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In this paper, an innovative system called grouping frequency-time index modulation-based differential chaos shift keying (GFTIM-DCSK-I) is presented to improve the energy efficiency (EE), spectral efficiency, and data rate of the recently proposed grouping subcarrier index modulation in differential chaos shift keying (GSIM-DCSK) system. The proposed system optimally utilizes both frequency and time resources, enabling efficient transmission at high data rates. The data information bits are divided into equal L groups, each containing (p1+p2+1) bits. Within each group, the first set of bits, referred to as p1 bits, are assigned as carrier-indexed bits, whereas the second set of bits, known as p2 bits, are designated as time-indexed bits. Additionally, one bit is assigned for modulation. The p1 bits serve as an index selector for choosing a single active subcarrier from a total of 2p1 subcarriers. p2 bits are utilized to choose a single time slot out of a total of 2p2 available options. The modulated bit undergoes DCSK modulation and is thereafter sent via the active subcarriers. Mathematical expressions are constructed to examine the system performance of energy efficiency, spectral efficiency, and system complexity, then compared with the traditional DCSK modulations. Analytical formulas for the bit error rate (BER) of the proposed system are obtained under the impact of multipath Rayleigh fading channel and additive white Gaussian noise (AWGN). Results from simulations and analysis confirm that the theoretical analysis is accurate. The performance of the suggested approach is also evaluated by comparing it to conventional DCSK techniques, showing an improvement in the performance.

Na $\ddot {i}$ ve simulated additive white Gaussian noise (AWGN) may not fully characterize the complexity of real world noisy images. Owing to optimal sparsity in image representation, we propose a curvelet based model for denoising real-world RGB images. Initially, the image is decomposed in three curvelet scales, namely: the approximation scale (that retains low-frequency information), the coarser scale and the finest scale (that preserves high-frequency components). Coefficients in the approximation and finest scale are estimated using NLM filter, while a scale dependent threshold is adopted for signal estimation in the coarser scale. The reconstructed image in spatial domain is further processed using Guided Image Filter (GIF) to suppress the ringing artifacts due to curvelet thresholding. The proposed approach known as CTuNLM method is extended for color image denoising using uncorrelated YUV color space. Extensive experiments on multi-channel real noisy images are conducted in comparison with eight sate-of-the-art methods. With four encouraging qualitative and quantitative measures including PSNR and SSIM, we found that CTuNLM method achieves better denoising performance in terms of noise reduction and detail preservation. We further examined the potential of proposed approach by focusing only on the Finest scale curvelet Coefficients (FC). Features like small details, edges and textures always add up to improve the overall denoising performance, while minimizing spurious details. We studied “The Curious Case of the Finest Scale” and constructed “Deep Curvelet-Net”: an encoder-decoder-based CNN architecture, as a pilot work. The encoder uses multiscale spatial characteristics from noisy FC, while the decoder processes de-noised FC under the supervision of encoder’s multiscale spatial attention map. The “Deep Curvelet-Net” links encoder multiscale feature modeling with decoder spatial attention supervision to learn the most essential features for denoising. The CNN-based architecture only estimates FC, while all other CTuNLM stages are left unchanged to produce the denoised output. Results presented in this article validated the design of proposed CNN architecture in curvelet domain and motivated us to search beyond classical thresholding and/or filtering approaches.

During the recording time, electrocardiogram (ECG) signals are subject to multiple artefact noises, such as muscle activity, white Gaussian noise (WGN), baseline wander, and power line interference (PLI). Therefore, pre-processing of ECG signals is essential to eliminate these artefacts and to obtain efficient ECG features. Many approaches have been proposed for removing ECG noises, including ECG signal denoising using wavelet transform (WT). However, the effectiveness and performance of the WT technique are strongly related to the configuration of its control parameters, which are typically fine-tuned through a laborious and time-consuming series of experiments. This paper introduces a technique that combines particle swarm optimisation (PSO) with WT for ECG signal denoising. The key contribution of this research is the use of PSO to determine the optimum settings for all WT parameters for ECG signal denoising (type of wavelet basis function Φ, thresholding function β, level of decomposition L, rule for threshold selection λ, and rescaling method ρ). The efficiency of the proposed method is evaluated using the percentage root mean square difference (PRD) and the signal-to-noise ratio (SNR), employing various ECG signals available online from the MIT-BIH Arrhythmia database. Experimental results show that the proposed PSO-WT technique yields better results than state-of-the-art techniques in terms of SNR, particularly for PLI measured at 60 Hz and still acceptable at 50 Hz. For example, a denoised ECG signal resulting from the proposed technique at an SNR input of 10 dB corresponds to an SNRoutput of 27.47 dB at 60 Hz, improving the quality of the denoised ECG signal and making it more appropriate for clinical diagnosis. Furthermore, the proposed method also shows promising efficiency in the presence of WGN, making it highly relevant for IoT applications and RF transmission.

Orthogonal Frequency Division Multiplexing (OFDM) is the best choice for wireless and wired high data rate communications. The OFDM system has many advantages such as high spectral efficiency, robustness to channel fading, and immunity to impulse interference. However, it has a main drawback, which is the Peak to Average Power Ratio (PAPR). Selecting Mapping (SLM) and Partial Transmit Sequences (PTS) are the two essential techniques for reducing the PAPR; however, they need to send side information to indicate how the transmitter generates signals. In this paper, Particle Swarm Optimization (PSO)-based dummy sub-carriers are inserted with the data to reduce PAPR without transmitting side information. The incorporation of PSO-based Dummy Sub-carriers Insertion (DSI) method on this system is performed by measuring the PAPR at the IFFT output (Inverse Fast Fourier Transform) after adding 6 adaptive sub-carrier sequences to the input data of IFFT. The PSO-based dummy algorithm decides to send the data once the PAPR of this data sequence and dummy sub-carrier is under a specific threshold. Using MATLAB as a mathematical simulation tool, simulation results are presented for a standard OFDM network model. The network model has been simulated in an Additive White Gaussian Noise (AWGN) channel environment to investigate PAPR and Bit-Error Rate (BER) performance. The simulation results show that the dummy sequence based on PSO reduces PAPR down to 4 dB compared to a conventional OFDM system and down to 3 dB compared with the clipping technique for the same BER performance.

A new bound on the error probability of coding with limited code length over additive white Gaussian noise (AWGN) channels is proposed. The developed bound is proved to be universal for two connected encoding ways. On the one hand, we conceive folding the conventional codes, such as Hadamard and binary random ones, in order to adapt shorter code length. On the other hand, we further extend the above folded structure to Gaussian random coding and hence to bound its error probability. Finally, we demonstrate that the bound of the above two constructions can be unified as $\sqrt {\frac {log_{2}e}{2\pi nC}}2^{-n(C/2-R)}$ where $C$ represents the capacity of the AWGN channel, $n$ and $R$ stand for the code length and rate, respectively. This theoretical contribution confirms that, in the context of short code length and low rate, the developed two constructions exhibit excellent performance even close to the Shannon bound on AWGN channels.

Orthogonal frequency division multiplexing with index modulation (OFDM-IM), stands out among conventional communication technologies, as it uses the indices of the available transmit entities. Thanks to such an approach, it offers a novel method for the transmission of extra data bits. Recent years have seen a great interest in chaos-based communications. The spectrum-spreading signals used in chaotic signal modulation technologies are orthogonal to the existing mixed signals. This paper presents how well a non-coherent differential chaos shift keying communication system performs across an AWGN. Different types of detection methods are simulated, bit error rate and power spectral density are calculated and then compared with standard OFDM with index modulation. The results of simulations concerning the performance of a DCSK system, adding to the security of the proposed solution and offering a comparable bit error rate performance, are presented in the paper as well.

This work describes the implementation and testing of a FSK demodulator, within the framework of a modem re-engineering for navy communications. It was developed over a Spartan 6 XCSLX25 FPGA with its code in VHDL. For testing, a modulator was implemented in a STM32F407 microcontroller where different noise levels were added to the signal to try out the system.

Automatic modulation classification (AMC) represents an important integral part of modern communication systems. While novel AMC algorithms based on complex neural network structures showed significant performance improvements, in practical applications low algorithm complexity of AMC algorithms based on higher-order cumulants still make them very attractive. AMC algorithm based on sixth-order cumulants showed very good performance in this context, especially when it comes to distinguishing Binary Phase Shift Keying (BPSK) signals from complex constellations. Still, no further analysis of expected performance with other real constellations was presented for this algorithm so far. In this paper, the performance was explored in a wider context of real signals classification, by observing various Pulse Amplitude Modulation (PAM) constellations, whose statistical features are presented for the first time. Their classification performance was tested via Monte – Carlo simulations, and explained through the presence of bias under conditions of strong additive white Gaussian noise channel, reported in this paper for real signals for the first time. One new approach in AMC is proposed, which ensures improvement in the classification of real signal constellations. Achieved improvement is confirmed in many Monte – Carlo experiments, where proposed new AMC scheme is tested versus the most popular standard higher-order cumulants-based algorithms.

Aiming to address the problems of the high bit error rate (BER) of demodulation or low classification accuracy of modulation signals with a low signal-to-noise ratio (SNR), we propose a double-residual denoising autoencoder method with a channel attention mechanism, referred to as DRdA-CA, to improve the SNR of modulation signals. The proposed DRdA-CA consists of an encoding module and a decoding module. A squeeze-and-excitation (SE) ResNet module containing one residual connection is modified and then introduced into the autoencoder as the channel attention mechanism, to better extract the characteristics of the modulation signals and reduce the computational complexity of the model. Moreover, the other residual connection is further added inside the encoding and decoding modules to optimize the network degradation problem, which is beneficial for fully exploiting the multi-level features of modulation signals and improving the reconstruction quality of the signal. The ablation experiments prove that both the improved SE module and dual residual connections in the proposed method play an important role in improving the denoising performance. The subsequent experimental results show that the proposed DRdA-CA significantly improves the SNR values of eight modulation types in the range of −12 dB to 8 dB. Especially for 16QAM and 64QAM, the SNR is improved by 8.38 dB and 8.27 dB on average, respectively. Compared to the DnCNN denoising method, the proposed DRdA-CA makes the average classification accuracy increase by 67.59∼74.94% over the entire SNR range. When it comes to the demodulation, compared with the RLS and the DnCNN denoising algorithms, the proposed denoising method reduces the BER of 16QAM by an average of 63.5% and 40.5%, and reduces the BER of 64QAM by an average of 46.7% and 18.6%. The above results show that the proposed DRdA-CA achieves the optimal noise reduction effect.

Image noise occurs during acquisition and transmission and adversely affects processes, such as image segmentation and object recognition and classification. Various techniques are being studied for noise removal, and with the recent development of hardware and image processing algorithms, noise removal techniques that combine non-local techniques are attracting attention. However, one disadvantage of this method is that blurring occurs in the edges and boundary line of the resulting image. In this study, we proposed a modified local steering kernel based on image matching to improve these shortcomings. The proposed technique uses image matching to differentiate the weight obtained by the steering kernel according to the local characteristics of the image and calculates the weight of the filter based on the similarity between the center window and the matching window. The resulting images were quantitatively evaluation and enlargement of images were used and compared with the existing noise removal algorithms. The proposed algorithm showed clearer contrast in the enlarged images and better results than the conventional image restoration techniques in the quantitative evaluation using peak signal-to-noise ratio and structural similarity index.

ABSTRAK Komunikasi Vehicle to Infrastructure (V2I) memungkinkan kendaraan dapat terhubung ke berbagai macam infrastruktur. Dengan kondisi kendaraan yang bergerak, maka kondisi lingkungan yang dilewati mempengaruhi parameter komunikasi. Implementasi modulasi adaptif pada skema V2I memperbolehkan sistem menggunakan skema modulasi yang berbeda untuk mengakomodasi perubahan kondisi lingkungan. Pada penelitian ini digunakan skema modulasi QPSK, 8PSK, dan 16-QAM dengan memanfaatkan reinforcement learning dan algoritma epsilon greedy untuk menentukan skema modulasi yang digunakan berdasarkan level AWGN. Dari hasil simulasi dengan kondisi nilai epsilon yang divariasikan dari 0.1 hingga 0.5 didapatkan bahwa semakin tinggi nilai epsilon maka semakin sering agen tidak memilih skema modulasi dengan reward tertinggi. Kata kunci: Reinforcement learning, Modulasi Adaptif, AWGN ABSTRACT Vehicle to Infrastructure (V2I) communication allows vehicles to be connected to various infrastructures. Under the scenario of a moving vehicle, the environmental conditions which is passed by the vehicle will affect the communication parameters. The adaptive modulation implementation in the V2I scheme allows the system to use different modulation schemes to accommodate changing environmental conditions. In this study, the QPSK, 8PSK, and 16-QAM modulation schemes were used by utilizing reinforcement learning and the epsilon greedy algorithm to determine the modulation scheme used based on AWGN level. From the simulation results with the conditions of the epsilon value varying from 0.1 to 0.5, it is found that the higher the epsilon value, the more often the agent does not choose the modulation scheme with the highest reward. Keywords: Reinforcement learning, Adaptive Modulation, AWGN

Low Density Parity-Check (LDPC) codes are one of the hottest topics in coding theory today. This code invented in the early 1960's, and it having an amazing comeback in the last few years. In this paper, a scheme is proposed to analyze the performance of LDPC which is considered important rival to turbo codes, Convolutional Code (CC) and Read Solomon (RS) in terms of performance and complexity. This code is utilized in Orthogonal Frequency Division Multiplexing (OFDM) system to evaluate the improvement in the Bit Error Rate (BER) performance of the system. Comparison is done between turbo code and LDPC code through Additive White Gaussian Noise (AWGN) and fading channels. The effect of varying the code rate channel, number of iteration and the code length on the performance of the scheme are also explained.

We provide a theoretical foundation for further analysis and optimization of the Mth-power (MP) carrier phase estimator for MPSK modulation. Also known as the Viterbi-Viterbi (VV) estimator, it is commonly used in practice because it leads to low-latency receiver implementations. The MP carrier phase estimator first raises the received noisy signal samples to the Mth-power to remove the unknown phase modulation, and then extracts the unknown carrier phase of the mid-symbol using a weighted sum of these modulation-wiped-off received signal samples over a symmetrical observation window. Our starting point is the single-term, complex exponential expression for a complex sinusoid received in complex, additive, white, Gaussian noise (AWGN), which leads to a great deal of simplicity in dealing with arbitrary powers of the noisy received signal sample when compared with the conventional approach of raising the sum of signal plus noise to higher powers. The single-exponential expression enables us to first optimize the weighting coefficients of the MP carrier phase estimator with respect to the statistics of the AWGN, in a manner much simpler than previous approaches. Then, it enables us to apply the linear minimum mean square error (LMMSE) criterion to optimize the MP estimator with respect to both the statistics of the AWGN and the carrier phase noise that we model here as a Wiener process. Although the LMMSE MP estimator is computationally intensive for online implementation, a much less complex version is suggested that can be efficiently implemented in real time. Extensive simulation results are presented to demonstrate the improved performance of the LMMSE MP estimator over the conventional MP estimator. By using a sufficiently long symmetrical observation window, the LMMSE estimator does not suffer from the block length effect, which leads to much performance gain over the VV/MP estimator especially at high signal-to-noise ratio (SNR) and high phase noise. A phase unwrapping algorithm is also presented for accurate unwrapping of the estimated carrier phase before it is used in data detection. The proposed LMMSE carrier phase estimator is suitable for implementing a coherent receiver at all SNRs.

In this Letter, a robust technique is presented to detect and classify different electrocardiogram (ECG) noises including baseline wander (BW), muscle artefact (MA), power line interference (PLI) and additive white Gaussian noise (AWGN) based on signal decomposition on mixed codebooks. These codebooks employ temporal and spectral-bound waveforms which provide sparse representation of ECG signals and can extract ECG local waves as well as ECG noises including BW, PLI, MA and AWGN simultaneously. Further, different statistical approaches and temporal features are applied on decomposed signals for detecting the presence of the above mentioned noises. The accuracy and robustness of the proposed technique are evaluated using a large set of noise-free and noisy ECG signals taken from the Massachusetts Institute of Technology-Boston's Beth Israel Hospital (MIT-BIH) arrhythmia database, MIT-BIH polysmnographic database and Fantasia database. It is shown from the results that the proposed technique achieves an average detection accuracy of above 99% in detecting all kinds of ECG noises. Furthermore, average results show that the technique can achieve an average sensitivity of 98.55%, positive productivity of 98.6% and classification accuracy of 97.19% for ECG signals taken from all three databases.

In the maritime Very High Frequency (VHF) band, there are no systems for transmitting large amounts of data. Therefore, it is necessary to develop new systems that would modernize the Global Maritime Distress and Safety System (GMDSS), significantly relieve the Automatic Identification System’s (AIS) communication channels, and set guidelines for the development of communication infrastructure of the e-Navigation. In line with this, analytical and simulation models of the maritime VHF data transmission communication system using Orthogonal Frequency Division Multiplexing (OFDM) modulation are worked out in this paper. The achieved data rate, the spectral efficiency and the bit error rate (BER) represent validation parameters on which the results of the analytical and simulation models are evaluated. It is concluded that the application of the digital OFDM modulation in the maritime VHF band may improve the GMDSS system by achieving higher data rates compared to the current terrestrial mandatory systems for data exchange, i.e. Digital Selective Calling (DSC) and AIS.

Behavior of communication medium play vital role in the growth of wireless communication system. To understand various wireless channel environments such as additive white Gaussian noise (AWGN) and Rayleigh fading channels in orthogonal frequency division multiplexing (OFDM) along with multiple input and multiple output (MIMO) system, we analyze mathematical relation of bit error rate (BER) against Signal to Noise ratio (SNR) and verified the same using MATLAB simulation, while considering the BPSK modulation scheme. The performance measured in terms of BER is evaluated for various channels of OFDM-MIMO system along with variation in number of antennas at transmitter and receiver side. It has been demonstrated that the BER and probability of detection improves against SNR per bit, as the diversity employs at transmitter or/and receiver end.

Noise reduction in audio is a process of minimizing the presence of noise in the audio signal. Noise reduction approach helps user understand how to remove noise from the signal. Audio is very susceptible with noise and it presence will give impact on two major ways; first it will degrade the quality of information being transfer and second limit the capacity of data being transmit. There are lot of noise reduction techniques been proposed as to remove noise from audio signal such as wiener filter and average filter. In this project, wavelet theory implementation is proposed for reducing noise from audio signal. The main objective is to identify and remove the presence of noise in the signal. Furthermore, measurements of noise signal pattern are recorded before and after the noise reduction process. To be specific, this project will focus on speech type of audio. Speech acquisition of the participant were recorded in two types of environments; controlled and uncontrolled environments. Types of speech recorded in each environment are normal, whispering and angry speech. Speech signal patterns are analysed using cross-correlation between three wavelets families consists of Coiflet 5, Daubechies 10 and Daubechies 9 in order to determine best fit the original signal.

Noise level estimation is a challenging area of digital image processing with a variety of applications, including image enhancement, image segmentation, and feature extraction. In this paper, an adaptive estimation of additive white Gaussian noise level based on the singular value decomposition (SVD) of images is proposed. The proposed algorithm aims to improve the performance of noise level estimation in the SVD domain at low noise levels. An initial noise level estimate is used to adjust the parameters of the algorithm in order to increase the accuracy of noise level estimation. The proposed algorithm exhibits the ability to adapt the number of considered singular values and to accordingly adjust the slope of a linear function that describes how the average value of the singular value tail varies with noise levels. Although, for each image, the proposed algorithm performs the noise level estimation twice in two distinct stages, the singular value decompositions are only performed in the first stage of the algorithm. The experimental results demonstrate that the proposed algorithm improves the noise level estimation at low noise levels without a significant increase in computational complexity. At noise level $\sigma = 15$ , the improvements in the mean square level are about 39% at the expense of slightly higher additional computational time.

We present an algorithm to estimate direction of arrival (DOA) of an incoming wave received at an array antenna in the scenario where the incoming wave is contaminated by the additive white Gaussian noise and scattered by arbitrary shaped 3D scatterer(s). We present different simulation examples to show the validity of the proposed method. It is observed that the proposed algorithm is capable of closely estimating the DOA of an incoming wave irrespective of the shape of the scatterer provided the decision is made over multiple iterations. Moreover, presence of noise affects the estimate especially in the case of low signal-to-noise ratio (SNR) that gives a relatively large estimation error. However, for larger SNR the DOA estimation is primarily dependent on the scatterer only.

Low-Density Parity-Check (LDPC) codes are one of the hottest topics in coding theory today. This code was invented in the early 1960s, and it having an amazing comeback in the last few years. In this paper, a scheme is proposed to analyze the performance of LDPC which is considered an important rival to turbo codes, Convolutional Code (CC), and Read Solomon (RS) in terms of performance and complexity. This code is utilized in the Orthogonal Frequency Division Multiplexing (OFDM) system to evaluate the improvement in the Bit Error Rate (BER) performance of the system. Comparison is done between turbo code and LDPC code through Additive White Gaussian Noise (AWGN) and fading channels. The effect of varying the code rate channel, number of iterations, and code length on the performance of the scheme is also explained.

Photovoltaic systems are the important part of the energy market in many countries around the world. Such systems contain several parts and one of them is the inverter to produce the AC signal. In this paper, an estimation method is used to obtain the value of frequency, amplitude and phase of the grid signal used to drive the inverter in a proper way. The method is based on the 3-point spectrum interpolation and I class Rife-Vincent time windows. The tested signal contains harmonics and AWGN noise to reflect real and practical measurement conditions. Additionally, simulations were performed for various values of measurement parameters to show broadly properties of the method. The estimation time is only up to two CiR (cycles of the signal in the measurement window). Harmonic components and noise negatively affect the accuracy but the method is so flexible that it can be adjusted to the needs of a current estimation. The estimation error for SNR = 50–60 dB and for two additional harmonics is in the order of approximately 10^−3.

En este trabajo se muestra las distribuciones de probabilidad que presentan los valores singulares, obtenidos de la matriz de autocorrelación de las muestras de señales continuas, adquiridas con muestreo Sub-Nyquist random demodulator. Los resultados provienen de un proceso experimental a nivel de simulación desarrollado en Matlab®. El proceso de simulación parte de la experimentación con tonos senoidales puros, continuando con señales con modulación am, y finalizando con modulación en frecuencia. Estas señales se encuentran inmersas en ruido blanco aditivo gaussiano, con el fin de acercarse a la realidad. Artí­culo Resultado de Investigación

Orthogonal Frequency Division Multiplexing (OFDM) has become a popular modulation method for high data rate wireless communications. In this paper, two schemes are proposed. In the first scheme the Bit Error Rate (BER) and the Packet Error Rate(PER) performancesof Fast Fourier Transform-FFT based OFDM are compared with Discrete Cosine Transform DCT -based OFDM using (QPSK) and (16 QAM)as modulation techniques over Additive White Gaussian Noise environment (AWGN) and Multipath Rayleigh Fading environment.To improve the performance of the uncoded OFDM schemes,the second coded scheme is investigated .Convolution coding is used to enhance the BER for the previous systems. The proposed systems have been tested and evaluated using MATLAB 7 package.

En este informe de trabajo de grado bajo la modalidad de investigación se presenta la implementación en bloques hardware de un sistema de transmisión y recepción de señales digitales moduladas en fase diferencial DBPSK y DQPSK. Los bloques del sistema de comunicación digital, se desarrollaron en el lenguaje de descripción de hardware VHDL y se utilizó aritmética en punto fijo para la expresión de los datos en cada una de las etapas de transmisión y recepción. Esta implementación se realizó con el ánimo de servir de apoyo en la investigación y la enseñanza en el área de circuitos digitales y áreas relacionadas con las comunicaciones, que será un componente del laboratorio modular de comunicaciones digitales, elaborado por los grupos de investigación GNTT y GRIAL de la Universidad del Cauca. En este caso los diseños de los bloques son creados y simulados a través de la herramienta System Generator con ayuda del Matlab, para posteriormente sintetizarlos en lenguaje VHDL a través del Project Navigator, y a su vez después de esto implementados a través de la herramienta ISE Impact sobre la FPGA Spartan3axc3s700a-4fg484 de Xilinx.

To show the ease of use of the programming environment of LabVIEW in the teaching of telecommunications at the undergraduate level, it is implemented and simulates a system of modern communications using QAM modulation of higher order and coding Reed-Solomon shortened version (204,188, t = 8), steps used in the transmission of digital terrestrial television DVB-T. The system model is proposed, a brief description of the VI is used and the performance curves of bit error rates are presented in an AWGN channel for each modulation schemes modeled.

This article presents a design methodology for designing an artificial neural network as an equalizer for a binary signal. Firstly, the system is modelled in floating point format using Matlab. Afterward, the design is described for a Field Programmable Gate Array (FPGA) using fixed point format. The FPGA design is based on the System Generator from Xilinx, which is a design tool over Simulink of Matlab. System Generator allows one to design in a fast and flexible way. It uses low level details of the circuits and the functionality of the system can be fully tested. System Generator can be used to check the architecture and to analyse the effect of the number of bits on the system performance. Finally the System Generator design is compiled for the Xilinx Integrated System Environment (ISE) and the system is described using a hardware description language. In ISE the circuits are managed with high level details and physical performances are obtained. In the Conclusions section, some modifications are proposed to improve the methodology and to ensure portability across FPGA manufacturers.

This article is dedicated to the model of low rate telemetry system, which has been developed for Matlab-Simulink environment. The purpose of this model is a research of the low rate telemetry transmission reliability in those cases where the modulation scheme carrier-subcarrier is used. This modulation scheme is widely used in case of the interplanetary spacecrafts. The main purpose of the model is a research of the effects of AWGN and phase noise especially for very low value of Eb/N0. Effects can be evaluated for the whole transmission system or for its components parts. The model described is very versatile and it can be easily modified or expanded.

Spread spectrum (SS) is a modulation technique in which the signal occupies a bandwidth much larger than the minimum necessary to send the information. A synchronized reception with the code at the receiver is used for despreading the information before data recovery. From a long period, Walsh codes and Gold codes have been used as spread spectrum codes in Code Division Multiple Access (CDMA) communications because of their ease of generation than the efficiency of these codes. Walsh codes are perfectly orthogonal binary user codes that have many popular applications in synchronous multicarrier communications although they perform poorly for asynchronous multi-user communications. Therefore, the nearly orthogonal Gold codes with their superior performance are the preferred user codes in asynchronous CDMA communications with small number of simultaneous users in the system due to their good auto-correlation (intracode correlation) and cross-correlation (inter-code) properties. Major drawback of these codes is that they are limited in number and in their lengths. In this paper, we performed MATLAB (7.1version) algorithm to obtain the new orthogonal sets of binary space for multiuser spread-spectrum communications. We compared their performance with existing codes like Gold and Walsh code families. Our comparisons include their time domain properties like auto and cross-correlations along with bit error rate (BER) performances in additive white Gaussian noise (AWGN) and Rayleigh channel for the synchronous and asynchronous DS-CDMA communications. It is shown that these codes outperform the Walsh codes significantly and they match in performance with the popular nearly orthogonal Gold codes closely for asynchronous multiuser communications in AWGN noise. It is also shown that all of the binary code families considered performed comparable for Rayleigh flat-fading channels. So these new codes can be used both for asynchronous and synchronous direct sequence spread spectrum CDMA communications. As a result, these can be used in both cases along with the advantage of their large availability and flexible code sizes.

Our work deals with studies of a noise behavior in space communication systems. Two most important noise types the additive thermal noise and the multiplicative phase noise, respectively, are included. A simple model of the narrowband communication system is created and simulated in the Ansoft Designer system simulator. The additive thermal noise is modeled as AWGN in a communication channel. The phase noise is produced in transmitter and receiver oscillators. The main intention is to investigate the receiver filter bandwidth decrease effect on powers of both noise types. Results proposed in this paper show that for defined system conditions and for a certain filter bandwidth value, the power of the multiplicative phase noise equals to the additive thermal noise power. Another decrease of the filter bandwidth causes the phase noise power exceeding. To demonstrate the noise behavior transparently, input system parameters are properly selected. All simulation results are documented by theoretical calculations. Simulation outcomes express a good coincidence with presumptions and calculations.

In this paper, a proposed model based on In-Place Wavelet Transform (IP-WT) was suggested to improve the performance of the Orthogonal Frequency Division Multiplexing (OFDM) under the Additive White Gaussian Noise (AWGN), and flat fading channel. The proposed model does not require additional arrays at each sweep such as in the ordered Haar wavelet transform; this ensures fast processing time with minimum memory size. The results extracted by a computer simulation and compared with the performance of the conventional model based on Fast Fourier Transform (FFT). As a result, it can be seen that the proposed technique has high performance improvement over the conventional OFDM system based FFT, where the Bit Error Rate (BER) is widely reduced under these models of channels.

In this paper the pulse response estimation of radio channel by Six-port reflectometer (SPR) is described. The measurement of pulse response is in real time, with baseband conversion and without demodulation. This system is simple, small, exact and inexpensive. In the present, it is insisted on signal processing in real time. In present time it is requested touse faster systems of signal processing, so the using of high performance digital devices is needed. Pulse response of radio channel, six-port reflectometer and radio channel are simulated in program language Delphi 7. In this work the pulse response measurement of MIMO radio channel by Six-port reflectometer technique. A pulse response matrix, Rayleighfading in the radio channel, SPR technology, AWGN radio channel has been simulated in program language Delphi 7.

Analisa efek Doppler ini menggunakan pemrograman Matlab dengan citra yang berukuran 160 128 piksel, pada eksentrisitas (e) satelit yang diasumsikan 0 sehingga bentuk lintasannya circular, dengan ketinggian 700 km dari stasiun bumi, sudut inklinasi sebesar 53° dan sinyal informasi ditransmisikan pada transmisi downlink dengan frekuensi carrier 2.4 GHz. Doppler shift terbesar terjadi saat satelit berada pada posisi terjauh dari terminal bumi yakni sebesar 51.077 KHz. Untuk menghilangkan efek Doppler maka data output dikompensasi dengan invers dari efek Doppler tersebut. Berdasarkan hasil simulasi diperoleh bahwa BER untuk frekuensi Doppler maksimum maupun minimum adalah mendekati atau hampir sama yaitu 0.5001 dan 0.4998, dan dalam keadaan tanpa terkena Doppler shift yaitu ± 0.0197 untuk SNR 0 sampai 10 dB. Sedangkan dari segi kualitas citra, diperoleh bahwa untuk Doppler shift maksimum, kualitas citra lebih baik dibandingkan saat Doppler shift minimum.

The Cyclic Prefix (CP) technique is widely used in Orthogonal Frequency Division Multiplexing (OFDM) systems. A CP of length greater than the channel order guarantees the orthogonality of the consecutive OFDM symbols. Therefore, the effects of Inter Symbol Interference (ISI) and Inter Carrier Interference (ICI) are cancelled. On the other hand, CP reduces the transmission efficiency. Conventional OFDM systems use constant length CP. For time varying channels, CP length may become shorter than channel order resulting in considerable loss in orthogonality and performance degradation. Otherwise, when CP length becomes much greater than channel order it results with time and power wasting, and hence decreasing transmission efficiency. This paper proposes the usage of a multipath delay-tracking module to provide the OFDM system with the actual channel order and accordingly the suitable CP length will be determined. Computer simulations show that the proposed system saves about 47.6% of the time and power spent by the same constant length CP OFDM system tested under the same conditions.