Members

• Future Research Work:

• Cybersecurity in Large Scale Massive Wireless Networks: Malware epidemics Characterization and Countermeasures

• Cybersecurity of Smart Grids: Practical Challenges in Tampering detection of Smart Meters (Interdisciplinary with the Power Area)

• Continuation of Geoseismic Wireless data Acquisition

faculty.kfupm.edu.sa/EE/mesbahw/

To address the new challenges imposed by next generation wireless networks, holistic designs that spans multiple disciplines of signal processing, wireless communications, networking, machine learning, big data, and cyber security are required. This necessitates developing new theoretical foundations and mathematical models that are able to capture the new characteristics of next generation networks (e.g., high node density, wide spatial existence, multitude heterogeneity, context awareness, diverse QoS constraints) and jointly account for the multidisciplinary design perspectives. The center research focuses on developing such multidisciplinary theoretical bases that will lay the foundations to achieve intelligent, self-organized, self-optimized, and context-aware management/operation for next generation wireless networks, and hence, realizing and unleashing the potentials of the foreseen smart world era.

sites.google.com/site/elsawyhesham/

• My research spans different areas of wireless communications and sensing, including visible light communications, physical layer security, resource allocations in cell-free communications, employing advanced deep learning tools to optimization problems in wireless communications, among others. From the sensing side, I have a great interest in applying deep learning tools to enhancing seismic image feature extraction as well as designing and implementation of localized drone detection radars.

• As for the themes, I suggest the following 4 wide-scope areas as a start. Later more focus can be discussed:

• Wireless systems design and optimization

• Radar systems design and implementation

• Advanced Radar signal processing

• Advanced Seismic image processing

faculty.kfupm.edu.sa/EE/zummo/index.htm

• Energy Efficient Communication for future wireless networks (Green Communications)

• Spectral Efficient Communication to meet exponentially growing users’ data-rate requirements

• Ensuring secure communication by employing physical layer security.

• Resource Allocation/Optimization (power allocation or beamforming design) in futuristic (5G/6G) wireless communication systems, e.g., UAV-enabled communication, millimeter wave communication, massive-MIMO commutation, NOMA based communication, Ultrareliable and low-latency communication (URLLC), etc.

faculty.kfupm.edu.sa/EE/anasir/

• Future Communication Systems

• Free space optical networks, Ultra-reliable low latency (uRLLC), massive Machine-type communications (mMTC), enhance Mobile Broadband (eMBB), Reconfigurable Intelligent Surfaces (RIS), UAV networks, Underwater wireless networks, mmWave and TeraHertz wireless networks, Machine learning for wireless communication systems, RFID and backscatter communications.

• IoT, IIoT, & Sensor Networks

• IoT Networks for Smart Cities, Smart Grids, Smart Living Spaces, Industry 4.0, Intelligent Transportation Systems, massive IoT (mIoT), Underwater and Underground Sensor and IoT Networks, Industrial Cyber-Physical Systems (I-CPS) and interactions amongst the machines, data, and humans. Physical and virtual sensing-as-a-service between physical and cyber worlds.

• Signal Processing for Communications

• Adaptive antennas and beamforming, Channel estimation, acquisition, and equalization, Compressive sensing and sparse signal processing algorithm, Localization of Things (LoT), Localization, positioning, and tracking techniques,

• Green Communication Solutions

• higher agricultural productivity, industrial automation, clean air and clean water, convenient and safe city life, technology viability of green and energy-sustainable communication solutions ranging from low-rate telemetric communications to highly reliable, ultra-low latency, and bandwidth-intensive communications.

faculty.kfupm.edu.sa/EE/suhaild/

faculty.kfupm.edu.sa/ee/samir/

•advances in signal processing/communications theory and mathematical tools (optimization, constrained or non-constrained, theory, Markov chain, probability theory, stochastic processes, etc.) to address the challenges.

•Of course, these algorithms are devised for different access techniques, such as SC-FDMA, TDMA, CDMA, or the latest technology named non-orthogonal multiple access (NOMA). For the case of NOMA, we leverage and capitalize our experience on the work done on CDMA and blind source separation (mainly second order statistics (SOS) techniques), coming up with either a corresponding serial interference canceller (SIC) or a parallel one (PIC).

•Not to forget, other tools such whitening and beam forming in massive MIMO (used in 5G/6G systems, mm Wave) are of paramount importance including the use of learning (e.g., machine learning (MI) or deep learning (DI)) or using heuristic approach (PSO-based technique). Indeed, it is clear today that all scientific research activities are directly influenced by these technologies, which propose new architectures for information processing based on huge amounts of data storage, management and computing resources.

•Globally, 5G network deployment is rapidly moving from trials to early commercialization and is promising to provide higher data speeds at low latency and enhanced throughput to handle more simultaneous connections without causing disruptions. However, some issues and challenges have not been fully yet addressed in 5G mobile networks and they are attracting further research efforts. The aspect of high mobility is a challenging one as well. Certainly, sophisticated tracking algorithms must be appropriately designed to track these challenging changes, including the reduction of the effect of nonlinearity on the system’s behavior.

• Based on the above, I can now list some of my areas of interest including, but are not limited to:

•Channel Estimation for Intelligent Reflecting Surface Assisted MIMO Communication in 5G and beyond.

•Massive MIMO for Next Generation Wireless Systems.

•Beamforming Optimization for Wireless Network Aided By Intelligent Reflecting Surface.

•Equalization for Wideband fast Varying Wireless Communication Channels.

•Efficient equalization of nonlinear multichannel systems.

•Wideband Millimeter-Wave Propagation Measurements and Channel Models for Future Wireless Communication System Design.

•A Blind Strategy over Adaptive Sensor Networks.

•Structure-Aided Blind SIMO/MIMO System Identification.

•Adaptive Impairments Modeling in Broadband Nonlinear Transmitters.

•Signal Processing for Communications.

• Five different themes that I think can represent the center subareas:

•Massive MIMO for Next Generation Wireless Systems.

•Channel Estimation for Intelligent Reflecting Surfaces.

•Signal Processing for Communications.

•Internet of Things (IoT) applications.

•Signal Processing for Communications.

faculty.kfupm.edu.sa/EE/azzedine/

faculty.kfupm.edu.sa/EE/ahmadisa/

faculty.kfupm.edu.sa/EE/malhassoun/

•My research over the last decade has focused on the areas of high-speed optical communications and sensing. In the following, I have elaborated on some of my research interests:

•Design of Fiber Amplifiers and Lasers for Optical Communications:

•The design of novel optical amplifiers and fiber lasers is currently at the forefront of research due to their potential applications in the areas of high-speed dense wavelength division multiplexing systems and networks. Furthermore, these light sources provide an effective solution for the next generation passive optical networks (NG-PONs) that show promising outlooks in meeting the ever-growing demand for telecommunication capabilities and internet traffic. My research activities focus on the design of novel fiber amplifiers and fiber laser designs based on gain media comprising of doped fiber and semiconductor optical amplifiers. The novel proposed designs will potentially save the cost of the transmitter side optical sources currently deployed in high-speed optical communications.

•Design of Smart Optical Sensors:

•Smart materials with embedded devices to sense, measure, and react to external stimuli are required to contribute to intelligent systems at small and large scales. While embedded inside the host material, the sensors should be able to capture any phenomenon based on the sensor type; measure it, and transmit the information. These types of materials with built-in sensors are called nervous materials and can feel multiple structural and external stimuli, e.g., stress, force, pressure, and temperature. My current research activities focus on the use of optical fiber based sensors for health monitoring of materials and concrete structures.

•Potential Research Themes:

•Design of distributed Sensors

•Development of lasers for optical communications

faculty.kfupm.edu.sa/EE/kqureshi/

• In the following I list a few research areas of my interest.

• Action anticipation and V2V path prediction

• I have been working on human action recognition and prediction in the scenarios where actions are structured such as making wudu. We have utilized state-of-the-art machine learning methods to perform this task. Recently, we have switched our focus on human action anticipation based on the history of the actions that the person has already performed. This requires understanding the way a person performs a particular task. While there are many applications of human action anticipation, I foresee the application of the developed machine/deep learning methods in a very different field - V2V communications.

• In V2V communications, some information is shared by vehicles among themselves to have a 360 degrees view around them. This information includes, for each vehicle, the position, speed, acceleration, brake status etc. Another important information is the vehicle's predicted path. This requires a deep understanding of the driver's behavior as well as the understanding of the dynamics in a particular area of the roads. I believe the knowledge we will gain from the design of deep learning models for human action anticipation will be useful to predict the path of vehicles. Therefore, this could be one possible direction to explore and would allow us to utilize the different data modalities available in a vehicle equipped with V2V communications.

• Physical Layer Security

• As mentioned above, I have recently been working on AI/ML solutions for numerous problems. Recently, I got interested in using AI for physical layer security (PLS). I believe it will be interesting to explore and dig deeper in this direction with the aim to realize PLS for energy-constrained scenarios. Specifically, I believe PLS is important when it comes to securing IoT and IIoT infrastructures where many devices/sensors could be battery-powered and thus constrained in energy. I am also familiar with compressive sensing which could play an important role in implementing PLS in energy-constrained IoT/IIoT environments. Signal, Image and Video Processing I have worked extensively in the fields of signal and image processing. For example, my most recent works include the design of denoising approaches for both day-to-day images and the sub-surface volumes (seismic volumes). Very recently, I have been involved in a work where traditional signal processing algorithms are unrolled and implemented using NN/CNNs etc. I am interested in pursuing this direction to solve more signal processing/communication related problems.

https://sites.google.com/view/husseinattia/home

faculty.kfupm.edu.sa/EE/sheikhsi/

faculty.kfupm.edu.sa/EE/zahedmk/

faculty.kfupm.edu.sa/EE/masoud/

faculty.kfupm.edu.sa/EE/makousa/

faculty.kfupm.edu.sa/EE/ymahnashi/

Nowadays, most of the research in wireless communications tries to come up with new cutting-edge techniques, algorithms, and protocols. A lot of ongoing research aims also to deal with some well-known problems in wireless networks such as co-channel interference, spectrum scarcity, and others. New techniques and solutions that help in increasing the system capacity in terms of number of served users are being proposed in these days. New techniques that support mixing different types of wireless links such as radio frequency, visible light communication, and free space optical links are now attracting huge consideration by many researchers in the world. All these techniques and solutions aim to enhance the wireless network performance and the quality of provided services for the end users. The conducted research is done in all networks layers. Adopting the machine learning techniques in wireless communications is currently attracting the attention of many researchers too. Among the new hot topics in research in these days are the following:

• Free space optical communications, indoor and outdoor.

• Mixing radio frequency links with optical and visible light communication links.

• Reconfigurable intelligent surface communications.

• Underwater wireless optical communications.

• Unmanned aerial vehicles networks.

• Machine learning techniques for wireless communication systems.

• Device-to-device communications.

• Security techniques in physical layer and other layers for wireless communication networks.

• Energy harvesting techniques and green communications.

The research work on the above topics could be done from various aspects, starting with the basic research at the low technology readiness levels up to the applied research and prototyping some of these new techniques at the high technology readiness levels. Coming up with new solutions and techniques requires collaborations among researchers from different specialties. This motivates the establishment of our multidisciplinary center.

faculty.kfupm.edu.sa/EE/SALHAB/

Sidqy is currently a PhD student. His research interests primarily lie in the areas of wireless communications performance analysis and modeling, physical layer security of wireless networks, and employment of machine learning techniques in wireless communications.

Kabiru Nasiru Aliyu received BSc in Electronics from Bayero University Kano (BUK), Nigeria, in 2016 and MSc in Electrical Engineering (Communication) from King Fahd University of Petroleum and Minerals, (KFUPM) Dhahran, Saudi Arabia in 2020. Currently, he is Pursuing his Ph.D. in the department of electrical engineering at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia. His research interests include Electronics, Communication, and Neural Network.