The Information Processing and Transmission (IPT) Lab is intended to provide a research platform that investigates problems at the interface of wireless communication theory, signal processing theory, and Applied Mathematics. The research at IPT helps in solving theoretical problems that find applications in real system. The mission of the lab is to provide innovative solutions from a variety of areas, including communication and information theories, statistical signal processing, signal estimation and detection, multi-hop cooperative networks, green wireless communications, smart grid communications, and multi-user systems.
School of Electrical Engineering and Computer Science
National University of Sciences and Technology
Biography: Syed Ali Hassan received his Ph.D. in Electrical Engineering from Georgia Institute of Technology, Atlanta, USA in 2011. He received his MS Mathematics from Georgia Tech in 2011 and MS Electrical Engineering from University of Stuttgart, Germany, in 2007. He was awarded BE Electrical Engineering (highest honors) from National University of Sciences and Technology (NUST), Pakistan, in 2004. His broader area of research is signal processing for communications. Currently, he is working as a Professor at the School of Electrical Engineering and Computer Science (SEECS), NUST, where he is heading the IPT research group, which focuses on various aspects of theoretical communications.
Dr. Syed Ali Hassan
[J96] M. K. Shehzad, L. Rose, S. Wesemann, M. Assaad and S. A. Hassan, “Design of an Efficient CSI Feedback Mechanism in Massive MIMO Systems: A Machine Learning Approach using Empirical Data,” arXiv preprint arXiv:2208.11951, 2022.
[J95] S. Munawar, Z. Ali, M. Waqas, S. Tu, S. A. Hassan and G. Abbas, “Cooperative Computational Offloading in Mobile Edge Computing for Vehicles: A Model-based DNN Approach,” IEEE Transactions on Vehicular Technology, to appear, 2022, doi: 10.1109/TVT.2022.3217323.
[J94] Q. Abbas, S. A. Hassan, H. K. Qureshi, K. Dev, H. Jung, “A comprehensive survey on age of information in massive IoT networks,” Computer Communications, vol. 197, pp. 199-213, January 2023.
[J93] N. Waqar, S. A. Hassan, H. Pervaiz, H. Jung, K. Dev, “Deep multi-agent reinforcement learning for resource allocation in NOMA-enabled MEC,” Computer Communications, vol. 196, pp. 1-8, December 2022.
[J92] S. Zeb, A. Mahmood, S. A. Hassan, M. Gidlund, M. Guizani, “Analysis of Beyond 5G Integrated Communication and Ranging Services Under Indoor 3-D mmWave Stochastic Channels,” IEEE Transactions on Industrial Informatics, vol. 18, no. 10, pp. 7128-7138, October 2022.
[J91] M. Anjum, A. Khan, S. A. Hassan, H. Jung, K. Dev, “Analysis of time-weighted LoRa-based positioning using machine learning,” Computer Communications, vol. 193, pp. 266-278, September 2022.
[J90] N. Waqar, S. A. Hassan, A. Mahmood, K. Dev, D. T. Do, M. Gidlund, “Computation Offloading and Resource Allocation in MEC-Enabled Integrated Aerial-Terrestrial Vehicular Networks: A Reinforcement Learning Approach,” IEEE Transactions on Intelligent Transportation Systems, to appear, 2022.
[C122] S. A. Ullah, S. Zeb, A. Mahmood, S. A. Hassan, M. Gidlund, “Deep RL-assisted Energy Harvesting in CR-NOMA Communications for NextG IoT Networks“, IEEE GLOBECOM, Brazil, December 2022.
[C121] M. W. Akhtar, A. Mahmood, S. F. Abedin, S. A. Hassan, M. Gidlund, “Exploiting NOMA for Radio Resource Efficient Traffic Steering Use-case in O-RAN“, IEEE GLOBECOM, Brazil, December 2022.
[C120] A. Umar, S. Basharat, S. A. Hassan, H. Jung, “On the Performance of Multi-tier Space-Air-Ground Integrated Network Exploiting mmWave and THz Capabilities for 6G Communication“, ACM MobiCom’22, Australia, October 2022.
[C119] N. Rubab, S. Zeb, A. Mahmood, S. A. Hassan, M. Gidlund, “Interference Mitigation in RIS-assisted 6G Systems for Indoor Industrial IoT Networks“, IEEE Sensor Array and Multichannel Signal Processing, Finland, June 2022.
[C118] F. M. A. Khan, S. A. Hassan, R. I. Ansari, H. Jung, “Analyzing Convergence Aspects of Federated Learning: More Devices or More Network Layers?“, IEEE VTC Spring 2022, Finland, June 2022.
[C117] M. Hassaan, M. B. Azhar, K. N. Syed, S. A. Hassan, H. Pervaiz, H. Jung, “Performance Analysis of THz Enabled HetNets in Diverse Building Densities“, IEEE VTC Spring 2022, Finland, June 2022.
[C116] N. Waqar, S. A. Hassan, A. J. Hashmi, H. Jung, “NOMA-enabled COMP Transmission in Satellite-Aerial-Terrestrial Networks“, IEEE ICC, South Korea, May 2022.
[Chapter 18] M. K. Shehzad, S. A. Hassan, M. A. L-Nieto, P. Otero, “UAV Trajectory Optimization and Choice for UAV Placement for Data Collection in Beyond 5G Networks“, in Intelligent Unmanned Air Vehicles Communications for Public Safety Networks, Springer, Singapore, ISBN 9789811912924, May 2022.
[Chapter 17] M. W. Akhter, S. A. Hassan, “Future Autonomous Transportation: Challenges and Prospective Dimensions“, in Intelligent Cyber Physical Systems for Autonomous Transportation, Springer, Cham, ISBN 9783030920548, December 2021.
[Chapter 16] M. Amjad, M. Waheed, S. A. Hassan, H. K. Qureshi, “UAV-assisted Energy Harvesting for WSN/IoT Networks“, in Energy Harvesting in Wireless Sensor Networks and Internet of Things, IET Publishers, ISBN 9781785617362, December 2021.
[Chapter 15] M. K. Shehzad, M. W. Akhtar, S. A. Hassan, “Performance of mmWave UAV-Assisted 5G Hybrid Heterogeneous Networks“, in Autonomous Airborne Wireless Networks, First Edition, John Wiley and Sons, ISBN 9781119751687, July 2021.
[Chapter 14] O. Popoola, S. Ansari, R. I. Ansari, L. Mohjazi, S. A. Hassan, et al, “IRS-Assisted Localization for Airborne Mobile Networks“, in Autonomous Airborne Wireless Networks, First Edition, John Wiley and Sons, ISBN 9781119751687, July 2021.
[Chapter 13] R. Mustafa, S. A. Hassan, “Machine-learning-enabled smart cities“, in Communication Technologies for Networked Smart Cities, IET Digital Library, ISBSN 9781839530296, June 2021.
[Chapter 12] Shah Zeb, Qamar Abbas, Syed Ali Hassan, Aamir Mahmood, and Mikael Gidlund, “Enhancing Backscatter Communication in IoT Networks with Power-Domain NOMA“, in Wireless-Powered Backscatter Communications for Internet of Things, pp. 81-101, Springer, Cham, 2020.
Estimates of signal-to-noise ratio (SNR) are used in many wireless receiver functions, including signal detection, power control algorithms and turbo decoding etc. Although SNR is an important parameter in studying performance analysis of different communication systems, it can also be used in determining which nodes to participate in the Cooperative Transmission (CT), which is an emerging area of research.
Multi-hop wireless transmission, where radios forward the message of other radios, is becoming popular both in cellular as well as sensor networks. This research is concerned with the statistical modeling of multi-hop wireless networks that do cooperative transmission (CT). CT in a physical layer wireless communication scheme in which spatially separated wireless nodes collaborate to form a virtual array antenna for the purpose of increased reliability. The key contribution of this research is to model the transmissions that hop from one layer of nodes to another under the effects of channel variations, carrier frequency offsets, and path loss. It has been shown that the successive transmission process can be modeled as a quasi-stationary Markov chain in discrete time..
Blind source separation (BSS) has become an area of prime interest. Conventional adaptive source separation systems use a training sequence to estimate and separate sources with the help of predefined optimization criteria. In BSS, the key idea is to use the data statistics to get apriori knowledge and thus separate the sources blindly
Cooperative relaying methods have attracted a lot of interest in the past few years. A conventional cooperative relaying scheme has a source, a destination, and a single relay. This cooperative scheme can support one symbol transmission per time slot, and is called full rate transmission. However, existing full rate cooperative relay approaches provide asymmetrical gain for different transmitted symbols..
The objective of this study is a comparison of WiMAX and Wireless DOCSIS, two access technologies for fixed wireless access (FWA), for rural environments. The band of interest is 2.5 GHz. In this band, WiMAX is called Mobile WiMAX, even though it is used also for FWA. The technologies will be compared in terms of data density, expressed as Mbps per km. The study is to be limited to the PHY layer and for a single cell in the downlink direction.
The IEEE 802.11 WiFi standard has been widely used in wireless local area networks (WLAN), which specifies an over-the-air interface between wireless clients and access point or between two wireless clients. With the recent development of multiple-input multiple-output (MIMO) systems at the physical (PHY) layer and frame aggregation at the medium access control (MAC) layer, the IEEE 802.11n standard provides the fastest data rates and larger coverage areas in different environments. However, as wireless network proliferates in indoor environments specially homes, the network topology has evolved from simple single access point-based network into more complex multi-hop topologies.
Design and Development of Opportunistic Large Array Networks for Smart Grid Communications
Sensors and sensor networks have an important impact in meeting environmental challenges. Sensor applications in multiple fields such as smart power grids,smart buildings/meters and smart industrial process control significantly contribute to more efficient use of resources. Wireless sensor and actuator networks (WSANs) are networks of nodesthat sense and potentially also control their environment. They communicate the information through wirelesslinks enabling interaction between people, devices, or computers and the surrounding environment.
Interference Alignment in Femtocells
The topology and architecture of cellular networks are undergoing a major paradigm shift from voice- centric, circuit switched and centrally optimized for coverage towards data-centric, packet switched and organically deployed for capacity. Current cellular systems in the world, especially in Pakistan, are homogenous in the sense that there is a base station that serves a specified larger area (in kilometers) and then an adjacent base station serves the adjacent area. This macro-cellular system is deployed in most parts of the world since 3 last decades. However, a disadvantage of the macro-cellular system is that in remote areas or some typical terrains where the base-station’s signal cannot reach the end-user, the probability of outage (i.e., a user without signal coverage) increases
In recent years, wireless data traffic has exponentially grown due to a change in the way today’s society creates, shares and consumes information. This change has been accompanied by an increasing demand for higher speed wireless communication. Massive MIMO links are expected to become a reality within the next ten years. Towards this aim, the Massive MIMO communication is envisioned as one of the key wireless technologies of the next decade. These very high bit-rates will enable a plethora of long-awaited applications, such as ultra-fast massive data transfers among nearby devices, or high-definition videoconferencing among mobile personal devices in small cells, also to address spectrum scarcity and capacity limitations of current cellular systems. The latter application of current cellular systems is one of the most critical one that motivates one to carry out research in this particular area.
Dr. Syed Ali Hassan and Dr. Aamir Mahmood (Assistant Professor, Mid Sweden University, Sweden) established their collaboration through an Initiation Grant from STINT, Sweden in 2017, for a joint research project. Since then, they have actively worked together in joint supervision of students are various levels, writing funding applications, organizing bilateral research visits, extending their internationalization activities and networks, and arranging special issues in conferences and journals.