Kamal Shahtalebi - Academia.edu (original) (raw)

Papers by Kamal Shahtalebi

Research paper thumbnail of Efficient spectrum leasing in cognitive radio networks: Disjoint secondary user selection and protocol selective relaying

Transactions on Emerging Telecommunications Technologies, 2016

Research paper thumbnail of A Cyclic Frequency Tracking Loop for Wideband Spectrum Sensing and FM Demodulation

IEEE Communications Letters, 2016

Research paper thumbnail of On the adaptive linear estimators, using biased Cram�r-Rao bound

Signal Processing, 2007

The idea of minimizing the variance in biased estimation along with controlling the gradient of b... more The idea of minimizing the variance in biased estimation along with controlling the gradient of bias is well established for the case of singular Fisher information matrix (FIM) in order to find the biased estimators. In this paper, the biased Crame´r-Rao lower bound (BCRLB) is used to derive and study the estimate of unknown parameters in a linear model with a known twice differentiable additive noise probability density function (PDF). Even if the additive noise is not Gaussian, we show that the derived linear estimators (not unique) are linear functions of the observations (where a constant number is inserted into observation vector) in a particular form. Examples are included to illustrate the estimators performances. We show that a biased estimator obtained by optimization of BCRLB is not necessary satisfactory in a general case; therefore, additional considerations must be taken into account when using this approach. For the case where the PDF of the additive noise is not differentiable, such as uniformly distributed or time invariant magnitude noises, an asymptotical approach is given to find the estimators. As an example, we evaluate the performance of the derived adaptive filter for a first-order Markov time varying system. If the FIM is singular, we use the method of singular value decomposition (SVD) to extract the parameter estimate of the linear models. For example we show that in a linear model, parameter estimation based on single observation leads to the normalized least mean square (NLMS) algorithm. In this example using BCRLB optimization, we find the relation between the step-size of the NLMS algorithm and the bound of the bias gradient matrix. r

Research paper thumbnail of Full MIMO Channel Estimation Using A Simple Adaptive Partial Feedback Method

Eprint Arxiv 0710 4173, Oct 1, 2007

Partial feedback in multiple-input multiple-output (MIMO) communication systems provides tremendo... more Partial feedback in multiple-input multiple-output (MIMO) communication systems provides tremendous capacity gain and enables the transmitter to exploit channel condition and to eliminate channel interference. In the case of severely limited feedback, constructing a quantized partial feedback is an important issue. To reduce the computational complexity of the feedback system, in this paper we introduce an adaptive partial method in which at the transmitter, an easy to implement least square adaptive algorithm is engaged to compute the channel state information. In this scheme at the receiver, the time varying step-size is replied to the transmitter via a reliable feedback channel. The transmitter iteratively employs this feedback information to estimate the channel weights. This method is independent of the employed space-time coding schemes and gives all channel components. Simulation examples are given to evaluate the performance of the proposed method.

Research paper thumbnail of Parallel optimisation of time-varying adaptive algorithms for interference cancellation in code division multiple access systems

Iet Communications, Dec 5, 2010

In this study, we propose a least mean square-partial parallel interference cancellation (LMS-PPI... more In this study, we propose a least mean square-partial parallel interference cancellation (LMS-PPIC) method named parallel LMS-PPIC (PLMS-PPIC) in which the normalised least mean square (NLMS) adaptive algorithm with optimised chip time-varying step-size is engaged to obtain the cancellation weights. The former LMS-PPIC method is based on fixed not optimised step-size, which causes propagation of error from one stage to the next one and increases the bit error rate (BER). The unit magnitude of the cancellation weights is the principal property in our step-size optimisation. To avoid computational complexity a small set of NLMS algorithms with different step-sizes are executed. In each iteration the parameter estimate of that NLMS algorithm which the elements magnitudes of its cancellation weight estimate have the best match with unit is chosen. Magnificent decrease in BER is achieved by executing the proposed method. Moreover PLMS-PPIC like former LMS-PPIC method comes to practice only when the channel phases are known. When they are unknown, having only their quarters in (0, 2p), we propose modified versions of LMS-PPIC and PLMS-PPIC to find the channel phases and the cancellation weights simultaneously. Simulation scenarios are given to compare the performance of our methods with that of LMS-PPIC in two cases: balanced channel and unbalanced channel. The results show that in both cases the proposed method outperforms LMS-PPIC, especially for high processing gains.

Research paper thumbnail of A new fairness index and novel approach for QoS-aware resource allocation in LTE networks based on utility functions

2015 Signal Processing and Intelligent Systems Conference (SPIS), 2015

Research paper thumbnail of Interference Cancelation in Non-coherent CDMA Systems Using Parallel Iterative Algorithms

Parallel least mean square-partial parallel interference cancelation (PLMS-PPIC) is a partial int... more Parallel least mean square-partial parallel interference cancelation (PLMS-PPIC) is a partial interference cancelation which employs adaptive multistage structure. In this algorithm the channel phases for all users are assumed to be known. Having only their quarters in (0,2\pi), a modified version of PLMS-PPIC is proposed in this paper to simultaneously estimate the channel phases and the cancelation weights. Simulation examples are given in the cases of balanced, unbalanced and time varying channels to show the performance of the modified PLMS-PPIC method.

Research paper thumbnail of Spectrum leasing with disjoint secondary user selection in cognitive radio networks

2014 Iran Workshop on Communication and Information Theory (IWCIT), 2014

ABSTRACT Previous works in spectrum leasing for centralized cognitive radio networks (CRNs) are b... more ABSTRACT Previous works in spectrum leasing for centralized cognitive radio networks (CRNs) are based on selecting a secondary user as a relay to cooperatively transmit the primary data and then leasing the released spectrum due to the cooperation to the selected user. In this paper, we propose a new spectrum leasing scheme to improve the throughput and thus the spectrum efficiency of the secondary system. The proposed approach selects two secondary users for cooperation and secondary transmission independently, which are the best users towards the primary and secondary systems, respectively. We show that the outage performance of the secondary system is enhanced as a result of the independent secondary user selection. Analytical and simulation results are presented to verify the efficiency of our approach and performance improvement in the secondary system.

Research paper thumbnail of NLMS algorithm with variable step-size using set-membership identification

Scientia Iranica

In this paper, set-membership identification is used to derive a simple algorithm which is a sign... more In this paper, set-membership identification is used to derive a simple algorithm which is a sign version of the normalized least mean square algorithm. Convergence analysis is carried out. With some simulation examples, the performance of the algorithm, in the cases of slow and fast variations of a parameter, is compared with the modified Dasgupta-Huang optimal bounding ellipsoid algorithm. These examples show the performance of the proposed algorithm.

Research paper thumbnail of A Full-Three-Dimensional Reference Model for Wideband MIMO Mobile-to-Mobile Communication Channels

Wireless Personal Communications, 2015

Research paper thumbnail of A Simple Method for Throughput Maximization of OFDMA Based CR Networks

Wireless Personal Communications, 2015

Research paper thumbnail of Computationally efficient adaptive algorithm for resource allocation in orthogonal frequency-division multiple-access-based cognitive radio networks

Research paper thumbnail of Spatial-temporal-frequency decomposition for 3D MIMO microcellular environments

Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513), 2004

ABSTRACT A three-dimensional (3D) model is proposed for multiple-input multiple-output (MIMO) mic... more ABSTRACT A three-dimensional (3D) model is proposed for multiple-input multiple-output (MIMO) microcell Rayleigh fading channels with an ample number of scatterers. We assume appropriate probability density functions (pdf) for relevant physical parameters of the complex scattering media. The impact of these parameters are discussed using the expression of the correlation function (CF) between each of the two sub-channels of the MIMO channel. The CF is decomposable into several components that describe spatial, temporal, and frequency characteristics of the MIMO communication system. Such a decomposition allows easier investigation and gives a better understanding of the full potential of MIMO wireless communications. The describing components do not always have closed-form expressions. Therefore, closed-form expressions are obtained for some special cases. In practice, a linear convex combination of the expressions from these cases can approximate almost any model of microcellular environments. The proposed model is a generalization of several existing models including the Jake's/Clark model.

Research paper thumbnail of A set membership nlms algorithm for colored noise environment

IEEE Global Telecommunications Conference, 2004. GLOBECOM '04., 2004

Abstract— The performance of an adaptive filter is restricted by the statistical behavior of the ... more Abstract— The performance of an adaptive filter is restricted by the statistical behavior of the additive noise. The aim of this pa-per is to improve the convergence speed and steady state error of the Set-Membership Normalized Least Mean Square (SM-NLMS) algorithm in a ...

Research paper thumbnail of Adaptive linear estimators, using biased cramer-RAO bound

IEEE/SP 13th Workshop on Statistical Signal Processing, 2005, 2005

In this paper, the biased Cramer-Rao lower bound (BCRLB) is used to derive the estimate of unknow... more In this paper, the biased Cramer-Rao lower bound (BCRLB) is used to derive the estimate of unknown parameters in a linear model with an arbitrary known additive noise probability density function (PDF).We show that the derived linear estimators (not unique) are linear functions of the observations. Examples are included to illustrate their performances. We show that a biased estimator obtained

Research paper thumbnail of A modified two-ring reference model for MIMO Mobile-to-Mobile communication channels

2008 International Symposium on Telecommunications, 2008

... Department of Electrical Engineering Yazd University, Yazd, Iran Email: rsaadat@yazduni. ac.i... more ... Department of Electrical Engineering Yazd University, Yazd, Iran Email: rsaadat@yazduni. ac.ir Kamal Shahtalebi Department of Information Technology University of Isfahan, Isfahan Iran, Postal Code: 81746-73441 Email: shahtalebi@eng.ui.ac.ir ...

Research paper thumbnail of Interference Cancelation in Coherent CDMA Systems Using Parallel Iterative Algorithms

Least mean square-partial parallel interference cancelation (LMS-PPIC) is a partial interference ... more Least mean square-partial parallel interference cancelation (LMS-PPIC) is a partial interference cancelation using adaptive multistage structure in which the normalized least mean square (NLMS) adaptive algorithm is engaged to obtain the cancelation weights. The performance of the NLMS algorithm is mostly dependent to its step-size. A fixed and non-optimized step-size causes the propagation of error from one stage to the

Research paper thumbnail of A novel Full-Three-Dimensional MIMO Mobile-to-Mobile channel reference model

2009 3rd International Conference on Signal Processing and Communication Systems, 2009

Abstract—Analysis and design of multi-element antenna sys-tems in mobile fading channels require ... more Abstract—Analysis and design of multi-element antenna sys-tems in mobile fading channels require a model for the space-time cross-correlation among the links of the underlying multiple-input multiple-output (MIMO) Mobile-to-Mobile (M-to-M) com-munication ...

Research paper thumbnail of Interference Cancelation in Non-Coherent CDMA Systems Using Parallel Iterative Algorithms

2008 IEEE Wireless Communications and Networking Conference, 2008

Parallel least mean square-partial parallel interference cancelation (PLMS-PPIC) is a partial int... more Parallel least mean square-partial parallel interference cancelation (PLMS-PPIC) is a partial interference cancelation which employs adaptive multistage structure [1]. In this algorithm the channel phases for all users are assumed to be known. Having only their quarters in (0, 2π), a modified version of PLMS-PPIC is proposed in this paper to simultaneously estimate the channel phases and the cancelation weights. Simulation examples are given in the cases of balanced, unbalanced and time varying channels to show the performance of the modified PLMS-PPIC method.

Research paper thumbnail of Interference cancellation in coherent CDMA systems using parallel iterative algorithms

2008 International Symposium on Telecommunications, 2008

Least mean square-partial parallel interference cancellation (LMS-PPIC) is a partial interference... more Least mean square-partial parallel interference cancellation (LMS-PPIC) is a partial interference cancellation using adaptive multistage structure in which the normalized least mean square (NLMS) adaptive algorithm is engaged to obtain the cancellation weights. The performance of the NLMS algorithm is mostly dependent to its step-size. A fixed and non-optimized step-size causes the propagation of error from one stage to the

Research paper thumbnail of Efficient spectrum leasing in cognitive radio networks: Disjoint secondary user selection and protocol selective relaying

Transactions on Emerging Telecommunications Technologies, 2016

Research paper thumbnail of A Cyclic Frequency Tracking Loop for Wideband Spectrum Sensing and FM Demodulation

IEEE Communications Letters, 2016

Research paper thumbnail of On the adaptive linear estimators, using biased Cram�r-Rao bound

Signal Processing, 2007

The idea of minimizing the variance in biased estimation along with controlling the gradient of b... more The idea of minimizing the variance in biased estimation along with controlling the gradient of bias is well established for the case of singular Fisher information matrix (FIM) in order to find the biased estimators. In this paper, the biased Crame´r-Rao lower bound (BCRLB) is used to derive and study the estimate of unknown parameters in a linear model with a known twice differentiable additive noise probability density function (PDF). Even if the additive noise is not Gaussian, we show that the derived linear estimators (not unique) are linear functions of the observations (where a constant number is inserted into observation vector) in a particular form. Examples are included to illustrate the estimators performances. We show that a biased estimator obtained by optimization of BCRLB is not necessary satisfactory in a general case; therefore, additional considerations must be taken into account when using this approach. For the case where the PDF of the additive noise is not differentiable, such as uniformly distributed or time invariant magnitude noises, an asymptotical approach is given to find the estimators. As an example, we evaluate the performance of the derived adaptive filter for a first-order Markov time varying system. If the FIM is singular, we use the method of singular value decomposition (SVD) to extract the parameter estimate of the linear models. For example we show that in a linear model, parameter estimation based on single observation leads to the normalized least mean square (NLMS) algorithm. In this example using BCRLB optimization, we find the relation between the step-size of the NLMS algorithm and the bound of the bias gradient matrix. r

Research paper thumbnail of Full MIMO Channel Estimation Using A Simple Adaptive Partial Feedback Method

Eprint Arxiv 0710 4173, Oct 1, 2007

Partial feedback in multiple-input multiple-output (MIMO) communication systems provides tremendo... more Partial feedback in multiple-input multiple-output (MIMO) communication systems provides tremendous capacity gain and enables the transmitter to exploit channel condition and to eliminate channel interference. In the case of severely limited feedback, constructing a quantized partial feedback is an important issue. To reduce the computational complexity of the feedback system, in this paper we introduce an adaptive partial method in which at the transmitter, an easy to implement least square adaptive algorithm is engaged to compute the channel state information. In this scheme at the receiver, the time varying step-size is replied to the transmitter via a reliable feedback channel. The transmitter iteratively employs this feedback information to estimate the channel weights. This method is independent of the employed space-time coding schemes and gives all channel components. Simulation examples are given to evaluate the performance of the proposed method.

Research paper thumbnail of Parallel optimisation of time-varying adaptive algorithms for interference cancellation in code division multiple access systems

Iet Communications, Dec 5, 2010

In this study, we propose a least mean square-partial parallel interference cancellation (LMS-PPI... more In this study, we propose a least mean square-partial parallel interference cancellation (LMS-PPIC) method named parallel LMS-PPIC (PLMS-PPIC) in which the normalised least mean square (NLMS) adaptive algorithm with optimised chip time-varying step-size is engaged to obtain the cancellation weights. The former LMS-PPIC method is based on fixed not optimised step-size, which causes propagation of error from one stage to the next one and increases the bit error rate (BER). The unit magnitude of the cancellation weights is the principal property in our step-size optimisation. To avoid computational complexity a small set of NLMS algorithms with different step-sizes are executed. In each iteration the parameter estimate of that NLMS algorithm which the elements magnitudes of its cancellation weight estimate have the best match with unit is chosen. Magnificent decrease in BER is achieved by executing the proposed method. Moreover PLMS-PPIC like former LMS-PPIC method comes to practice only when the channel phases are known. When they are unknown, having only their quarters in (0, 2p), we propose modified versions of LMS-PPIC and PLMS-PPIC to find the channel phases and the cancellation weights simultaneously. Simulation scenarios are given to compare the performance of our methods with that of LMS-PPIC in two cases: balanced channel and unbalanced channel. The results show that in both cases the proposed method outperforms LMS-PPIC, especially for high processing gains.

Research paper thumbnail of A new fairness index and novel approach for QoS-aware resource allocation in LTE networks based on utility functions

2015 Signal Processing and Intelligent Systems Conference (SPIS), 2015

Research paper thumbnail of Interference Cancelation in Non-coherent CDMA Systems Using Parallel Iterative Algorithms

Parallel least mean square-partial parallel interference cancelation (PLMS-PPIC) is a partial int... more Parallel least mean square-partial parallel interference cancelation (PLMS-PPIC) is a partial interference cancelation which employs adaptive multistage structure. In this algorithm the channel phases for all users are assumed to be known. Having only their quarters in (0,2\pi), a modified version of PLMS-PPIC is proposed in this paper to simultaneously estimate the channel phases and the cancelation weights. Simulation examples are given in the cases of balanced, unbalanced and time varying channels to show the performance of the modified PLMS-PPIC method.

Research paper thumbnail of Spectrum leasing with disjoint secondary user selection in cognitive radio networks

2014 Iran Workshop on Communication and Information Theory (IWCIT), 2014

ABSTRACT Previous works in spectrum leasing for centralized cognitive radio networks (CRNs) are b... more ABSTRACT Previous works in spectrum leasing for centralized cognitive radio networks (CRNs) are based on selecting a secondary user as a relay to cooperatively transmit the primary data and then leasing the released spectrum due to the cooperation to the selected user. In this paper, we propose a new spectrum leasing scheme to improve the throughput and thus the spectrum efficiency of the secondary system. The proposed approach selects two secondary users for cooperation and secondary transmission independently, which are the best users towards the primary and secondary systems, respectively. We show that the outage performance of the secondary system is enhanced as a result of the independent secondary user selection. Analytical and simulation results are presented to verify the efficiency of our approach and performance improvement in the secondary system.

Research paper thumbnail of NLMS algorithm with variable step-size using set-membership identification

Scientia Iranica

In this paper, set-membership identification is used to derive a simple algorithm which is a sign... more In this paper, set-membership identification is used to derive a simple algorithm which is a sign version of the normalized least mean square algorithm. Convergence analysis is carried out. With some simulation examples, the performance of the algorithm, in the cases of slow and fast variations of a parameter, is compared with the modified Dasgupta-Huang optimal bounding ellipsoid algorithm. These examples show the performance of the proposed algorithm.

Research paper thumbnail of A Full-Three-Dimensional Reference Model for Wideband MIMO Mobile-to-Mobile Communication Channels

Wireless Personal Communications, 2015

Research paper thumbnail of A Simple Method for Throughput Maximization of OFDMA Based CR Networks

Wireless Personal Communications, 2015

Research paper thumbnail of Computationally efficient adaptive algorithm for resource allocation in orthogonal frequency-division multiple-access-based cognitive radio networks

Research paper thumbnail of Spatial-temporal-frequency decomposition for 3D MIMO microcellular environments

Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513), 2004

ABSTRACT A three-dimensional (3D) model is proposed for multiple-input multiple-output (MIMO) mic... more ABSTRACT A three-dimensional (3D) model is proposed for multiple-input multiple-output (MIMO) microcell Rayleigh fading channels with an ample number of scatterers. We assume appropriate probability density functions (pdf) for relevant physical parameters of the complex scattering media. The impact of these parameters are discussed using the expression of the correlation function (CF) between each of the two sub-channels of the MIMO channel. The CF is decomposable into several components that describe spatial, temporal, and frequency characteristics of the MIMO communication system. Such a decomposition allows easier investigation and gives a better understanding of the full potential of MIMO wireless communications. The describing components do not always have closed-form expressions. Therefore, closed-form expressions are obtained for some special cases. In practice, a linear convex combination of the expressions from these cases can approximate almost any model of microcellular environments. The proposed model is a generalization of several existing models including the Jake's/Clark model.

Research paper thumbnail of A set membership nlms algorithm for colored noise environment

IEEE Global Telecommunications Conference, 2004. GLOBECOM '04., 2004

Abstract— The performance of an adaptive filter is restricted by the statistical behavior of the ... more Abstract— The performance of an adaptive filter is restricted by the statistical behavior of the additive noise. The aim of this pa-per is to improve the convergence speed and steady state error of the Set-Membership Normalized Least Mean Square (SM-NLMS) algorithm in a ...

Research paper thumbnail of Adaptive linear estimators, using biased cramer-RAO bound

IEEE/SP 13th Workshop on Statistical Signal Processing, 2005, 2005

In this paper, the biased Cramer-Rao lower bound (BCRLB) is used to derive the estimate of unknow... more In this paper, the biased Cramer-Rao lower bound (BCRLB) is used to derive the estimate of unknown parameters in a linear model with an arbitrary known additive noise probability density function (PDF).We show that the derived linear estimators (not unique) are linear functions of the observations. Examples are included to illustrate their performances. We show that a biased estimator obtained

Research paper thumbnail of A modified two-ring reference model for MIMO Mobile-to-Mobile communication channels

2008 International Symposium on Telecommunications, 2008

... Department of Electrical Engineering Yazd University, Yazd, Iran Email: rsaadat@yazduni. ac.i... more ... Department of Electrical Engineering Yazd University, Yazd, Iran Email: rsaadat@yazduni. ac.ir Kamal Shahtalebi Department of Information Technology University of Isfahan, Isfahan Iran, Postal Code: 81746-73441 Email: shahtalebi@eng.ui.ac.ir ...

Research paper thumbnail of Interference Cancelation in Coherent CDMA Systems Using Parallel Iterative Algorithms

Least mean square-partial parallel interference cancelation (LMS-PPIC) is a partial interference ... more Least mean square-partial parallel interference cancelation (LMS-PPIC) is a partial interference cancelation using adaptive multistage structure in which the normalized least mean square (NLMS) adaptive algorithm is engaged to obtain the cancelation weights. The performance of the NLMS algorithm is mostly dependent to its step-size. A fixed and non-optimized step-size causes the propagation of error from one stage to the

Research paper thumbnail of A novel Full-Three-Dimensional MIMO Mobile-to-Mobile channel reference model

2009 3rd International Conference on Signal Processing and Communication Systems, 2009

Abstract—Analysis and design of multi-element antenna sys-tems in mobile fading channels require ... more Abstract—Analysis and design of multi-element antenna sys-tems in mobile fading channels require a model for the space-time cross-correlation among the links of the underlying multiple-input multiple-output (MIMO) Mobile-to-Mobile (M-to-M) com-munication ...

Research paper thumbnail of Interference Cancelation in Non-Coherent CDMA Systems Using Parallel Iterative Algorithms

2008 IEEE Wireless Communications and Networking Conference, 2008

Parallel least mean square-partial parallel interference cancelation (PLMS-PPIC) is a partial int... more Parallel least mean square-partial parallel interference cancelation (PLMS-PPIC) is a partial interference cancelation which employs adaptive multistage structure [1]. In this algorithm the channel phases for all users are assumed to be known. Having only their quarters in (0, 2π), a modified version of PLMS-PPIC is proposed in this paper to simultaneously estimate the channel phases and the cancelation weights. Simulation examples are given in the cases of balanced, unbalanced and time varying channels to show the performance of the modified PLMS-PPIC method.

Research paper thumbnail of Interference cancellation in coherent CDMA systems using parallel iterative algorithms

2008 International Symposium on Telecommunications, 2008

Least mean square-partial parallel interference cancellation (LMS-PPIC) is a partial interference... more Least mean square-partial parallel interference cancellation (LMS-PPIC) is a partial interference cancellation using adaptive multistage structure in which the normalized least mean square (NLMS) adaptive algorithm is engaged to obtain the cancellation weights. The performance of the NLMS algorithm is mostly dependent to its step-size. A fixed and non-optimized step-size causes the propagation of error from one stage to the