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.

Enhanced Model for Spectrum Handoff in Cognitive Radio Networks

Abstract: It's a challenging task and important technical issue when it comes to mobility management between multiple wireless technologies among different users. Cognitive Radio Network(CRN)is the solution for utilizing the bandwidth of all spectrums efficiently. The Spectrum is used by the Secondary user(SU) in the absence of Primary user(PU). Secondary user needs to vacate the channel when primary user starts to interrupt as it is the licensed user. To continue the seamless communication secondary user needs to occupy other channel. Multiple Attribute Decision Making (MADM) methods are most appropriate for handoff in CRN. Vlsekriterijumska Optimizacija l KOm- promisno Resenje method (VIKOR) is one of MADM method used for handoff process and is considered better than Simple Additive Weighting (SAW) and Multiplicative Exponent Weighting (MEW). The proposed method has 12% better results than VIKOR in channel selection by means of simulation in MATLAB based on relative standard deviation. Values of attributes within Telecom standards are considered for simulation purpose.

A linear model of call intercepting probability of integrated WLANs in a 3g cell

Abstract: 3G/WLAN integration is thought to be a viable solution for next generation heterogeneous access networks. Estimation of traffic in 3G and WLAN systems is essential to compute the performance of a 3G/WLAN mixed cell. The sharing of calls between 3G and WLAN is dependent on call intercepting (CI) probability of WLAN inside a 3G cell. CI probability is the key parameter for model based analysis of capacity gain and call dropping performance of a mixed cell. Most of the existing models do not derive CI probability. Rather the analysis has been done on the basis of assumed values of CI probability. In this article, we propose an analytical model to derive the CI probability as a function of some realistic cell parameters. The model provides linear changes of CI probability with increasing number of WLAN-hotspots. The model facilitates to represent all WLAN-hotspots by an equivalent single WLAN. Proposed model removes the error in calculating CI probability by 7.6% over existing models. The numerical results are useful to estimate the net traffic in 3G and WLAN systems of mixed cell.

Dynamic Weight Assignment based Vertical Handoff Algorithm for Load Optimization

Abstract: Objectives: Consolidating any two dissimilar networks leads to a formation of a heterogeneous wireless network. Vision to achieve distinct networks to get converged such that characterizing of the upcoming wireless networks becomes a reality. This in turn ushers in vertical handoff such that handoff among different technologies is efficient. And at the same time it is so smooth that naming it as seamless is justifiable. Pragmatic consideration of the network characteristics and the dynamics are very essential to choose one of the best available network handoff decisions. Methods: Stating conventionally, when a mobile client is roaming, a single criterion- for example, received signal strength is employed to realize the vertical handoff. But, single criterion consideration is not sufficient and taking into account of other parameters is needed for a proper handoff decision. The present paper puts forth a strong load balancing algorithm M-OPTF that is based on dynamic weight assignment technique for allocation of fresh calls and handoff calls. Findings: In the present scheme assignment of weight factor is done to attachment points basing on the distribution of load on them. In addition it contains a process for handoff decision that takes into account the velocity of mobile node to do triggering of handoff. The put forth M-OPTF algorithm is compared along with Remote Sensing Systems (RSS) and OPT-F algorithm in this paper. Application/Improvements: The simulation results confirm the fact that M-OPTF algorithm apart from balancing the network load it can effectively decrease congestion in network, reduce the number of handoffs that are unnecessary, and increases the battery life time, thus improve the overall performance of the system.

IEEE Standard for Local and Metropolitan Area Networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems Draft Amendment: Management Information Base Extensions

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.

Adversarial Attacks in Modulation Recognition With Convolutional Neural Networks

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.

Structural health monitoring of civil engineering structures by using the internet of things: A review

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.