEE, 2005. http://dx.doi.org/10.1049/cp:20051506.

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Chin-Chen Chang, Keng-Chu Lin, and Jung-San Lee. "DH-based communication method for cluster-based ad hoc networks." In IEE Mobility Conference 2005. The Second International Conference on Mobile Technology, Applications and Systems. IEEE, 2005. http://dx.doi.org/10.1109/mtas.2005.207189.

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Tuah, Norah, Mahamod Ismail, and Kasmiran Jumari. "Analysis of optimal cluster number in heterogenous wireless sensor networks." In 2012 IEEE International Conference on Communication Systems (ICCS). IEEE, 2012. http://dx.doi.org/10.1109/iccs.2012.6406097.

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Sharma, Manan, Shivam Tiwari, Suchetana Chakraborty, and Dip Sankar Banerjee. "Behavior Analysis through Routine Cluster Discovery in Ubiquitous Sensor Data." In 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS). IEEE, 2020. http://dx.doi.org/10.1109/comsnets48256.2020.9027377.

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