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IET Communications (17518628)18(17)pp. 993-1001
This paper investigates the changes in the waveform of a sinusoidal carrier resulting from amplitude modulation (AM) process. Based on this analysis, a novel method for extracting amplitude information is proposed. The proposed method uses the behaviour of the amplitude limitation which does not significantly affect the slope of the sinusoidal signal near zero crossing points. A simple comparator is used to convert the changes in sinusoidal slope near zero crossing points into pulse width changes. A simple circuit is proposed which keeps the output pulse width of the comparator constant by a simple control loop. The accuracy of the method is evaluated through simulation and is experimentally tested. If the modulation index is high and the amplitude of the input signal to the detector is limited, the proposed method can yield up at least 9 dB improvement in relative error power. However, if the modulation index is small, the improvement in relative error power can be at least 35 dB compared to other conventional types of AM demodulators. © 2024 The Author(s). IET Communications published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
In the context of medical body sensor networks that rely on visible light communication (VLC), adaptive modulation plays a crucial role. Despite VLC's advantages, challenges arise due to fluctuating signal strength caused by patient movement. To address this, we propose an adaptive modulation system that adjusts based on link conditions, specifically the signal-to-noise ratio (SNR). Our approach involves an uplink channel for feedback, allowing the receiver to select the appropriate modulation scheme based on measured SNR after noise mitigation. The analysis focuses on various medical situations and investigates machine learning algorithms. The study compares adaptive modulation based on supervised learning with that based on reinforcement learning. By implementing a bi-directional system with real-time modulation tracking, we demonstrate the effectiveness of adaptive VLC in handling environmental changes (interference and noise). Notably, the use of the Q-learning algorithm enables real-time adaptation without prior knowledge of the environment. Our simulation results show that photodetectors placed on the shoulder and wrist benefit significantly from this approach, experiencing improved performance. © 2024 IEEE.
Iranian Journal Of Electrical And Electronic Engineering (17352827)20(4)
Visible Light Communication, a key optical wireless technology, offers reliable, high-bandwidth, and secure communication, making it a promising solution for a variety of applications. Despite its many advantages, optical wireless communication faces challenges in medical environments due to fluctuating signal strength caused by patient movement. Smart transmitter structures can improve system performance by adjusting system parameters to the fluctuating channel conditions. The purpose of this research is to examine how adaptive modulation performs in a medical body sensor network system that uses visible light communication. The analysis focuses on various medical situations and investigates machine learning algorithms. The study compares adaptive modulation based on supervised learning with that based on reinforcement learning. The findings indicate that both approaches greatly improve spectral efficiency, emphasizing the significance of implementing link adaptation in visible light communication-based medical body sensor networks. The use of the Q-learning algorithm in adaptive modulation enables real-time training and enables the system to adjust to the changing environment without any prior knowledge about the environment. A remarkable improvement is observed for photodetectors on the shoulder and wrist since they experience more DC gain. © 2024, Iran University of Science and Technology. All rights reserved.
IEEE Transactions on Aerospace and Electronic Systems (00189251)58(3)pp. 2291-2303
The efficiency of using Karhunen-Loeve (KL) decomposition for retrieving global navigation satellite system (GNSS) signals from interference has been proven in the literature. The main drawback is its high computational cost. To get the potential benefit of its capability alongside reduction in computational demand, we consider an inverse strategy. Our proposed method applies the Marcenko-Pastur law to the sample covariance matrix of the received signal to systematically distinguish the jamming-related eigenvalues. Then, the KL coefficients of jamming signal are estimated and a synthetic replica of jamming signal is built and subtracted from the received signal. Simulation results indicate that our proposed method significantly outperforms other existing methods in terms of how it handles jamming signals in GNSS receivers. The impact of the jamming power on the performance of the proposed algorithm is also studied analytically. © 1965-2011 IEEE.
Digital Signal Processing: A Review Journal (10954333)129
Detection and estimation of feeble signals in noise is of great importance in practice. In this paper, we use the properties of eigen-space and eigen-spectrum of symmetric and Toeplitz covariance matrix, to address the problem of detecting/estimating very low signal-to-noise ratio (SNR) sinusoidal signals. We show that as the input signal vector length increases, the sign of the dominant eigenvalue of flipped covariance matrix changes with the same frequency as the input sinusoidal signal. Based on this fact, we introduce two algorithms to detect weak sinusoidal signal buried in additive white Gaussian noise. These algorithms have similarities with the bordered-autocorrelation-method Karhunen-Loeve transform (BAM-KLT) method, which is previously proposed in the literature for weak signal detection. However, the BAM-KLT has some limitations and bottlenecks in computational burden, performance and implementation. Moreover, its exact analysis in the discrete domain is missed in the literature. In this paper, we provide the detailed analysis of discrete BAM-KLT. We also show analytically that if the discrete BAM-KLT is applied to flipped covariance matrix instead of covariance matrix itself, its limitations and bottlenecks can be overcome. This idea is the basis of the proposed algorithms. The algorithms are studied analytically and evaluated through numerical simulation. The results show that the proposed methods effectively increase the capability of existing methods, in terms of detection/estimation performance, root-mean-square frequency error, contrast, as well as the number of detectable signal sources. © 2022 Elsevier Inc.
ICT Express (24059595)8(2)pp. 161-165
Steering vector and covariance matrix estimation mismatch along with moving jammer/platform, can affect the performance of null-steering beamformer. In this paper, by utilizing null-widening, null-deepening and diagonal loading shrinkage in space–time adaptive processing (STAP) structure, two methods for nullifying GNSS (global navigation satellite system) jamming/interference in cruise moving platforms are introduced. The enhanced performance of the proposed methods is investigated through numerical simulations. The results indicate improvement in the number of acquired GNSS satellites, in heavy jamming (GNSS denied) scenario, by reconstructing and acquiring at least 87% of satellites. © 2021 The Korean Institute of Communications and Information Sciences (KICS)
ICT Express (24059595)7(2)pp. 239-243
Global navigation satellite systems (GNSS) are the main navigation and control systems in unmanned aerial vehicles (UAVs) and their ground control stations. Without the GNSS signals, the UAV and its ground control stations cannot follow the waypoints of the desired path in jamming environments. In this paper, two new methods for detection of GNSS signal jamming attack for UAV ground control station are proposed based on random matrix theory. By using limiting distribution of mean vector and asymptotic behavior of the defined test statistic, a hypothesis test is introduced and evaluated to detect presence of jamming signal. Simulation results show that the proposed methods have significant performance in terms of detection and false alarm probabilities. Compared to existing methods, at low jamming-to-signal ratio (JSR), more than 2.5 dB improvement is achieved. © 2021 The Korean Institute of Communications and Information Sciences (KICS)
Signal, Image and Video Processing (18631711)15(4)pp. 835-842
The purpose of this paper is to develop a novel method based on recursive least squares (RLS) adaptive algorithm for progressive image transmission (PIT). The image is divided into non-overlapping blocks. Having an agreed vector sequence between the transmitter and the receiver, each block is related to a regressive model. Meanwhile, at the transmitter the blocks are estimated using the RLS algorithm. The high correlation between error vectors, regarding to the RLS execution, causes a very high compression rate in their transmission. The error vectors at the receiver are used to run the RLS algorithm and to estimate the image in a same manner. The method is easy to implement with a low computational complexity and achieves high quality, compared to other well-known methods. In comparison with its counterparts, simulation results show how efficient the proposed method is. © 2020, Springer-Verlag London Ltd., part of Springer Nature.
IET Radar, Sonar and Navigation (17518784)14(3)pp. 487-494
In this study, the authors address the issue of clutter mitigation in monostatic pulse-Doppler radars, using sub-Nyquist sampling and compressed sensing (CS) recovery algorithms. Generally, clutter is modelled as a coloured random process and a whitening filter is employed to maximise the signal to clutter ratio. Here, the authors apply this approach to the case in which the received signal sampling rate is much smaller than the Nyquist rate. They also generalise the recently proposed sub-Nyquist method based on difference set (DS) codes, which uses very few samples to detect targets in the presence of only white Gaussian noise. By using the frequency-coded modulation waveform with the frequencies selected in accordance to the DS, the detection performance of the proposed method can be significantly improved compared with the previously proposed sub-Nyquist methods in the presence of clutter. Furthermore, the authors show that the proposed method can increase the target recovery resolution due to the features of the DS codes and the employed CS model. © The Institution of Engineering and Technology 2020.
Signal Processing (01651684)177
Infrared small target detection in an infrared search and track (IRST) system is a challenging task. This situation becomes more complicated when high gray-intensity structural backgrounds appear in the field of view (FoV) of the infrared seeker. While the majority of the infrared small target detection algorithms neglect directional information, in this paper, a directional approach is presented to suppress structural backgrounds and develop a more effective detection algorithm. To this end, a similar concept to the average absolute gray difference (AAGD) is utilized to construct a novel directional small target detection algorithm called absolute directional mean difference (ADMD). Also, an efficient implementation procedure is presented for the proposed algorithm. The proposed algorithm effectively enhances the target area and eliminates background clutter. Simulation results on real infrared images prove the significant effectiveness of the proposed algorithm. © 2020
IEEE Transactions on Aerospace and Electronic Systems (00189251)56(6)pp. 4723-4733
The effect of jammer on radar or jamming performance has been and is being assessed on the basis of range reduction where consistency in tracking target ability is more important than range reduction in a tracking radar. A new criterion known as relative radar functionality destruction time is defined and introduced as the relative of functionality destruction time of radar to one period of jammer, where jammer signal and target echo power are of concern. The effective parameters in relative time of the receiver functioning destruction are assessed. Next, this criterion is applied in the assessment of simple conical scan radar receiver against a conventional jamming (sweep noise jamming). This criterion is modeled and simulated on a search radar in the jamming environment where the minimum required standard deviation of noise for destroying the radar function yields. By implementing the structure of a frequency modulated continuous wave tracking radar structure, a simple target based on digital radio frequency memory method and one type of jamming against this radar in a simultaneous manner, the functionality destruction is extracted for different radar parameters. This new criterion on outperforms its counterparts. © 1965-2011 IEEE.
IET Radar, Sonar and Navigation (17518784)14(12)pp. 1976-1983
Performance of global navigation satellite systems (GNSSs) mounted on aerial platforms could be degraded by the presence of jamming or spoofing threats. Detection of jamming and spoofing is essential considering practical applications of satellite navigation in passenger aircrafts, unmanned aerial vehicles (UAVs), helicopters and fighters. Different algorithms and methods have been proposed for detection of these threats; however, their usage has many limitations because of their demanding weight, size and computational complexity, when embedded on aerial systems. In this study, the authors develop a theoretical framework to detect the presence of the threat of UAVs. The idea is based on the fact that, due to the UAV motion, the samples of received signal power from a fixed threat and from a GNSS satellite have different empirical probability density functions. Moreover, by using two antennas (an omnidirectional and a down-tilted-directional), they introduce a new method to distinguish between aerial and ground-based threats. The proposed algorithms have a low-computational burden and can consider the fading loss as well. Simulation results show the superior performance of the proposed methods, in terms of detection and false alarm probability, compared to the existing methods. © The Institution of Engineering and Technology 2020.
Electronics Letters (1350911X)56(12)pp. 619-621
Sparse representation-based classification (SRC) possesses remarkable characteristics for application in synthetic aperture radar (SAR) automatic target recognition (ATR), for instance, inherent feature extraction and robustness to articulation, and so on. However, the performance of SRC is highly sensitive to parameters such as sufficient training samples, SAR images quality, and targets' changing conditions in depression, pose, configuration, and so on. Unfortunately, the training sample resources for SAR ATR are often expensive and scarce. Further, the targets in SAR images, even with slightest changes in conditions, display mutable characteristics attributable to unique SAR image formation, and speckle noise corruption. To overcome these obstacles, this Letter proposes to establish several compact and complementary dictionaries using monogenic signal's components of SAR images and Fisher discriminative dictionary learning. Then, an optimal decision fusion (ODF) strategy is proposed, which utilises SRC and the latter dictionaries for robust SAR ATR. Compared with single classifiers or multiple parallel classifiers, the proposed ODF increases the accuracy of recognition, while at the same time, decreases the complexity of the system. The proposed methods have considerable features making them applicable in practical situations. Based on the experimental results, the proposed methods outperform state-of-the-art approaches. © The Institution of Engineering and Technology 2020
IEEE Communications Letters (10897798)24(3)pp. 672-675
Pilot contamination (PC) is a practical drawback of massive multiple-input multiple-output (mMIMO) systems. It prevents the exploitation of the inherent spectral-efficiency (SE) of mMIMO systems, especially in dense networks. In this letter, we consider multi-antenna users in a multi-cell network and propose a novel approach based on interference alignment (IA) to remove PC. We show that the extra degrees of freedom (DoFs), provided by multi-antennas at the users' side, can be used efficiently when employed for pilot decontamination, especially in heavy-loaded networks. Thus, while the intra-cell interference is removed due to the properties of mMIMO the out-of-cell interference is eliminated by the proposed IA-based pilot decontamination. The proposed algorithm uses linear zero-forcing (ZF) and needs no continuous cooperation between the base stations (BSs). Moreover, the users need no channel state information (CSI). Our simulations show that the proposed method outperforms the conventional PC precoding algorithms significantly, particularly in heavy-loaded networks. © 1997-2012 IEEE.
Progress in Electromagnetics Research C (19378718)99pp. 251-267
Space borne accurate emitter localization has become an important and indispensable part of electronic warfare (EW) systems. In this paper, a system-level approach to design a space borne receiver for accurate localization of long range co-channel radars (e.g., a network of similar surveillance radars) is presented. Due to the wide frequency range of modern radar signals, the receiver should have a wide instantaneous bandwidth and requires high sampling rate analog-to-digital converters (ADCs). To address this issue, we propose a receiver structure with an appropriate sub-Nyquist sampling scheme and fast sparse recovery algorithm. The proposed sub-Nyquist sampler employs a three dimensional uniform linear array (ULA), followed by a modulated wideband converter (MWC). To accurately estimate the location of the co-channel radars from sub-Nyquist samples, a novel quad-tree variational Bayesian expectation maximization (QVBEM) algorithm is proposed. The QVBEM algorithm minimizes the computational load and grid mismatch error by iteratively narrowing the search area. This is done by a smart grid refinement around radars’ locations. To evaluate the performance of the proposed receiver, location finding of pulsed radars is studied through numerical simulations in various scenarios. The results show that the proposed QVBEM method has a significantly lower estimation error than conventional deterministic and Bayesian approaches, with a reasonably computational complexity. © 2020, Electromagnetics Academy. All rights reserved.
Signal, Image and Video Processing (18631711)14(2)pp. 397-405
Diagnosis of Parkinson’s disease (PD) in the early stages is very critical for effective treatments. In this paper, we propose a simple and low-cost biomarker to diagnose PD, using the electroencephalography (EEG) signals. In the proposed method, EEG is used to detect the brain electrical activities in internal regions of brain, e.g., basal ganglia (BG). Based on the high correlation between PD and brain activities in the BG, the proposed method provides a highly accurate PD diagnostic measure. Moreover, we obtain a quantitative measure of the disease severity, using the spectral analysis of extracted brain sources. The proposed method is denoted by Parkinson’s disease stage detection (PDSD). The PDSD includes brain sources separation and localization steps. The accuracy of the method in detection and quantification of PD is evaluated and verified by using information of ten patients and ten healthy people. The results show that there is a significant difference in the number of brain sources within the BG region, as well as their power spectral density, between healthy cases and patients. The accuracy and the cross-validation error of PDSD to detect PD are 95% and 6.25%, respectively. Furthermore, it is shown that the total power of extracted brain sources within the BG region in the α and β rhythms can be used effectively to determine the severity of PD. © 2019, Springer-Verlag London Ltd., part of Springer Nature.
Radio Science (00486604)55(3)
In this paper, we study the estimation of the spatially sparse radio emitter locations from space, via the proposed Quad-tree variational Bayesian expectation maximization (QVBEM) algorithm. First, we assume that the emitters are approximately placed on a uniform grid points in the region under surveillance. The VBEM algorithm is applied and the points exceeding the threshold level are considered as potential targets. Then, the grids are refined around the potential targets via the Quad-tree algorithm, and the process is iterated. It allows us to find the location of sparse emitters with much less computational complexity due to the use of fewer grid points. Simulation results show the superiority of the QVBEM to existing methods. The impact of threshold value on the performance of QVBEM is also studied. © 2020. American Geophysical Union. All Rights Reserved.
In order to solve the problem of multipath propagation of sound waves generated by sea surface reflection, a time difference of arrival (TDOA) localization method based on maximum or minimum value screening is proposed. Firstly, based on the propagation characteristics of underwater acoustic channel, the distance equation of propagation path in the case of sea surface reflection and linear propagation is derived, and four kinds of measurement value equations of TDOA localization in the deepsea multipath environment are established. Then, the measured TDOA values of linear propagation of sound waves are obtained by screening the measured TDOA values for the twice maximum or minimum value. Finally, the underwater target localization is realized based on Chan and Taylor algorithm. Simulation results show that the localization accuracy of this algorithm is within 1 meter in the deep sea multipath environment with the ocean depth of less than 100 meters, which is greatly improved compared with the multipath TDOA algorithm based on statistical characteristics. The proposed algorithm can effectively eliminate the multipath error in the deep-sea environment and has high practicability and reliability. © 2019 IEEE.
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 420-423
In a radar and infrared sensor synergistic tracking system, an improved radar and infrared sensor cooperative tracking algorithm is proposed based on interacting multiple model and unscented Kalman filter (IMMUKF), which can reduce the radar radiation time. Firstly, the tracking model for the radar and infrared sensor is built and IMMUKF is employed as a filter. Secondly, a novel tracking quality factor is designed for control the radar's radiation. The residual of the new information obtained by comparing the filtering result with the estimated measurement is selected as a criterion. Finally, the working time of radar and infrared sensor is adaptively controlled. And the simulation results show that the proposed method can reduce the radiation time with excellent tracking accuracy. © 2019 IEEE.
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 307-308
This paper presents a novel array allocation method for radar and communication integration. Firstly, the math model between the array resource and tracking and communication performance is built and analyzed.The primary objectives of radar and communication are then designed respectively to minimize tracking error and bit error rate in the presence of multiple target tracking and channel communication.Furthermore, we transfer both problems to convex problems which are solved by checking the conditions of Karush-Kuhn-Tucker(KKT). Simulation results on array allocation performance of the proposed method and conventional one are conducted finally, which also prove effectiveness of the proposed method. © 2019 Copyright is held by the owner/author(s).
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025
Stepped frequency radars have been extensively used to achieve high range resolution. They use inverse discrete Fourier transform (IDFT) for processing a set of different frequency pulses in radar receiver. Due to the usually small number of targets in radar scene, there is a sparsity in the time, frequency and space domain. Thus, compressive sensing (CS) is a promising solution to target detection and estimation. In this paper, we propose a novel sampling scheme using difference set codes in CS-based stepped frequency radars. In the proposed method, the required sampling rate for signal recovery can be far less than the Neuquist rate11By the Neuquist rate, we mean twice the maximum frequency component of signal., Simulation results show that by using difference codes for pulsating pattern, high range resolution can be achieved, and at the same time, a significant reduction in the number of transmitted pulse is obtained, compared to conventional IDFT-based processing method. © 2019 IEEE.
IEEE Transactions on Signal Processing (19410476)67(1)pp. 136-148
In this paper, we consider compressive sensing (CS)-based recovery of delays and Doppler frequencies of targets in high resolution radars. We propose a novel sub-Nyquist sampling method in the Fourier domain based on difference sets (DS), called DS-sampling, to create dictionaries with highly incoherent atoms. The coherence of the dictionary reaches the Welch minimum bound if the DS-sampling is employed. This property let us to implement sub-Nyquist high resolution radars with minimum number of samples.1 Two low-complexity recovery methods are developed and sufficient condition of target recovery with specific resolution obtained theoretically for noisy and noiseless conditions. We also propose a new waveform, called DS-frequency coded modulated waveform, to boost the recovery performance of the sub-Nyquist radar in noisy environments. The proposed method solves some of the common problems in many CS-based radars and overcome disadvantages of the conventional Nyquist processing (i.e., matched filtering) in high resolution radar systems. The proposed method allows us to design sub-Nyquist radars, which require less than 2% of Nyquist samples and recover targets without resolution degradation in comparison to the conventional Nyquist processing. © 2018 IEEE.
IEEE Signal Processing Letters (10709908)26(12)pp. 1917-1921
Blind source separation (BSS), i.e. extracting unknown sources from mixtures of them, has attracted great interest in various fields of signal processing, for instance in neurophysiological data analysis. By increasing the availability of multiple and complementary data, associated with a given case, many joint BSS (JBSS) algorithms have been developed, which attempt to jointly analyze all datasets and meaningfully integrate information from them. In this letter, we study the special case of multiple datasets analysis, where all datasets share the same set of underlying sources which contribute to different datasets through different mixing matrices. With the aim of efficient dimension reduction, we propose a novel joint preprocessing method to accurate and robust source separation from multipldatasets. We sequentially separate the source with the most significant impact on all datasets on average. To this end, the magnitudes of source projections on the subspaces spanned by each dataset are obtained and sum of their $p{th}$ power is maximized. Dependency between datasets can be efficiently treated using $p$. Simulation results show the considerable improvement of the proposed method over existing JBSS algorithms. © 1994-2012 IEEE.
AEU - International Journal of Electronics and Communications (16180399)110
Interference alignment (IA) is an effective scheme for counteracting multi-user interference in wireless networks. Unfortunately, IA is sensitive to channel-state-information (CSI) imperfections. Achieving perfect CSI knowledge at a central node in large scale antenna wireless networks implies a huge feedback which is prohibitive. In this paper, we assume a distributed multicellular scenario, where there is no central node that knows global CSI and optimizing IA's precoder and combiner matrices is done by exchanging the local channel information between users and base stations (BSs) in several iterations. By using low-rank matrix approximation theory, we propose an efficient method to iteratively optimize precoder and combiner matrices for distributed IA. In each iteration, only a part of the CSI is fed back to BSs. More precisely, based on the latest available CSI and certain performance criteria, a few columns of the effective channel are sent back to the transmitters to approximate the interference covariance matrix which is then used to update the precoder matrices. We also propose a new method for quantizing the channel information matrix non-uniformly, which improves upon the conventional channel feedback quantization techniques. We evaluate the proposed methods by simulating a cellular network with various number of BS antennas and different feedback channel capacities. Simulation results show that our methods outperform both the conventional and improved channel feedback quantization algorithms significantly. © 2019 Elsevier GmbH
Multidimensional Systems And Signal Processing (15730824)30(1)pp. 93-117
An anti-deception jamming technique is proposed for moving target indication in a pulse-Doppler (PD) radar. The deceive targets are produced by digital radio frequency memory, which tries to pull off the range and velocity gates of real targets. Similar to orthogonal frequency division multiplexing, we use different sets of orthogonal sub-carriers in consecutive coherent pulse intervals (CPIs). By changing sub-carriers in different CPIs, we show that the deceive targets appear as interference in receiving signals. The generalized likelihood ratio test is used for detection and discrimination of real targets. The performance of the proposed method is achieved analytically and by simulations. Furthermore, we implement a hardware block using a TMS6416-DSK DSP for a PD radar prototype exploiting the proposed algorithm to deception discrimination. The presented results demonstrate the good accordance with theoretical predictions. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.
Infrared Physics and Technology (13504495)89pp. 387-397
False alarm rate and detection rate are still two contradictory metrics for infrared small target detection in an infrared search and track system (IRST), despite the development of new detection algorithms. In certain circumstances, not detecting true targets is more tolerable than detecting false items as true targets. Hence, considering background clutter and detector noise as the sources of the false alarm in an IRST system, in this paper, a false alarm aware methodology is presented to reduce false alarm rate while the detection rate remains undegraded. To this end, advantages and disadvantages of each detection algorithm are investigated and the sources of the false alarms are determined. Two target detection algorithms having independent false alarm sources are chosen in a way that the disadvantages of the one algorithm can be compensated by the advantages of the other one. In this work, multi-scale average absolute gray difference (AAGD) and Laplacian of point spread function (LoPSF) are utilized as the cornerstones of the desired algorithm of the proposed methodology. After presenting a conceptual model for the desired algorithm, it is implemented through the most straightforward mechanism. The desired algorithm effectively suppresses background clutter and eliminates detector noise. Also, since the input images are processed through just four different scales, the desired algorithm has good capability for real-time implementation. Simulation results in term of signal to clutter ratio and background suppression factor on real and simulated images prove the effectiveness and the performance of the proposed methodology. Since the desired algorithm was developed based on independent false alarm sources, our proposed methodology is expandable to any pair of detection algorithms which have different false alarm sources. © 2018 Elsevier B.V.
A real-Time algorithm for spectrum balancing (SB) of digital subscriber lines (DSL) is proposed. A real-Time SB algorithm is an algorithm for which the PSD and power regulatory constraints are always met after each iteration. The algorithm is based on fixed-point iterations and has a low computational complexity. Our simulations show that the proposed technique converges much faster than a recently proposed real-Time SB algorithm. Moreover, the achievable bit rates by the algorithm are near-optimal. Particularly the algorithm outperforms the iterative SB (ISB) algorithm in large scenarios. © 2018 IEEE.
IET Radar, Sonar and Navigation (17518784)12(8)pp. 889-899
The electronic support (ES) receivers require wide instantaneous bandwidth as a result of a wide-frequency range of modern radar signals. Thus, analogue-to-digital converters (ADCs) with high sampling rates are required for digital ES receivers. One of the bottlenecks in designing such systems is the high power consumption of the back-end ADCs at high sampling rates. In this study, a system-level approach with the goal of minimising the required digitisation rate is presented by exploiting compressive sampling. Using the proposed receiver structure, the location finding of pulsed radars in wideband scenarios is studied. To fulfil the need for frequency and position finding, the proposed receiver employs a three-dimensional antenna array, followed by radio-frequency back-end and ADC blocks, inspired by the modulated wideband converter technique. Furthermore, an algorithm based on Bayesian compressed sensing, incorporating off-grid techniques, is employed to jointly estimate the azimuth and the elevation angles of incoming signals, as well as their carrier frequencies. Simulation results are provided to support the theoretical results obtained in this study. The results show that the proposed off-grid Bayesian method has a significantly lower mean square estimation error than the conventional deterministic approaches, while its average computation complexity can be reduced in multi-snapshot scenarios. © The Institution of Engineering and Technology 2018.
Wireless Personal Communications (1572834X)95(3)pp. 3167-3184
This paper focuses on beamforming problem in a cooperative cognitive radio communication system where primary users (PUs) coexist with a secondary user (SU). An adaptive partial feedback structure for computing the channel state information is proposed. PUs and SU receivers execute their associated normalized least mean square adaptive algorithms. The output of each algorithm contains an estimate of the related channel coefficients. The receivers also reply the quantized step-size values of their algorithms via feedback channel to the transmitter, which empower it to execute these algorithms simultaneously. The transmitter iteratively employs the feedback information to estimate the channel weights and uses them for its beamforming scheme, in such a way that the SU receiver’s channel gain is maximized while the interference on PUs is maintained below a predefined level. Analysis of the proposed method shows that, with a simple modification, the required bits in feedback channel are considerably reduced. The method is applicable for time-varying systems. Besides, when the cross correlation matrix is the only available channel information between primary and secondary networks, a simple and compatible beamforming scheme is proposed. Simulation results evaluate the reasonable performance of the proposed method. © 2017, Springer Science+Business Media New York.
IET Radar, Sonar and Navigation (17518784)11(2)pp. 330-340
In this study, the use of a family of Chebyshev chaotic maps for pulse compression in multiple input-multiple output (MIMO) radars is studied. It is shown that, these one-dimensional chaotic maps, which are amongst the simplest chaotic systems, can produce arbitrary number of sequences with arbitrary length, low peak-to-average power ratio (PAPR), high merit factor (MF) or equivalently low integrated side-lobe ratio (ISLR), very low peak side-lobe ratio and low cross-correlation levels. The complexity of algorithm for generating sequences in this method is linear. Besides, because of the flat spectrum of the generated sequences, high spectral efficiency can be achieved utilising these sequences. Moreover, simplicity of the map results in cheap building blocks of MIMO radars. Additionally, a simple method to improve the autocorrelation side-lobe is given. By lowering the autocorrelation side-lobes, ISLR or equivalently MF is enhanced. Nevertheless, in comparison with well-designed unimodular sequences, the produced sequences show higher PAPRs. By utilising a PAPR reduction mechanism, this shortcoming is alleviated. © The Institution of Engineering and Technology.
IEEE Transactions on Signal Processing (19410476)65(3)pp. 690-704
Controlling peak side-lobe level (PSL) is of great importance in high-resolution applications of multiple input multiple output (MIMO) radars. In this paper, designing sequences with good autocorrelation properties are studied. The PSL of the autocorrelation is regarded as the main merit and is optimized through newly introduced cyclic algorithms, namely, PSL minimization quadratic approach, PSL minimization algorithm where the smallest rectangular, and PSL optimization cyclic algorithm. It is revealed that minimizing PSL results in better sequences in terms of autocorrelation side lobes when compared with traditional integrated side-lobe level minimization. In order to improve the performance of these algorithms, fast-randomized singular value decomposition is utilized. To achieve waveform design for MIMO radars, this algorithm is applied to the waveform generated from a modified Bernoulli chaotic system. The numerical experiments confirm the superiority of the newly developed algorithms compared to high-performance algorithms in monostatic and MIMO radars. © 2016 IEEE.
Signal, Image and Video Processing (18631711)11(6)pp. 1025-1032
In this article, the effects of the number of quantization levels and the sampled signal are considered in the airborne digital radio frequency memory (DRFM). A different model of analog-to-digital conversion is proposed. The histogram of the proposed model is utilized to release synchronization of signals for integration. Then, the local variance technique is used to highlight the differences between a continuous signal and the sampled pre-quantized DRFM signal. Furthermore, the effects of analog reconstruction filter on a DRFM signal are considered. Simulation results show the efficiency and robustness of the proposed method. Finally, a hardware implementation is provided to prove the proposed method. © 2017, Springer-Verlag London.
Wireless Personal Communications (1572834X)97(3)pp. 3875-3889
In this paper a sequential algorithm is proposed for joint blind channel equalization and decoding for orthogonal frequency-division multiplexing (OFDM) in frequency selective channels. This algorithm offers a recursive method to sequentially calculate the posterior probability for maximum a posteriori detection. Recursive calculations are done along the indexes in each OFDM symbol using a particle filter. By defining an appropriate importance function, and a proper prior probability distribution function for the channel tap coefficients (and marginalizing it), an efficient method is presented for joint equalization and channel decoding in OFDM based systems. Performance of the proposed detector is evaluated using computer simulations and its bit error rate is compared with the trained turbo equalizer and a conventional particle filter-based method. The results show that the proposed method outperforms the previously presented particle filter-based method without a need for training data. © 2017, Springer Science+Business Media, LLC.
IEEE Access (21693536)5pp. 11455-11467
In this paper, the effects of phase noise difference in receiving signals are introduced to discriminate targets. Oscillators and signal sources have their own phase noise levels and specific patterns. This property can be used for discriminating a real target from the airborne digital radio frequency memory (DRFM) in continuous wave tracking radar sensor networks with linear frequency modulation. A simulated signal made through complex circuits by DRFM has higher phase noise with different patterns. To investigate the phase noise level of oscillators, a system is provided to measure the phase noise. Then, the probability of detection ( P-{D} ) and the probability of false alarm ( P-{fa} ) can be achieved by defining an appropriate threshold to evaluate the performance of discriminating between real targets and DRFM targets. The phase noise powers are measured through the same sets of circuits and coherent time periods in various radar sensor systems. To control the amplitude fluctuation of the received signal, the normalization of signal phase power is defined in phase noise bandwidths. The likelihood ratio test is used for target discrimination by a threshold level to achieve the minimum P-{fa} of target discrimination. The proposed method has a simple structure without any additional complexities, and is easily compatible with common radar systems. Two real DRFM systems are used to evaluate the performance of the proposed method in both the L-band and X-band frequencies. The presented results are investigated in different ranges, Doppler frequencies, signal-to-noise ratios, and signal-to-jammer ratios. The experimental results prove the capability of proposed method in radar sensor networks. © 2013 IEEE.
Chinese Optics Letters (16717694)15(10)
In this Letter, a method based on the effects of imperfect oscillators in lasers is proposed to distinguish targets in continuous wave tracking lidar. This technique is based on the fact that each lidar signal source has a specific influence on the phase noise that makes real targets from the false ones. A simulated signal is produced by complex circuits, modulators, memory, and signal oscillators. For example, a deception laser beam has an unequal and variable phase noise from a real target. Thus, the phase noise of transmitted and received signals does not have the same power levels and patterns. To consider the performance of the suggested method, the probability of detection (PD) is shown for various signal-to-noise ratios and signal-to-jammer ratios based on experimental outcomes. © 2017 Chinese Optics Letters.
Electronics Letters (1350911X)53(12)pp. 808-810
By using the effects of non-ideal oscillators, a technique is proposed to discriminate targets in continuous wave (CW) tracking radar. This method is based on the fact that each oscillator has an individual effect on the phase noise that helps to recognise real targets from the simulated ones. A simulated fake target, made through complex circuits, e.g. a digital RF memory, has a different phase noise from a real backscatter. Therefore, the transmitted and received signals are different in phase noise levels and patterns. To evaluate the performance of the proposed technique, the probability of detection (PD) is shown in different signal-to-noise ratios, ranges, and signal-tojammer ratios based on an experimental setup. © The Institution of Engineering and Technology.
Transactions on Emerging Telecommunications Technologies (21613915)28(6)
In this paper, we consider the weighted sum rate (WSR) maximization problem in a partially coordinated multiple-input multiple-output multicell broadcast channel with constraints on base stations' transmit powers where the communication is based on dirty paper coding. To be able to obtain a computationally efficient solution for this non-convex optimization problem, we solve it by a fast algorithm for WSR maximization under per-user power constraints. The main idea is to define virtual per-user power constraints that add up to the per-base station power budgets in each cell and optimize the per-user power constraints to maximize the WSR. We propose two computationally efficient power allocation algorithms to find the per-user power constraints, namely, the waterfilling-based power update and the gradient descent–based power update algorithms. In the latter one, we find a closed-form expression for the derivative of the maximum of WSR wrt the per-user power constraints resulting in a considerable reduction in the complexity. The resulting algorithms are computationally efficient, and our simulation results show that they achieve significantly higher bit rates than the current algorithms at the same signal-to-noise power ratio. Copyright © 2016 John Wiley & Sons, Ltd.
Sabahi, M.F.,
Shahtalebi, K.,
Rezaei M.J.,
Zaeem R.M.,
Sadeghi R.,
Rezaei M.J.,
Rezaei M.J.,
Sabahi, M.F.,
Sabahi, M.F.,
Shahtalebi, K.,
Shahtalebi, K.,
Zaeem R.M.,
Zaeem R.M.,
Sadeghi R.,
Sadeghi R. 2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 124-127
In this paper, a new fairness index to measure resource allocation performance for real-time/delay-tolerant applications is introduced. This index can suggest a new approach for resource allocation. There are several methods have been previously introduced in the literature for resource allocation in cellular networks. Fairness index have an important role to evaluate the performance of these methods. Here, we focus on utility function based resources allocation and related algorithms. According to the introduced method, the base station (BS) allocates resources based on different services requirements. Because of using the appropriate utility function for each application, the requested quality-of-services (QoS) are satisfied. The new well-defined fairness index shows that the proposed method has a good performance for different real-time/delay-tolerant applications. Additionally, numerical results show that this approach is able to improve other important indicators such as throughput and mean opinion score (MOS) as well. © 2015 IEEE.
IET Communications (17518628)10(13)pp. 1655-1664
The authors study the power spectrum density (PSD) estimation of wideband wide-sense stationary (WSS) signals with sub-Nyquist sampling rate. Owing to the large bandwidth, Nyquist rate sampling of such signals needs very high rate analogue-to-digital converters. It is important to note that PSD estimation does not necessarily require reconstruction of the original signal. Indeed, the power spectrum can be directly obtained from sub-Nyquist samples. In this study, a new method for reconstructing the power spectrum in the frequency domain for WSS signals is presented. The main idea is to divide the whole spectrum into N equal-length segments and calculate the average PSD in each segment using a frequency-domain representation of sub-Nyquist samples. In addition, the capability of the proposed method, as a detector of spectrum holes, is studied using receiver operating characteristic (ROC) curves. Then, the analysis of false alarm probability is provided. Simulation results for the additive white Gaussian noise channel and the slowly fading frequency selective channel show that the proposed method considerably outperforms available techniques. © The Institution of Engineering and Technology 2016.
Wireless Personal Communications (1572834X)87(1)pp. 45-62
Optimal resource management in a cognitive radio network has been studied using the game theory. Based on personal interests, users select their own desired utility function and compete for channel and power selection. This non-cooperative approach is controlled through an appropriate pricing method. We have shown that if the utility function in a cooperative potential game is used as the pricing function in a non-cooperative network, the game governing the non-cooperative network will also become potential and will thus converge to Nash equilibrium. The existence of selfish users will cause the network to be unstable, the one which has presumptively been designed with users’ cooperation. Besides, it decreases resource utilization gain. Using the recommended pricing has been shown to equilibrate the network. The equilibrium points also enjoy some optimality criteria such as Pareto optimality. By conducting simulations and studying parameters like sum-rate of network and its total interference, it is shown that resource utilization will also approaches to optimal states. © 2015, Springer Science+Business Media New York.
One of the main impairments for advanced digital subscriber line (DSL) systems is crosstalk. Crosstalk can be effectively cancelled using vectoring. However, some challenges such as implementation and computational complexities associated with full users' coordination when the number of DSL lines is large or when they are not co-located at any end make full vectoring impractical in many scenarios. In this paper, we consider interference alignment (IA) as an alternative technique when full vectoring is not practical. We apply this technique to both non-coordinated and partially coordinated very fast digital subscriber line 2 (VDSL2) systems. The computational complexity of IA can be prohibitive, however, we reduce it by applying IA to subsets of tones resulting in a computational complexity much smaller than that of vectoring. We also use iterative IA algorithms for performance improvement. Simulation results show that IA increases the achievable rates of VDSL2 loops considerably without a need for signal coordination among users. Moreover, when IA and partial vectoring are applied together, the users can achieve bit rates moderately close to that of a crosstalk-free network. © 2016 IEEE.
Infrared Physics and Technology (13504495)77pp. 27-34
Small target detection is one of the major concern in the development of infrared surveillance systems. Detection algorithms based on Gaussian target modeling have attracted most attention from researchers in this field. However, the lack of accurate target modeling limits the performance of this type of infrared small target detection algorithms. In this paper, signal to clutter ratio (SCR) improvement mechanism based on the matched filter is described in detail and effect of Point Spread Function (PSF) on the intensity and spatial distribution of the target pixels is clarified comprehensively. In the following, a new parametric model for small infrared targets is developed based on the PSF of imaging system which can be considered as a matched filter. Based on this model, a new framework to boost model-based infrared target detection algorithms is presented. In order to show the performance of this new framework, the proposed model is adopted in Laplacian scale-space algorithms which is a well-known algorithm in the small infrared target detection field. Simulation results show that the proposed framework has better detection performance in comparison with the Gaussian one and improves the overall performance of IRST system. By analyzing the performance of the proposed algorithm based on this new framework in a quantitative manner, this new framework shows at least 20% improvement in the output SCR values in comparison with Laplacian of Gaussian (LoG) algorithm. © 2016 Elsevier B.V.
Electric Power Components and Systems (15325016)44(19)pp. 2212-2223
The main aim of this work is to present the results of the shape design optimization process of an interior permanent-magnet synchronous motor. The shape design optimization process is accomplished based on the variations of the rotor structure using the Taguchi method. The time-stepping finite-element method is used for analysis of the motor. It is found that the optimal two-layer Machaon design has the lowest torque pulsation compared with the other structures. Finally, the optimized Machaon and preliminary one-layer interior permanent-magnet synchronous motors, which are amended from industrial three-phase induction motors, are manufactured. The results of numerical, analytical, and practical tests are in good agreement. © 2016, Copyright © Taylor & Francis Group, LLC.
Wireless Personal Communications (1572834X)85(3)pp. 1351-1365
To successfully design and evaluate the performance of multiple-input multiple-output (MIMO) mobile-to-mobile (M-to-M) communication systems, it is necessary to have detailed knowledge of the multipath fading channel and its statistical properties. In this paper, we propose a full-three-dimensional (3-D) reference model for wideband MIMO M-to-M communication channels. From the reference model, the corresponding space-time-frequency correlation function is derived, assuming 3-D non-isotropic and single-bounce scattering environment. This model includes many existing models as special cases. Some numerical results are presented to validate special cases of the proposed reference model. © 2015, Springer Science+Business Media New York.
In this paper, we address the problem of direction-of-arrival (DOA) estimation using a novel spatial sampling scheme based on difference set (DS) codes, called DS-spatial sampling. It is shown that the proposed DS-spatial sampling scheme can be modeled by a deterministic dictionary with minimum coherence. We also develop a low complexity compressed sensing (CS) model for DOA estimation. The proposed methods can reduce the number of array elements as well as the number of receivers. Compared with the conventional DOA estimation algorithm, the proposed sampling and processing method can achieve significantly higher resolution. © 2015 IEEE.
Wireless Personal Communications (1572834X)85(4)pp. 1869-1882
This paper investigates reducing the computation complexity in resource allocation of cognitive radio networks. The orthogonal frequency division multiple access scheme is assumed. Secondary users are permitted to capture any portion of the bands while their interference to the primary users remains below a given threshold level. A very simple method with low complexity for resource allocation is proposed in which the throughput logarithmic function is changed into a linear form. The method is applicable in a wide range of problems where the efforts are maximizing the throughput under power budget and interference constraint. Although the proposed method achieves the optimal solution in low channel-gain-to-noise ratio (CNR) cases, the results for high CNRs are also satisfactory. Comparisons between the proposed method and previous works via simulation show the superior performance of the proposed method. © 2015, Springer Science+Business Media New York.
Analog Integrated Circuits and Signal Processing (09251030)85(3)pp. 505-512
In this paper, two various applications of elliptic discrete Fourier transform type I (EDFT_I) are presented in the communication area. In the first application, EDFT_I is applied to reduce the additive uniform and Gaussian noise in the sinusoidal signal. The noise reduction is independent from the type of noise and the corresponding amplitude. In the second application, an EDFT_I-based receiver has been proposed which improves the signal to noise at least about 2 dB for the same error-probability as compared with the optimum receiver considering an additive non-Gaussian noise. In this approach, a binary orthogonal signaling is created using the EDFT_I, which cosine and sine signals are used as carrier for 0 and 1 information. Moreover, for an additive non-Gaussian noise, the proper choice of this transform’s parameters as well as the decision threshold, results in improving the accuracy of digital information’s transmission. © 2015, Springer Science+Business Media New York.
AEU - International Journal of Electronics and Communications (16180399)69(10)pp. 1445-1452
Abstract In this paper an importance sampling (IS)-based technique is proposed to achieve the blind equalizer and detector for chaotic communication systems. Chaotic signals are generated using nonlinear dynamical systems. These signals have wide applications in communication as a result of their appropriate properties such as pseudo-randomness, large bandwidth, and unpredictability for long time. Based on the different chaotic signal properties, different communication methods such as chaotic modulation, masking, and spread spectrum have been proposed before. In this paper, chaos masking is adopted for transmitting modulated message symbols over an unknown channel, in which the joint demodulation and equalization is a nonlinear problem. Several methods such as extended Kalman filter (EKF), particle filter (PF), minimum nonlinear prediction error (MNPE), have been previously presented for this problem. Here, a new approach, based on Monte Carlo sampling, is proposed to joint channel equalization and demodulation. At the receiver end, importance sampling is used to detect binary symbols according to maximum likelihood (ML) criterion. Simulation results show that the proposed method has better performance, compared to existing methods, especially at low SNR. © 2015 Elsevier GmbH.
Spectrum Sensing (SS) is the first step to establish a cognitive radio network. Current non-cooperative spectrum sensing methods exhibit a poor performance in certain applications. Therefore, cooperation can be pursued to improve the sensing performance. In addition, some applications need overall space-frequency perspective of spectrum in which spectrum mapping can be applied instead of point-by-point spectrum sensing. Generally, the spectrum mapping algorithms lead to computationally extensive optimization problems. Reducing the computational costs of algorithms, would extend the application domain of these methods. In this paper we propose a solution to attain space-frequency spectrum map of cognitive radio networks with a low computational complexity using the past behavior of space and frequency variations in time. The proposed algorithm offers a solution to reduce complexity and estimation error of spectrum sensing by forming a sensing time queue. © 2014 IEEE.
In this paper a new method is introduced for evaluating effect of sweep noisy barrage jammer on tracking radars. In this method, jammer interfering energy that injected in radar receiver bandwidth is calculated during jammer scan period, then according to the minimum signal to jammer power ratio that is required for receiver proper functioning (kJα), ratio of receiver proper functioning time to the jamming scan period or ratio of receiver destruction time to the jammer scan period is determined. These parameters are more important than only presence of jammer in receiver bandwidth. We define new performance criteria to evaluate the jammer effect on tracking radars. This is done by considering ratio of receiver destruction time to jammer scan period and the ratio of received power from the jammer to received power from the target at receiver front end. © 2014 IEEE.
International Journal of Electronics (13623060)101(12)pp. 1694-1704
The most important goal of spreading spectrum communication system is to protect communication signals against interference and exploitation of information by unintended listeners. In fact, low probability of detection and low probability of intercept are two important parameters to increase the performance of the system. In Direct Sequence Code Division Multiple Access (DS-CDMA) systems, these properties are achieved by multiplying the data information in spreading sequences. Chaotic sequences, with their particular properties, have numerous applications in constructing spreading codes. Using one-dimensional Bernoulli chaotic sequence as spreading code is proposed in literature previously. The main feature of this sequence is its negative auto-correlation at lag of 1, which with proper design, leads to increase in efficiency of the communication system based on these codes. On the other hand, employing the complex chaotic sequences as spreading sequence also has been discussed in several papers. In this paper, use of two-dimensional Bernoulli chaotic sequences is proposed as spreading codes. The performance of a multi-user synchronous and asynchronous DS-CDMA system will be evaluated by applying these sequences under Additive White Gaussian Noise (AWGN) and fading channel. Simulation results indicate improvement of the performance in comparison with conventional spreading codes like Gold codes as well as similar complex chaotic spreading sequences. Similar to one-dimensional Bernoulli chaotic sequences, the proposed sequences also have negative auto-correlation. Besides, construction of complex sequences with lower average cross-correlation is possible with the proposed method. © 2014 © 2014 Taylor & Francis.
Saberali, S.M.,
Sabahi, M.F.,
Hosseini S.,
Hosseini S.,
Hosseini S.,
Saberali, S.M.,
Saberali, S.M.,
Sabahi, M.F.,
Sabahi, M.F. 2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 1239-1244
In this paper, we propose two new information criteria to select the desired model order for probability density function (PDF) estimation using the maximum entropy method (MEM). These two proposed information criteria are based on Akaike information criterion (AIC) and Bayesian information criterion (BIC), respectively. The PDF estimation using MEM can be presented using integer and fractional moments. We use two proposed information criteria by considering trade-off between the goodness of fit of the model and the complexity of the model which result in obtaining the appropriate model order. In underlay cognitive radio (CR) systems, the primary user makes a powerful interference for the secondary user which changes the system noise PDF to a non-Gaussian one. The MEM can estimate this non-Gaussian PDF which in turn can be used in nonlinear detection schemes to suppress the degrading effect of the primary user. The simulation results show the high accuracy of the proposed model order selection criteria. © 2014 IEEE.
Sabahi, M.F.,
Shahtalebi, K.,
Zabihi P.,
Zabihi P.,
Zabihi P.,
Sabahi, M.F.,
Sabahi, M.F.,
Shahtalebi, K.,
Shahtalebi, K. 2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 1166-1171
In this paper we have integrated Game theory framework, effective capacity theory and interference minimization for power allocation analysis over fading multiple access channels (MAC). Game theory is a powerful tool for modeling selfish behavior of competitors in resource allocation contest and can be used effectively in designing and modeling behavior of users in distributed resource allocation situations. Effective capacity is a useful tool that can impressively characterize delay constraint for wireless links. Interference consideration is too critical in multiple access channels and dynamic spectrum access policies. Here we set up a non-cooperative game and then we derive Nash equilibrium by analyzing the two player game. In the sense of simultaneous transmission our proposed policy caused less interference to users and better rates in Shannon capacity region achieved while considering QoS of users. We investigate the performance of our scheme for cases in which the QoS constraints of users increased and then we compare our scheme with the QoS-Driven power allocation game. © 2014 IEEE.
IEEE Signal Processing Letters (10709908)20(11)pp. 1006-1009
In this letter, we derive formulas for optimal discrete-time pulse shaping for communications in multiband channels. Furthermore, we propose a technique for extending a short signal segment for the purpose of power spectral estimation using the available information about the signal stopbands. The later technique can be also used for minimizing the energy leakage into stopbands of a signal, e.g., as in windowing for orthogonal frequency division modulation (OFDM). Simulation results show that when the pulse duration is long enough, the stopband energy can be practically reduced to zero using the proposed technique. The proposed power spectral estimation technique can improve the resolution and reduce the energy leakage from signal passbands into adjacent stopbands. Moreover, it can reduce the out-of-band power leakage significantly when used for windowing in OFDM. © 1994-2012 IEEE.
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 1286-1291
In the following paper a Cognitive Radio Network (CRN) is studied by means of the "mathematical tool of game theory". When we are faced with a distributed CRN, it is observed that selfishness of users will decrease the efficiency of network resource usage. Indeed, this is the selfishness of the users dispossessing them of optimum achievable state in the network. Using a game theoretical approach, we will offer a suitable pricing method which formulates the game as a potential one and allows the users to get more of network resources as long as they pay for it. Furthermore, how this method functions in a simulated CRN will be shown. According to simulation results, it can be perceived that in a non-cooperative environment, an ordinary network face a considerable drop in the number of convergence trials and the access of users to network resources, whereas exploiting the suggested pricing method mitigates the negative effects of selfishness of users. Moreover, the simulation results show that there are even some parameters which are bettered using the pricing method in the network in comparison with cooperative setting. © 2012 IEEE.
In this paper a sensorless speed vector control method at standstill and low speed in the Surface Mount Permanent Magnet Synchronous Motor (SMPMSM) drive system is described. A high-frequency model of an SMPMSM in the rotor reference frame is developed based on a sensorless rotor speed estimation algorithm. Furthermore, a digital filter is used to reduce the delay effect of conventional analog filters. The coefficients of the digital filter are optimized by using Genetic Algorithm (GA). Also the speed and current PI controllers which are used in the vector control scheme are adjusted based on GA. Simulation results for a 370 V 2.8 Kw, 1500rpm SMPMSM confirm the good performances of the proposed method in standstill and low speed cases. © 2011 AmirKabir Univ of Tech.
IET Radar, Sonar and Navigation (17518784)2(6)pp. 458-467
A new approach to detect a target with an unknown amplitude in clutter is proposed. The received signal models under two hypotheses, H0 and H1, are assumed to be the same, except that the target amplitude is zero under H0. Using the Bayesian approach, it is shown that the likelihood ratio can be calculated as the ratio of the prior to posterior probabilities of the target amplitude. Based on this relation, a new method for target detection in Gaussian clutter is presented. This method is applied to cases with both known and unknown clutter statistics and in each case, white and coloured clutters are considered. Simulation results show that the proposed detector has a much better performance compared with conventional generalised likelihood ratio test detectors. © The Institution of Engineering and Technology 2008.
In this paper we introduce a new detection algorithm based on Monte Carlo sampling method. The proposed method is numerical in nature. We use Importance Sampling to estimate unknown parameters and calculate likelihood ratio and call it Particle Detector (PD). This detector can be used in wide range of detection problems. We have also presented an adaptive radar detection algorithm based on our proposed particle detection scheme. © 2006 IEEE.
