Sharif Digital Repository

The emerging field of compressed sensing deals with the techniques of combining the two blocks of sampling and compression into a single unit without compromising the performance. Clearly, this is not feasible for any general signal; however, if we restrict the signal to be sparse, it becomes possible. There are two main challenges in compressed sensing, namely the sampling process and the reconstruction methods. In this thesis, we will focus only on the deterministic sampling process as opposed to the random sampling. The sampling methods discussed in the literature are mainly linear, i.e., a matrix is used as the sampling operator. Here, we first consider linear sampling methods and... 

Digital images degrade during transmittion via noisy channels. The goal of this thesis is to propose new methods for image recovery from random and block losses In the first part of the thesis, various techniques for image recovery from random losses will be reviewd and then a method will be proposed based on the correlation among image pixels in the spatial domain. The method is fast, efficient and robust against Gaussian noise. Also a technique will be developed for quality estimation in the recipient. The second part of the thesis devotes image recovery from block losses. After a brief survey for image inpainting techniques we intoduce the concept of image reconstruction using the... 

The two central topics of information theory are the compression and the transmission of data. Shannon, in his seminal work, formalized both these problems and determined their fundamental limits. Since then the main goal of coding theory has been to find practical schemes that approach these limits.Polar codes, recently invented by Arıkan, are the first practical codes that are known to achieve the capacity for a large class of channels. Their code construction is based on a phenomenon called “channel polarization”.
Since the performance of polar code degrades when the block length is small, several kinds of Reed – Solomon concatenation is considered in order to improve the... 

This thesis is dedicated to examine performance of compressive sensing based MIMO radar systems. MIMO radars have the ability to achieve higher target detection and parameter estimation as well as better performance in noisy and clutter environments than SISO or phased array radars. The need for high-speed analog to digital converters is one of the weaknesses in implementation of radar systems. With the advent of compressive sensing providing necessary guarantees for reconstruction of sparse signal using fewer samples than what Nyquist thorem describes, the need for such a high-speed converters that are either not available or too expensive is resolved. What allowes us to use compressive... 

There is a vast amount of publications in the literature on various types of tampering detection. In this thesis, we propose two methods for tampering detection and recovery of speech signals with WAV format. Due to redundancy of speech signals, the watermarking technique is utilized for this purpose. In embedder side,the watermark is generated using a similar version of the original signal. In first method, watermark is generated by the downsampled signal. Output of hash generator and some framing headers are used to detect the tampered region automatically. In second method, The original signal is compressed using a source encoder. The output is then packetized to detect the tampered... 

Cognitive radio (CR) can successfully deal with the growing demand and scarcity of the wireless spectrum. To exploit limited spectrum efficiently, CR technology allows unlicensed users to access licensed spectrum bands. Since licensed users have priorities to use the bands, the unlicensed users need to continuously monitor the licensed users activities to avoid interference and collisions. How to obtain reliable results of the licensed users activities is the main task for spectrum sensing. Based on the sensing results, the unlicensed users should adapt their transmit powers and access strategies to protect the licensed communications. The requirement naturally presents challenges to the... 

In  this  dissertation,  we  investigate  the  frequency  hopped  spread  spectrum  systems  which are extensively used in many communication systems. We derive the capacity region  of  Synchronous  Frequency  Hopped  Multiple  Access  (FHMA)  channels  (for  any  kind of noisy or nonselective fading environment) by using the side information which exists in the multi‐user detection. We assume that random hopping patterns are used by all the transmitters, and the common receiver knows the hopping patterns. We also compute  the  capacities  of  FHMA  with  and  without  power  control  for  AWGN  and  noiseless MFSK (in particular BFSK) modulated systems and compare the ... 

The main purpose of the thesis is Digital image Processing using the sparsity of image. The issue could be described in two ways. First is reconstruction of missed blocks of an image based on the sparsity of image in the transform domain and second is impulsive noise removal using the sparsity of noise in the spatial domain. In the first approach we will review Guleryuz method and simulate and analyze it. In the second approach, two new methods named RDE and Knockout will be introduced. These methods try two remove the impulsive noise of an image using its sparseness. RDE method is a development of conventional methods, but Knockout has a completely new idea. We will show that Knockout is... 

Sensor Networks are set of devices which are distributed throughout an environment and are connected to each other, usually wirelessly, to collect environmental information including temperature, aire pressure, moist, pollution and physiological functions of the human body. Each device consists of a microprocessor, converter and power supply, transmitter and a receiver. In this study we intend to investigate such setup and the measured signals assuming they are sparse. A sparse signal is a discrete time signal most of indices of which are equal to zero. With this assumption at hand, we will be able to reduce the sampling rate and take advantage of sparse signal processing techniques. This... 

Direction Of Arrival (DOA) estimation or direction finding refers to determining the arrival angle of a planar wave impinging on the array of sensors or antennas. The DOA information can be used by the smart antenna system for beam-forming and reliable data transmission. The problem of DOA estimation in propagating plane waves played a fundamental role in many applications including acoustic, wireless communication systems, navigation, biomedical imaging, radar/sonar systems, seismic sensing, and wireless 911 emergency call locating. In the conventional DOA estimating systems, an array of elements (antennas or sensors) is used that are colocated in a uniform pattern called, Uniform Linear... 

CDMA is one of the main multiple access techniques. The aim of this work is to propose optimum signature codes to improve the performance of such systems. First, we introduce criteria such as Sum Channel Capacity and Bit Error Rate (BER) to measure the performance of a CDMA system. Also a set of measures named as Distance criteria are proposed to reduce the computational complexity. Various optimization methods are used to optimize these criteria such as Genetic Algorithms and the Particle Swarm Optimization techniques. Then, several sub-optimum signature matrices are derived based on different factors and criteria to improve the performance of Overloaded CDMA systems in terms of the sum... 

Converting analog signal to digital one is one of the most important issues in signal processing which can be done by using analog to digital converter (A/D). In the first part of this thesis, sigma delta converters based on minimum support filter are investigated. Then, we will show that iterative algorithm can be used in order to improve the performance of the overall system significantly. Asynchronous converters can be utilized for the sake of decreasing power in the process of analog to digital converting. In these converters, a few numbers of samples will be taken from the regions which signal has high autocorrelation. In other words, samples in the asynchronous converters have more... 

The emerging field of compressed sensing has found wide-spread applications in signal processing. Exploiting the sparsity of natural image signals on basis of a set of atoms called dictionary, one can find numerous examples for applications of compressed sensing in the field of image processing. One of these interesting applications is to help recover missing samples of a damaged or lossy image signal which is also known as image inpainting. There are dozens of reasons why an image may get damaged, for instance, during data transmission, some blocks of an image (or frames of a video ) may get lost due to error in the telecommunication channel (this is known as block-loss). In this case image... 

One of the most effective and robust algorithms in watermarking are additive and multiplicative methods. Although the detector of additive watermarking methods are easier than the multiplicative one, they do not gain from human visual or auditory systems. This is the main drawback of additive watermarking techniques. On the other hand, the most advantage of multiplicative watermarking methods is that the power of the watermark is proportional to the power of the host signal. In this thesis, we have introduced a new multiplicative watermarking technique for audio and image signals. For the audio signal, the embedding is performed on the wavelet coefficients. We used Maximum likelihood rule... 

Direction of arrival (DOA) estimation has various applications in different areas such as wireless communication and signal processing in medical applications. Most of the previous methods were not based on digitalization, but the advantages of digitalized methods have been proved in recent decades. Furthermore, because of existing the phase error, we need to use the algorithms to find the solution with amplitude measurements. A solution method to this problem was introduced in 2015 for the first time, and then newer algorithms were proposed. However, most of them need reference signals to resolve the inherent ambiguity of the problem. By contrast, this dissertation not only does not use... 

In this thesis, some algorithms for PAPR reduction of OFDM systems are investigated and some of these methods are extended to MIMO-OFDM systems. Two types of multiple antenna OFDM systems are considered; OFDM systems with spatial multiplexing for increasing the data rate and OFDM systems with spatial diversity for improvement of the symbol error rate. For the systems of the first type we have proposed two PAPR reduction algorithms. In the first method, the signals of transmitter antennas are clipped and filtered independently. Then, at the receiver side an iterative algorithm is proposed to compensate for the clipping noise. In the second method, we have extended TR method to spatial... 

High peak to average power ratio (PAPR) is one major drawback of OFDM system which highly affects the performance if untreated. Several methods have been proposed to overcome this problem. In all these methods reduction in PAPR is gained through a tradeoff with another system figure such as mean transmit power, bandwidth or BER. In this thesis we investigate high PAPR problem in OFDM, and we will introduce some methods proposed to alleviate it. These methods are divided into two classes; methods in the first class are based on finding a peak cancelling signal and methods in second class rely on solving a discrete optimization problem. We give a general formulaion for the methods in second... 

In modern wireless mobile telephony networks, DS-CDMA based physical layers has gained much attention due to their ease of implementation at relatively low overall cost, ability to provide high speed data services, increased user capacity, and many other outstanding features. One of the challenges facing these systems is the synchronization of the users’ signature codes (received via communication channel) to the receiver’s locally generated replica, as the only distinguishing feature between users in such systems is the pseudo-orthogonal properties of these signature codes. To fully utilize this orthogonality, all sequences need to have a common time reference. But when relative sequence... 

Considering the tremendous development in imaging systems’ industry, today we can afford to have imaging equipment, capable of taking multispectral images in very high resolution. One of the remarkable benefits of this technology is in the realm of arts and particularly in museums. Taking advantage of the potentials of multispectral, highquality imaging, curators will be able to probe their priceless works of art ( e.g. paintings ) without putting them in danger through invasive research. Besides, one can investigate and control the transformation of these works through time by using this new imaging method. Recently, Multispectral Imaging of paintings, in different frequency bands from... 

Super-resolution means increasing the resolution so that the quality improves. This is defined for both image and video. In this regard, machine-learning based methods, especially convolutional neural networks, have shown great potential in recent years. Finding the right structure that can deliver high speed and accuracy is the key to solving the super-resolution problem.Despite the myriad of methods for image super-resolution, less attention has been paid to its generalization to video. This generalization should be such that more detail is created in the output using adjacent frames.In this dissertation, the existing methods for image and video super-resolution are reviewed, and then a...