In this communication, necessary and sufficient conditions are presented for the unique blind identification of possibly nonminimum phase channels driven by cyclostationary processes. Using a frequencydomain formulation, it is first shown that a channel can be identified by the second-order statistics of the observation if and only if the channel transfer function does not have special uniformly spaced zeros. This condition leads to several necessary and sufficient conditions on the observation spectra and the channel impulse response. Based on the frequency-domain formulation, a new identification algorithm is proposed

Blind channel identification based on second-order statistics: a frequency-domain approach

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Conformal Array Antenna Theory And Design

This paper presents a dual band circular microstrip patch antenna with an elliptical slot for future 5G mobile communication networks. The antenna has resonating frequencies of 28 GHz and 45 GHz, with bandwidths of 1.3 GHz and 1 GHz, respectively. Efficiency of the antenna is 85.6% at 28 GHz and 95.3% at 45 GHz. The return loss at 28 GHz is −40 dB, with maximum gain of 7.6 dB while at 45 GHz return loss is −14 dB with maximum gain of 7.21 dB. The antenna is designed on a Rogers RT5880 (lossy) substrate with dielectric constant of 2.2 and loss tangent (tan δ) of 0.0013. The antenna has a compact size of 6× 6× 0.578 mm3. Array configuration is used to achieve 12 dB gain, required for mobile communication. The proposed array has resonance frequencies of 28 GHz, 34 GHz and 45 GHz with maximum gain of 13.5 dB and radiation efficiency of 98.75%. Centre series fed technique is used for the excitation of array. SAR value of array antenna obtained at 28 GHz is 1.19 W/kg, at 34 GHz is 1.16 W/kg, and at 45 GHz is 1.2 W/kg. CST Microwave Studio, a 3D simulating tool, is used for the antenna design and calculation of the antenna parameters along with the SAR analysis.

https://www.jpier.org/download/18101401.pdf

Elliptical slot circular patch antenna array with dual band behaviour for future 5G mobile communication networks

https://cyberleninka.org/article/n/192835.pdf

Symmetric encryption algorithms using chaotic and non-chaotic generators: A review.

A depth camera-based novel method is proposed here for efficient facial expression recognition. For each pixel in a depth image, eight local directional strengths are obtained and ranked. Once the rank of all pixels is obtained, eight histograms are developed for the eight surrounding directions. The histograms are then concatenated to represent features for a depth image of a face. This approach is named local directional rank histogram pattern (LDRHP). To combine with LDRHP features, one more robust feature extraction technique named local directional strength pattern (LDSP) is proposed. Typical local directional pattern (LDP) considers only absolute values of edge strengths for a pixel. This generalization in LDP may generate the same patterns for two different kinds of edge pixels. LDSP can overcome this problem. It considers the binary values of the position with the directions representing the highest and lowest original strengths. The highest strength indicates the strongest direction on the bright side of a pixel and the lowest one indicates the strongest direction in the dark side of that pixel. Hence, combining binary positions of these two directions can generate more robust patterns than LDP. Besides, LDSP pattern of a pixel is of six bits, whereas traditional LDP-based patterns are of eight bits (e.g., local directional deviation-based pattern and local directional position pattern). Thus, LDSP reduces the dimension of features with the same time adding robustness. For a depth image in a depth video, LDSP features are augmented with LDRHP features followed by Kernel principal component analysis and generalized discriminant analysis to generate more robust features. At last, the features are trained with a deep learning approach and convolutional neural network for successful facial expression recognition. The proposed approach is compared and shown to outperform the traditional expression recognition methods.

Facial Expression Recognition Using Salient Features and Convolutional Neural Network

The wavelet based denoising has proven its ability to denoise the bearing vibration signals by improving the signal-to-noise ratio (SNR) and reducing the root-mean-square error (RMSE). In this paper seven wavelet based denoising schemes have been evaluated based on the performance of the Artificial Neural Network (ANN) and the Support Vector Machine (SVM), for the bearing condition classification. The work consists of two parts, the first part in which a synthetic signal simulating the defective bearing vibration signal with Gaussian noise was subjected to these denoising schemes. The best scheme based on the SNR and the RMSE was identified. In the second part, the vibration signals collected from a customized Rolling Element Bearing (REB) test rig for four bearing conditions were subjected to these denoising schemes. Several time and frequency domain features were extracted from the denoised signals, out of which a few sensitive features were selected using the Fisher's Criterion (FC). Extracted features were used to train and test the ANN and the SVM. The best denoising scheme identified, based on the classification performances of the ANN and the SVM, was found to be the same as the one obtained using the synthetic signal.

/pdf/evaluation-of-effectiveness-of-wavelet-based-denoising-57szl0ma2r.pdf

Evaluation of effectiveness of wavelet based denoising schemes using ANN and SVM for bearing condition classification

In the present scenario, cellular service provider facing bandwidth shortage in conventional cellular system, and delivering high quality, low latency video and multimedia applications using 3G system which is on ground .The 4 Generation cellular networks are expected to be implemented in next few years. Here, we present the motivational approach for millimeter wave mobile communication antenna for nextgeneration microand Pico-cellular wireless Networks (5 generation). The Millimeter Wave mobile communication works on 28 GHz and 38GHz frequency by employing steerable directional antennas (high dimensional antenna array) at base stations and mobile devices [1]. This paper describes a future antenna for 5G mobile communication. This antenna consists of two rectangular patch elements using a single layer RT/Duroid 5880 substrate with transformer coupled impedance matching network, which provides high gain of 9.0583dB and efficiency 83.308%. This antenna has good performance in terms of antenna gain, directivity, return losses, VSWR, Characteristics impedance, Band width and efficiency at the centre frequency 38GHz.

/pdf/millimeter-wave-mobile-communications-microstrip-antenna-for-251rzlqvwx.pdf

Millimeter-Wave Mobile Communications Microstrip Antenna for 5G - A Future Antenna

A sensor network is a system that consists of thousands of very small stations called sensor nodes. The communication among nodes is done in a wireless fashion, and thus, the name of wireless sensor networks. Wireless sensor networks (WSN) have generated tremendous interest among researchers in recent years because of their potential usage in wide variety of applications [1]. In mobile sensor network (MSN), nodes are free to move with wireless links without any infrastructure.This paper investigates & undertakes simulation based study of Adhoc Routing Protocols in wireless sensor Network. In this paper comparison of four Routing Protocols AODV, DYMO, OLSR & IERP is done by using random waypoint mobility model and changing the nodes mobility using QualNet 5.0.2 Simulator. The metrics used for performance evaluation are Average Jitter, Throughput, Endto End delay, Signals received with errors, Average Queue Length, Packets to Application Layer, Total packets Received at the Receiver end.

/pdf/simulation-and-performance-analysis-of-routing-protocols-in-452d1rjtd6.pdf

Simulation and Performance Analysis of Routing Protocols in Wireless Sensor Network using QualNet

Several traditional encryption schemes have been analysed and based on the literature survey, it has been found that chaotic sequences are very much useful to create randomness. In this paper, a new encryption scheme has been proposed with two phases. In the first phase the input image is transformed using a new transformation technique whereas in the second phase .Chirikov Standard Map is used for pixel shuffling and modified Logistic Map is used for diffusion. Chirikov standard map , decor relate the strong relationship among adjacent pixels hence employed to shuffle the pixel positions of the plain image. The modified logistic map is used for generating the random sequence which is completed the purpose of changing pixel values. Various images and standard lena image is used to demonstrate the validity of the proposed algorithm. The results of experiments show that the proposed algorithm for image cryptosystems provides a no correlation between the original image and cipher image. The scheme is key sensitive and shows impressive resistance against brute force attack and statistical attack.

Comparative Image Encryption Method Analysis Using New Transformed - Mapped Technique

Wireless sensor network consists various sensor nodes that are used to monitor any target area like forest fire detection by our army person and monitoring any industrial activity by industry manager. Wireless sensor networks have been deployed in several cities to monitor the concentration of dangerous gases for citizens. In wireless sensor network when sensor nodes communicate from each other then routing protocol are used for communication between protocol layers. Wireless sensor network protocol stack consist five layers such as Application layer, Transport layer, Network layer, MAC Layer, Physical layer. In this paper we study and analysis Bellman-Ford routing algorithm and check the flow of data between these protocol layers. For simulation purpose we are using Qualnet 5.0.2 simulator tool.

http://journal.portalgaruda.org/index.php/EEI/article/download/577/895

Sandip Vijay

Papers

Evaluation of effectiveness of wavelet based denoising schemes using ANN and SVM for bearing condition classification

Millimeter-Wave Mobile Communications Microstrip Antenna for 5G - A Future Antenna

Simulation and Performance Analysis of Routing Protocols in Wireless Sensor Network using QualNet

Comparative Image Encryption Method Analysis Using New Transformed - Mapped Technique

Data Flow in Wireless Sensor Network Protocol Stack by Using Bellman-Ford Routing Algorithm