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S. Nandakumar

Bio: S. Nandakumar is an academic researcher from VIT University. The author has contributed to research in topics: Handover & Cognitive radio. The author has an hindex of 6, co-authored 22 publications receiving 92 citations.

Papers
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Journal ArticleDOI
TL;DR: The novel method of IWO algorithm for decision making during Vertical Handoff is brought out and the proposed VHO decision making algorithm is compared with the existing SSF and OPTG methods.

12 citations

Proceedings ArticleDOI
04 May 2018
TL;DR: A particular weight have been designated to each CR participating in the process to classify according to reliability so as to facilitate the eradication of issues faced by individual CRs in precise spectrum sensing.
Abstract: We know that there is an issue for spectrum resources being unavailable because of increasing wireless services. To solve this a newer intelligent technology have been developed called as Cognitive Radio (CR). This technology inculcates the use of spectrum holes that occur due to the underutilization of the licensed spectrum. The identification of the spectrum holes can be done by using a method known as spectrum sensing. There are a variety of issues faced by individual CRs in precise spectrum sensing such as hidden terminal problem, shadowing and multipath fading. In order to facilitate the eradication of these issues a newer design of cooperative spectrum sensing have been developed called as Cooperative Spectrum Sensing (CSS). In this a particular weight have been designated to each CR participating in the process to classify according to reliability. Instead of using the conventional threshold equation an adaptive threshold equation have been devised for the initial energy detection algorithm and utilizing the adaptive threshold equation we have designed our algorithm

11 citations

Journal ArticleDOI
TL;DR: A power distribution method based on NASH bargaining solutions is proposed to efficiently use the nodes with the least available to significantly improve the energy efficiency, network life time and throughput rate.

10 citations

Journal ArticleDOI
TL;DR: An efficient handoff scheme for cognitive radio networks using hybrid priority queuing model with discretion rule has been proposed using discretion rule and the normalized load, arrival rate and the service time of this model is compared to the existing models with respect to the average data delivery time of the users.
Abstract: Cognitive radio networks can achieve high spectrum efficiency through dynamic spectrum allocation to the secondary users (SU) by way of using primary user (PU) spectrum. An efficient handoff scheme for cognitive radio networks using hybrid priority queuing model has been proposed using discretion rule. This method is divided into two parts: (1) hybrid priority queuing model with discretion rule is proposed by prioritizing the secondary users in the channel and then calculate the waiting time during the spectrum handoff and (2) to obtain better efficiency by reducing the waiting time, the learning rate of the secondary users from the other users should be increased. This can be done with multi teacher apprentice learning (MAL) along with sparse regression by considering multiple users into consideration at a time instead of a single user for better efficiency of the spectrum. The normalized load, arrival rate and the service time of the proposed model is compared to the existing models with respect to the average data delivery time of the users.

9 citations

Journal ArticleDOI
TL;DR: In the case of streaming class of network traffic, the proposed method improves the performance of the system and reduces the handover by 13.14%, 19.35% and 8.62% of RAT modifications for TOPSIS, PROMETHEE and SAW respectively.
Abstract: Traditional multi-criteria decision making (MCDM) algorithms are used in the handover of user equipment (UE) in an Ultra Dense Network (UDN). UDN refers to the increased density of the Radio Access Technologies (RATs) in a region which leads to the overlapping of the areas covered by individual RATs. MCDM algorithms such as TOPSIS, PROMETHEE and SAW are used to initiate handovers between these RATs based on the parameters obtained by the UE from each of the overlapping networks. However, initiating a handover abruptly and frequently, in case of availability of a new RAT without any thresholding technique proves to be unfriendly to the system resources. This can degrade the performance of the system. In this paper, a thresholding approach to the handover procedure is integrated to the MCDM process for the selection of RATs. First, an application-specific approach has been used in the selection of weights using the analytical hierarchy process which, is depending upon the application being used by the user. Then the ranking of the available RATs is done using the various MCDM algorithms and depending on the threshold specified for a handover, a decision is made whether to perform the handover process or not. In the case of streaming class of network traffic, the proposed method improves the performance of the system and reduces the handover by 13.14%, 19.35% and 8.62% of RAT modifications for TOPSIS, PROMETHEE and SAW respectively.

7 citations


Cited by
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01 Jan 2007
TL;DR: In this paper, the authors provide updates to IEEE 802.16's MIB for the MAC, PHY and asso-ciated management procedures in order to accommodate recent extensions to the standard.
Abstract: This document provides updates to IEEE Std 802.16's MIB for the MAC, PHY and asso- ciated management procedures in order to accommodate recent extensions to the standard.

1,481 citations

Journal ArticleDOI
TL;DR: The experimental results show that the EIWO algorithm can find equal or better optimal solution compared with other algorithms, and the convergence ability, stability and robustness are verified.

92 citations

Journal ArticleDOI
Yun Lin1, Haojun Zhao1, Xuefei Ma1, Ya Tu1, Meiyu Wang1 
TL;DR: The results indicate that the accuracy of the target model reduce significantly by adversarial attacks, when the perturbation factor is 0.001, and iterative methods show greater attack performances than that of one-step method.
Abstract: Deep learning (DL) models are vulnerable to adversarial attacks, by adding a subtle perturbation which is imperceptible to the human eye, a convolutional neural network (CNN) can lead to erroneous results, which greatly reduces the reliability and security of the DL tasks. Considering the wide application of modulation recognition in the communication field and the rapid development of DL, by adding a well-designed adversarial perturbation to the input signal, this article explores the performance of attack methods on modulation recognition, measures the effectiveness of adversarial attacks on signals, and provides the empirical evaluation of the reliabilities of CNNs. The results indicate that the accuracy of the target model reduce significantly by adversarial attacks, when the perturbation factor is 0.001, the accuracy of the model could drop by about 50 ${\%}$ on average. Among them, iterative methods show greater attack performances than that of one-step method. In addition, the consistency of the waveform before and after the perturbation is examined, to consider whether the added adversarial examples are small enough (i.e., hard to distinguish by human eyes). This article also aims at inspiring researchers to further promote the CNNs reliabilities against adversarial attacks.

89 citations

Journal ArticleDOI
TL;DR: In this paper , the authors summarized the applications of the wireless IoT technology in the monitoring of civil engineering infrastructure and discussed several case studies on real structures and laboratory investigations for monitoring the structural health of real-world constructions.
Abstract: Structural health monitoring (SHM) and damage assessment of civil engineering infrastructure are complex tasks. Structural health and strength of structures are influenced by various factors, such as the material production stage, transportation, placement, workmanship, formwork removal, and concrete curing. Technological advancements and the widespread availability of Wi-Fi networks has resulted in SHM shifting from traditional wire-based methods to Internet of Things (IoT)-based real-time wireless sensors. Comprehensive structural health assessment can be performed through the efficient use of real-time test data on structures obtained from various types of IoT sensors, which monitor several health parameters of structures, available on cloud-based data storage systems. The sensor data may be subsequently used for various applications, such as forecasting masonry construction deterioration, predicting the early-stage compressive strength of concrete, forecasting the optimum time for the removal of formwork, vibration and curing quality control, crack detection in buildings, pothole detection on roads, determination of the construction quality, corrosion diagnosis, identification of various damage typologies and seismic vulnerability assessment. This review paper summarizes the applications of the wireless IoT technology in the monitoring of civil engineering infrastructure. In addition, several case studies on real structures and laboratory investigations for monitoring the structural health of civil engineering constructions are discussed.

76 citations

Journal ArticleDOI
01 May 2022-Heliyon
TL;DR: A thorough review of state-of-the-art and classical strategies for PID controller parameters tuning using metaheuristic algorithms can be found in this article , where the primary objectives of PID control parameters are to achieve minimal overshoot in steady state response and lesser settling time.

62 citations