Image Distortion Estimation by Hash Comparison

Wavelet transform-based methodologies for both Automatic Modulation Recognition (AMR) and Demodulation of digitally modulated communications signals can be utilized in an enabling platform for the implementation of a new class of communications systems. In particular, such techniques could enable the development of agile radio transceivers for use in both commercial and military applications. Such radio transceivers would have the ability to transmit and receive signals using many different modulation schemes while employing a common receiver architecture based on a single demodulator. In this dissertation, the development of AMR and Demodulation techniques are based on the relatively new mathematical theory of Wavelet Transforms (WTs). Information-bearing signals acquired by communications receivers are transformed into the wavelet-domain using the Continuous Wavelet Transform (CWT) and then applied to signal processing algorithms that also use the CWT in conjunction with pattern recognition techniques. In particular, the method of template-matching is used for both the AMR and Demodulation processes. Signal templates characterizing various modulated signals are used for both processes. The signal templates are determined based on the signal features present in the fractal patterns of their corresponding scalograms for specific modulation schemes as they appear in the wavelet-domain. The algorithms developed in this work are capable of both classifying the method of modulation used in the acquired signal, as well as subsequently automatically demodulating the signal to recover the message. The classes of digitally modulated signals considered in this work include variants of the Amplitude-, Frequency-, Phase-Shift Keying modulation families, i.e., ASK, FSK, and PSK, respectively, and multiple-level Quadrature Amplitude Modulation (M-ary QAM) families. The AMR and Demodulation performances are evaluated in the presence of Additive White Gaussian Noise (AWGN) over a wide range of Signal-to-Noise Ratio (SNR) values. Through extensive Monte Carlo computer simulations it is determined that the average correct classification rates using wavelet-based AMR for PSK, ASK, and QAM are over 98%, and over 90% for FSK signals, all at an SNR of 0 dB. The Bit Error Rate (BER) performance obtained using wavelet-based Demodulation is at least one order of magnitude better than the matched filter-based BER performance realized for the modulation schemes considered.

The growth of modern wireless communications has increased the demand for high quality data services. This article presents an analysis of the performance of a DVB-S2 system with MIMO technology. A method for using a receiver-transmitter based on DVB-S2 with MIMO technology, provides a better quality of service for data transmission and discusses ways to improve the quality of data transmission using size and type converters of transmitting and receiving data, an amplifier and a normalizer Gain. The circuit was examined for bit error rate (BER) and peak signal-to-noise ratio (PSNR) between AWGN and multipath Rayleigh fading images operating under intersymbol interference (ISI). The analysis was carried out and a graph of the influence of ISI was obtained. The proposed system has the best quality of service for data transmission for fading channels. The transmission of images in the system includes a Rayleigh channel and AWGN with different values of the signal-to-noise ratio (SNR, dB) and different values of Gain. The Gain values change the BER and PSNR values (7.834 dB, 8.385 dB, and inf) at an SNR of -58 dB with respect to Gain values of 1, 32400 and 648000, respectively. Also obtained eye diagrams, where you can see a decrease in the negative impact of intersymbol interference with an increase in the value of Gain..This system can be used to wirelessly transmit higher quality, high-resolution radiological images (such as computed tomography or magnetic resonance imaging) over a wireless network to remote healthcare workers.

The performance of encoded opportunistic transmission schemes in wireless channels affected by Rayleigh fading and additive white Gaussian noise (AWGN) is analyzed. In opportunistic transmission, the information is transmitted only when the fading amplitude is above a threshold. For this, the receiver with the knowledge of the channel state information notifies the instants the transmitter should transmit. Opportunistic systems with convolutional error correcting codes or with trellis coded modulation are analyzed in terms of closed-form bit error rate (BER) expressions. Nevertheless, the approach presented can be employed with any kind of error correcting codes. Hence, the performance of turbo codes is also presented in the simulations. Monte Carlo simulations verify the accuracy of the derived expressions and provide insights on the system performance. Performance results show that uncoded and encoded opportunistic systems are superior to uncoded and encoded ordinary systems (non-opportunistic), respectively. In particular, the BER curves of the opportunistic system decay exponentially when the signal-to-noise ratio (SNR) increases. On the other hand, BER curves for ordinary transmission decay linearly, where the slope is proportional to the diversity that depends on the error correcting code. Thus, opportunistic systems require less SNR to guarantee the same BER of ordinary transmission. The BER gain increases as the SNR increases. It is also observed that uncoded opportunistic systems are even superior to encoded ordinary ones. The results are validated guaranteeing the same spectral efficiency for all the scenarios. Finally, due to the exponential decay of the BER curves, coding gain expressions, used in ordinary systems over AWGN, can be used as approximations for opportunistic transmission in fading channels.

The increasing demand for high-density and high-speed digital optical recording systems has made the development of advanced coding and signal processing techniques for fast and reliable data recovery increasingly important. In recent years, the parity-check (PC)-code-based reception technique has been widely studied for magnetic recording systems, and it is projected to be highly promising for high-density optical recording. The PC code is an inner error correction code (ECC), which can detect dominant short error events of the system, using only a few parity bits. This reduces the loss in error correction capability of the outer ECC due to random short errors and results in a simple and efficient solution to improve the overall performance. This thesis is dedicated to the design and analysis of PCcode- based recording systems to achieve higher recording capacity with low implementation complexity, for high-density blue laser disc systems. In particular, most of the key components of the PC-code-based optical recording system have been designed and optimized for different recording densities, and different proportions of white noise and media noise. During the development of advanced coding and detection techniques, it becomes necessary to investigate the system’s performance with different coding schemes and recording densities. In Chapter 2 of the thesis, we propose a generalized Braat-Hopkins model for optical recording channels, which provides a fair basis for the performance comparison of detection schemes over different coding schemes and recording densities, for channels with additive, white Gaussian noise (AWGN) and media noise. Various basic issues associated with the PC-code-based systems are investigated in Chapter 3. These include bounds for bit error rates and error event probabilities, the dominant error events at channel detector output, different PC codes, simple and efficient post-processors, the impact of error events that are split across data block boundaries and the corresponding remedy, as well as the effects of code rates and recording densities. Simulation results show that a 4-bit PC code achieves the best performance. The corresponding bit error rates (BERs) are very close to the performance bounds, at both nominal and high densities. Constrained codes, which serve as a key component in the read-write channel of data storage systems, are desired to have a high code rate with low-complexity encoder/decoder. In Chapter 4, we investigate the design of certain capacity-approaching constrained codes for optical recording systems. In particular, we derive analytically the relationship between the number of encoder states and the maximum size of these codes. We identify the minimum number of encoder states that maximizes the code rate, for any desired codeword length. The design of constrained PC codes is key to the development of PCcode- based systems, and the systematic design of efficient constrained PC codes remains a challenging problem. In Chapter 5, we propose a general and systematic code design technique for constructing capacity-approaching constrained PC codes, which can detect any type of error events of the system, with the minimum code rate loss. Compared to the rate 2/3 code without parity, the newly designed constrained 4-bit PC code achieves a performance gain of 2 dB at nominal density, and 1.5 dB at high density, at BER = 10-5. As the dominant noise for high-density optical recording systems, media noise severely degrades the performance of channel detectors and postprocessors that are designed for AWGN. In Chapter 6, we propose two novel modifications to the bit detector to combat media noise. We further develop a data-dependent post-processing scheme for error correction. Compared to the system designed without considering media noise and without PC codes, the overall performance gain of the developed scheme can be more than 11 dB at high media noise levels. In data storage systems, the ECC failure rate (EFR) serves as the ultimate measure of the data recovery performance. In Chapter 7, we develop semi-analytical approaches for estimating the EFR, and analyze EFRs for the developed PC-code-based systems, for the cases without and with interleaving. Our analysis shows that with the optimum interleaving degrees, compared to the rate 9/13 code without parity, the 2-bit PC code achieves a gain of around 0.5 dB, and the 4-bit PC code gains 0.6 dB, at high record ing density and EFR = 10-16. The thesis concludes in Chapter 8 with some suggestions for further work.

Traditionally, channel generated bit error rates (BERs) at a certain signal to noise ratio (SNR) have been modeled by a Gaussian distribution function. This approach has been suitable for a peak detection channel as the analysis is performed in only one bit. In the case of a partial response maximum likelihood (PRML) channel, one data bit is determined by multiple code bits. There is a burst of errors detected if any one of the involved code bits gives an error. The chi-square distribution function, which is a sum of several independent Gaussian-squared distributions, is another method to model BERs of a PRML channel. Particularly, different PRML codes could be modeled by a chi-square distribution with different degrees of freedom. In this paper, the relationship of SNR to BER is generated using the chi-square method. The measured on-track rms SNR, read sensitivity function, and media magnetization are the input parameters. Old data and adjacent track interference are considered as random variables. At specified track pitch and read write misregistration, the probability distributions of these random variables are defined by the read sensitivity function and media magnetization. For a given interference, the off-track SNR is calculated. Error rate at a given interference is then derived from off-track SNR by using the SNR to BER relationship defined by a chi-square distribution. The BER at a specific track pitch and read–write misregistration is computed by integrating the error rate at a given interference with the probability distribution of the interference. This model describes the statistical nature of the BER in magnetoresistance head applications and provides very good correlation to experimental data.

Modulation techniques in 5G wireless communication systems play a crucial role in meeting demands for higher data rates, lower latency, and improved connectivity. This involves optimizing power spectral density (PSD), enhancing data transmission reliability, and reducing bit error rates (BER) and interference. The objective of this paper is to evaluate primary modulation schemes used in 5G—Orthogonal Frequency Division Multiplexing (OFDM), Filter-Orthogonal Frequency Division Multiplexing (F-OFDM), Filter Bank Multi-Carrier (FBMC), and Universal Filtered Multi-Carrier (UFMC)—based on performance metrics such as PSD, BER, and signal-to-noise ratio (SNR) using MATLAB. OFDM demonstrates low BER at high SNR but faces degradation at lower SNRs, necessitating a higher SNR for maintaining low BER. F-OFDM improves BER in noisy environments through reduced out-of-band emissions and improved spectral efficiency. FBMC shows lower BER than OFDM, especially in multipath fading scenarios, despite its higher complexity. UFMC provides balanced performance with moderate BER across varying SNRs, offering a trade-off between simplicity and efficiency, with stable BER and enhanced spectral efficiency, and reduced latency compared to OFDM. Each modulation scheme in 5G presents specific strengths and weaknesses. OFDM is robust and widely used, while F-OFDM, FBMC, and UFMC enhance spectral efficiency, BER, and SNR management. Selecting the appropriate technique depends on network requirements, with MATLAB simulations playing a crucial role in optimizing 5G network performance.

Non-orthogonal multiple access (NOMA) is one of the potential future mobile network methods that can give better spectral efficiency, huge connectivity, and low latency. As a result, academic and industry researchers have studied the error performances and capacity of NOMA systems. The main drawback of NOMA methods is user interference, which is generally addressed by interference cancellation techniques such as Successive Interference Cancellation (SIC) at receivers. Therefore, it is better to obtain the bit error rate (BER) performance of NOMA. Each user's power level is determined by the power level assigned to them. As a result, this work presents BER analysis for two NOMA users using BPSK modulation in additive white Gaussian noise (AWGN), Rayleigh, and Rician fading channels. Initially, we assessed BER performance for various Signal to Noise Ratio (SNR) values by assuming two users who are equally spaced from the base station (BS). Later, the BER performance for various transmit powers is assessed by assuming two users are situated at varying distances from the BS. The performances are discussed using MATLAB simulations. The comparative BER analysis is also studied for various fading environments.KeywordsBERNOMABPSKSICFading

In wireless communication, channel equalization is one of the most challenging tasks because the broadcast channels are often subjected to multipath fading and several bandwidth limitations. Our project is mainly concerned with the Single Carrier Long Term Evolution (SC-LTE) uplink system model and its performance analysis when Fractionally Spaced Constant Modulus Algorithm (FS-CMA) and Recursive Least Squares Algorithm (RLS) are implemented. FS-CMA (CMA (1, 2) and CMA (2, 2)) and RLS algorithms are used individually to eliminate noise caused by multipath fading and Additive White Gaussian Noise (AWGN) in the stationary channel. The performance of conventional FS-CMA and RLS algorithm are compared using Bit Error Rate (BER) vs. Signal to Noise Ratio (SNR), Convergence, Equalizer output, Peak to Average Power Ratio (PAPR) vs. SNR.

The Orthogonal Frequency Division Multiplexing (OFDM) is also known as multicarrier technology. Wideband digital communications in the recent past have increasingly utilized OFDM. It can withstand difficult channel circumstances, efficiently utilize spectrum resources, decrease ISI, and operate at a high data rate, among many other benefits. It has been used in several wireless and wired communication systems, including fourth generation Long-Term Evolution (4G LTE) mobile communications. The performance assessment and analysis of the OFDM system under Additive White Gaussian Noise (AWGN) channel has been carried out in this work. The factors in which system performance is assessed include the signal quality, Bit Error Rates (BERs), and Signal to Noise Ratios (SNRs) of the received signals. To improve performance while employing multicarrier modulation, the subcarriers must be kept orthogonal to one another, in the process known as OFDM. The sole focus of this study is the performance analysis of PAPR, BER, and SNR utilizing various modulation methods and schemes.

A new Dynamic Bit Loading (DBL) scheme with the Orthogonal Generalized Frequency Division Multiplexing (OGFDM) is, for the first time, proposed, discussed and assessed. The key concept of this hybrid modulation format depends substantially on the adaptive distribution of the bit stream to be more compatible with the gained capacity of the realistic channel state. Due to the negative impact of employing the fixed schemes of digital modulation on the performance of the conventional telecommunications systems, the influence of using the multi-level modulation system is investigated for the future applications of mobile communications. Utilising the DBL in the physical layer (PHY), a flexible range of modulation formats can be optimally assigned for each applied frequency sub-carrier in accordance with wireless channel circumstances. In addition, depending on the supportive features of the proposed modulation system, the performance in terms of channel capacity can be maximised at the acceptable limit of the Bit Error Rate (BER). As such, an extra enhancement can be achieved in the spectrum efficiency (SE) of the adaptively modulated wireless signal. Thus, an adjustable boost of the transmission range of used modulation formats can be reached with the introduced adaptation system. The performance of the DBL system through a wireless mobile channel under the Additive White Gaussian Noise (AWGN) is evaluated according to a various level of the Signal to Noise Ratio (SNR). Ultimately, regarding the numerical simulation, a MATLAB code is employed to simulate the performance (channel capacity & BER) of the proposed DBL that is fundamentally accommodated by the recent candidate waveform of future mobile technology (OGFDM).

When it comes to studies on smart receiver designs, using machine learning and deep learning techniques for the development of automatic modulation classifiers as well as demodulators which require little to no information about the transmitted signal or the channel state is an area of interest. Through this study, we have proposed a combined classifier-demodulator system that is entirely deep learning-based and one that is focused on higher-order quadrature amplitude modulation (QAM) schemes such as 64QAM and 256QAM that can be used in next-generation mobile technologies. The system was developed by training a bidirectional long-short-term memory (BiLSTM) and long-short-term memory (LSTM) network for the classifier and demodulator, respectively, using randomly generated data, demodulated using binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), 16QAM, 64QAM, and 256QAM transmitted through a simulated additive white Gaussian noise (AWGN) channel of varying signal to noise ratio (SNR) levels. The classifier was then tested for its prediction accuracy while the demodulator models were tested against traditional mathematical models while calculating the effective capacity. The results showcased that the classifier worked extremely well for the QAM schemes across all SNR levels and less so with the PSK models. Considering the demodulator models’ performance, all schemes except the 256QAM demodulator were able to reach a zero or near zero bit error rate (BER) level within minimum acceptable SNR ranges.

Recently, network coding considers as a major ability to achieve effectiveness and Reliability for wireless networks. This article examine the channel capacity and Bit Error Rate (BER) of Network Coding and channel coding for different channel models using convolutional encoding with Viterbi decoding algorithm. We identify the results of a bit stream transmitted through different channel models such as Binary Symmetric Channel (BSC), Additive White Gaussian Noise (AWGN) and Slow Rayleigh Fading Channel (SRFC). It shown that, all channel models achieve the same capacity in higher signal to noise ratio (SNR). Furthermore, the BER performance has shown that the propose scheme outperform conventional scheme. We have done our simulation using Matlab to show the performance evaluation of both schemes for different scenario.

Long Term Evolution (LTE) has many desirable features such as high data rate, better signal, and low latency which are required for modern communication systems. The LTE technology is based on an Orthogonal Frequency Division Multiplexing (OFDM) modulation scheme. For these benefits, LTE uses for the majority of communication systems that are used on civilian and military applications. Electronic Warfare (EW) researchers are interested in measuring the performance of the LTE communication systems in presence of intentional optimized jamming techniques. In this paper, the standard 3GPP (TS 36.104 v8.7.0) LTE Downlink Frequency Division Duplexer Single Input Single Output (DL FDD SISO) communication system designed on the SystemVue 2015.01 software program libraries has been used. The performance of the LTE communication system has been studied in the Additive White Gaussian Noise (AWGN) Channel without jamming for the three available modulation types for the Physical Downlink Shared Channel (PDSCH) [QPSK – 16QAM – 64QAM] by swept the Signal to Noise Ratio (SNR) versus Bit Error Rate (BER). The effectiveness of jamming has been studied by fixed the SNR and swept the Jamming to Signal Ratio (JSR) versus BER in two different cases. Firstly, the AWGN jamming signal has been added to the AWGN channel. Secondly, the optimized jamming signal has been added to the AWGN channel. Finally, the results of the jamming signal modulation type, bandwidth, and its location in the frequency and time have been optimized.

The bit error rate (BER) in relation to the signal-to-noise ratio (SNR) serves as a widely recognized metric for assessing the performance of communication systems. The concept of SNR is so integral that many existing studies presume its definition to be understood, often omitting the specifics of its calculation in their simulations. Notably, the computation of SNR from the perspective of the transmitter yields distinct behaviors and outcomes compared to that from the receiver’s side, particularly when the channel encompasses more than mere noise. Typically, research papers utilize the transmitter-side (or ensemble-average) SNR to benchmark the BER performance across various methodologies. Conversely, the receiver-side (or short-term) SNR becomes pertinent when prioritizing the receiver’s performance. In the context of simulating the long-term evolution (LTE) downlink, applying both SNR calculation approaches reveals that the receiver-side SNR not only produces a significantly lower BER compared to the transmitter-side SNR but also alters the relative BER performance rankings among the channel models tested. It is deduced that while the transmitter-side SNR is apt for broad performance comparisons, it falls short in thoroughly examining the BER behavior of a receiver across varying SNR scenarios. Therefore, the transmitter-side SNR is useful when comparing the performance of the simulated system with other studies. Conversely, if the primary concern is the actual BER performance of the receiver, the receiver-side SNR could provide a more accurate performance assessment.

Multicarrier differential chaos shift keying (MC-DCSK) systems transmit the reference chaotic signal for information recovery to remove the complex synchronization circuit. However, transmission errors in the reference chaotic signal would induce the error propagations when directly used for demodulations. In order to address this issue, we propose a low-rank approximation of matrices (LRAM) detection method to improve the reliability performances. In our design, we exploit the low-rank characteristic of MC-DCSK signals sharing the reference chaotic signal. Instead of directly using the received reference chaotic signal for correlated demodulation, we propose to apply the LRAM method to jointly estimate the reference signal and the information-bearing signal. We use the singular value decomposition and generalized LRAM methods to minimize the distances between the estimates and transmitted data. Thus, the signal-to-noise ratio (SNR) can be improved to achieve lower bit error rate (BER). Moreover, theoretical BER expression is derived and LRAM-aided system is proved to be capable of proving the maximum-likelihood detection for received signals. Simulation results demonstrate the BER performances of our design outperform counterparts over additive white Gaussian noise and fading channels.