Sharif Digital Repository

CDMA is one of the main multiple access techniques. In this thesis, we study the channel capacity and the optimum codes for CDMA systems under different conditions. The optimality has different meaning for each studied scenario. The discussed scenarios differ from the aspects of the alphabet of the system, the ability of getting active or inactive for users, and the random fluctuation of the user powers. The first scenario is the systems with real input alphabet. In this case, by optimum codes, we mean a code that maximizes the sum channel capacity of the system. The second scenario is the systems with binary input alphabets and binary signatures. In this section, optimum codes are the codes... 

In this thesis, we aim to explore the recovery of sparse signals from their compressive or random samples. At first, the Compressed Sensing (CS) recovery is considered and an iterative method with adaptive thresholding has been suggested which has superior performance compared to its counterparts in both reconstruction quality and simplicity. Then, random sampling, a special kind of compressive sensing, is investigated which is practically more efficient to be implemented than the compressive sampling scheme. A number of random sampling recovery techniques are offered based on sparsity which has very low computational complexity in a way that largedimensional signals can efficiently be... 

In this correspondence, a non-linear method of convergence accelerating and improving for iteration based algorithms is introduced. After convergence analysis, some enough conditions are proposed to guarantee convergence of the algorithm.For the sake of low complexity implementation of the proposed algorithm, some simple stabilizing methods are suggested. Simulation results show desirable performance of the proposed method and its capability to stabilize the iteration based algorithms. In the literature of missing samples recovery, the proposed method is applied to an Iterative Method (IM) as a general signal reconstruction method,then it is extended to the image recovery problem where... 

One of the funadmental problems in signal processing is finding the best sampling strategy of a continuous time signal, and then finding the best strategy for compressing the obtained signal samples. The sampling and compression steps are designed with the aim of minimizing the distortion of the reconstructed signal. The problem of finding the best sampling strategy has been widely studied in the signal processing literature. In particular, the Nyquist–Shannon sampling theorem gives a sufficient condition for perfect reconstruction of a continuous-time signal of finite bandwidth. Most of the signal processing literature deals with deterministic signals, with relatively less attention paid to... 

In this dissertation, Data analysis and information retrieval from incomplete observations are investigated in different applications. Incomplete observations may be induced by lack of observations or part of data affected by specific noise (quantization noise). Data-driven algorithms are among important hot topics. Our goal is to process the lost information inducing certain assumption on big data structures. Then, the approach is to mathematically model the problem of interest as an optimization problem. Next, the designed algorithms for the optimization problems are proposed trying to cut down on the computational complexity of as well as enhancing recovery accuracy for big data... 

Level crossing sampling is a sampling method in which a sample is taken whenever signal crosses predefined and specific levels. In this dissertation, some recommendations are made in order to increase the sampler’s performance in the sampling, data compression, and reconstruction stages.The IMATMirror algorithm is introduced in the sample reconstruction stage. This algorithm is derived from the IMAT reconstruction method. However, additional data processing is done in each iteration, causing the reconstructed signal to satisfy some properties of the Level-Crossing samples.In order to solve the problem of level crossing sampling of extremely bursty signals (ECG signals for example), a sampler... 

Increasing dynamics of mobile users intensifies the Doppler effect and degrades the performance of the communication system. Considering Fourier kernel-based modulation, in this research, we focus on dealing with the Doppler effect and compensating non-ideal communication channel response suffered from the Doppler-delay spread. In the first step, we study Zak transform and present a new transform for 2-D representation of time signals. This mapping is a well-known transformation that can be considered as a generalized discrete-time Fourier transform in the field of signal processing and can be used to represent a signal in the delay-Doppler domain. After providing a new 2-D transform, we... 

In this thesis, two novel image noise reduction approaches are proposed which can be implemented both in sparse signal processing domains such as learned dictionaries or wavelet and DCT. We first introduced a new probability density function (PDF) for the coefficients of image in transform domain and after that by using distinct thresholding function for each of coefficients we reduce noise in transform domain that is equivalent to reduce noise in time domain, since our transformation are unitary . In this scheme, we used variational approximation theory to find the optimum threshold values and noise variance simultaneously. In second method, we focus on impulsive noise reduction using... 

In this thesis, we investigate the problem of OFDM channel estimation exploiting channel sparsity. Due to the sparse nature of the scattering objects, most of wireless multipath channel have a sparse impulse response. Therefore it is possible to use the methods in the field of sparse signal processing for the purpose of estimating such channels for better accuracy, and efficient spectrum usage.
First of all the problem of OFDM channel estimation using scattered pilots is stated. Then the so-called IMAT methods together with the other sparse signal processing methods are used for the purpose of estimating channel nonzero taps. Furthermore, since efficient use of spectrum in... 

This project aims to highlight vision related tasks centered around "car". First, we gathered a dataset of 4343 front view car images, captured from the streets of Iran and Syria during daylight, the images of which are all manually cropped around their corresponding accurately chosen bounding boxes. we also extracted seven parts (i.e. left and right front lights, left and right mirrors, bumper, plate, and air intake) from each car image in the dataset. Our dataset is suitable for developing and testing bounding box extraction algorithms, holistic and part based analyses, occlusion handling algorithms, etc. next, we utilized Viola-Jones Detector to develop a system for car detection, in... 

This thesis considers theoretical, analytical and engineering design issues relating to non-orthogonal Spectrally Efficient Frequency Division Multiplexing (SEFDM) communication systems that exhibit significant spectral merits when compared to Orthogonal FDM (OFDM) schemes. Alas, the practical implementation of such systems raises significant challenges, with the receivers being the bottleneck.
This research explores detection of SEFDM signals. The mathematical foundations of such signals lead to proposals of different orthonormalisation techniques as required at the receivers of non-orthogonal FDM systems. To address SEFDM detection, two approaches are considered: either attempt to... 

Free-Space Optical (FSO) communication has received an increasing attention in recent years with its ability to achieve ultra-high data rates (at the order of multiple gigabits per second) over unlicensed optical spectrum. A major degrading factor, particulary in long links is the stmospheric turbulence induced fading. In this thesis, we use spatial diversity and use and make several contributions to the performance analysis of MIMO (Mutli Input-Multi Output) FSO systems. We use MRC(Maximum Ratio Combining),EGC(Equal Gain Combinig),SC(Selection Combinig) and yield significant performance improvments. Finally we import the charectristic of different beamshapes and yields performance... 

Due to the extremely fast growth in high speed data rate demand in the recent years, it is necessary to make use of the optical technologies in telecommunication access networks. Passive optical networks (PONs) has got much attention compared to other optical access architectures due to some advantages such as low installation and maintenance expenses, and providing more reliable network transmission.
In this thesis, we will study two multiple access techniques, namely optical code division multiple access (OCDMA) and optical orthogonal frequency division multiple access (OOFDMA). Since the system performance of these techniques are mainly limited by multiple access interference, we... 

In this thesis, detection problem in CDMA systems in overloaded regim is investigated. To thid end, both wireless and optical CDMA systems are considered. In overloaded CDMA systems, if the spreading matrix is invertible and channel is ideal and noiseless, then in the receiver the information of users can be detected without any error. Previusely, it was proven that for limited information symbols space, there are some matrices which are invertible or detecting. However, optimal receiver in these systems is comlex and infeasible. The only case that the optimal receiver can be implemented in a fesible way, is when the spreading matrix is constructed using kronecker technique. Therefore, in... 

The remote sensing is the knowledge of gaining information about an event without having direct access to it, and synthetic aperture radars (SAR) have gained spectacular attention in this filed due to their wide applications and high efficiency. The performance of SAR, which are classified in the space-borne or space-borne radars is similar to that of pulse radars. The transmitted signals in SAR are generally chirp signals, and the received signal is two-dimensional which is scattered in two dimensions of range and azimuth called as raw data. Due to relative movement between the radar base and the target point, the distance between the radar base and the target point would not be fixed along... 

In this research, we propose analog to digital (A/D) converters based on Level Crossing (LC) sampling and the corresponding signal processing techniques for effecient acquisition of spectrum-sparse signals. Spectrum-sparse signals arise in many applications such as cognitive radio networks, frequency hopping communications, radar/sonar imaging systems, musical audio signals and many more. In such cases, the signal components maybe sparsely spread over a wide spectrum and need to be acquired at a reasonable cost without prior knowledge of their frequencies. Compared with the literature, the proposed scheme not only enables efficient acquisition of spectrum-sparse signals with a less complex... 

Due to its higher degrees of freedom in comparison with a Single-Input Single-Output (SISO) radar , a Multiple-Input Multiple-Output (MIMO) radar has superior resolution , higher accuracy in detection and estimation , and more flexibility in beamforming . As there are multiple receivers in a MIMO radar system , if we can reduce the sampling rate and send fewer samples to the common processing center , the cost can significantly be reduced . Sometimes , the problem is not even the cost . It is the technology issues of high sampling rates . The reduction in sampling rate can be achieved using Compressive Sensing (CS) or in a much simpler form Random Sampling (RS) . In CS , we take... 

On one hand Code Devision Multiple Access (CDMA) as an efficient spread spectrum multiple access solution was under consideration in recent years. On the other hand one of the main challenges in cellular networks was near-far effect and fading effect which cause different received powers from different users.
In this thesis we are going to investigate near-far effects in overloaded CDMA systems from different aspects. Firstly we will investigate on the robust systems over near-far effect, propose near-far resistance codes and a very low complexity ML decoder for a subclass of these codes. Secondly we deal evaluation of the sum capacity of finite dimensional CDMA systems. These systems... 

Due to the ever-growing applications of video signals in day-to-day life and the large amount of information they contain, the compressing and processing of these signals is vital. In this thesis, a deep neural network called MC-ResNet is proposed which provides an approximation of non-reference frames based on reference ones. Next, three scenarios for compressed video sensing are presented. In all three scenarios, the reference frames are sampled and transmitted independently and reconstructed in the receiver by BCS-SPL method. In the first scenario, the difference between the non-reference frame and the approximation obtained from the MC-ResNet network is sampled and transmitted. In the... 

In this thesis, we focus on decomposition of a matrix into low rank and sparse matrices. We propose two algorithms. The first one is based on smoothed l0-norm where the l0-norm is approximated by smoothed one. Almost all previous works are based on l1-norm where the l0-norm is approximated by the l1-norm. The second algorithm is based on adaptive thresholding; to make a matrix low rank, its singular values are thresholded and to make a matrix sparse, its entries are also thresholded. Various simulations have been performed to compare the proposed algorithms with the previous ones. The results confirm the fact that the proposed algorithms have better performance in terms of quality and speed...