IEEE Signal Processing Letters (10709908)28pp. 1868-1872
In this paper, an empirical characteristic function (ECF) based estimator of the line-of-sight (LOS) power for the near user in an uplink non-orthogonal multiple access (NOMA) system with unknown impulsive noise is proposed. The channels between the users and the base station (BS) are assumed to have Rician fading. The performance of the proposed estimator is analytically evaluated, which demonstrates the asymptotic unbiasedness and consistency of the estimator. Furthermore, the approximate expression derived for the variance is confirmed through computer simulations. Numerical results show that the proposed estimator outperforms the previous estimator for the LOS power in the mixture of Gaussian and α-stable noise. © 1994-2012 IEEE.
IEEE Communications Letters (10897798)25(12)pp. 3970-3974
In this letter, we modify the multi-threshold detector (MTD) for detection of downlink non-orthogonal multiple access (NOMA) signals in the Rician fading channel with statistical knowledge of channel state information (CSI). First, the error probability (Pe) for both MTD and successive interference cancellation (SIC) with statistical CSI is calculated. Then, we use the obtained Pe expression to fairly allocate power to different users in the sense that the maximum Pe of the users is minimized. Finally, computer simulations are performed, which show that MTD outperforms the SIC in the case that error propagation happens in the noise-free SIC. © 1997-2012 IEEE.
Vehicular Communications (22142096)29
In this paper, we derive an analytical expression for the bit error probability of a multi-threshold (MTh) detector in the downlink three-user non-orthogonal multiple access (NOMA) based vehicular communication system with unknown noise. The MTh detector directly detects the signal of vehicle user with the highest channel gain without detecting the signals of weaker users and removing their effects. It is shown that the bit error probability performance of the MTh detector is superior to that of the successive interference cancellation (SIC) detector in a special case. Then, we propose a blind empirical characteristic function (ECF) based method to estimate the signal levels of vehicle users, required to implement the MTh detector, in unknown noise. Next, we derive an analytical expression for the variance of the proposed ECF-based estimator which is validated via computer simulations. It is shown that the ECF-based estimator is asymptotically unbiased and consistent. Furthermore, we obtain the normalized Cramér-Rao lower bound (NCRLB) for the estimators of signal levels which shows that the ECF-based estimator is almost efficient in small generalized signal-to-noise ratio (GSNR) values. Numerical results show that the ECF-based MTh detector outperforms the absolute median-based SIC detector in the mixture of Gaussian and α-stable noise. © 2020 Elsevier Inc.
Wireless Networks (10220038)26(5)pp. 3521-3537
Vehicular ad hoc networks (VANETs) are able to facilitate data exchange among vehicles and provide diverse data services. The benefits of cooperative communications are such as to make it a proper idea to improve the achievable rate and diversity in VANETs. We investigate a dual-hop relay vehicular network with different transmit powers in vehicles on non-uniform shadowed double Nakagami-m fading channels in the presence of non-uniform co-channel interferers. In this paper, we investigate the diversity-multiplexing tradeoff (DMT) in such a network for three different schemes, namely, dynamic decode and forward (DDF), dynamic quantize map and forward and static quantize map and forward and prove that the DDF strategy has the optimal DMT. Also, the optimal listening and transmitting time of vehicles in various strategies as a function of the channel conditions in vehicles are determined. Finally, we extend our results to a general multi-hop relay vehicular network model with multiple half-duplex relay terminals and different average SNRs over links. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
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.
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.
Digital Signal Processing: A Review Journal (10954333)92pp. 20-25
In this paper, we evaluate the mean square error (MSE)performance of empirical characteristic function (ECF)based signal level estimator in a binary communication system. By calculating Cramér-Rao lower bound (CRLB)we investigate the performance of the ECF based estimator in the presence of Laplace and Gaussian mixture noises. We have derived an analytic expression for the variance of the ECF based estimator which shows that it is asymptotically unbiased and consistent. Simulation and analytic results indicate that the ECF based level estimator outperforms the previously proposed estimators in some signal to noise ratio (SNR)regions when the observation noise distribution is unknown. © 2019 Elsevier Inc.
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.
This paper studies the diversity-multiplexing trade-off (DMT) of half-duplex diamond relay channels. Diversity and multiplexing gains usually evaluate the performance of any relaying strategy, in wireless relay networks with fading channels. DMT captures the fundamental trade-off between these two gains, for communications at high signal to noise ratios (SNR). In this paper, we propose an efficient algorithm that computes the DMT of static-QMF communication strategy in half-duplex diamond relay channels. To find DMT of static QMF, one needs to solve a cumbersome optimization problem. The proposed algorithm, breaks the given optimization to finite1 number of sub-optimization problems, each one of which is a quasi-concave optimization problem. Then, using a binary search method, each sub-optimization problem is solved efficiently and the results of sub-optimization problems are combined to find DMT of the static QMF communication in the network. © 2016 IEEE.
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 119-123
This paper deals with the relationship of the Cramer-Rao lower bound (CRLB) and the channel capacity in a channel with interference. The former quantity is the representative of estimation theory and the latter is the envoy to information theory. CRLB is the lower bound on the variance of any unbiased estimator and channel capacity is the upper bound on the rate of reliable transmission. In the region that signal-to-interference ratio (SIR) is close to zero, the local minimum of the capacity of binary channel and local maximum of the CRLB happens. The log-likelihood ratio (LLR) is investigated to interpret the estimation and the capacity characteristics and plays a main role in this way. © 2015 IEEE.
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 19-23
One of the important challenges in communication systems is drift in the carrier frequency of received signal due to the clock skew and Doppler effect. Every communication receiver requires an automatic frequency control (AFC) loop to estimate the carrier drift in the received signal. One of the well-known AFC loops in communication systems is the Costas loop. In this paper a modified version of Costas loop for binary phase-shift keying (BPSK) modulation is presented which is capable to estimate the carrier frequency of the quadrature phase-shift keying (QPSK) modulation, and therefore significantly simplifies practical implementation. The performance of the modified Costas loop is investigated for the carrier recovery of a QPSK signal in the presence of a co-channel interference. Both simulations and analytical results illustrate that the modified Costas loop may estimate the carrier frequency drift of received signal when the desired signal is stronger than interference. © 2016 IEEE.
IEEE Communications Letters (10897798)19(8)pp. 1295-1298
A simple asymptotic bound on the error of the ordinary normal approximation (ONA) to the Student's t-distribution is derived. The proposed bound provides a quick calculation of the minimum number of degrees of freedom required to ensure a given approximation error. Then, the application of the ONA is investigated in confidence interval determination and detection theory. Finally, using the proposed bound, further simple bounds on the approximation error of the confidence level and the false-Alarm probability are obtained. © 1997-2012 IEEE.
In this paper, we propose a new approach for signal level estimation in binary phase shift keying (BPSK) modulation based on the empirical characteristic function (ECF), when the probability density function (PDF) of the noise is unknown. Then, we compare our proposed method with two other estimators that are suggested for systems with known noises. Numerical results show that, in the presence of Laplace noise, the ECF estimator has a better performance in low signal-to-noise ratios (SNR) in comparison with previously proposed methods. Moreover, the proposed method does not require the knowledge of noise PDF and works without any training sequence. © 2015 IEEE.
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025pp. 1561-1564
In this paper, we address the multiuser detection problem in the presence of strong interference, mixture of Gaussian and α-stable noises. We initially obtain locally optimal (LO) detection rule for this problem which can almost completely suppress interference effect and combat α-stable noise to some extent using oversampling in the receiver or channel coding in the transmitter. Then, we derive a new low complexity suboptimal detector considering the LO detector characteristics. This detector suppresses the degradation in the system performance due to interferer which is more substantial than α-stable noise degradation. We demonstrate that for the new suboptimal detector we only require the estimation of the interferer level which in turn is accurately estimated blindly based on a small number of observation samples through the empirical characteristic function (ECF) calculation. © 2014 IEEE.
IET Communications (17518628)8(9)pp. 1527-1533
In this study, monomials with odd integer powers are proposed for blind multiuser detection of code-division multiple access signals with long spreading codes, in the near-far situation. The performance of the new non-linear detectors are substantiated asymptotically and confirmed via simulations. It is demonstrated that the proposed non-linear detectors significantly outperform the matched filter detector in the block fading and Ricean fading channels, at the cost of a small increase in computational complexity. The optimum integer power value for the block fading channel with a limited interferer level, the Ricean channel with a given K factor and asynchronous channel is determined. The proposed multiuser detectors are blind in the sense that they require neither training nor the spreading code of the interferers. The detectors also do not require long convergence time for decision making in contrast to conventional blind multiuser detectors. © The Institution of Engineering and Technology 2014.
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.
IEEE Communications Letters (10897798)18(5)pp. 737-740
In this letter, we obtain the exact bit error rate (BER) of the successive interference cancellation (SIC). Then, the relationship between \sic and the optimal multiuser detector is determined. Next, a nonlinear scheme is proposed to detect code division multiple access (CDMA) signals in the presence of unknown interferers. The proposed scheme is derived based on maximum entropy estimation of the probability density function (PDF). Analysis and simulation show that the \ber performance of the proposed scheme approaches that of optimal multiuser detector and also \sic for low signal to interference ratio values. © 2014 IEEE.
IET Signal Processing (17519675)7(2)pp. 128-133
The authors use stochastic resonance (SR) for binary signal detection in the presence of a special type of Gaussian mixture noise. This type of noise naturally exists in signal detection problems in a channel with an interferer, and consequently, the investigations are beneficial for analysing the interferer suppression capability of the linear SR-based detectors. The authors demonstrate analytically that the region where SR-based detectors outperform the matched filter (MF) detector coincides with the region where the maximum likelihood (ML) detector outperforms the MF detector. An analytical expression is also obtained for error probability performance of the optimal SR-based detector and ML detector in an interferer channel. © The Institution of Engineering and Technology 2013.
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025
In this paper we introduce a multiple access scheme in which frequency reuse is achieved using the difference in the signal amplitudes. For this amplitude division multiple access (ADMA) system, a locally optimal multiuser detector (LOMUD) is proposed to detect a weak binary phase shift keying (BPSK) signal in the presence of a similar modulated cochannel interference and additive white Gaussian noise (AWGN). For the proposed detector, there is no need for signal level estimation, which is a computational burden when the desired signal is weak. An analytic expression for the bit error probability of the LOMUD detector is also derived. Furthermore, it is shown that the performance of the proposed detector approaches the lower bound when the signal to interference ratio (SIR) is low enough. We also present some estimators for estimation of the required parameters in the receiver and investigated their efficiencies. © 2011 IEEE.
Signal Processing (01651684)90(3)pp. 891-899
The paper provides a blind binary detection approach in an unknown non-Gaussian noise. In our scheme, we use maximum likelihood (ML) detection rule in conjunction with maximum entropy method (MEM) for probability density function (PDF) estimation of the unknown observation noise from the samples of the received data. We constrain MEM on estimated moment generating function (MGF). The estimated PDF based on MEM-MGF is quite close to the true PDF and has a direct applicability for blind implementation. The results indicate that the new nonlinear detector outperforms conventional matched filter, and approaches the performance of the optimal ML detector which assumes the complete knowledge for the noise PDF. Then, we analyze the scheme by probability of error (Pe) calculation and interpret the results. © 2009 Elsevier B.V.
IEEE Signal Processing Letters (10709908)16(12)pp. 1087-1090
In this letter we develop a new blind binary level detection in presence of unknown non-Gaussian noise using maximum entropy method (MEM). We show that the performance of the designed detector based on blind maximum entropy (BME) method is near to the one that is designed based on best entropy estimate (BEE) criterion. © 2009 IEEE.
IEEE Communications Letters (10897798)12(10)pp. 705-707
We propose an optimal single user detector (OSUD) for a binary phase shift keying (BPSK) signal corrupted by a cochannel interferer and additive white Gaussian noise (AWGN). We obtain an analytical expression for the detector bit error rate (BER). The capacity of this channel is also investigated to interpret the BER performance of the optimal detectors. © 2008 IEEE.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (15206149)pp. 3193-3196
In this paper, we introduce a new nonlinear detector to improve the performance of a weak BPSK system in the presence of like-modulated cochannel interference and additive white Gaussian noise (AWGN) with time varying characteristics. In our scheme we use locally optimal (LO) detection rule in conjunction with maximum entropy method (MEM) for probability density function (PDF) estimation of the observation noise. We utilize MEM based on moment generating function (MGF) constraints instead of moments, as a new criterion. The estimated PDF based on MEM-MGF is quite close to the true PDF and yields better uniform approximation, especially in the tail of PDF. The results indicate that the new nonlinear detector outperforms conventional matched filter, and approaches the optimal receiver when desired signal is weak. For the new detector, there is no need for any signal level estimation, which is a computational burden when these parameters are time varying. ©2008 IEEE.
This paper provides a new spread spectrum signal detection in the presence of digital narrowband interference using nonlinear detectors by utilizing several moments in a frequency band. The proposed procedure amounts to a nonlinear processing on the received data and matched filtering. The performance assessments indicate that this receiver is able to suppress the effect of narrowband interference, which is assumed as an Mary amplitude shift keying (ASK) signal. The new detector uses the information available in a bit duration of the spread spectrum signal and requires no training data. © 2007 IEEE.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (15206149)3
In this paper we introduce a new nonlinear detector to improve the performance of spread spectrum receiver in the presence of narrowband interference. The new detector is blind in the sense that no training data is required. In our scheme we use maximum likelihood (ML) detection rule in conjunction with maximum entropy method (MEM) for probability density function (PDF) estimation of the observation noise. We use MEM with a new approach based on fractional moments instead of integer moments. The estimated PDF based on fractional moments is quite close to the true PDF. The results indicate that the new nonlinear detector outperforms conventional matched filter, and well known locally optimal (LO) detector. © 2007 IEEE.
Overlaying spread spectrum systems on narrowband services has been proposed as a way to obtain greater bandwidth efficiencies with respect to sparsely narrowband systems. It is shown that, in overlay situation, the performances of both narrowband and spread spectrum systems are significantly degraded by each other. This paper presents a new nonlinear detector which enhances the performance of the narrowband system considerably. In our approach we use maximum likelihood (ML) and maximum entropy, which are two optimal criteria. Computer simulation results show that the proposed detector has much better performance than the conventional matched filter. The estimated narrowband signal can be subtracted from the received signal in the spread spectrum receiver to enhance its performance.
Non-Gaussian noise poses a challenge to conventional detector techniques. In such a case it is possible to design a nonlinear detector that performs better than the optimal linear detectors. Locally optimal detector is one that has good performance when the signal is weak and the probability density function (PDF) of noise is known precisely. This paper deals with a new nonlinear detector for binary signal detection in Gaussian mixture noise. This detector is optimal without any constraints on signal strength, and it is convenient for non-Gaussian even symmetric PDF's. furthermore, it does not require the knowledge of the exact noise PDF. We use maximum likelihood (ML) and maximum entropy, that are two optimal criteria, in obtaining this new detector. The proposed detector consists of new nonlinear functions followed by an accumulator and threshold comparator. These new nonlinear functions are polynomials consisting of odd power terms. Simulation results confirm the superiority of the new detector with respect to the previously proposed methods. © 2006 IEEE.
Previous methods for narrowband interference suppression in spread spectrum systems require training sequences. In practical overlay systems, transmission of the training sequences is impossible, because narrowband system and spread spectrum system are two separate entities, and presently the narrowband systems are in use and standardized and any changes may not be allowed. Hence, the narrowband systems cannot transmit training sequences for the spread spectrum system. In this paper we present a blind method for narrowband interference suppression in direct sequence Code Division Multiple Access (CDMA) systems. The proposed scheme is a nonlinear predictor consisting of a non-linear device and two random walk tracking algorithms. The main feature of this approach is that it does not require training sequences for tracking and suppressing narrowband interference. Simulation results show that in multiuser case, the performance of the proposed approach is better than Kalman filter. © 2004 IEEE.
It has been shown that the narrowband interference suppression capability of a direct sequence spread spectrum system can be enhanced considerably by processing the received signal via a prediction error Alter prior to correlating it with the Pseudo Noise (PN) sequence. In this paper we present a new method to suppress narrowband interference in Direct Sequence Code Division Multiple Access (DS-CDMA) systems. The proposed scheme is a nonlinear predictor that consists of a quantizer and random walk tracking algorithm. This algorithm is used for tracking a random walk in white Gaussian noise. This algorithm has two important features. First, this algorithm does not require the estimation of the interference statistics. Second, it does not require training sequences. Computer simulation results show that the proposed approach has better performance than conventional linear filtering. © 2003 IEEE.
