Yazar "Sevindik, Volkan" seçeneğine göre listele

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    Interference coordination for millimeter wave communications in 5G networks for performance optimization
    (Springeropen, 2019) Wang, Jiao; Weitzen, Jay; Bayat, Oğuz; Sevindik, Volkan; Li, Mingzhe
    To address the increasing data rate demands for future wireless networks, a dense deployment of base stations or access points is the most promising approach; however, doing so may cause high intercell interference (ICI). Numerous interference coordination (IC) approaches have been proposed to reduce ICI. Conducting 5G communication on millimeter wave (mmWave) bands is more complex because of its higher propagation losses and greater attenuation variance, all of which depend on environment change. Massive antenna arrays with beamforming techniques can be used to overcome high propagation loss, reduce interference, deliver performance gains of coordination without a high overhead, and deliver high network capacity with multiplex transmitters. The central challenge of a massive antenna array that uses beamforming techniques is coordinating the users and beams for each transmitter within a large network. To address this challenge, we propose a novel two-level beamforming coordination approach that partitions a large network into clusters. At the intracluster level, this approach performs intracluster coordination similar to the user selection algorithms in a multiuser multiple input and multiple output (MU-MIMO); doing this maximizes the utility function or minimizes the signal-to-interference-plus-noise ratio (SINR) function within a cluster. A dynamic time domain IC approach is employed at the intercluster level, collecting interference information for cluster-edge user equipment (UE) and allocating the UE dynamically among the clusters to reduce the intercluster interference for a switched-beam system (SBS). Simulation results show that the proposed two-level IC approach achieves a higher edge user performance or cell capacity than with the current uncoordinated/coordinated approaches.
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    Joint interference coordination approach in femtocell networks for QoS performance optimization
    (Wiley, 2017) Wang, Jiao; Weitzen, Jay; Bayat, Oğuz; Sevindik, Volkan; Li, Mingzhe
    Future heterogeneous networks with dense cell deployment may cause high intercell interference. A number of interference coordination (IC) approaches have been proposed to reduce intercell interference. For dense small-cell deployment with high intercell interference between cells, traditional forward link IC approaches intended to improve edge user throughput for best effort traffic (ie, file transfer protocol download), may not necessarily improve quality of service performance for delay sensitive traffic such as voice over long-term evolution traffic. This study proposes a dynamic, centralized joint IC approach to improve forward link performance for delay-sensitive traffic on densely deployed enterprise-wide long-term evolution femtocell networks. This approach uses a 2-level scheme: central and femtocell. At the central level, the algorithm aims to maximize network utility (the utility-based approach) and minimize network outage (the graphic-based approach) by partitioning the network into clusters and conducting an exhaustive search for optimized resource allocation solutions among femtocells (femto access points) within each cluster. At the femtocell level, in contrast, the algorithm uses existing static approaches, such as conventional frequency reuse (ReUse3) or soft frequency reuse (SFR) to further improve user equipment quality of service performance. This combined approach uses utility-and graphic-based SFR and ReUse3 (USFR/GSFR and UReUse3/GReUse3, respectively). The cell and edge user throughput of best effort traffic and the packet loss rate of voice over long-term evolution traffic have been characterized and compared using both the proposed and traditional IC approaches.
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    Packet scheduling and traffic differentiation in femtocell environment
    (Ieice-Inst Electronics Information Communications Eng, 2011) Sevindik, Volkan; Bayat, Oğuz
    This paper proposes new scheduling algorithms for best effort (BE) traffic classification in business femtocell networks. The purpose of traffic classification is to provide differentiated services to BE users depending on their traffic classes, and the concept of traffic classification is called Inter User Best Effort (IUBE) in CDMA2000 1x Evolution Data Optimized (EVDO) standard. Traffic differentiation is achieved by introducing Grade of Service (GoS) as a quality of service (QoS) parameter into the scheduler's decision metric (DM). New scheduling algorithms are called QoS Round Robin (QoS-RR), QoS Proportionally Fair (QoS-PF), QoS maximum data rate control (DRC)(QoS-maxDRC), QoS average DRC (QoS-aveDRC), QoS exponent DRC (QoS-expDRC), QoS maxDRC-PF (QoS-maxDRC-PF). Two different femtocell throughput experiments are performed using real femtocell devices in order to collect real DRC values. The first experiment examines 4, 8, 12 and 16 IUBE users, while second experiment examines 4 IUBE + 2 Voice over IP (VoIP), 8 IUBE + 2 VoIP, 12 IUBE + 2 VoIP, 16 IUBE + 2 (VoIP) users. Average sector throughput, IUBE traffic differentiation, VoIP delay bound error values are investigated to compare the performance of the proposed scheduling algorithms. In conclusion, QoS-maxDRC-PF scheduler is proposed for business femtocell environment.
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    Performance evaluation of a real long term evolution (LTE) network
    (Ieee, 2012) Sevindik, Volkan; Wang, Jiao; Bayat, Oğuz; Weitzen, Jay
    This paper analyzes the performance of a real LTE network through the real LTE network drive tests. Test cases were performed under stationary and mobile conditions. Paper presents the results under high user mobility conditions and compares these results with the ones collected under stationary conditions. User mobility affects average received user throughput, block error rates (BLER), Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ) and Reference Signal Strength Indicator (RSSI) values significantly. All of the test cases were performed using real LTE device in a real LTE network. Video traffic was used in drive tests under stationary and mobile conditions. The main key performance indicators used in this paper are average sector throughput, the number of codewords (CW) used, channel quality indicator (CQI), block error rate (BLER), signal-to-noise-plus-interference ratio (SNIR), RSSI, RSRQ, and RSRP values. Average throughput values are very important to show the promised throughput performance of the LTE network. User mobility affects average delivered user throughput, BLER, and CQI values significantly.
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    Performance model for factory automation in 5G networks
    (2022) Wang, Jiao; Weitzen, Jay; Bayat, Oğuz; Sevindik, Volkan; Li, Mingzhe
    The fifth generation (5G) of mobile networks is emerging as a key enabler of modern factory automation (FA) applications that ensure timely and reliable data exchange between network components. Network slicing (NS), which shares an underlying infrastructure with different applications and ensures application isolation, is the key 5G technology to support the diverse quality of service requirements of modern FA applications. In this article, an end-to-end (E2E) NS solution is proposed for FA applications in a 5G network. Regression approaches are used to construct a performance model for each slice to map the service level agreement to the network attributes. Interference coordination approaches for switched beam systems are proposed to optimize radio access network (RAN) performance models. A case study of a non-public network is used to show the proposed NS solution. Simulation result shows that for services with different QoS requirements, different IC approaches should be used as optimization methods. Design prediction using regression approach has been evaluated and shows that the prediction successful rate increases when more existing data are used.
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    Performance model for video service in 5G networks
    (Mdpi, 2020) Wang, Jiao; Weitzen, Jay; Bayat, Oğuz; Sevindik, Volkan; Li, Mingzhe
    Network slicing allows operators to sell customized slices to various tenants at different prices. To provide better-performing and cost-efficient services, network slicing is looking to intelligent resource management approaches to be aligned to users' activities per slice. In this article, we propose a radio access network (RAN) slicing design methodology for quality of service (QoS) provisioning, for differentiated services in a 5G network. A performance model is constructed for each service using machine learning (ML)-based approaches, optimized using interference coordination approaches, and used to facilitate service level agreement (SLA) mapping to the radio resource. The optimal bandwidth allocation is dynamically adjusted based on instantaneous network load conditions. We investigate the application of machine learning in solving the radio resource slicing problem and demonstrate the advantage of machine learning through extensive simulations. A case study is presented to demonstrate the effectiveness of the proposed radio resource slicing approach.
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    Scheduler design for traffic classification in CDMA2000 1xEVDO network
    (Springer, 2011) Sevindik, Volkan; Bayat, Oğuz; Weitzen, Jay
    In CDMA2000 Evolution Data Optimized (EVDO) network, initial applications have been mainly focused on Best Effort (BE) traffic. Network operators observed that even though BE traffic users were the lowest priority users paying small subscription fees, they were heavily consuming the network resources. Therefore, operators demanded to charge BE users depending on their different levels of data usage. In this paper, we have designed a novel forward link (FL) scheduler called Throughput Based Adaptive Scheduler (TBAS)to differentiate BE traffic users, and at the same time to optimize the sector throughput. A set of live network experiments has been conducted to understand the behavior of current scheduler in CDMA 1xEVDO network, and then better throughput efficiency and traffic differentiation is achieved by introducing new TBAS method. TBAS algorithm utilizes BE traffic classes to exploit the multi-user diversity by combining it with multi-class diversity. TBAS method uses adaptive technique to calculate the scheduler's QoS parameter which is used for BE traffic differentiation. The problem with existing scheduling algorithm is that existing technique uses pre-determined constant QoS parameter to classify the traffic. Used QoS parameter does not reflect the changes in channel or user conditions. Therefore, scheduler can not efficiently exploit the existing channel information for more accurate scheduling decisions and can not provide high sector throughput. TBAS solves this problem by using average values of each BE traffic class throughput to calculate QoS parameter of each class. As average class throughput is a function of channel capacity, TBAS implicitly uses the channel information to calculate accurate QoS parameter for each traffic class. The performances of proposed and existing scheduler are evaluated in terms of average sector throughput, cumulative distribution function (CDF) of BE class throughput values, and throughput fairness. The performance characterization of existing scheduler is investigated through real network experiments conducted in live CDMA2000 1xEVDO network. Throughput measurements, received mobile terminal power, and signal-to-noise-plus-interference ratio (SNIR) were evaluated in the experiments. Since TBAS is out novel scheduling algorithm, only computer simulations were performed in order to assess its performance.