Abdul Karim Gizzini

SogetiLabs Research and Innovation (part of Capgemini)

The support of artificial intelligence (AI) based decision-making is a key element in future 6G networks, where the concept of native AI will be introduced. Moreover, AI is widely employed in different critical applications such as autonomous driving and medical diagnosis. In such applications, using AI as black-box models is risky and challenging....

Doubly-selective channel estimation represents a key element in ensuring communication reliability in wireless systems. Due to the impact of multi-path propagation and Doppler interference in dynamic environments, doubly-selective channel estimation becomes challenging. Conventional symbol-by-symbol (SBS) and frame-by-frame (FBF) channel estimation...

Research into 6G networks has been initiated to support a variety of critical artificial intelligence (AI) assisted applications such as autonomous driving. In such applications, AI-based decisions should be performed in a real-time manner. These decisions include resource allocation, localization, channel estimation, etc. Considering the black-box...

Reliable and fast channel estimation is crucial for next-generation wireless networks supporting a wide range of vehicular and low-latency services. Recently, deep learning (DL)-based channel estimation has been explored as an efficient alternative to conventional least-square (LS) and linear minimum mean square error (LMMSE) approaches. Most of th...

p>Reliable and fast channel estimation is crucial for next-generation wireless networks supporting a wide range of vehicular and low-latency services. Recently, deep learning (DL) based channel estimation has been explored as an efficient alternative to conventional least-square (LS) and linear minimum mean square error (LMMSE) approaches. Most of...

Doubly-selective channel estimation represents a key element in ensuring communication reliability in wireless systems. Due to the impact of multi-path propagation and Doppler interference in dynamic environments, doubly-selective channel estimation becomes challenging. Conventional channel estimation schemes encounter performance degradation in hi...

Doubly-selective channel estimation represents a key element in ensuring communication reliability in wireless systems. Due to the impact of multi-path propagation and Doppler interference in dynamic environments, doubly-selective channel estimation becomes challenging. Conventional symbol-by-symbol (SBS) and frame-by-frame (FBF) channel estimation...

Research into 6G networks has been initiated to support a variety of critical artificial intelligence (AI) assisted applications such as autonomous driving. In such applications, AI-based decisions should be performed in a real-time manner. These decisions include resource allocation, localization, channel estimation, etc. Considering the black-box...

p>Reliable and fast channel estimation is crucial for next-generation wireless networks supporting a wide range of vehicular and low-latency services. Recently, deep learning (DL) based channel estimation is being explored as an efficient alternative to conventional least-square (LS) and linear minimum mean square error (LMMSE) based channel estima...

p>Reliable and fast channel estimation is crucial for next-generation wireless networks supporting a wide range of vehicular and low-latency services. Recently, deep learning (DL) based channel estimation is being explored as an efficient alternative to conventional least-square (LS) and linear minimum mean square error (LMMSE) based channel estima...

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 exper...

In this paper, we evaluate and make a comparison of the channel estimation performance for three different frame structures of IEEE 802.11p, IEEE 802.11bd-draft and a unique-word (UW)-based physical layer (PHY). As in vehicle-to-everything communication the wireless channel conditions may vary significantly depending on the environment and vehicle...

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, especiall...

Wireless communications play a significant role in facilitating several mobile applications like unmanned aerial vehicles, high-speed railway, and vehicular communications. Particularly, the concept of connected vehicles brings a new level of connectivity to vehicles. Along with novel on- board computing and sensing technologies, vehicular networks...

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 exper...

Wireless communications revolution plays a significant role in facilitating severalmobile applications like unmanned aerial vehicles, high-speed railway, and vehicularcommunications. Particularly, the concept of connected vehicles brings a new level ofconnectivity to vehicles. Along with novel on board computing and sensing technologies,vehicular n...

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 es...

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, especiall...

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 es...

Recently, a non-orthogonal multiple access scheme called multi-user shared access (MUSA) was proposed to provide massive connection capability of low-complexity devices in the 5G networks. MUSA achieves higher spectral efficiency allowing independent devices to transmit data on the same physical layer time-frequency resources. Furthermore, MUSA int...

IEEE 802.11p standard enables the wireless technology that defines vehicular communications. However, IEEE 802.11p frame structure employing low pilot density is not enough to track the channel variations in high mobility scenarios, leading to significant performance degradation. Therefore, ensuring communication reliability in vehicular environmen...

Channel state information is very critical in various applications such as physical layer security, indoor localization, and channel equalization. In this paper, we propose an adaptive channel estimation based on deep learning that assumes the signal-to-noise power ratio (SNR) knowledge at the receiver, and we show that the proposed scheme highly o...

IEEE 802.11p standard is specially developed to define vehicular communications requirements and support cooperative intelligent transport systems. In such environment, reliable channel estimation is considered as a major critical challenge for ensuring the system performance due to the extremely time-varying characteristic of vehicular channels. T...

Least square (LS) channel estimation employed in various communications systems suffers from performance degradation especially in low signal-to-noise ratio (SNR) regions. This is due to the noise enhancement in the LS estimation process. Minimum mean square error (MMSE) takes into consideration the noise effect and achieves better performance than...

High resolution remote sensing data can provide worldwide images rapidly contrasted with conventional strategies for information accumulation. Therefore tiny objects like cars can be easily detected. Automatic vehicles enumeration research domain plays an important role in various applications including traffic monitoring and management. In this pa...

The human eye can easily identify shadows of illuminated objects. However, automatically detecting such shadows with the use of computer tools is a challenging research problem. In this paper, an approach toward successful building shadow detection based on multi-threshold image segmentation technique is introduced and analyzed. Accuracy assessment...

Automated building extraction from high-resolution satellite imagery is a challenging research problem, and several issues remain with respect to the variety of variables to be accounted for. In this paper we present an approach for building detection using multiple cues. We use the shadow, shape, and color features of buildings to propose our appr...

Natural disasters and wars wreak havoc not only on individuals and critical infrastructure, but also leave behind ruined residential buildings and housings. The size, type and location of damaged houses are essential data sources for the post-disaster reconstruction process. Building damage detection due to war activities has not been thoroughly di...

Building detection tool demo, where colored and non-colored buildings are detected from an input image.

With the remarkable advances in high-resolution Earth Observation, we are wit- nessing an explosive growth in the volume, and also velocity, of Remote Sensing data. Generally, the volume of archived data which is growing everyday by ter- abytes. Furthermore, the European Space Agency will launch several satellites in the next few years, which will...

Our project is a Home Control system that works via new technologies: NFC (Near Field Communication) and Raspberry Pi (a mini-computer system). A home control system simplifies people's lives by making everyday tasks easier. For example, from turning on and off any appliances throughout the house to opening and closing doors, a home control system...

This project includes the preparation of a detailed conduit map and optical fiber schematic diagram map, Defining the topology and active equipment using DWDM technology, and calculations of the attenuation and dispersion of the optical fiber links.

This project aims to design a simple robot arm (Hardware + Software). Concerning the hardware part, we take into our consideration all the mechanical issues related to the movements done by the robot arm, the design of the base and the arms are constructed according to the ability of each motor to carry the weights. The software part (control progr...

This project proposes a complete automatic irrigation system for a plant field. The objective of this system is to provide irrigation to the plant field based on vital parameters like temperature and light intensity.

In this report, we will talk about the summer training period that we spent in Rafic Hariri university hospital in the IT department, which was aimed to develop and build a special application for doctors to be able to carry through on the patients' files and information in an easy and clear manner. This application is an iOS-based application. The...

The medical booking system web application aims to facilitate the process of booking dates in order to go to the doctor and to make laboratory tests and radiographs (X-ray). By using this application, the patient can reserve a date for the tasks listed above online via the internet, without going to the medical center. In addition, the patient will...