Dr Ammar Ghazal

Job: Senior Lecturer in Wireless Communications

Faculty: Computing, Engineering and Media

School/department: School of Engineering and Sustainable Development

Research group(s): Institute of Engineering Sciences (IoES)

Address: De Montfort University, The Gateway, Leicester, LE1 9BH UK

T: 00 44 (0)116 201 3947

E: ammar.ghazal@dmu.ac.uk

W: https://www.dmu.ac.uk/about-dmu/academic-staff/technology/ammar-ghazal/ammar-ghazal.aspx

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Personal profile

Ammar Ghazal is a Senior Lecturer in Wireless Communications in the Faculty of Computing, Engineering and Media at De Montfort University, Leicester, UK. He is also the programme leader of BEng/MEng Electrical and Electronic Engineering programme. Ammar received the BSc degree in Electronics and Telecommunication Engineering from Damascus University, Syria. He studied for his MSc by Research and PhD degrees at the Universities of Edinburgh and Heriot-Watt University, Edinburgh, UK.

Upon his BSc graduation, Ammar worked as a Lab Instructor at International University for Science & Technology (IUST) before moving to Industry as a mobile communication engineer. In the first instance, he worked as a Radio Planning & Optimisation Engineer then as a Core Network Engineer. He has also worked as a Lab Instructor at Damascus University, where he was awarded a full scholarship to pursue a postgraduate degree in the UK. His PhD and MSc research have focused on propagation channel characterisation and modelling in 4G and 5G communication systems.

Ammar’s current research interests include (B)5G communication systems, wireless propagation channel characterisation and modelling, non-stationary channel models, high mobility wireless propagation, and advanced MIMO communication technologies.

Research group affiliations

Signal Processing and Communication Systems, Institute of Engineering Sciences (IoES)

Applied Electromagnatics Group

Publications and outputs

Non-Stationarity Characterization and Geometry-Cluster-Based Stochastic Model for High-Speed Train Radio Channels
Non-Stationarity Characterization and Geometry-Cluster-Based Stochastic Model for High-Speed Train Radio Channels Zhang, Yan; Zhang, Kaien; Ghazal, Ammar; Zhang, Wancheng; Ji, Zijie; Xiao, Limin In time-variant high-speed train (HST) radio channels, the scattering environment changes rapidly with the movement of terminals, leading to a serious deterioration in communication quality. In the system- and link-level simulation of HST channels, this non-stationarity should be characterized and modeled properly. In this paper, the sizes of the quasi-stationary regions are quantified to measure the significant changes in channel statistics, namely, the average power delay profile (APDP) and correlation matrix distance (CMD), based on a measurement campaign conducted at 2.4 GHz. Furthermore, parameters of the multi-path components (MPCs) are estimated and a novel clustering-tracking-identifying algorithm is designed to separate MPCs into line-of-sight (LOS), periodic reflecting clusters (PRCs) from power supply pillars along the railway, and random scattering clusters (RSCs). Then, a non-stationary geometry-cluster-based stochastic model is proposed for viaduct and hilly terrain scenarios. Furthermore, the proposed model is verified by measured channel statistics such as the Rician K factor and the root mean square delay spread. The temporal autocorrelation function and the spatial cross-correlation function are presented. Quasi-stationary regions of the model are analyzed and compared with the measured data, the standardized IMT-Advanced (IMT-A) channel model, and a published nonstationary IMT-A channel model. The good agreement between the proposed model and the measured data demonstrates the ability of the model to characterize the non-stationary features of propagation environments in HST scenarios. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link Zhang, Y., Zhang, K., Ghazal, A., Zhang, W., Ji, Z. and Xiao, L. (2023) Non-Stationarity Characterization and Geometry-Cluster-Based Stochastic Model for High-Speed Train Radio Channels. IEEE Transactions on Intelligent Transportation Systems,
Accuracy-Complexity Tradeoff Analysis and Complexity Reduction Methods for Non-Stationary IMT-A MIMO Channel Models
Accuracy-Complexity Tradeoff Analysis and Complexity Reduction Methods for Non-Stationary IMT-A MIMO Channel Models Zhang, Yan; Ghazal, Ammar; Wang, Cheng-Xiang; Zhou, Hongrui; Duan, Weiming; Aggoune, el-Hadi High-mobility wireless communication systems have attracted growing interests in recent years. For the deployment of these systems, one fundamental work is to build accurate and efficient channel models. In high-mobility scenarios, it has been shown that the standardized channel models, e.g., IMT-Advanced (IMT-A) multiple-input multiple-output (MIMO) channel model, provide noticeable longer stationary intervals than measured results and the wide-sense stationary (WSS) assumption may be violated. Thus, the non-stationarity should be introduced to the IMT-A MIMO channel model to mimic the channel characteristics more accurately without losing too much efficiency. In this paper, we analyze and compare the computational complexity of the original WSS and non-stationary IMT-A MIMO channel models. Both the number of real operations and simulation time are used as complexity metrics. Since introducing the nonstationarity to the IMT-A MIMO channel model causes extra computational complexity, some computation reduction methods are proposed to simplify the non-stationary IMT-A MIMO channel model while retaining an acceptable accuracy. Statistical properties including the temporal autocorrelation function, spatial cross-correlation function, and stationary interval are chosen as the accuracy metrics for verifications. It is shown that the tradeoff between the computational complexity and modeling accuracy can be achieved by using these proposed complexity reduction methods. open access journal Zhang, Y., Ghazal, A., Wang, C.-X., Zhou, H., Duan, W. and Aggoune, E. M. (2019) Accuracy-complexity tradeoff analysis and complexity reduction methods for non-stationary IMT-A MIMO channel models. IEEE Access,
Channel Measurements and Models for High-Speed Train Wireless Communication Systems in Tunnel Scenarios: A Survey
Channel Measurements and Models for High-Speed Train Wireless Communication Systems in Tunnel Scenarios: A Survey Liu, Yu; Ghazal, Ammar; Wang, Cheng-Xiang; Ge, Xiaohu; Yang, Yang; Zhang, Yapei The rapid developments of high-speed trains (HSTs) introduce new challenges to HST wireless communication systems. Realistic HST channel models play a critical role in designing and evaluating HST communication systems. Due to the length limitation, bounding of tunnel itself, and waveguide effect, channel characteristics in tunnel scenarios are very different from those in other HST scenarios. Therefore, accurate tunnel channel models considering both large-scale and small-scale fading characteristics are essential for HST communication systems. Moreover, certain characteristics of tunnel channels have not been investigated sufficiently. This article provides a comprehensive review of the measurement campaigns in tunnels and presents some tunnel channel models using various modeling methods. Finally, future directions in HST tunnel channel measurements and modeling are discussed. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Liu, Y., Ghazal, A., Wang, C.-X., Ge, X., Yang, Y. and Zhang, Y. (2017) Channel measurements and models for high-speed train wireless communication systems in tunnel scenarios: a survey. Science China Information Sciences, 60: 101301
A Non-Stationary IMT-Advanced MIMO Channel Model for High-Mobility Wireless Communication Systems
A Non-Stationary IMT-Advanced MIMO Channel Model for High-Mobility Wireless Communication Systems Ghazal, Ammar; Yuan, Yi; Wang, Cheng-Xiang; Zhang, Yan; Yao, Qi; Zhou, Hongrui; Duan, Weiming With the recent developments of high-mobility wireless communication systems, e.g., high-speed train (HST) and vehicle-to-vehicle (V2V) communication systems, the ability of conventional stationary channel models to mimic the underlying channel characteristics has widely been challenged. Measurements have demonstrated that the current standardized channel models, like IMT-Advanced (IMT-A) and WINNER II channel models, offer stationary intervals that are noticeably longer than those in measured HST channels. In this paper, we propose a non-stationary channel model with time-varying parameters including the number of clusters, the powers and the delays of the clusters, the angles of departure (AoDs), and the angles of arrival (AoAs). Based on the proposed non-stationary IMT-A channel model, important statistical properties, i.e., the local spatial cross-correlation function (CCF) and local temporal autocorrelation function (ACF) are derived and analyzed. Simulation results demonstrate that the statistical properties vary with time due to the non-stationarity of the proposed channel model. An excellent agreement is achieved between the stationary interval of the developed non-stationary IMT-A channel model and that of relevant HST measurement data, demonstrating the utility of the proposed channel model. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Ghazal et al. (2017) A non-stationary IMT-A MIMO channel model for high-mobility wireless communication systems, IEEE Transaction Wireless Communication,
Statistical Properties of High-Speed Train Wireless Channels in Different Scenarios
Statistical Properties of High-Speed Train Wireless Channels in Different Scenarios Liu, Yu; Zhang, Yapei; Ghazal, Ammar; Wang, Cheng-Xiang; Yang, Yang In this paper, we compare the statistical properties of high-speed train (HST) wireless channels in different scenarios using a generic non-stationary HST channel model that has been verified by channel measurements (Ghazal et al., 2015). We mainly focus our comparison and analysis on the three most common HST scenarios, i.e., the rural area, cutting, and viaduct scenarios. Several channel statistical properties such as the temporal autocorrelation function (ACF), space cross-correlation function (CCF), and space- Doppler (SD) power spectrum density (PSD) are investigated. The impacts of different scenario- specific parameters on the channel statistical properties are also studied via numerical analysis. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Liu, Y., Zhang, Y., Ghazal, A., Wang, C.X. and Yang, Y. (2016) Statistical Properties of High-Speed Train Wireless Channels in Different Scenarios. In: Vehicular Technology Conference (VTC Spring), 2016 IEEE 83rd (pp. 1-5). IEEE.
Performance Investigation of Spatial Modulation Systems Under Non-Stationary Wideband High-Speed Train Channel Models
Performance Investigation of Spatial Modulation Systems Under Non-Stationary Wideband High-Speed Train Channel Models Fu, Yu; Wang, Cheng-Xiang; Ghazal, Ammar; Aggoune, el-Hadi M.; Alwakeel, Mohammed M. In this paper, the bit error rate (BER) performance of a new multiple-input-multiple-output technique, named spatial modulation (SM), is studied under a novel non-stationary wideband high-speed train (HST) channel model in different scenarios. Time-varying parameters obtained from measurement results are used to configure the channel model to make all results more realistic. A novel statistic property called the stationary interval in terms of the space-time correlation function is proposed to describe the channel model's time-varying behavior. The accurate theoretical BER expression of SM systems is derived under the time-varying wideband HST channel model with the non-ideal channel estimation assumption. The simulation results demonstrate that the BER performance of SM systems shows a time-varying behavior due to the non-stationary property of the employed HST channel model. The system performance can maintain a relative stationary status within the specified stationary interval. It can also be observed that the BER performance of SM systems under the HST channel model is mainly affected by the correlation between sub-channels, inter-symbol-interference, Doppler shift, and channel estimation errors. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Fu, Y., Wang, C.X., Ghazal, A. and Alwakeel, M.M. (2016) Performance investigation of spatial modulation systems under non-stationary wideband high-speed train channel models. IEEE Transactions on Wireless Communications, 15 (9), pp. 6163-6174
A generic non-stationary MIMO channel model for different high-speed train scenarios
A generic non-stationary MIMO channel model for different high-speed train scenarios Ghazal, Ammar; Wang, Cheng-Xiang; Liu, Yu; Fan, Pingzhi; Chahine, Mohamed Khaled This paper proposes a generic non-stationary wideband geometry-based stochastic model (GBSM) for multiple-input multiple-output (MIMO) high-speed train (HST) channels. The proposed generic model can be applied on the three most common HST scenarios, i.e., open space, viaduct, and cutting scenarios. A good agreement between the statistical properties of the proposed generic model and those of relevant measurement data from the aforementioned scenarios demonstrates the utility of the proposed channel model. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Ghazal, A., Wang, C.X., Liu, Y., Fan, P. and Chahine, M.K. (2015) A generic non-stationary MIMO channel model for different high-speed train scenarios. In: Communications in China (ICCC), 2015 IEEE/CIC International Conference on (pp. 1-6). IEEE.
A 3D GBSM for high-speed train communication systems under deep cutting scenarios
A 3D GBSM for high-speed train communication systems under deep cutting scenarios Feng, Liu; Fan, Pingzhi; Wang, Cheng-Xiang; Ghazal, Ammar This paper proposes a novel three-dimensional (3D) cylinder geometry-based stochastic model (GBSM) for non-isotropic multiple-input multiple-output (MIMO) Rice fading channels in high-speed train (HST) wireless communications under deep cutting scenarios. Using a validated approximation, the closed-form expression of the space-time correlation function (ST CF) of the proposed GBSM is obtained. Different from two-dimensional (2D) channel models, in the 3D GBSM the elevation angles and the height of the base station (BS) antenna relative to the mobile station (MS) one are introduced. The numerical results show the rationality of the approximation and how the arrangements of antennas affect the ST CF. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Feng, L., Fan, P., Wang, C.-X., and Ghazal, A. (2015) A 3D GBSM for high-speed train communication systems under deep cutting scenarios, In 2015 International Workshop on High Mobility Wireless Communications (HMWC) (pp. 86-90). IEEE
Channel Measurements and Models for High-Speed Train Communication Systems: A Survey
Channel Measurements and Models for High-Speed Train Communication Systems: A Survey Wang, Cheng-Xiang; Ghazal, Ammar; Ai, Bo; Liu, Yu; Fan, Pingzhi The recent development of high-speed trains (HSTs) as an emerging high mobility transportation system, and the growing demands of broadband services for HST users, introduce new challenges to wireless communication systems for HSTs. Accurate and efficient channel models considering both large-scale and non-stationary small-scale fading characteristics are crucial for the design, performance evaluation, and parameter optimization of HST wireless communication systems. However, the characteristics of the underlying HST channels have not yet been sufficiently investigated. This paper first provides a comprehensive review of the measurement campaigns conducted in different HST scenarios and then addresses the recent advances in HST channel models. Finally, key challenges of HST channel measurements and models are discussed and several research directions in this area are outlined. Wang, C.X., Ghazal, A., Ai, B., Liu, Y. and Fan, P. (2016) Channel measurements and models for high-speed train communication systems: a survey. IEEE Communications Surveys & Tutorials, 18 (2), pp. 974-987
A Multi-mode Waveguide Tunnel Channel Model for High-Speed Train Wireless Communication Systems
A Multi-mode Waveguide Tunnel Channel Model for High-Speed Train Wireless Communication Systems Liu, Yu; Wang, Cheng-Xiang; Ghazal, Ammar; Wu, Shangbin; Zhang, Wensheng The recent development of high-speed trains (HSTs) introduces new challenges to wireless communication systems for HSTs. For demonstrating the feasibility of these systems, accurate channel models which can mimic key characteristics of HST wireless channels are essential. In this paper, we focus on HST channel models for the tunnel scenario, which is different from other HST channel environments, such as rural area and viaducts. Considering unique characteristics of tunnel channel environments, we extend the existing multi-mode waveguide tunnel channel model to be time dependent, obtain the channel impulse responses and then further investigate the certain key tunnel channel characteristics such as temporal autocorrelation function (ACF) and power spectrum density (PSD). The impact of time on ACFs and PSDs, and the impact of frequency on the received power are revealed via numerical results. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Liu, Y., Wang, C.X., Ghazal, A., Wu, S. and Zhang, W., 2015, May. A multi-mode waveguide tunnel channel model for high-speed train wireless communication systems. In Antennas and Propagation (EuCAP), 2015 9th European Conference on (pp. 1-5). IEEE.

Research interests/expertise

5G communication systems
Wireless propagation channel characterisation and modelling
Vehicular communication
Non-stationary channel models
High-mobility wireless propagation
Advanced MIMO communication technologies

Areas of teaching

Mobile communication
Communication networks
Electromagnetism

Qualifications

PhD in Electrical Engineering, University of Edinburgh and Heriot-Watt University
MSc by Research in Electrical Engineering, Heriot-Watt University and University of Edinburgh
BSc in Electronics and Communication Engineering, Damascus University

Courses taught

Principle of mobile communications
Communications and networks
Communication systems
Digital circuits
Electrical circuits
Control and instrumentation engineering

Honours and awards

First Class Prize (Bassel Prize), Damascus University, September 2006
Full-Scholarship for PhD study, Damascus University, August 2008

Membership of professional associations and societies

Member of IEEE
IEEE Electromagnetic Compatibility Society Membership
Fellow of the higher education association (FHEA)
Microsoft certified professional (MCP)

Professional licences and certificates

LabVIEW Core 1, National Instruments
LabVIEW FPGA, National Instruments
LabVIEW Communications LTE Application Framework, National Instruments
Modern Digital RF Transceivers, Rohde & Schwarz
5G System Principles, IEEE
Understanding 5G Fundamentals, IEEE
CST STUDIO SUITE 2018 Workshop, CST
CST STUDIO SUITE - Microwave and Antenna Training, CST
Review of Signal Systems and Digital Signal Processing, IEEE
Radar Systems Engineering, IEEE
4G Broadband LTE, IEEE
Core Networks Signaling for 3G Networks Rel.4, Nokia Siemens
3G Rel.4 Switching Core Network Operation & Maintenance, Nokia Siemens
GSM Cell Planning Workshop, Ericsson
Practical Communication Strategies, MAK / SYRIATEL
CCNP-BSCI Course, CISCO, New Horizons
MCP certificate, Microsoft
Windows Server 2003 Infrastructure, SBS
Windows Server 2003 Management, SBS

Current research students

Badar Al Maamari, International PhD, 1 ^stsupervisor
Amruthavarshini Subburaya Bharathi, PhD, 2^ndsupervisor
Lokesh Devaraj, PhD, additional supervisor

Externally funded research grants information

2022 - 24: KTP Academic Supervisor

Project scope: To advance specifications and future-proof the design of products which testelectromagnetic compatibility.

2020-21: Co-I of a Local+ project with Leicester City Council

Project: "Smart Environment: IoT-based Air Pollution Monitoring System"

Project scope: The project developed an IoT-based testbed for smart city applications. The testbed is made of a gatewayconnected wirelessly to a variety of sensors forming a standard low-power network, which represents a typical platform toexplore the potential benefits of the fifth-generation (5G) communication system that supports IoT applications. The system is currently used to monitor the concentration of major air pollutant gasses and particles in the De MontfortUniversity campus in Leicester and the surrounding area.
More details can be found here: https://www.dmu.ac.uk/research/centres-institutes/ioes/iot.aspx

Internally funded research project information

2022 - 23: Living in Digital Society - Spotlight

Project: "Smart Environment: IoT-based Air Pollution Heat Map"

The project aims to develop a heatmap of the concentration of different gases and particles at DMU campus, Leicester.

2021 - 22: HEIF

Project: "Smart Environment: IoT-based Air Pollution"

The project aims to develop a visualisation of air pollution around the DMU campus in Leicester using a portable Internet of things (IoT)-based system. This is to prove the concept of such a system for a larger city-wide deployment and to contribute to Leicester’s Air Quality Action Plan.

2019-20: VC2020 Additional Fund

Project: "Feasibility study of device-to-device (D2D) prototyping using software-defined radio (SDR) devices"

A prototype of a D2D wireless communication system was set up and tested using USRP devices. The aim was to prove the concept of D2D prototyping, and thus low-end USRP equipment from Ettus Research were used inestablishing the system.