arXiv subjects

Marwa Chafii

Publications and source records attributed to Marwa Chafii.

88 records · Page 5Linked to original sources

arXiv2022

A Survey on Deep Learning based Channel Estimation in Doubly Dispersive Environments

Wireless communications systems are impacted by multi-path fading and Doppler shift in dynamic environments, where the channel becomes doubly-dispersive and its estimation becomes an arduous task. Only a few pilots are used for channel estimation in conventional approaches to preserve high data rate transmission. Consequently, such estimators experience a significant performance degradation in high mobility scenarios. Recently, deep learning has been employed for doubly-dispersive channel estimation due to its low-complexity, robustness, and good generalization ability. Against this backdrop, the current paper presents a comprehensive survey on channel estimation techniques based on deep learning by deeply investigating different methods. The study also provides extensive experimental simulations followed by a computational complexity analysis. After considering different parameters such as modulation order, mobility, frame length, and deep learning architecture, the performance of the studied estimators is evaluated in several mobility scenarios. In addition, the source codes are made available online in order to make the results reproducible.

cs.IT↗

arXiv2022

A Framework for Amalgamating Optical-OFDM and Optical-OFDM with Index Modulation for Optical Wireless Systems

In this communication, we propose a framework for amalgamating optical-orthogonal frequency-division multiplexing (O-OFDM) and O-OFDM with index modulation (O-OFDM-IM) for optical wireless systems. Both schemes individually have some limitations, e.g., O-OFDM does not provide any granularity for spectral efficiency (SE)/energy efficiency (EE) trade-off, and O-OFDM-IM loses EE for higher order modulation alphabets. By combining O-OFDM and O-OFDM-IM together, the above limitations can be circumvented. Following on from providing the general framework, we use asymmetrically clipped (AC)O-OFDM and ACO-OFDM-IM to demonstrate the validity of the framework. The results presented herein establish that, by consolidating O-OFDM and O-OFDM-IM, in addition to providing SE/EE trade-off, we may realise higher SE and outperform O-OFDM-IM in terms of EE for high SE.

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arXiv2022

Context-Aware Security for 6G Wireless The Role of Physical Layer Security

Sixth generation systems are expected to face new security challenges, while opening up new frontiers towards context awareness in the wireless edge. The workhorse behind this projected technological leap will be a whole new set of sensing capabilities predicted for 6G devices, in addition to the ability to achieve high precision localization. The combination of these enhanced traits can give rise to a new breed of context-aware security protocols, following the quality of security (QoSec) paradigm. In this framework, physical layer security solutions emerge as competitive candidates for low complexity, low-delay and low-footprint, adaptive, flexible and context aware security schemes, leveraging the physical layer of the communications in genuinely cross-layer protocols, for the first time.

cs.CR↗

arXiv2022

A Novel Approach for Cancellation of Non-Aligned Inter Spreading Factor Interference in LoRa Systems

Long Range (LoRa) has become a key enabler technology for low power wide area networks. However, due to its ALOHA-based medium access scheme, LoRa has to cope with collisions that limit the capacity and network scalability. Collisions between randomly overlapped signals modulated with different spreading factors (SFs) result in inter-SF interference, which increases the packet loss likelihood when signal-to-interference ratio (SIR) is low. This issue cannot be resolved by channel coding since the probability of error distance is not concentrated around the adjacent symbol. In this paper, we analytically model this interference, and propose an interference cancellation method based on the idea of segmentation of the received signal. This scheme has three steps. First, the SF of the interference signal is identified, then the equivalent data symbol and complex amplitude of the interference are estimated. Finally, the estimated interference signal is subtracted from the received signal before demodulation. Unlike conventional serial interference cancellation (SIC), this scheme can directly estimate and reconstruct the non-aligned inter-SF interference without synchronization. Simulation results show that the proposed method can significantly reduce the symbol error rate (SER) under low SIR compared with the conventional demodulation. Moreover, it also shows high robustness to fractional sample timing offset (STO) and carrier frequency offset (CFO) of interference. The presented results clearly show the effectiveness of the proposed method in terms of the SER performance.

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arXiv2022

Temporal Averaging LSTM-based Channel Estimation Scheme for IEEE 802.11p Standard

In vehicular communications, reliable channel estimation is critical for the system performance due to the doubly-dispersive nature of vehicular channels. IEEE 802.11p standard allocates insufficient pilots for accurate channel tracking. Consequently, conventional IEEE 802.11p estimators suffer from a considerable performance degradation, especially in high mobility scenarios. Recently, deep learning (DL) techniques have been employed for IEEE 802.11p channel estimation. Nevertheless, these methods suffer either from performance degradation in very high mobility scenarios or from large computational complexity. In this paper, these limitations are solved using a long short term memory (LSTM)-based estimation. The proposed estimator employs an LSTM unit to estimate the channel, followed by temporal averaging (TA) processing as a noise alleviation technique. Moreover, the noise mitigation ratio is determined analytically, thus validating the TA processing ability in improving the overall performance. Simulation results reveal the performance superiority of the proposed schemes compared to recently proposed DL-based estimators, while recording a significant reduction in the computational complexity.

cs.IT↗

arXiv2022

CNN aided Weighted Interpolation for Channel Estimation in Vehicular Communications

IEEE 802.11p standard defines wireless technology protocols that enable vehicular transportation and manage traffic efficiency. A major challenge in the development of this technology is ensuring communication reliability in highly dynamic vehicular environments, where the wireless communication channels are doubly selective, thus making channel estimation and tracking a relevant problem to investigate. In this paper, a novel deep learning (DL)-based weighted interpolation estimator is proposed to accurately estimate vehicular channels especially in high mobility scenarios. The proposed estimator is based on modifying the pilot allocation of the IEEE 802.11p standard so that more transmission data rates are achieved. Extensive numerical experiments demonstrate that the developed estimator significantly outperforms the recently proposed DL-based frame-by-frame estimators in different vehicular scenarios, while substantially reducing the overall computational complexity.

cs.IT↗

arXiv2021

Indoor Localization Under Limited Measurements: A Cross-Environment Joint Semi-Supervised and Transfer Learning Approach

The development of highly accurate deep learning methods for indoor localization is often hindered by the unavailability of sufficient data measurements in the desired environment to perform model training. To overcome the challenge of collecting costly measurements, this paper proposes a cross-environment approach that compensates for insufficient labelled measurements via a joint semi-supervised and transfer learning technique to transfer, in an appropriate manner, the model obtained from a rich-data environment to the desired environment for which data is limited. This is achieved via a sequence of operations that exploit the similarity across environments to enhance unlabelled data model training of the desired environment. Numerical experiments demonstrate that the proposed cross-environment approach outperforms the conventional method, convolutional neural network (CNN), with a significant increase in localization accuracy, up to 43%. Moreover, with only 40% data measurements, the proposed cross-environment approach compensates for data inadequacy and replicates the localization accuracy of the conventional method, CNN, which uses 75% data measurements.

eess.SP↗

arXiv2021

Alternative Chirp Spread Spectrum Techniques for LPWANs

Chirp spread spectrum (CSS) is the modulation technique currently employed by Long-Range (LoRa), which is one of the most prominent Internet of things wireless communications standards. The LoRa physical layer (PHY) employs CSS on top of a variant of frequency shift keying, and non-coherent detection is employed at the receiver. While it offers a good trade-off among coverage, data rate and device simplicity, its maximum achievable data rate is still a limiting factor for some applications. Moreover, the current LoRa standard does not fully exploit the CSS generic case, i.e., when data to be transmitted is encoded in different waveform parameters. Therefore, the goal of this paper is to investigate the performance of CSS while exploring different parameter settings aiming to increase the maximum achievable throughput, and hence increase spectral efficiency. Moreover, coherent and non-coherent reception algorithm design is presented under the framework of maximum likelihood estimation. For the practical receiver design, the formulation of a channel estimation technique is also presented. The performance evaluation of the different variants of CSS is carried out by inspection of the symbol error ratio as a function of the signal-to-noise ratio together with the maximum achievable throughput each scheme can achieve.

eess.SP↗

arXiv2021

Channel Estimation for MIMO Space Time Coded OTFS under Doubly Selective Channels

In this paper, we present a unique word (UW)-based channel estimation approach for multiple-input multiple-output (MIMO) systems under doubly dispersive channels, which is applied to orthogonal time frequency space (OTFS) with space time coding (STC). The OTFS modulation has been recently proposed as a robust technique under time varying channels due to its property of spreading the data symbols over time and frequency. Yet another relevant aspect is the employment of multiple antennas at the transmitter and receiver. Therefore, we consider an STC MIMO system with cyclic delay diversity at the transmitter and maximum ratio combining at the receiver, where we develop a UW-based channel estimation scheme for multiple transmit antennas. We show a recently proposed frame optimization scheme for SISO is directly applicable to MIMO. In addition, we evaluate numerically the frame error rate (FER) of OTFS and OFDM with 2x2 and 4x4 MIMO, where the time varying channel is estimated using the UW-based approach. The FER results reveal that OTFS becomes more advantageous than OFDM for MIMO-STC systems with higher order modulation and code rate.

eess.SP↗

arXiv2021

OFDM with Index Modulation in Orbital Angular Momentum Multiplexed Free Space Optical Links

Communication using orbital angular momentum (OAM) modes has recently received a considerable interest in free space optical (FSO) communications. Propagating OAM modes through free space may be subject to atmospheric turbulence (AT) distortions that cause signal attenuation and crosstalk which degrades the system capacity and increases the error probability. In this paper, we propose to enhance the OAM FSO communications in terms of bit error rate and spectral efficiency, for different levels of AT regimes. The performance gain is achieved by introducing orthogonal frequency division multiplexing (OFDM) with index modulation technique to the OAM FSO system.

eess.SP↗

arXiv2020

In-phase and Quadrature Chirp Spread Spectrum for IoT Communications

This paper describes a coherent chirp spread spectrum (CSS) technique based on the Long-Range (LoRa) physical layer (PHY) framework. LoRa PHY employs CSS on top of a variant of frequency shift keying (FSK), and non-coherent detection is employed at the receiver for obtaining the transmitted data symbols. In this paper, we propose a scheme that encodes information bits on both in-phase and quadrature components of the chirp signal, and rather employs a coherent detector at the receiver. Hence, channel equalization is required for compensating the channel induced phase rotation on the transmit signal. Moreover, a simple channel estimation technique exploits the LoRa reference sequences used for synchronization to obtain the complex channel coefficient used in the equalizer. Performance evaluation using numerical simulation shows that the proposed scheme achieves approximately 1 dB gain in terms of energy efficiency, and it doubles the spectral efficiency when compared to the conventional LoRa PHY scheme. This is due to the fact that the coherent receiver is able to exploit the orthogonality between in-phase and quadrature components of the transmit signal.

eess.SP↗

arXiv2019

Performance Analysis of a 5G Transceiver Implementation for Remote Areas Scenarios

The fifth generation of mobile communication networks will support a large set of new services and applications. One important use case is the remote area coverage for broadband Internet access. This use case ha significant social and economic impact, since a considerable percentage of the global population living in low populated area does not have Internet access and the communication infrastructure in rural areas can be used to improve agribusiness productivity. The aim of this paper is to analyze the performance of a 5G for Remote Areas transceiver, implemented on field programmable gate array based hardware for real-time processing. This transceiver employs the latest digital communication techniques, such as generalized frequency division multiplexing waveform combined with 2 by 2 multiple-input multiple-output diversity scheme and polar channel coding. The performance of the prototype is evaluated regarding its out-of-band emissions and bit error rate under AWGN channel.

eess.SP↗

arXiv2019

Low-Complexity Iterative Receiver for Orthogonal Chirp Division Multiplexing

This paper proposes a low-complexity iterative receiver for the recently proposed Orthogonal Chirp Division Multiplexing (OCDM) modulation scheme, where we consider a system under frequency-selective channels and constrained to channel state information availability only at the receiver. It has been shown that under these assumptions, OCDM becomes an optimal waveform in terms of performance, i.e., frame error rate (FER), when employing a receiver capable of achieving perfect feedback equalizer (PFE) performance. Thus, this work targets proposing such a receiver for OCDM with low-complexity. Our approach is based on the well accepted minimum mean squared error with parallel interference cancellation (MMSE-PIC), where we derive an approximated equalizer whose complexity is reduced to two fast Fourier transforms (FFTs) per iteration. The FER results reveal that i) the proposed low-complexity receiver perform as good as the original MMSE-PIC, ii) OCDM performs very closely to PFE, and iii) OCDM has approximately 2.5 dB improvement over OFDM.

eess.SP↗

arXiv2018

Practical GFDM-based Linear Receivers

The conventional receiver designs of generalized frequency division multiplexing (GFDM) consider a large scale multiple-input multiple-output (MIMO) system with a block circular matrix of combined channel and modulation. Exploiting this structure, several approaches have been proposed for low complexity joint linear minimum mean squared error (LMMSE) receiver. However, the joint design is complicated and inappropriate for hardware implementation. In this paper, we define the concept of GFDM-based linear receivers, which first performs channel equalization (CEq) and afterwards the equalized signal is processed with GFDM demodulator. We show that the optimal joint LMMSE receiver is equivalent to a GFDM-based one, that applies LMMSE-CEq and zero-forcing demodulation. For orthogonal modulation, the optimal LMMSE receiver has an implementation-friendly structure. For the non-orthogonal case, we propose two practical designs that approach the performance of the joint LMMSE. Finally, we analytically prove that GFDM-based receivers achieve equal signal-to-interference-plus-noise ratio per subsymbols within the same subcarrier.

eess.SP↗

arXiv2018

Unified Low Complexity Radix-2 Architectures for Time and Frequency-domain GFDM Modem

Most of the conventional multicarrier waveforms explicitly or implicitly involve a generalized frequency division multiplexing (GFDM)-based modem as a core part of the baseband processing. Some are based on GFDM with a single prototype filter, e.g. orthogonal frequency division multiplexing (OFDM) and others employ multiple filters such as filter bank multicarrier (FBMC). Moreover, the GFDM degrees of freedom combined with multiple prototype filters design allow the development and optimization of new waveforms. Nevertheless, GFDM has been widely considered as a complex modulation because of the requirements of odd number of subcarriers or subsymbols. Accordingly, the current state of the art implementations consume high resources. One solution to reduce the complexity is utilizing radix-2 parameters. Due to the advancement in GFDM filter design, the constraint of using odd parameters has been overcome and radix-2 realization is now possible. In this paper, we propose a unified low complexity architecture that can be reconfigured to provide both time-domain and frequency-domain modulation/demodulation. The design consists of several radix-2 fast Fourier transform (FFT) and memory blocks, in addition to one complex multiplier. Moreover, we provide a unified architecture for the state of the art implementations, which is designed based on direct computation of circular convolution using parallel multiplier chains. As we demonstrate in this work, the FFTbased architecture is computationally more efficient, provides more flexibility, significantly reduces the resource consumption, and achieves similar latency for larger block size.

eess.SP↗

arXiv2018

Extended GFDM Framework: OTFS and GFDM Comparison

Orthogonal time frequency space modulation (OTFS) has been recently proposed to achieve time and frequency diversity, especially in linear time-variant (LTV) channels with large Doppler frequencies. The idea is based on the precoding of the data symbols using symplectic finite Fourier transform (SFFT) then transmitting them by mean of orthogonal frequency division multiplexing (OFDM) waveform. Consequently, the demodulator and channel equalization can be coupled in one processing step. As a distinguished feature, the demodulated data symbols have roughly equal gain independent of the channel selectivity. On the other hand, generalized frequency division multiplexing (GFDM) modulation also employs the spreading over the time and frequency domains using circular filtering. Accordingly, the data symbols are implicitly precoded in a similar way as applying SFFT in OTFS. In this paper, we present an extended representation of GFDM which shows that OTFS can be processed as a GFDM signal with simple permutation. Nevertheless, this permutation is the key factor behind the outstanding performance of OTFS in LTV channels, as demonstrated in this work. Furthermore, the representation of OTFS in the GFDM framework provides an efficient implementation, that has been intensively investigated for GFDM, and facilitates the understanding of the OTFS distinct features.

eess.SP↗