Co-operative sensor localization using maximum likelihood estimation algorithm

In wireless sensor networks, self-localizing sensors are required in a wide variety of applications, from environmental monitoring and manufacturing logistics to geographic routing. In sensor networks which measure high-dimensional data, data localization is also a means to visualize the relationships between sensors’ high dimensional data in a low-dimensional display.This thesis considers both to be part of the general problem of estimating the coordinates of networked sensors. Sensor network localization is ‘cooperative’ in the sense that sensors work locally, with neighboring sensors in the network, to measure relative location, and then estimate a global map of the network.The choice of sensor measurement technology plays a major role in the network’s localization accuracy, energy and bandwidth efficiency, and device cost. This thesis considers measurements of time-of-arrival(TOA), received signal strength (RSS), quantized received signal strength (QRSS), and connectivity. I have taken the simulated data taking varity position of the sensor. From these different position the Cram´er-Rao lower bounds on the variance possible from unbiased location estimators are derived and studied. In this CRB calculation I have taken the RSS case only. Maximum Likelihood estimation algorithm is studied and applied for a particular node position

Retournement temporel : application aux réseaux mobiles

This thesis studies the time reversal technique to improve the energy efficiency of future mobile networks and reduce the cost of future mobile devices. Time reversal technique consists in using the time inverse of the propagation channel impulse response (between a transceiver and a receiver) as a prefilter. Such pre-filtered signal is received with a stronger power (this is spatial focusing) and with a strong main echo, relatively to secondary echoes (this is time compression). During a previous learning phase, the transceiver estimates the channel by measuring the pilot signal emitted by the receiver. Space-time focusing is obtained only at the condition that the propagation remains identical between the learning phase and the data transmission phase: this is the ‘channel reciprocity’ condition. Numerous works show that spatial focusing allows for the reduction of the required transmit power for a given target received power, on the one hand, and that time compression allow for the reduction of the required complexity at the receiver side to handle multiple echoes, on the other hand. However, studies on complexity reduction are limited to ultra wideband. Some works of this thesis (based on simulations and experimental measurements) show that, for bands which are more typical for future networks (a carrier frequency of 1GHz and a spectrum of 30 MHz to 100 MHz), thanks to time reversal, a simple receiver and a mono-carrier signal are sufficient to reach high data rates. Moreover, the channel reciprocity condition is not verified in two scenarios which are typical from mobile networks. Firstly, in most European mobile networks, the frequency division duplex mode is used. This mode implies that the transceiver and the receiver communicate on distinct carriers, and therefore through different propagation channels. Secondly, when considering a receiver on a moving connected vehicle, the transceiver and the receiver communicate one with each other at distinct instants, corresponding to distinct positions of the vehicles, and therefore through different propagation channels. Some works of this thesis propose solutions to obtain space-time focusing for these two scenarios. Finally, some works of this thesis explore the combination of time reversal with other recent signal processing techniques (spatial modulation, on the one hand, a new multi-carrier waveform, on the other hand), or new deployment scenarios (millimeter waves and large antenna arrays to interconnect the nodes of an ultra dense network) or new applications (guidance and navigation) which can be envisaged for future mobile networks.Cette thèse étudie la technique dite de ‘Retournement Temporel’ afin d’améliorer l’efficacité énergétique des futurs réseaux mobiles d’une part, et réduire le coût des futurs terminaux mobiles, d’autre part. Le retournement temporel consiste à utiliser l’inverse temporel de la réponse impulsionnelle du canal de propagation entre un émetteur et un récepteur pour préfiltrer l’émission d’un signal de données. Avantageusement, le signal ainsi préfiltré est reçu avec une puissance renforcée (c’est la focalisation spatiale) et un écho principal qui est renforcé par rapport aux échos secondaires (c’est la compression temporelle). Lors d’une étape préalable d’apprentissage, l’émetteur estime le canal en mesurant un signal pilote provenant du récepteur. La focalisation spatiotemporelle n’est obtenue qu’à condition que la propagation demeure identique entre la phase d’apprentissage et la phase de transmission de données : c’est la condition de ‘réciprocité du canal’. De nombreux travaux montrent que la focalisation spatiale permet de réduire la puissance émise nécessaire pour atteindre une puissance cible au récepteur d’une part, et que la compression temporelle permet de réduire la complexité du récepteur nécessaire pour gérer l’effet des échos multiples, d’autre part. Cependant, les études sur la réduction de la complexité du récepteur se limitent à l’ultra large bande. Des travaux de cette thèse (basés sur des simulations et des mesures expérimentales) montrent que pour des bandes de fréquences plus typiques des futurs réseaux mobiles (fréquence porteuse à 1GHz et spectre de 30 MHz à 100 MHz), grâce au retournement temporel, un récepteur simple et un signal monoporteuse suffisent pour atteindre de hauts débits. En outre, la condition de réciprocité du canal n’est pas vérifiée dans deux scénarios typiques des réseaux mobiles. Tout d’abord, dans la plupart des réseaux mobiles européens, le mode de duplex en fréquence est utilisé. Ce mode implique que l’émetteur et le récepteur communiquent l’un avec l’autre sur des fréquences porteuses distinctes, et donc à travers des canaux de propagations différents. De plus, lorsqu’on considère un récepteur sur un véhicule connecté en mouvement, l’émetteur et le récepteur communiquent l’un avec l’autre à des instants distincts, correspondants à des positions distinctes du véhicule, et donc à travers des canaux de propagations différents. Des travaux de cette thèse proposent des solutions pour obtenir la focalisation spatio-temporelle dans ces deux scenarios. Enfin, des travaux de la thèse explorent la combinaison du retournement temporel avec d’autres techniques de traitement de signal récentes (la modulation spatiale, d’une part, et une nouvelle forme d’onde multiporteuse, d’autre part), ou des scenarios de déploiement nouveaux (ondes millimétriques et très grands réseaux d’antennes pour inter-connecter les noeuds d’un réseau ultra dense) ou de nouvelles applications (guidage et navigation) envisageables pour les futurs réseaux mobiles

Spatial diversity in MIMO communication systems with distributed or co-located antennas

The use of multiple antennas in wireless communication systems has gained much attention during the last decade. It was shown that such multiple-input multiple-output (MIMO) systems offer huge advantages over single-antenna systems. Typically, quite restrictive assumptions are made concerning the spacing of the individual antenna elements. On the one hand, it is typically assumed that the antenna elements at transmitter and receiver are co-located, i.e., they belong to some sort of antenna array. On the other hand, it is often assumed that the antenna spacings are sufficiently large, so as to justify the assumption of independent fading. In this thesis, the above assumptions are relaxed. In the first part, it is shown that MIMO systems with distributed antennas and MIMO systems with co-located antennas can be treated in a single, unifying framework. In the second part this fact is utilized, in order to develop appropriate transmit power allocation strategies for co-located and distributed MIMO systems. Finally, the third part focuses on specific synchronization problems that are of interest for distributed MIMO systems

Adaptive power control in CDMA cellular communication systems

Power control is an essential radio resource management method in CDMA cellular communication systems, where co-channel interference is the primary capacity-limiting factor. Power control aims to control the transmission power levels in such a way that acceptable quality of service for the users is guaranteed with lowest possible transmission powers. All users benefit from the minimized interference and the preserved signal qualities. In this thesis new closed loop power control algorithms for CDMA cellular communication systems are proposed. To cope with the random changes of the radio channel and interference, adaptive algorithms are considered that utilize ideas from self-tuning control systems. The inherent loop delay associated with closed loop power control can be included in the design process, and thus alleviated with the proposed methods. Another problem in closed-loop power control is that extensive control signaling consumes radio resources, and thus the control feedback bandwidth must be limited. A new approach to enhance the performance of closed-loop power control in limited-feedback-case is presented, and power control algorithms based on the new approach are proposed. The performances of the proposed algorithms are evaluated through both analysis and computer simulations, and compared with well-known algorithms from the literature. The results indicate that significant performance improvements are achievable with the proposed algorithms.reviewe

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest