Wireless Channel Models for Indoor Environments

Wireless networks have made significant advancement in recent times by adding a new dimension to theway people communicate. Development of wireless standards have constantly aimed at providing higher datarates even under complex environments using smart antennas, multiple-input, and multiple-output systems.This has necessitated an understanding of the indoor propagation channel. Channel models describe acommunication channel and are essential in developing efficient wireless communication networks. This papersurveys different channel models used to characterise wireless indoor environment. This survey may be usefulfor the army, where the communication over wide areas during wargames that they hold periodically, isnecessary. Moreover, it may also be useful for communication near the border areas for surveillance operations.Defence Science Journal, 2008, 58(6), pp.771-777, DOI:http://dx.doi.org/10.14429/dsj.58.170

Secondary Injection Thrust Vector Control Power Plant Linearisation using Fuzzy Logic for a Launch Vehicle

Control forces are required for steering a launch vehicle to guide it to follow an optimal trajectory. Launch vehicle control involves two control loops, the inner loop deals with short-period dynamics, stability and the outer loop, known as the guidance loop, optimises the trajectory. The general nonlinear plant model is first approximated as a linear time-varying plant over a nominal trajectory and then segmented as linear, time-invariant plant models at different time intervals. A major part of the plant model is the control power plant, which for a secondary injection thrust vector control system used for the solid booster stage of a launch vehicle is nonlinear due to various reasons. The controllers designed for different time regimes assume the control power plant as linear and are adapted smoothly by a technique called gain scheduling to cope with the plant model changes wrt time. In this paper, a fuzzy logic-based pre-compensator is developed to linearise the control power plant so that the controller design becomes valid. Simulation results are presented to validate the design and a novel preprocessing technique is developed to reduce the size of the fuzzy inference system

Punctured Turbo Codes for Bandwidth-efficient Transmission

Turbo codes are the error-coding schemes applied nowadays in wireless networks. In navalapplications, the information is mostly sent through wireless networks and the data is moreprone to noise. Since very important data has to be communicated, it is necessary to get backthe original data in the receiver. In military applications also, the soldiers wear electronic jacketswhich are connected by wireless networks. In such applications, the data loss is not affordableand there is also a need to utilise the bandwidth efficiently through puncturing by means ofwhich certain bits are deleted before transmission from the output of encoder. By means of thispunctured turbo codes, bandwidth-efficient coding is achieved. Hence, it is necessary to designturbo codes with an efficient puncturing pattern so that the performance of the punctured codeis also improved in spite of deletion of few bits before transmission. This paper deals in choosingthe puncturing patterns that lead to systematic rate-compatible punctured turbo codes (RCPTCs)which also give a reduction in bit-error rate. The design criterion for choosing the best puncturingpatterns is based on the minimum weight of code words and their multiplicities. The best puncturingpattern chosen is tested for its performance by simulating turbo codes for an additive whiteGaussian noise (AWGN ) channel. Compared with the existing puncturing pattern, the patternproposed is able to achieve a gain of 0.5 dB at a bit-error rate of 10-3

Video denoising without motion estimation using K-means clustering

251-255This study presents a novel dictionary pruning algorithm that found dictionaries of optimized size for a given dataset, without compromising its approximation accuracy and performance. It is achieved by applying KSVD (K-means singular value decomposition) algorithm to patches of dictionary. Proposed method optimized dictionary selection, and with KSVD yielded better video denoising than KSVD with fixed dictionary

Wavelet Based Contourlet Transform for Image Compression

Wavelet transforms are not capable of reconstructing curved images perfectly, hence we go for this new concept, called Contourlet Transform. It is a multiresolution and directional decomposition of a signal using a combination of Laplacian Pyramid (LP) and a Directional Filter Bank (DFB). The Contourlet transform has good approximation properties for smooth 2D functions and finds a direct discrete-space construction, and is therefore computationally efficient. Recently introduced the wavelet-based contourlet transform (WBCT), it is a non-redundant version of the contourlet transform, and appropriately used this transform for image coding. In this work, we start with a discretedomain construction and then investigate its convergence to an expansion in the continuous-domain. This construction results in a flexible multiresolution, local, and directional image expansion using contour segments, and thus it is named the contourlet transform. Furthermore, a precise link between the developed filter bank and the associated continuous – domain contourlet expansion via a directional multiresolution analysis framework is established. Our simulation results also show that this new coding approach is competitive to the wavelet coder and is visually superior to the wavelet coder for the mentioned images. The original Contourlet Transform has high redundancy, in order to reduce that we have used wavelet transform followed by Directional Filter Bank

Investigation and correction of error in impedance tube using intelligent techniques

AbstractErrors arise in the measurement of sound absorption coefficient using impedance tube due to various factors. Minimizing the errors require additional hardware or proper calibration of certain components. This paper proposes a new intelligent error correction mechanism using mathematical modelling and soft computing paradigms. A low cost impedance tube is designed, developed and its performance is compared with a commercially available standard tube. A particle swarm optimization and neural network based system is developed to reduce the random and systematic errors in the developed impedance tube. The proposed system is tested using various porous and non-porous functional textile materials and the results are validated. A significant reduction in error is obtained at all frequency ranges with PSO based prediction method

QoS cross layer architecture with adaptive enhanced distributed channel access for efficient video transmission

783-785This paper addresses transmission of H.264 video over IEEE 802.11e based WLAN by proposing an enhanced QoS cross layer architecture with Adaptive Enhanced Distributed Channel Access (AEDCA) mechanism. Proposed architecture minimizes mean packet loss and end-to-end delays over existing EDCA and AEDCA mechanisms