Sowmya Nistala ¹, S. Subashini ¹

Affiliations
1 Department SENSE, VIT University, Chennai – 632014, Tamil Nadu, IN

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)

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S. Subashini ¹, S. Appavu alias Balamurugan ²

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

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

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K. Elangovan ¹, S. Subashini ¹

Affiliations
1 VIT University, Chennai - 632014, Tamil Nadu, IN

Abstract

Background/Objectives: This paper considers combatting the jamming and selfish attacks in Cognitive Radio (CR) networks operating at the white (unused) and grey (underused) spaces in the RF spectrum. CR facilitates effective utilization of RF spectrum resources but still vulnerable to various network attacks. Methods/Statistical Analysis: This study considered the jamming and selfish type of attack detection and to defend against them because of its severity. An Intrusion Detection System (IDS) is formed to combat the against jamming and selfish type of attacks in CR. Findings: In this system cumulative-sum algorithm is used, which incorpates the control centre information over the channel. The cumulative-sum based algorithm shows improved performance in provisioning better packet delivery ratio, throughput and minimum energy and packet drop. Further, this algorithms works better for more number of Secondary Users (SU), and the Unlicensed Users. Applications/Improvements: This work can be enhanced further by simulating under various network attacks and in the presence of numerous SU.

Keywords

Cognitive Radio, Jamming Attacks, Network Security,Selfish Attacks, Secure Spectrum Sensing

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