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Claude Damours

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Papers by Claude Damours

On the Impact of CDL and TDL Augmentation for RF Fingerprinting Under Impaired Channels

Deleted Journal, Mar 21, 2024

Cyber-physical systems have recently been used in several areas (such as connected and autonomous... more Cyber-physical systems have recently been used in several areas (such as connected and autonomous vehicles) due to their high maneuverability. On the other hand, they are susceptible to cyber-attacks. Radio frequency (RF) fingerprinting emerges as a promising approach. This work aims to analyze the impact of decoupling tapped delay line and clustered delay line (TDL+CDL) augmentation-driven deep learning (DL) on transmitter-specific fingerprints to discriminate malicious users from legitimate ones. This work also considers 5G-only-CDL, WiFi-only-TDL augmentation approaches. RF fingerprinting models are sensitive to changing channels and environmental conditions. For this reason, they should be considered during the deployment of a DL model. Data acquisition can be another option. Nonetheless, gathering samples under various conditions for a train set formation may be quite hard. Consequently, data acquisition may not be feasible. This work uses a dataset that includes 5G, 4G, and WiFi samples, and it empowers a CDL+TDL based augmentation technique in order to boost the learning performance of the DL model. Numerical results show that CDL+TDL, 5G-only-CDL, and WiFi-only-TDL augmentation approaches achieve 87.59%, 81.63%, 79.21% accuracy on unobserved data while TDL/CDL augmentation technique and no augmentation approach result in 77.81% and 74.84% accuracy on unobserved data, respectively.

Human Activity Classification in Underwater using Sonar and Deep Learning

Proceedings of the International Conference on Underwater Networks & Systems

In this paper, we study the classification of human activity on the surface of a body of water us... more In this paper, we study the classification of human activity on the surface of a body of water using sonar. In particular, we investigate the classification of three different swimming styles; freestyle, butterfly, and backstroke. Experiments are conducted in a swimming pool to capture acoustic micro-Doppler signatures produced by the different swimming styles. Two acoustic hydrophones are used underwater; one to transmit a single tone signal in the direction of a swimmer and the other to receive the reflected waveform from the swimmer's body. We apply joint time-frequency analysis on the received acoustic signal to extract the micro-Doppler signatures present in the spectrogram. Each of these swimming style activities presents their own unique micro-Doppler signatures. To classify the acoustic micro-Doppler signatures, we explore a deep convolution neural network (DCNN) algorithm. Spectrogram can be considered as an image in which case applying DCNN can serve well for feature recognition purposes. We show that using the spectrogram images the DCNN algorithm can classify different swimming styles performed on the surface of the water with fairly high accuracy. Using the collected data set, we performed experiments where we used 80% of the data for training and the remaining 20% for validation purposes. The DCNN algorithm averaged 93.7% accuracy during training while it had a 90.8% average validation accuracy.

Digital Recording System Identification Based on Blind Deconvolution

2019 Wireless Telecommunications Symposium (WTS)

In this work, we develop a theoretical framework for reliable digital recording system identifica... more In this work, we develop a theoretical framework for reliable digital recording system identification from digital audio files alone, for forensic purposes. A digital recording system consists of a microphone and a digital sound processing card. We view the cascade as a system of unknown impulse response. We expect the same manufacturer and model microphone-sound card combinations to have very similar/near identical impulse responses, bar any unique manufacturing defect. Input voice (or other) signals are modeled as non-stationary processes. The technical problem under consideration becomes blind deconvolution with non-stationary inputs, as it manifests itself in the specific application of digital audio recording equipment classification. We propose a conditionally maximum-likelihood (CML) algorithm to estimate underlying systems impulse response together with a novel nearest neighborhood algorithm for recording system identification. Experimental results demonstrate over 99.2% accuracy in identification of the recording devices.

Multidisciplinary Discussion on 5G from the Viewpoint of Algebraic Combinatorics

2019 Computer Science and Information Technologies (CSIT)

In this paper, we present some of the interesting questions raised in the "5G and Beyond" worksho... more In this paper, we present some of the interesting questions raised in the "5G and Beyond" workshop discussions. We propose to explore alternative solutions in other discipline such as algebraic combinatorics and discrete optimization. Construction of matrices that possess certain desirable properties in discrete tomography can be exploited for the 5th generation (5G) multiuser waveform design. Moreover, we propose to investigate thoroughly the random graph theory developed by Erdős and A. Rényi for 5G multiuser waveform design. Furthermore, we explore using the "Best Match" algorithm, which has a polynomial time complexity, in 5G communications. Index Terms-Non-orthogonal multiple-access (NOMA), codedivision multiple access (CDMA), low-density spreading signatures (LDS), sparse-code multiple-access (SCMA).

2-D DOA Estimation of Coherent Wideband Signals with Auxiliary-Vector Basis

2018 IEEE International Conference on Communications Workshops (ICC Workshops), 2018

We develop a two-dimensional (2-D) direction-ofarrival (DOA) estimation scheme for coherent wideb... more We develop a two-dimensional (2-D) direction-ofarrival (DOA) estimation scheme for coherent wideband source signals using coherent signal subspace method based auxiliaryvector (CSSM-AV) basis. Computation of the basis is carried out by a modified version of the orthogonal CSSM-AV filtering algorithm. The proposed method reconstructs the signal subspace using a cross-correlation matrix after which the modified CSSM-AV algorithm is employed to estimate the azimuth and elevation angles. Then, successive orthogonal maximum cross-correlation auxiliary vectors are calculated to form a basis for the scannerextended signal subspace. This technique is very efficient in reducing the algorithm complexity. Since it does not require that the eigenvectors be determined in order to find the signal subspace and yields a superior resolution performance for closely spaced sources even when the number of samples is low. Specifically, the complexity of the proposed 2-D DOA estimation algorithm compared to the CSSM algorithm is more favorable when the number of signals arriving on the antenna element is much less than the number of antenna elements. Performance evaluation shows that the proposed method outperforms competing methods such as CSSM, TOPS and WAVES algorithms in terms of estimation error, probability of resolution and number of sample support for a given SNR in scenarios in which many sources are present in the system, the array size is large, and the number of samples is small. Index Terms-Wideband direction-of-arrival (DOA) estimation, uniform circular arrays (UCA), auxiliary-vector (AV) filtering, small sample support.

Improved Soft Decoding of Reed-Solomon Codes on Gilbert-Elliott Channels

2019 IEEE International Symposium on Information Theory (ISIT), 2019

It was shown by Guruswami and Rudra that Reed-Solomon codes can be list decoded to recover from p... more It was shown by Guruswami and Rudra that Reed-Solomon codes can be list decoded to recover from phased burst errors (i.e. errors occurring within fixed regular intervals) up to the information-theoretic limit and, in particular, beyond the Guruswami-Sudan bound. In this paper, we present evidence that the algorithm developed by Guruswami and Rudra can also give improvement for more "irregular" burst errors. We develop a low-complexity multiplicity assignment scheme for soft decoding of Reed-Solomon (RS) codes. Specifically, we present simulation results where such soft decoding of RS codes outperforms the existing soft decision decoding algorithms of Koetter and Vardy as well as the algorithm of Das and Vardy on Gilbert-Elliott channels (under QAM and BPSK modulations) for channels that are more bursty. We also present a theoretical result that shows that for certain Gilbert-Elliott channels, with high probability of errors, the output list size for list decoding RS codes is one.

Sign Language Gesture Recognition Using Doppler Radar and Deep Learning

2019 IEEE Globecom Workshops (GC Wkshps), 2019

In this paper, we study American sign language (ASL) hand gesture recognition using Doppler radar... more In this paper, we study American sign language (ASL) hand gesture recognition using Doppler radar. A set of ASL hand gesture motions are captured as micro-Doppler signals using a microwave X-band Doppler radar transceiver. We apply joint time-frequency analysis and observe the presence of the micro-Doppler signatures in the spectrogram. The micro-Doppler signatures of different hand gestures are analyzed using Matlab. Each hand gesture is observed to contain unique spectral characteristics. Based on unique spectral characteristics, we investigate the classification of ASL essential short phrases including emergency signals. For recognizing and characterizing the presence of micro-Doppler signatures in spectrogram we explore deep convolution neural network (DCNN) algorithm. We show that the DCNN algorithm can classify different sign language gestures based on the presence of micro-Doppler signatures in the spectrogram with fairly high accuracy. Experimental results reveal that utilizing 80% of data for training, and the remaining 20% for validation purposes in DCNN algorithm a validation accuracy of 87.5% is achieved. To further improve the recognition system, we apply a very deep learning algorithm VGG-16 using transfer learning, which improves the validation accuracy to 95%.

NOMA Computation Over Multi-Access Channels for Multimodal Sensing

IEEE Wireless Communications Letters, 2021

An improved mean squared error (MSE) minimization solution based on eigenvector decomposition app... more An improved mean squared error (MSE) minimization solution based on eigenvector decomposition approach is conceived for wideband non-orthogonal multiple-access based computation over multi-access channel (NOMA-CoMAC) framework. This work aims at further developing NOMA-CoMAC for next-generation multimodal sensor networks, where a multimodal sensor monitors several environmental parameters such as temperature, pollution, humidity, or pressure. We demonstrate that our proposed scheme achieves an MSE value approximately 0.7 lower at E b /No = 1 dB in comparison to that for the average sum-channel based method. Moreover, the MSE performance gain of our proposed solution increases even more for larger values of subcarriers and sensor nodes due to the benefit of the diversity gain. This, in return, suggests that our proposed scheme is eminently suitable for multimodal sensor networks. Index Terms-Non-orthogonal multiple-access (NOMA), computation over multi-access channels (CoMAC).

Low-Complexity Detection for Faster-than-Nyquist Signaling Based on Probabilistic Data Association

IEEE Communications Letters, 2019

In this paper, we investigate the sequence estimation problem of faster-than-Nyquist (FTN) signal... more In this paper, we investigate the sequence estimation problem of faster-than-Nyquist (FTN) signaling as a promising approach for increasing spectral efficiency (SE) in future communication systems. In doing so, we exploit the concept of Gaussian separability and propose two probabilistic data association (PDA) algorithms with polynomial time complexity to detect binary phase-shift keying (BPSK) FTN signaling. Simulation results show that the proposed PDA algorithm outperforms the recently proposed SSSSE and SSSgbKSE algorithms for all SE values with a modest increase in complexity. The PDA algorithm approaches the performance of the semidefinite relaxation (SDRSE) algorithm for SE values of 0.96 bits/sec/Hz, and it is within the 0.5 dB signal-to-noise ratio (SNR) penalty at SE values of 1.10 bits/sec/Hz for the fixed values of β = 0.3.

Uniquely Decodable Ternary Codes for Synchronous CDMA Systems

2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2018

In this paper, we consider the problem of recursively designing uniquely decodable ternary code s... more In this paper, we consider the problem of recursively designing uniquely decodable ternary code sets for highly overloaded synchronous code-division multipleaccess (CDMA) systems. The proposed code set achieves larger number of users K < K t max than any other known state-of-the-art ternary codes that offer low-complexity decoders in the noisy transmission. Moreover, we propose a simple decoder that uses only a few comparisons and can allow the user to uniquely recover the information bits. Compared to maximum likelihood (ML) decoder, which has a high computational complexity for even moderate code length, the proposed decoder has much lower computational complexity. We also derived the computational complexity of the proposed recursive decoder analytically. Simulation results show that the performance of the proposed decoder is almost as good as the ML decoder. * where γ(n) function is the number of ones in the binary expansion of all positive integers less than n.

Design of permutation-based sparse code multiple access system

2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2017

We consider the problem of designing a sparse code multiple access (SCMA) codebook that is based ... more We consider the problem of designing a sparse code multiple access (SCMA) codebook that is based on permutation. Conventional SCMA is a multidimensional codebook-based non-orthogonal spreading technique, in which each layer of incoming bits are directly mapped to multidimensional codewords which have nonzero entries on the same resources. In this paper, unlike the traditional SCMA scheme, the data bits to be transmitted determine the nonzero entry locations based on the permutation. The proposed SCMA codebooks are converted to a multiuser code-division multiple-access (CDMA) detection system before applying an iterative decoder. The complexity of the proposed iterative decoder is lower in comparison to exponential message passing algorithm (MPA) and outperforms in terms of bit-error-rate (BER).

Low-Density Spreading Codes for NOMA Systems and a Gaussian Separability-Based Design

IEEE Access, 2021

Improved low-density spreading (LDS) code designs based on the Gaussian separability criterion ar... more Improved low-density spreading (LDS) code designs based on the Gaussian separability criterion are conceived. We show that the bit error rate (BER) hinges not only on the minimum distance criterion, but also on the average Gaussian separability margin. If two code sets have the same minimum distance, the code set having the highest Gaussian separability margin will lead to a lower BER. Based on the latter criterion, we develop an iterative algorithm that converges to the best known solution having the lowest BER. Our improved LDS code set outperforms the existing LDS designs in terms of its BER performance both for binary phase-shift keying (BPSK) and for quadrature amplitude modulation (QAM) transmissions. Furthermore, we use an appallingly low-complexity minimum mean-square estimation (MMSE) and parallel interference cancellation (PIC) (MMSE-PIC) technique, which is shown to have comparable BER performance to the potentially excessive-complexity maximum-likelihood (ML) detector. This MMSE-PIC algorithm has a much lower computational complexity than the message passing algorithm (MPA). a a Code sets for MPA are designed similar to low-density parity-check (LDPC) codes to avoid cycles and to increase girth of the Tanner graph, code sets that are ''optimal'' for MMSE-PIC might not be optimal for MPA.

The use of decorrelation and code division multiplexed pilots for DS-CDMA systems with multiantenna receivers

by Naser Salam and Claude Damours

2005 13th European Signal Processing Conference, Sep 1, 2005

In this paper, we investigate the use of code division multiplexed (CDM) pilots for channel estim... more In this paper, we investigate the use of code division multiplexed (CDM) pilots for channel estimation for directsequence code division multiple access (DS-CDMA) systems with multiple receive antennas. Decorrelation is used on the output of each receive antenna to remove MAI from both the data and pilot streams. This leads to more reliable channel estimation which in turn reduces the combination loss. We look at the bit error rate (BER) performance of this system in flat Rayleigh fading.

Adaptive Iterative Soft-Input Soft-Output Parallel Decision-Feedback Detectors for Asynchronous Coded DS-CDMA Systems

EURASIP Journal on Wireless Communications and Networking, 2005

The optimum and many suboptimum iterative soft-input soft-output (SISO) multiuser detectors requi... more The optimum and many suboptimum iterative soft-input soft-output (SISO) multiuser detectors require a priori information about the multiuser system, such as the users' transmitted signature waveforms, relative delays, as well as the channel impulse response. In this paper, we employ adaptive algorithms in the SISO multiuser detector in order to avoid the need for this a priori information. First, we derive the optimum SISO parallel decision-feedback detector for asynchronous coded DS-CDMA systems. Then, we propose two adaptive versions of this SISO detector, which are based on the normalized least mean square (NLMS) and recursive least squares (RLS) algorithms. Our SISO adaptive detectors effectively exploit the a priori information of coded symbols, whose soft inputs are obtained from a bank of single-user decoders. Furthermore, we consider how to select practical finite feedforward and feedback filter lengths to obtain a good tradeoff between the performance and computational complexity of the receiver.

Comparison of MFSK variants for a hybrid DS/FH-CDMA system in Rayleigh fading

Lecture Notes in Computer Science, 1996

This paper compares the spectral efficiency of a hybrid DS/FH-CDMA system employing variants of M... more This paper compares the spectral efficiency of a hybrid DS/FH-CDMA system employing variants of MFSK modulation. The proposed modulation schemes are: non-coherent MFSK, MFSK-DPSK, and wideband MT-FSK. In each case, the signal to be transmitted is modulated by a high rate BPSK signal (the PN sequence) and then hopped at a rate higher than the symbol rate into different frequency

Hybrid DS/FH-CDMA system employing MT-FSK modulation for mobile radio

Proceedings of 6th International Symposium on Personal, Indoor and Mobile Radio Communications, 1995

... Thus it can con-vey at most log2 ( ; ) bits of information per character. It has the potentia... more

Linear soft-input soft-output multiuser detection for coded multiuser systems

For coded multiuser systems, an iterative receiver consisting of a soft-input soft-output (SISO) ... more For coded multiuser systems, an iterative receiver consisting of a soft-input soft-output (SISO) multiuser detector and a bank of single-user (SISO) decoders can provide a system performance which approaches that of the single user system after many iterations. In this paper, we transform the traditional linear multiuser detectors, namely the decorrelator and MMSE detector, into SISO detectors which can cooperate with single-user decoders iteratively. The resulting system performance converges quickly, while the computational complexity is proportional to the number of users squared. Both performance analysis and simulation results are provided. Finally, the comparison between these two types of linear SISO detectors is presented.

Rapid prototyping of MIMO-OFDM based on parity bit selected and permutation spreading

International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 2015

In this paper, a novel MIMO-OFDM transmission scheme is developed to effectively enable multi-acc... more In this paper, a novel MIMO-OFDM transmission scheme is developed to effectively enable multi-access by joint code design across multiple antennas, subcarriers, OFDM frames, and users. It achieves better spectrum efficiency while improving bit error rate performance. The proposed scheme uses either parity bit selected or permutation techniques to assign spreading codes at the transmitter side. As a result, the detection at the receiver is greatly improved because of the fact that identifying the spreading code(s) directly yields the transmitted data symbols. The paper also investigates the field-programmable gate array implementation of the proposed algorithms; optimization techniques are proposed to reduce area, power, and time. These techniques include a pipelined architecture for inverse FFT/FFT blocks, an efficient low complexity algorithm for despreading based on counters and comparators and an optimized architecture for complex matrix inversion using Gauss-Jordan elimination (GJ-elimination). Finally, the fixed-point optimized field-programmable gate array architecture for MIMO-OFDM transceiver is developed, where the maximum allowed performance loss because of quantization is defined, the tradeoffs between BER performance and area reduction are investigated.

Subspace decomposition approach to multi-user MIMO channel estimation in SC-FDE systems

Multiuser multiple-input multiple-output (MU-MIMO) wireless systems that employ single-carrier fr... more Multiuser multiple-input multiple-output (MU-MIMO) wireless systems that employ single-carrier frequencydomain equalization (SC-FDE) for uplink transmissions can provide high data rates with increased spectral efficiency under severe channel conditions. However, the availability of accurate channel estimates at the base station (BS) receiver is crucial for achieving peak performance. In this paper, we investigate the use of subspace decomposition and derive a novel algorithm for the blind estimation of MU-MIMO channels in SC-FDE systems, as specified by the 3GPP LTE. By exploiting the long data blocks available in LTE standards, our proposed blind algorithm can obtain accurate estimates of the MU-MIMO channels over every block of transmitted data. This provides for a bandwidthefficient solution in SC-FDE systems by eliminating (reducing) the need to allocate an entire block of pilot sequences for each active transmitter. Furthermore, since the channel estimation is deployed at the BS, the computational complexity is not considered to be a significant burden for future systems in exchange for the increased spectral efficiency. The results of simulations over fading channels, using realistic system parameters representative of LTE-Advanced, demonstrate the advantages of our proposed blind subspace-based channel estimation algorithm and support the feasibility of the resulting MU-MIMO SC-FDE scheme with reduced training.

A Low Complexity Multi-User Detector Employing Partial Decision Techniques for SCDMA Systems

2006 Canadian Conference on Electrical and Computer Engineering, 2006

In this paper, we propose and investigate a multiple antenna, space-code division multiple access... more In this paper, we propose and investigate a multiple antenna, space-code division multiple access (SCDMA) system operating on mobile Rayleigh fading channels, with the emphasis on measured channel data. The main objective is to improve the capacity performance of existing direct-spread code-division multiple access (DS- CDMA) systems by employing multiple transmit and/or multiple receive antennas. In the proposed system, partial