244 research outputs found

    Queueing Networks for Vertical Handover

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    PhDIt is widely expected that next-generation wireless communication systems will be heterogeneous, integrating a wide variety of wireless access networks. Of particular interest recently is a mix of cellular networks (GSM/GPRS and WCDMA) and wireless local area networks (WLANs) to provide complementary features in terms of coverage, capacity and mobility support. If cellular/ WLAN interworking is to be the basis for a heterogeneous network then the analysis of complex handover traffic rates in the system (especially vertical handover) is one of the most essential issues to be considered. This thesis describes the application of queueing-network theory to the modelling of this heterogeneous wireless overlay system. A network of queues (or queueing network) is a powerful mathematical tool in the performance evaluation of many large-scale engineering systems. It has been used in the modelling of hierarchically structured cellular wireless networks with much success, including queueing network modelling in the study of cellular/ WLAN interworking systems. In the process of queueing network modelling, obtaining the network topology of a system is usually the first step in the construction of a good model, but this topology analysis has never before been used in the handover traffic study in heterogeneous overlay wireless networks. In this thesis, a new topology scheme to facilitate the analysis of handover traffic is proposed. The structural similarity between hierarchical cellular structure and heterogeneous wireless overlay networks is also compared. By replacing the microcells with WLANs in a hierarchical structure, the interworking system is modelled as an open network of Erlang loss systems and with the new topology, the performance measures of blocking probabilities and dropping probabilities can be determined. Both homogeneous and non-homogeneous traffic have been considered, circuit switched and packet-switched. Example scenarios have been used to validate the models, the numerical results showing clear agreement with the known validation scenarios

    Performance model for two-tier mobile wireless networks with macrocells and small cells

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    [EN] A new analytical model is proposed to evaluate the performance of two-tier cellular networks composed of macrocells (MCs) and small cells (SCs), where terminals roam across the service area. Calls being serviced by MCs may retain their channel when entering a SC service area, if no free SC channels are available. Also, newly offered SC calls can overflow to the MC. However, in both situations channels may be repacked to vacate MC channels. The cardinality of the state space of the continuous-time Markov chain (CTMC) that models the system dynamics makes the exact system analysis unfeasible. We propose an approximation based on constructing an equivalent CTMC for which a product-form solution exist that can be obtained with very low computational complexity. We determine performance parameters such as the call blocking probabilities for the MC and SCs, the probability of forced termination, and the carried traffic. We validate the analytical model by simulation. Numerical results show that the proposed analytical model achieves very good precision in scenarios with diverse mobility rates and MCs and SCs loads, as well as when MCs overlay a large number of SCs.Authors would like to thank you the anonymous reviewers for the review comments provided to our work that have decisively contributed to improve the paper. Most of the contribution of V. Casares-Giner was done while visiting the Huazhong University of Science and Technolgy (HUST), Whuhan, China. This visit was supported by the European Commission, 7FP, S2EuNet project. The authors from the Universitat Politecnica de Valencia are partially supported by the Ministry of Economy and Competitiveness of Spain under grant TIN2013-47272-C2-1-R and TEC2015-71932-REDT. The research of Xiaohu Ge was supported by the National Natural Science Foundation of China (NSFC) grant 61210002, the Fundamental Research Funds for the Central Universities grant 2015XJGH011, and China International Joint Research Center of Green Communications and Networking grant 2015B01008.Casares-Giner, V.; Martínez Bauset, J.; Ge, X. (2018). Performance model for two-tier mobile wireless networks with macrocells and small cells. Wireless Networks. 24(4):1327-1342. https://doi.org/10.1007/s11276-016-1407-8S13271342244ABIresearch. (2016). In-building mobile data traffic forecast. ABIreseach, Technical Report.NGMN Alliance. (2015). Recommendations for small cell development and deployment. NGMN Alliance, Technical Report.Chandrasekhar, V., Andrews, J., & Gatherer, A. (2008). Femtocell networks: A survey. IEEE Communications Magazine, 46(9), 59–67.Yamamoto, T., & Konishi, S. (2013). Impact of small cell deployments on mobility performance in LTE-Advanced systems. In IEEE PIMRC workshops (pp. 189–193).Balakrishnan, R., & Akyildiz, I. (2016). Local anchor schemes for seamless and low-cost handover in coordinated small cells. IEEE Transactions on Mobile Computing, 15(5), 1182–1196.Zahir, T., Arshad, K., Nakata, A., & Moessner, K. (2013). Interference management in femtocells. IEEE Communications Surveys & Tutorials, 15(1), 293–311.Yassin, M., AboulHassan, M. A., Lahoud, S., Ibrahim, M., Mezher, D., Cousin, B., & Sourour, E. A. (2015). Survey of ICIC techniques in LTE networks under various mobile environment parameters. Wireless Networks, 1–16.Andrews, M., & Zhang, L. (2015). Utility optimization in heterogeneous networks via CSMA-based algorithms. Wireless Networks, 1–14.El-atty, S. M. A., & Gharsseldien, Z. M. (2016). Performance analysis of an advanced heterogeneous mobile network architecture with multiple small cell layers. Wireless Networks, 1–22.Huang, Q., Huang, Y.-C., Ko, K.-T., & Iversen, V. B. (2011). Loss performance modeling for hierarchical heterogeneous wireless networks with speed-sensitive call admission control. IEEE Transactions on Vehicular Technology, 60(5), 2209–2223.Bonald, T., & Roberts, J. W. (2003). Congestion at flow level and the impact of user behaviour. Computer Networks, 42, 521–536.Lee, Y. L., Chuah, T. C., Loo, J., & Vinel, A. (2014). Recent advances in radio resource management for heterogeneous LTE/LTE-A networks. IEEE Communications Surveys & Tutorials, 16(4), 2142–2180.Rappaport, S. S., & Hu, L.-R. (1994). Microcellular communication systems with hierarchical macrocell overlays: Traffic performance models and analysis. Proceedings of the IEEE, 82(9), 1383–1397.Ge, X., Han, T., Zhang, Y., Mao, G., Wang, C.-X., Zhang, J., et al. (2014). Spectrum and energy efficiency evaluation of two-tier femtocell networks with partially open channels. IEEE Transactions on Vehicular Technology, 63(3), 1306–1319.Song, W., Jiang, H., & Zhuang, W. (2007). Performance analysis of the WLAN-first scheme in cellular/WLAN interworking. IEEE Transactions on Wireless Communications, 6(5), 1932–1952.Ge, X., Martinez-Bauset, J., Gasares-Giner, V., Yang, B., Ye, J., & Chen, M. (2013). Modeling and performance analysis of different access schemes in two-tier wireless networks. In IEEE Globecom (pp. 4402–4407).Tsai, H.-M., Pang, A.-C., Lin, Y.-C., & Lin, Y.-B. (2005). Repacking on demand for hierarchical cellular networks. Wireless Networks, 11(6), 719–728.Maheshwari, K., & Kumar, A. (2000). Performance analysis of microcellization for supporting two mobility classes in cellular wireless networks. IEEE Transactions on Vehicular Technology, 49(2), 321–333.Whiting, P., & McMillan, D. (1990). Modeling for repacking in cellular radio. In 7th UK Teletraffic Symposium, IEE, Durham.Kelly, F. (1989). Fixed point models of loss networks. The Journal of the Australian Mathematical Society. Series B. Applied Mathematics, 31(02), 204–218.McMillan, D. (1991). Traffic modelling and analysis for cellular mobile networks. In A. Jensen & V. Iversen (Eds.), Proceedigs of ITC-13 (pp. 627–632). IAC. Copenhaguen: Elsevier Science.Fu, H.-L., Lin, P., & Lin, Y.-B. (2012). Reducing signaling overhead for femtocell/macrocell networks. IEEE Transactions on Mobile Computing, 12(8), 1587–1597.Eklundh, B. (1986). Channel utilization and blocking probability in a cellular mobile telephone system with directed retry. IEEE Transactions on Communications, 37, 329–337.Karlsson, J., & Eklundh, B. (1989). A cellular telephone system with load sharing—An enhancement of directed retry. IEEE Transactions on Communications, 37(5), 530–535.Nelson, R. (1995). Probability, stochastic processes and queueing theory. New York: Springer.Iversen, V.B. (Aug. 1987). The exact evaluation of multi-service loss systems with access control. In Proceedings of the Seventh Nordic Teletraffic Seminar (NTS-7) (Vol. 31, pp. 56–61) Lund, (Sweden).Ross, K. W. (1995). Multiservice loss models for broadband telecommunication networks. New York: Springer.Lin, Y.-B., & Mak, V. W. (1994). Eliminating the boundary effect of a large-scale personal communication service network simulation. ACM Transactions on Modeling and Computer Simulation (TOMACS), 4(2), 165–190.Karray, M.K. (2010). Evaluation of the blocking probability and the throughput in the uplink of wireless cellular networks. In IEEE ComNet (pp. 1–8)

    Modelling Pascal traffic in overflow systems

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    In this paper, impact of changes in parameters of offeredtraffic on the accuracy of determining the parameters of overflowtraffic in hierarchy systemswithmulti-service traffic was presented. Pascal typetrafficstreamswereoffered to the consideredsystems. The study investigated the impact of changes in the number of sources, intensity of trafficoffered by individualclasses, as well as changes in the trafficoffered by single free source. The presentedresultsarebased on determined relative errors of the values of overflowtrafficobtained in simulations and on the basis of calculations

    State-Dependent Bandwidth Sharing Policies for Wireless Multirate Loss Networks

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    We consider a reference cell of fixed capacity in a wireless cellular network while concentrating on next-generation network architectures. The cell accommodates new and handover calls from different service-classes. Arriving calls follow a random or quasi-random process and compete for service in the cell under two bandwidth sharing policies: 1) a probabilistic threshold (PrTH) policy or 2) the multiple fractional channel reservation (MFCR) policy. In the PrTH policy, if the number of in-service calls (new or handover) of a service-class exceeds a threshold (difference between new and handover calls), then an arriving call of the same service-class is accepted in the cell with a predefined state-dependent probability. In the MFCR policy, a real number of channels is reserved to benefit calls of certain service-classes; thus, a service priority is introduced. The cell is modeled as a multirate loss system. Under the PrTH policy, call-level performance measures are determined via accurate convolution algorithms, while under the MFCR policy, via approximate but efficient models. Furthermore, we discuss the applicability of the proposed models in 4G/5G networks. The accuracy of the proposed models is verified through simulation. Comparison against other models reveals the necessity of the new models and policies

    Mobile Networks

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    The growth in the use of mobile networks has come mainly with the third generation systems and voice traffic. With the current third generation and the arrival of the 4G, the number of mobile users in the world will exceed the number of landlines users. Audio and video streaming have had a significant increase, parallel to the requirements of bandwidth and quality of service demanded by those applications. Mobile networks require that the applications and protocols that have worked successfully in fixed networks can be used with the same level of quality in mobile scenarios. Until the third generation of mobile networks, the need to ensure reliable handovers was still an important issue. On the eve of a new generation of access networks (4G) and increased connectivity between networks of different characteristics commonly called hybrid (satellite, ad-hoc, sensors, wired, WIMAX, LAN, etc.), it is necessary to transfer mechanisms of mobility to future generations of networks. In order to achieve this, it is essential to carry out a comprehensive evaluation of the performance of current protocols and the diverse topologies to suit the new mobility conditions

    Final report on the evaluation of RRM/CRRM algorithms

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    Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

    Quality of service optimization of multimedia traffic in mobile networks

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    Mobile communication systems have continued to evolve beyond the currently deployed Third Generation (3G) systems with the main goal of providing higher capacity. Systems beyond 3G are expected to cater for a wide variety of services such as speech, data, image transmission, video, as well as multimedia services consisting of a combination of these. With the air interface being the bottleneck in mobile networks, recent enhancing technologies such as the High Speed Downlink Packet Access (HSDPA), incorporate major changes to the radio access segment of 3G Universal Mobile Telecommunications System (UMTS). HSDPA introduces new features such as fast link adaptation mechanisms, fast packet scheduling, and physical layer retransmissions in the base stations, necessitating buffering of data at the air interface which presents a bottleneck to end-to-end communication. Hence, in order to provide end-to-end Quality of Service (QoS) guarantees to multimedia services in wireless networks such as HSDPA, efficient buffer management schemes are required at the air interface. The main objective of this thesis is to propose and evaluate solutions that will address the QoS optimization of multimedia traffic at the radio link interface of HSDPA systems. In the thesis, a novel queuing system known as the Time-Space Priority (TSP) scheme is proposed for multimedia traffic QoS control. TSP provides customized preferential treatment to the constituent flows in the multimedia traffic to suit their diverse QoS requirements. With TSP queuing, the real-time component of the multimedia traffic, being delay sensitive and loss tolerant, is given transmission priority; while the non-real-time component, being loss sensitive and delay tolerant, enjoys space priority. Hence, based on the TSP queuing paradigm, new buffer managementalgorithms are designed for joint QoS control of the diverse components in a multimedia session of the same HSDPA user. In the thesis, a TSP based buffer management algorithm known as the Enhanced Time Space Priority (E-TSP) is proposed for HSDPA. E-TSP incorporates flow control mechanisms to mitigate congestion in the air interface buffer of a user with multimedia session comprising real-time and non-real-time flows. Thus, E-TSP is designed to provide efficient network and radio resource utilization to improve end-to-end multimedia traffic performance. In order to allow real-time optimization of the QoS control between the real-time and non-real-time flows of the HSDPA multimedia session, another TSP based buffer management algorithm known as the Dynamic Time Space Priority (D-TSP) is proposed. D-TSP incorporates dynamic priority switching between the real-time and non-real-time flows. D-TSP is designed to allow optimum QoS trade-off between the flows whilst still guaranteeing the stringent real-time component’s QoS requirements. The thesis presents results of extensive performance studies undertaken via analytical modelling and dynamic network-level HSDPA simulations demonstrating the effectiveness of the proposed TSP queuing system and the TSP based buffer management schemes

    Exploiting user contention to optimize proactive resource allocation in future networks

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    In order to provide ubiquitous communication, seamless connectivity is now required in all environments including highly mobile networks. By using vertical handover techniques it is possible to provide uninterrupted communication as connections are dynamically switched between wireless networks as users move around. However, in a highly mobile environment, traditional reactive approaches to handover are inadequate. Therefore, proactive handover techniques, in which mobile nodes attempt to determine the best time and place to handover to local networks, are actively being investigated in the context of next generation mobile networks. The Y-Comm Framework which looks at proactive handover techniques has de�fined two key parameters: Time Before Handover and the Network Dwell Time, for any given network topology. Using this approach, it is possible to enhance resource management in common networks using probabilistic mechanisms because it is now possible to express contention for resources in terms of: No Contention, Partial Contention and Full Contention. As network resources are shared between many users, resource management must be a key part of any communication system as it is needed to provide seamless communication and to ensure that applications and servers receive their required Quality-of-Service. In this thesis, the contention for channel resources being allocated to mobile nodes is analysed. The work presents a new methodology to support proactive resource allocation for emerging future networks such as Vehicular Ad-Hoc Networks (VANETs) by allowing us to calculate the probability of contention based on user demand of network resources. These results are veri�ed using simulation. In addition, this proactive approach is further enhanced by the use of a contention queue to detect contention between incoming requests and those waiting for service. This thesis also presents a new methodology to support proactive resource allocation for future networks such as Vehicular Ad-Hoc Networks. The proposed approach has been applied to a vehicular testbed and results are presented that show that this approach can improve overall network performance in mobile heterogeneous environments. The results show that the analysis of user contention does provide a proactive mechanism to improve the performance of resource allocation in mobile networks
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