Self generating square/triangular wave and pulse width modulator using a single MO-CCCDTA

A self-generating square/triangular wave and pulse width modulator (PWM) using multiple output current controlled current differencing transconductance amplifier (MO-CCCDTA) is presented. To obtain all the three functions simultaneously from the same topology, the MO-CCCDTA is modified a little bit. The characterisation of the modified MO-CCCDTA structure shows that the parasitic resistances at input terminals (n and p) can be varied via bias current. The maximum useful frequency range is found to be 635 MHz, which is higher than the available literature. The waveform generator and PWM circuit use only one MO-CCCDTA, one grounded capacitor and no resistor; hence suitable for IC implementation. The duty cycle of proposed pulse width modulation can be tuned by bias current of MO-CCCDTA over a wide range. The performances of the proposed block and its applications (square/triangular/PWM) are verified by PSPICE simulation using TSMC 0.35 µm technology. The power consumption is about 1.12 mW. To verify experimentally, a prototype of MO-CCCDTA has been made using commercially available ICs (AD844AN and CA3080) on printed circuit board. The simulation and experimental results verify theoretical proposition well. Monte carlo simulation is carried out, which proves satisfactory performance of the proposed circuit against mismatches. The performance of the proposed circuit is also verified through pre-layout and post-layout simulation results. The required chip area is only 22.415 × 14.6 µm².     

60 GHz indoor WLANs: insights into performance and power consumption

This paper presents a feasibility study of 60 GHz indoor WLANs. We evaluate 60 GHz performance in a typical academic office building under the primary assumption that 60 GHz WLAN APs and clients will be equipped with relatively wide-beam antennas to cope with client mobility. In contrast to previous works which measured performance at a single layer using custom, non-standard compliant hardware, we investigate performance across multiple layers using primarily 802.11ad-compliant wide-beam COTS devices. Our study shows that the large number of reflective surfaces in typical indoor WLAN environments combined with wider beams makes performance highly unpredictable and invalidates several assumptions that hold true in static, narrow-beam, Line-Of-Sight scenarios. Additionally, we present the first measurements, to our best knowledge, of power consumption of an 802.11ad NIC and examine the impact of a number of factors on power consumption.     

Machine Learning Based Resource Utilization and Pre-estimation for Network on Chip (NoC) Communication

Network on chip (NoC) is the solution to solve the problem of larger system on chip and bus based communication system. NoC provides scalable, highly reliable and modular approach for on chip communication and related problems. The wireless communication technologies such as IEEE 802.15.4 Zigbee technology follow mesh, star and cluster tree topology. The paper focuses on the development of machine learning model for design and FPGA synthesis of mesh, ring and fat tree NoC for different cluster size (N = 2, 4, 8, 16, 32, 64, 128 and 256). The fat-tree based topologies incorporate more links near the root of the tree, in order to fulfill the requirement for higher communication demand closer to the root of the tree, as compared to its leafs. It is an indirect topology in which not all routers are identical in terms of number of ports connecting to other routers or elements in the network. The research article presents the use of machine learning techniques to predict the FPGA resource utilization for NoC in advance. The present study helps in NoC chip planning before designing the chip itself by taking into account known hardware design parameters, memory utilization and timing parameters such as minimum and maximum period, frequency support etc. The machine learning is carried out based on multiple linear regression, decision tree regression and random forest regression which estimate the accuracy of the design and good performance. The interprocess communication among nodes is verified using Virtex-5 FPGA, in which data flows in packets and can vary up to ‘n’ bit. The designs are developed in Xilinx ISE 14.2 and simulated in Modelsim 10.1b with the help of VHDL programming language. The developed model has been validated and has performed well on independent test data.     

Fabrication of a <Emphasis Type="Italic">p</Emphasis>–<Emphasis Type="Italic">n</Emphasis> Heterojunction Using Topological Insulator Bi<Subscript>2</Subscript>Te<Subscript>3</Subscript>–Si and Its Annealing Response

A junction device has been fabricated by growing p-type Bi₂Te₃ topological insulator (TI) film on an n-type silicon (Si) substrate using a thermal evaporation technique. Annealing using different temperatures and durations was employed to improve the quality of the film, as confirmed by microstructural study using x-ray diffraction (XRD) analysis and atomic force microscopy (AFM). The p–n diode characteristics of the junction devices were studied, and the effect of annealing investigated. An improved diode characteristic with good rectification ratio (RR) was observed for devices annealed for longer duration. Reduction in the leakage or reverse saturation current (\( I_{\rm{R}} \)) was observed with increase in the annealing temperature. The forward-bias current (\( I_{\rm{F}} \)) dropped in devices annealed above 400°C. The best results were observed for the sample device annealed at 450°C for 3 h, showing figure of merit (FOM) of 0.621 with RR ≈ 504 and \( I_{\rm{R}} \) = 0.25 μA. In terms of ideality factor, the sample device annealed at 550°C for 2 h was found to be the best with \( n \) = 6.5, RR ≈ 52.4, \( I_{\rm{R}} \) = 0.61 μA, and FOM = 0.358. The majority-carrier density \( \left( {N_{\rm{A}} } \right) \) in the p-Bi₂Te₃ film of the heterojunction was found to be on the order of 10⁹/cm³ to 10¹¹/cm³, quite close to its intrinsic carrier concentration. These results are significant for fundamental understanding of device applications of TI materials as well as future applications in solar cells.     

Energy balanced data gathering approaches,issues and research directions

Telecommunication Systems - Wireless sensor networks (WSNs) and Internet of Things domain comprise of numerous small sized battery powered sensor nodes. Energy efficiency and energy balancing are...     

Opposition Based Artificial Flora Algorithm for Load Balancing in LTE Network

In recent years, telecommunication is progressed due to the development of Long-Term Evolution (LTE) standards. This LTE network provides high-speed wireless communication for mobile devices and satisfies the requirements of customers from multi-cells. However, due to the congestion of mobile devices, each cell in the network may get overloaded. So, load balancing is the main challenge to the LTE network for reducing congestion or load in the cell. For load balancing, the optimal cell selection method is presented in this paper. Initially, the load factor of each cell is estimated. Then the load factor is compared with the predefined threshold load value. After the comparison, the heavy loaded cell handover the users to the optimal cell or cell with minimum load. This optimal cell is selected with the Opposition Based Artificial Flora (OAF) algorithm. Simulation results show that the proposed approach decreases 6% of the call blocking ratio (CBR) and 14% of Call Dropping Ratio (CDR) than the previous approaches.

     

An Effective Traceback Network Attack Procedure for Source Address Verification

Wireless Personal Communications - The Internet is being extensively used in various fields to serve billions of users, which leads to the number of network security issues. Here, Internet Protocol...     

TD‐CFIE Formulation for Transient Electromagnetic Scattering from 3‐D Dielectric Objects

In this paper, we present a time domain combined field integral equation formulation (TD‐CFIE) to analyze the transient electromagnetic response from dielectric objects. The solution method is based on the method of moments which involves separate spatial and temporal testing procedures. A set of the RWG functions is used for spatial expansion of the equivalent electric and magnetic current densities, and a combination of RWG and its orthogonal component is used for spatial testing. The time domain unknowns are approximated by a set of orthonormal basis functions derived from the Laguerre polynomials. These basis functions are also used for temporal testing. Use of this temporal expansion function characterizing the time variable makes it possible to handle the time derivative terms in the integral equation and decouples the space‐time continuum in an analytic fashion. Numerical results computed by the proposed formulation are compared with the solutions of the frequency domain combined field integral equation.     

Performance analysis of wave atom transform in texture classification

Texture classification is an important application in image processing and pattern recognition such as detection of defects on the materials and diseases from the medical images. This paper presents the performance of wave atom transform on texture classification. Wave atom transform is a new multi-resolution technique that not only captures the coherence of the pattern along the oscillations, but also the pattern across the oscillations. The classification is done using a wave atom–transformed features reduced by singular value decomposition and a support vector machine. Experimental results are presented to demonstrate the effectiveness of this approach on Brodatz database, Alzheimer’s Disease Neuro Imaging database for Alzheimer’s disease classification and liver computed tomography images for tumor classification. The experimental results demonstrate that the proposed approach gives a percent correct classification of 97.29 % on Brodatz database, classification accuracy of 94 % on Alzheimer’s Disease Neuro Imaging database for Alzheimer’s disease diagnosis and 93.3 % on liver computed tomography images for tumor classification.     

SCT Based Adaptive Data Aggregation for Wireless Sensor Networks

Communication overhead is a major concern in wireless sensor networks because of inherent behavior of resource constrained sensors. To degrade the communication overhead, a technique called data aggregation is employed. The data aggregation results are used to make crucial decisions. Certain applications apply approximate data aggregation in order to reduce communication overhead and energy levels. Specifically, we propose a technique called semantic correlation tree, which divides a sensor network into ring-like structure. Each ring in sensor network is divided into sectors, and each sector consists of collection of sensor nodes. For each sector, there will be a sector head that is aggregator node, the aggregation will be performed at sector head and determines data association on each sector head to approximate data on sink node. We propose a doorway algorithm to approximate the sensor node readings in sector head instead of sending all sensed data. The main idea of doorway algorithm is to reduce the congestion and also the communication cost among sensor nodes and sector head. This novel approach will avoid congestion by controlling the size of the queue and marking packets. Specifically, we propose a local estimation model to generate a new sensor reading from historic data. The sensor node sends each one of its parameter to sector head, instead of raw data. The doorway algorithm is utilized to approximate data with minimum and maximum bound value. This novel approach, aggregate the data approximately and efficiently with limited energy. The results demonstrate accuracy and efficiency improvement in data aggregation.