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Subashini, S.
- An Effective Scheduling Algorithm for MIMO Systems in Long Term Evolution Networks
Abstract Views :146 |
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Authors
Affiliations
1 Department SENSE, VIT University, Chennai – 632014, Tamil Nadu, IN
1 Department SENSE, VIT University, Chennai – 632014, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 24 (2015), Pagination:Abstract
Background: Long Term Evolution (LTE) represents an emerging and competent innovation for giving an internet access. LTE standard paves way towards the fourth generation networks, which is intended to deliver high speed data as well as multimedia services. Statistical Analysis: In LTE system Radio Resource Management (RRM) plays a very crucial role in managing limited radio resources to enhance the data rate. The paper focuses in addressing the challenges in downlink scheduling and provides a solution for the users to achieve higher spectral efficiency and throughput. In LTE systems’ fading of a channel is a serious issue for signal degradation and the fading effect is minimized by a choice of time and space domain techniques. The overall performance of the algorithms is calculated in terms of the throughput and SNR where the resource distribution is analyzed and evaluated for every individual user %. Findings: Hence a novel scheduling algorithm is developed for Multiple Input Multiple Output (MIMO) systems, where as Alamouti scheme is used to reduce fading, for utilization of channel effectively and also transmit diversity is achieved without increase in bandwidth in LTE systems. The simulation results demonstrate that the developed scheduling algorithm provides effective throughput and fairness compared to some of the existing scheduling algorithms in LTE networks.Keywords
Channel Quality Indicator (CQI), Multiple Input Multiple Output (MIMO), Orthogonal Frequency Division Multiple Access (OFDMA), Transmission Time Interval (TTI), User Equipment (UE)- A Stage-by-Stage Pruning Method for Classifying Uncertain Data Streams
Abstract Views :186 |
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Authors
Affiliations
1 Department of Computer Science Engineering, Fatima Michael College of Engineering and Technology, Madurai – 625020, Tamil Nadu, IN
2 Department of Information Technology, K.L.N. College of Information and Technology, Madurai – 630612, Tamil Nadu, IN
1 Department of Computer Science Engineering, Fatima Michael College of Engineering and Technology, Madurai – 625020, Tamil Nadu, IN
2 Department of Information Technology, K.L.N. College of Information and Technology, Madurai – 630612, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 8 (2016), Pagination:Abstract
Background: We study an important problem of similarity grouping processing on stream data that inherently contain uncertainty. Method: In this paper SBSP - [Stage by Stage Pruning] a novel pruning method is proposed for fast, accurate clustering and classifying the data where the two stages were grouped into a single framework MYFRAME. Findings: The proposed approach group the data-by-data level pruning using Manhattan distance in first stage. In the second stage, the data is grouped by object level pruning in hyperspace. Improvements: Currently, this approach is applied in real time applications such as object detection, video retrieval, people detection and tracking, earth quake monitoring etc.Keywords
Clustering, Data Pruning, Distance, Group Nearest Neighbor, Grouping Process, Similarity Search, Uncertain Data Streams- Cumulative Cooperative Spectrum Sensing Scheme to Defend Against Selfish Users
Abstract Views :135 |
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Authors
K. Elangovan
1,
S. Subashini
1
Affiliations
1 VIT University, Chennai - 632014, Tamil Nadu, IN
1 VIT University, Chennai - 632014, Tamil Nadu, IN