Ibrahim AbuAlhaol
Ph.D. | P.Eng. | SMIEEE
Larus Technologies
Carleton University
Ottawa, ON, Canada
H (613) 216-9474
B ibrahimee@ieee.org
Í alhaol.com
Canadian Citizen
Summary
Senior Data Scientist
@ Larus Technologies and
Adjunct Research Professor
@ Carleton University in Ottawa,
Canada. Holds a BSc, an M.Sc, and a PhD in Electrical and Computer Engineering. Holds M.Eng in Technology
Innovation Management. Senior member of IEEE and Professional Engineer (P.Eng.) in Ontario, Canada. Interests
in machine learning and big-data analytics applications in Cybersecurity and Wireless Communication. Excellent
knowledge and hands-on experience in machine learning modeling and real-time Big Data analytics:
(i)
Python
programming (Data analysis and mining with pandas, visualization with matplotlib and seaborn, machine learning
with Scikit-learn/Spark-MLlib/TensorFlow, and natural language processing with NLTK/Gensim),
(ii)
Databases
(MySQL, MongoDB, and Cassandra), (iii) Real-time Big Data analytics (Spark streaming and Kafka).
Education
2005–2008 PhD in Electrical and Computer Engineering
, University of Mississippi, United States, GPA: 4.0/4.0.
2014–2015 M.Eng. in Technology Innovation Management, Carleton University, Canada, GPA: 11/12.
2002–2004 M.Sc. in Electrical Engineering, Jordan University of Science & Technology, Jordan, GPA: 84.4/100.
1995–2000 B.Sc. in Electrical Engineering, Jordan University of Science & Technology, Jordan, 84/100.
Employment
2017-Present Senior Data Scientist, Larus Technologies, Ottawa, Canada.
Business Intelligence Forecasting | LSTM Recurrent Neural Networks | Natural Language Processing | Multi-
objective Optimization (MOO) | Real-time Big Data Analytics.
2017-Present Adjunct Research Professor, Carleton University , Ottawa, Canada.
Machine Learning | Big Data Analytics | 5G Wireless Networks Personalization | User Satisfaction
2015-2017 CyberSecurity Research Scientist, VENUS Cybersecurity Corporation, Ottawa, Canada.
Collective Intelligence | Machine Learning | Big Data Analytics | BGP Hijacking | DDOS Attacks.
2014-2015 CyberSecurity Researcher, Carleton University and Xahive.com, Ottawa, Canada.
Device-to-Device Wireless Security | RSA Key Exchange | AES Encryption.
2009-2014 Assistant Professor, Khalifa University of Science & Technology, United Arab Emirates.
Probability and Statistics | Wireless Communications | Modulation and Coding | Digital Communications.
2008-2009 Wireless System Engineer, Broadcom Corp oration, San Diego, USA.
3G/4G System Design | RF Compliance | 3GPP Standard | Bluetooth | WLAN.
2008-2008 System Engineer Intern, Qualcomm Incorp oration, San Diego, USA.
4G Wireless Network Analysis and Simulation | HSPA | WiMAX | LTE.
2005-2008 Ph.D. Student/ Research Assistant, University of Mississippi, Oxford, United States.
Cooperative (UAV) Networks | MIMO/OFDM Systems | Modeling | Simulation.
Research Statistics
4 Book chapters | 8 Journals | 1 Patent | 35 Conferences | 303 Google Scholar citations.
Experience
AUG 2018
–Present
Senior Data Scientist, Larus Technologies, Ottawa, Canada.
Objective:
Minning massive amount of data (Big Data) to develop predictive analytics models and
machine learning algorithms in order to improve both internal and collaborative processes of our
clients.
Challenge:
Generation of Actionable Intelligence for Decision Support System using real-time Big
Data analytics. The Actionable Intelligence includes anomalies, alerts, threats, potential response
generation, process refinement and other types of knowledge that improve the efficiency of clients
operations and processes.
Tools/Software:
MOEA Framework-Java (Multi-objective Optimization), DEAP-Python (Evolution-
ary Algorithms), Big Data mining (PySpark and Kafka), Databases (Cassandra, PostgreSQL, and
MongoDB), Automatic Identification System (AIS) Data Mining (Python-Pandas and Spark SQL),
Data visualization (Python-Seaborn), Natural Language Processing (Python-NLTK and Python-
Gensim).
Responsibilities: [1]
Design, optimize, develop, and deliver Machine Learning (ML) enabled solutions
for Decision Support Systems (DSS).
[2]
Develop efficient and automated processes to collect, analyze
and provide compiled data to be utilized by Decision Support Systems.
[3]
Build scalable processes
to collect, manipulate, present, and analyze big datasets in a production environment.
[4]
Work
on data acquisition, investigation, visualization, feature engineering, experimentation with Machine
Learning (ML) algorithms, and deploying tuned/validated/tested models.
[5]
Develop functioning
prototypes of algorithms and evaluate and compare metrics based on the real-world big data sets.
[6]
Work on pattern learning, outlier detection, and identification of appropriate analytic and statistical
methodology.
[7]
Develop real-time predictive models with Spark-streaming and Kafka in a production
environment.
[8]
Data-Driven Vessel Service Time Forecasting using Long Short-Term Memory
Recurrent Neural Networks.
JAN 2017
–JUL 2018
Data Scientist, Larus Technologies, Ottawa, Canada.
Objective:
Exploiting massive amount of sensor data (Big Data) emitted by many maritime actors
in order to improve both internal and collaborative processes for maritime Internet-of-Things related
organizations.
Challenge:
Generation of Actionable Intelligence (AI) for Decision Support (DS) using real-time Big
Data analytics. The AI includes anomalies, alerts, threats, potential response generation, process
refinement and other types of knowledge that improve the efficiency of maritime-related organizations.
Tools/Software:
MOEA Framework-Java (Multi-objective Optimization), DEAP-Python (Evolu-
tionary Algorithms), Big Data (PySpark and MLLIB), Databases (Cassandra, PostgreSQL, and
MongoDB), Automatic Identification System (AIS) Data Mining (Python-Pandas), Data visualization
(Python-Seaborn).
Responsibilities: [1] Prepare literature reviews on supply chain management and optimization and
identify maritime related problems (pain points) to be solved (optimized) by real-time Big Data
analytics.
[2]
Exploring Meta-heuristic Multi-objective Optimization (MOO) techniques and prepare
a detailed document of the available state-of-the-art open source frameworks and tools.
[3]
Design,
develop, and evaluate data mining processes to extract global speed statistics and outliers for all sea
vessels categories at specific period of interest (POI) and time of interest (TOI) (tools: PySpark,
Cassandra, Pandas, and Seaborn)
[4]
Collaborate with the software team to improve the utilization of
real-time analytics and machine learning models to improve the accuracy of decision support system.
[5]
Harness publicly available maritime ports meta-data and establish efficient automated processes
to collect, analyze and provide compiled data to be utilized by other DS systems optimizers.
[6]
Mining port congestion indicators from big AIS data.
[7]
Co-authoring publications in the area of
meta-heuristics multi-objective optimization enabled by BD analytics and ML.
JAN 2017
–Present
Adjunct Research Professor, Carleton University, Ottawa, Canada.
Objective:
Modeling user satisfaction and zone of tolerance with Machine Learning (ML) and Big
Data analytics and proactively direct the scheduler to micro manage resource allocations in 5G
Networks.
Challenge:
Harnessing massive amount of contextual and performance data and model the features
that are correlated to the user satisfaction and zone of tolerance in spatial, temporal, and social
contexts.
Tools/Software: MATLAB, KNIME, Python (Scikit-learn, Pandas, PySpark, and Matplotlib).
Responsibilities: [1]
Co-supervising Ph.D. students to apply Machine Learning and Big Data (BD)
analytics on wireless communication problems.
[2]
Direct the students on designing, developing, and
evaluating machine learning models and techniques and apply them to personalize the distribution
of resources in 5G networks.
[3]
Direct the effort to synthesize and model user data and tune the
models to generate both usage and contextual data.
[4]
Co-authoring conferences and journals
papers.
[5]
Direct the work-flow of generating processes, models, and data in an effort to provide
open source tools and data that can be utilized by other members in the research community.
[6]
Acting as a reader and grader on Technology Innovation Management (TIM) Master of Engineering
(M.Eng.) projects (e.g.,
Machine Learning:
"Significance of Passenger Data for Better Forecasting
of Maximum Permissible Takeoff Weight",
Natural Language Processing:
"Analysis of Customer
Perspective of Identity and Access Management solutions using Topic Modeling Approach").
OCT 2015
DEC 2016
CyberSecurity Research Scientist, VENUS Cybersecurity Corporation, Ottawa, Canada.
Objective:
Data Mining (DM) and Exploratory Analysis (EA) of live and historical Border Gateway
Protocol (BGP) data in order to enable Cybersecurity operational monitoring, post-event analysis,
and real-time anomaly detections.
Challenge:
Real-time Big Data mining with unsupervised Machine Learning (ML) capabilities to
tune supervised ML predictors. This includes feature engineering, cleaning, averaging, filtering, and
time-series aggregation.
Tools/Software:
KNIME, MATLAB, Python (Skit-learn, Pandas, and PySpark), Databases (Mon-
goDB), Real-time streaming platform (Apache Kafka), Javascript visualization (D3, Crossfilter, DC).
Responsibilities: [1]
Prepare literature review on Exploratory Data Analysis (EDA), Border Gateway
Protocol (BGP) anomaly detection, and real-time Big Data analytics frameworks and software
architecture.
[2]
Design, prototype, and evaluate BGP anomaly indicators and build machine learning
models (supervised and unsupervised) to predict BGP IP prefix hijacking and Distributed Denial of
Service (DDOS) attacks.
[3]
Build a visual interactive dashboard on the data being ingested from
BGP stream. This includes displaying recent alerts and providing interactive visualizations of the
context of a given alert using timelines, histograms, and moving averages of several types of the
indicators that are being monitored.
[4]
Collaborate with the team to integrate the prototype as a
real-time analytic engine that ingests BGPstream real-time stream, and push it to Apache Kafka,
and store the processed indicators in a MongoDB Database and utilize Apache Spark MLLIB to
predict the anomalies. The generated intelligence is pushed to a web-based Dashboard that enables
the analyst to drill down and explore the incident.
[5]
Documentation and publish original research
in peer-reviewed conferences and journals.
[6]
Testing and validating the developed processes in a
large-scale and real-life IP prefix hijacking and DDOS incidents.
FEB 2014
SEP 2015
CyberSecurity Researcher, Carleton University and Xahive.com, Ottawa, Canada.
Objective: Investigating the security and privacy differentiation in end-to-end encryption services.
Challenge: Improving the value proposition through usability in end-to-end encryption services.
Tools/Software:
MATLAB and open source Javascript libraries (AES-JS: AES-256 encryp-
tion/decryption, JSENCRYPT: RSA key-exchange).
Responsibilities: [1]
Prepare literature review on solutions that achieves communication security and
privacy.
[2]
Identify limitations of the currently used communication encryption/decryption standards.
[3]
Conduct literature review to identify communication security standards to overcome the identified
limitations.
[1]
Propose a multi-layer-based approach to enable an agile defensive response for a
system under attack by shifting Device-to-Device (D2D) communication to a new combination of
encryption implementation, routing protocol, and media access technique and frequency band.
[4]
Provide recommendations on the chosen standards and how to customize/improve them.
[5]
Conduct
MATLAB system level simulations to prove the feasibility the of chosen algorithms/standards.
[6]
The applicable algorithms/standards are recommended to the development team for integration and
testing.
OCT 2009
JAN 2014
Assistant Professor, Khalifa University of Science & Technology, United Arab Emirates.
Objective: Teaching and conducting research in wireless communications.
Challenge: Teaching, supervising graduate students, and attract research fund.
Tools/Software: MATLAB and Latex.
Responsibilities: [1]
Teaching undergraduate courses: Introduction to Professional Engineering
(ENGR 110), Probability and Statistics (MATH 215), Wireless Communications (CMME 400),
Communication Networks (CMME 320), Modulation and Coding Techniques (CMME 404), Digital
Communications I (CMME 302), Communication Engineering Project Laboratory (CMME 395) and
Digital Communication Laboratory (CMME 300).
[2]
Advise students on academic matters and career
decisions.
[3]
Supervised the following undergraduate projects: Mobile Bluetooth-Based Parking
System, Multi-Sources Patient Localization System for Emergency Response, Wireless Control of Self-
Sustained Solar Power Generation System, Evaluation of Spectrum Sensing Techniques in Cognitive
Radio Networks, Solar Thermal Power Generation System, Performance Evaluation of MIMO-OFDM
System over Fading Channels, Simulation of Interference Mitigation for OFDM Multi-hop LTE
Networks, Single Carrier Frequency Division Multiple Access Air Interface for LTE, Wireless Device
to Alert Drivers to Keep a Safe Distance, Downlink Power Control Techniques in CDMA Systems,
Universal Mobile Telecommunications System (UMTS) Physical Layer, Orthogonal Frequency Division
Multiplexing (OFDM) Synchronization Techniques.
[4]
Electrical and Computer Engineering (ECE)
Committee Member: Responsible for establishing a Master of Science in Electrical and Computer
Engineering (M.Sc. in ECE) program.
[5]
Resources Committee Member: Assessed current and
future material requirements for the academic programs and propose new equipment and resources.
[6]
External Relations Committee Member: Identified best practices for interaction with all important
external constituencies and defined means that facilitated strong relationships with the University.
SEP 2008
OCT 2009
Wireless System Engineer, Broadcom Corporation, San Diego, USA.
Responsibilities: [1]
Performed system level test plan, execution, troubleshooting, optimization
and problem resolution on 2G/3G mobile devices.
[2]
Worked with a multi-discipline team to test
and commercialize UMTS (Single SIM/Dual SIM) solutions.
[3]
Actively involved in producing
requirements for tools and system simulators and work closely with development teams and test
equipment vendors to come up with the appropriate test setups and associated automation.
[4]
Ensured
close interaction with the modem stack, multi-media, RF, drivers, 3GPP standard representatives
and System Design Engineers to ensure proper test coverage of the features.
MAY 2008
–AUG 2008
System Engineer Intern, Qualcomm Incorporation, San Diego, USA.
Responsibilities: [1]
Analyzed and simulated fourth-generation (4G) wireless network core compo-
nents.
[2]
Characterized and improved the performance of RF/RX front in WiMax and LTE wireless
systems. [3] Identified RF/RX front functionality for which minimum standard system performance
requirements should exist (Digital filtering (down-sampling & jammer rejection), DC offset removal
(inner loop and outer loop), automatic gain control (AGC), digitally controlled variable gain amplifier
(DVGA), and IQ-imbalance.)
[4]
Generated and consolidated performance requirements data and
conducted analysis and evaluation of critical performance metrics for 4G using MATLAB and C++.
[5]
Compared system level performance findings with other wireless standards (i.e., GSM, WCDMA,
Bluetooth, WLAN).
Teaching Experience: [UG: Undergraduate, G: Graduate]
UG Introduction to Machine Learning
UG Introduction to Data Mining
UG Introduction to CyberSecurity
UG Introduction to Professional Engineering
UG Probability and Statistics
UG Wireless Communications
UG Data Communications and Networking
G Advanced Topics in Machine Learning: Deep Learning for Natural Language Processing
G Advanced Topics in Cybersecurity: Modeling and Forcasting with Recurent Neural Networks
G Advanced Topics in Modeling and Simulation: Bayesian Inference vs Deep Learning
G Technology Innovation Management: Startup vs Corporate
Software | Tools
OS UNIX, MAC, Windows.
Programming Python, Java, C++, MATLAB.
Databases MySQL, PostgreSQL, MongoDB, Cassandra.
Optimization Java (MOEA-Framework), Python (DEAP).
Visualization Python (Matplotlib, Seaborn, Bokeh, Folium), JavaScript (D3.js, DC.js, Crossfilter.js).
Data Mining Python-Pandas, Python-Orange, MATLAB, KNIME.
ML Python (Scikit-learn, TensorFlow, PySaprk-MLLIB).
NLP Python (NLTK, spaCy, Gensim).
BI Power BI, Python-Superset.
Cloud Google Cloud Platform (GCP).
Big Data Apache Spark.
Real-time Apache Kafka.
Research Grants
2013 Cross-Layer Design for Secure Land Transport Systems (Grant=200,000 AED).
Abstract:
The long-term goal of this research project is to develop both fundamental theories and
practical designs of efficient, secure and safe vehicular networks, key components of ITS, and their
seamless integration with other existing networks. To achieve the goal, the existing technologies
are examined in various layers (i.e., all major layers of the Open System Interface (OSI)). Then, we
proposed solutions to how available resources could be sensed, the information shared, and better
utilized if these layers cooperate.
2012 Vehicular ad-hoc networks (VANETs) for Intelligent Transportation Systems (ITSs): En-
hancing the safety and the traffic management in United Arab Emirates
(Grant=190,000
AED).
Abstract:
This research addresses physical layer techniques to meet the unique challenges in VANETs
operating in mobile wireless environments. Considering the unique requirements of VANETs, the
work involves analysis and design of cooperative transmission schemes which are optimized for
inter-vehicular communication scenarios. The research consists of three sub-projects that involve the
design of efficient cooperative schemes, the development of channel estimation/tracking algorithms,
and the design of a cooperative OFDM scheme.
Applied Research Interests
{ Real-time Big Data Analytics { Machine Leraning
{ Maritime Internet-of-Things { Wireless Security
{ Natural Language Processing { Wireless Communications
Publications [J: Journal, C: Conference, B: Book Chapter, P: Patent]
Cyber Security
B 2017
M. Gad and
I. Abualhaol
, "Securing Smart Cities Systems and Services: A Risk-Based Analytics-
Driven Approach," accepted for publication as a chapter for the book entitled "Transportation and
Power Grid in Smart Cities: Communication Networks and Services", John Wiley, UK.
J 2017
A. Shah,
I. Abualhaol
, M. Gad, and M. Weiss, "Combining Exploratory Analysis and Automated
Analysis for Anomaly Detection in Real-Time Data Streams", Technology Innovation Management
Review, 7(4): 25-31, 2017.
C 2016 I. Abualhaol
and S. Muegge "Securing D2D Wireless Links by Continuous Authenticity with Legiti-
macy Patterns," 49th Hawaii International Conference on System Sciences (HICSS), pp. 5763-5771,
Jan 2016
.
C 2016
Michael Weiss,
I. Abualhaol
and Mohamed Amin, "A Leader-Driven Open Collaboration Platform
for Exploring New Domains," OpenSym conference, Berlin, Germany, August 17-19, 2016.
J 2016
A. Shah, S. Selman,and
I. Abualhaol
, "License Compliance in Open Source Cybersecurity Projects,"
Technology Innovation Management Review, 6(2): 28-35, 2016
.
B 2014
C. Han, S. Muhaidat,
I. Abualhaol
, M. Dianati, and R. Tafazolli, "Intrusion Detection in Vehicular
Ad-Hoc Networks on Lower Layers," Security, Privacy, Trust, and Resource Management in Mobile
and Wireless Communications, pp. 148–173, IGI Global, PA, USA, 2014.
B 2013
Y. Abu Haeyeh,
I. Abualhaol
, Y. Iraqi, and S. Muhaidat, "Intrusion Detection in Vehicular Ad-Hoc
Networks: A Physical Layer Approach," Communication Systems: New Research, pp. 133–152, Nova
publishers, 2013.
Machine Learning | Data Mining | Big Data Analytics
C 2019
R. Alkurd,
I. Abualhaol
, and H.Yanikomeroglu, "A Synthetic Dataset Modeling for Data-Driven AI-
Based Personalized Wireless Networks," Accepted in IEEE International Conference on Communications
(ICC), Shanghai, China, May 2019.
J 2018
R. Alkurd,
I. Abualhaol
, and H. Yanikomeroglu, “Enabling network personalization in 5G and beyond
by machine learning and big data anlaytics”, submitted to the IEEE Wireless Communications
Magazine (Submitted: 30-SEP-2018).
P 2018
R. Alkurd,
I. Abualhaol
, and H. Yanikomeroglu , "Enabling wireless network personalization using
Zone of Tolerance modeling and predictive analytics", U.S. Provisional Pat. Ser. No. 62724195,
Filed on 31, August, 2018.
C 2018 I. Abualhaol
, R. Falcon, R. Abielmona, and E. Petriu, "Data-Driven Vessel Service Time Forecasting
using Long Short-Term Memory Recurrent Neural Networks”, in IEEE International Conference on
Big Data, Seattle, United States, 10-13 DEC, 2018
C 2018 I. Abualhaol, R. Falcon, R. Abielmona, and E. Petriu, "Mining port congestion indicators from big
AIS data”, in IEEE World Congress on Computational Intelligence (IEEE WCCI), Rio deJaneiro, Brazi,
8-13 July., pp. 3743–3750, 2018.
C 2017
I. Al Ridhawi , N. Mostafa, Y. Kotb ,M. Aloqaily and
I. Abualhaol
, "Data Caching and Selection
in 5G Networks Using F2F Communication", in 2017 IEEE International Symposium on Personal,
Indoor and Mobile Radio Communications (PIMRC 2017), Montreal, QC, Canada.
Modeling | Optimization
J 2017
F. Cheraghchib,
I. Abualhaol
R. Falcona, R. Abielmona, B. Raahemi, and E. Petriu, "Modeling the
Speed-based Vessel Schedule Recovery Problem using Evolutionary Multiobjective Optimization”,
Information Sciences 448 (2018): 53-74.
C 2017
F. Cheraghchib,
I. Abualhaol
, R. Falcon,b, R. Abielmona, B. Raahemi, and E. Petriu, "Big-Data-
Enabled Modelling and Optimization of Granular Speed-based Vessel Schedule Recovery Problem”,
in 2017 IEEE International Conference on Big Data, Boston, MA, USA, Dec 11-14, 2017.
C 2016
Rawan Alkurd,
I. Abualhaol
, Raed Shubair, and Muriel Medard, " Optimum HDAF Relay-Assisted
Combining Scheme with Relay Decision Information," IEEE 84th Vehicular Technology Conference,
Montréal, Canada, September 18-21, 2016.
C 2015
R. Alkurd, R. Shubair, and
I. Abualhaol
, "Optimum Decode-and-Forward Relay-Assisted Combining
Scheme with Relay Decision Information," IEEE International Conference on Communications (ICC),
pp. 2331–2337, June 2015.
C 2015
R. Alkurd, R. Shubair, and
I. Abualhaol
, "Modeling Conditional Error Probability for Hybrid Decode-
Amplify-Forward Cooperative System," IEEE Wireless Communications and Networking Conference
(WCNC), 7-12, March 2015.
J 2011 I. Abualhaol
and M. Matalgah "Unified Analysis of Optimized Relay-based Wireless Systems,"
Journal of Selected Areas in Telecommunications (JSAT), July Edition, 2011.
J 2009 I. Abualhaol
and M. Matalgah, "Throughput Optimization of Cooperative Teleoperated UGV
Network," International Journal of Mobile Computing and Multimedia Communications (IJMCMC),
pp. 32–46, 2009.
C 2006 I. Abualhaol
and M. Matalgah "Throughput Optimization of Cooperative UAVs Using Adaptive
Channel Assignment," IEEE Wireless Communications and Networking Conference (WCNC), vol. 4,
pp. 2279–2284, 3 -6 April, 2006.
Statistical and Performance Analysis
C 2014
R. Alkurd,
I. Abualhaol
, and S. Muhaidat, "Error Rate Performance Analysis of Cooperative SCR
in VANETs over Generalized Fading Channels," IEEE Wireless Communications and Networking
Conference (WCNC), pp. 3184–3189, 6-9 April, 2014.
C 2013
R. Alkurd, R. Shubair,
I. Abualhaol
, "Error rate performance analysis of cooperative MRC receivers
over generalized fading channels," IEEE 20th International Conference on Electronics, Circuits, and
Systems (ICECS), pp. 201–204, 8-11 Dec, 2013.
C 2013
E. Salahat and
I. Abualhaol
, "General BER analysis over Nakagami-m fading channels," the 6th
Wireless and Mobile Networking Conference (WMNC), pp. 1–4, 23-25 April, 2013.
J 2011 I. Abualhaol
and M. Matalgah "Performance analysis of cooperative multi-carrier relay-based UAV
networks over generalized fading channels," International Journal of Communication Systems (IJCS),
Jan 2011.
C 2011 I. Abualhaol
, "Symbol Error Rate Analysis of Relay-based Wireless Systems", IEEE 22nd International
Symposium on Personal Indoor and Mobile Radio Communications, pp. 1894–898, 11-14 Sep, 2011.
C 2011 I. Abualhaol
and M. Bawa’aneh "Capacity analysis of cooperative relay-based communication
system," IEEE GCC Conference and Exhibition, pp. 21–24, 19-22 Feb, 2011.
C 2007 I. Abualhaol
and M. Matalgah "End-to-End Performance Analysis of Cooperative Relay-Based
Wireless System Over Generalized Gaussian-Finite-Mixture Fading Channels," The 50th Annual IEEE
Global Communications Conference (GLOBECOM), pp. 3942–3947, 26-30 Nov, 2007.
C 2007 I. Abualhaol
and M. Matalgah "Capacity Analysis of MIMO System Over Identically Independent
Distributed Weibull Fading Channels," IEEE International Conference on Communications (ICC), pp.
5003-5008, 24-28 June, 2007.
C 2006 I. Abualhaol
and M. Matalgah "Outage Probability Analysis in a Cooperative UAVs Network Over
Nakagami-m Fading Channels," IEEE 64th Semiannual Vehicular Technology Conference (VTC), pp.
1–4, 25-28 Sep, 2006.
Wireless and Cooperative Communications
C 2014
R. Alkurd, R. Shubair, and
I. Abualhaol
, "Survey on device-to-device communications: challenges
and design issues," 12th IEEE International New Circuits and Systems Conference (NEWCAS), pp.
361–364, 22-25 June, 2014.
C 2013
S. Al Maeeni, S. Muhaidat, and
I. Abualhaol
, "Non-coherent detection for cooperative OFDM-based
system over time-varying fading channels," 20th IEEE International Conference on Electronics, Circuits,
and Systems (ICECS), pp. 197–200, 8-11 Dec, 2013.
C 2013
R. Alkurd,
I. Abualhaol
, and S. Muhaidat, "An efficient approximation of
Q
(
x
) function and
general BER performance analysis," IEEE 7th GCC Conference and Exhibition, pp. 367–371, 17-20
Nov, 2013.
C 2013
E. Salahat and
I. Abualhaol
, "Generalized average BER expression for SC and MRC receiver over
Nakagami-m fading channels," IEEE 24th International Symposium on Personal Indoor and Mobile
Radio Communications (PIMRC), pp. 3360–3365, 8-11 Sep., 2013.
C 2013
H. Eghbali,
I. Abualhaol
, S. Muhaidat, and Y. Iraqi, "Random-based Fair Allocation Algorithm
with Fuzzy Comprehensive Evaluation for Single Carrier Multi-Relay Cooperative Networks," 19th
European Wireless Conference (EW), pp. 1–5, 16-18 April, 2013.
J 2012
M. Ahmed, S. Jimaa, and
I. Abualhaol
, "Performance Enhancements of MIMO-OFDM system using
Various Adaptive Receiver Structures," International Journal of Computer and Information Technology
(IJCIT), pp. 99–106, vol. 1, 2012.
C 2012
M.A Ahmed, S.A Jimaa, and
I. Abualhaol
, "Enhanced channel estimation technique in MIMO-OFDM
system,", IEEE 8th International Conference on Wireless and Mobile Computing, Networking and
Communications (WiMob), pp. 545–549, 8-10 Oct. 2012.
C 2012
M. Ahmed, S. Jimaa, and
I. Abualhaol
, "BER Enhancement of MIMO-OFDM Using an Optimized
NLMS Receiver", 2012 6th Asia Modeling Symposium (AMS), pp. 211–214, 29-31 May, 2012.
C 2012
H. Eghbali,
I. Abualhaol
, S. Muhaidat, and Y. Iraqi, "Cluster-Based Fair Allocation Algorithm for
Multi-Relay Single Carrier Distributed Networks," IEEE 75th Vehicular Technology Conference (VTC
Spring), pp. 1–5, 6-9 May, 2012.
C 2012
H. Eghbali, S. Muhaidat, and
I. Abualhaol
, "Enhanced ZP-OFDM receiver in multi-relay cooperative
networks," 25th IEEE Canadian Conference on Electrical & Computer Engineering (CCECE), pp. 1–6,
29 April-2 May, 2012.
C 2012
Y. Iraqi,
I. Abualhaol
, and S. Muhaidat, "Lifetime Evaluation of Cooperative OFDM WSNs," IEEE
Wireless Communications and Networking Conference (WCNC), pp. 2054–2058, 1-4 April, 2012.
C 2011
H. Eghbali, S. Muhaidat, and
I. Abualhaol
, "Distributed single carrier frequency-domain equaliza-
tion for multi-relay cooperative networks over frequency selective Rician channels," 45th Asilomar
Conference on Signals, Systems and Computers(ASILOMAR), pp. 1115–1120, 6-9 Nov, 2011.
J 2011
H. Eghbali,
I. Abualhaol
, and S. Muhaidat, " Enhanced Iterative-based ZP-OFDM Receiver in Multi-
Relay Cooperative Networks," Journal of Selected Areas in Telecommunications (JSAT), September
Edition, 2011.
B 2010 I. Abualhaol
and M. Matalgah "Resource Allocation for a Cooperative Broadband MIMO-OFDM
System," Cooperative Communications for Improved Wireless Network Transmission: Frameworks for
Virtual Antenna Array Applications, pp. 382–398, IGI Global, PA, USA, 2010.
C 2010 I. Abualhaol
and M. Matalgah "Performance analysis of multi-carrier relay-based UAV network over
fading channels", IEEE GLOBECOM Workshops, pp.1811–1815, 6-10 Dec, 2010.
C 2010 I. Abualhaol
and Y. Iraqi, "Random-based fair allocation in Multi-Relay cooperative OFDM system,"
IEEE 6th International Conference on Wireless and Mobile Computing, Networking and Communica-
tions (WiMob), pp. 596–599, 11-13 Oct, 2010.
C 2010 I. Abualhaol
, M. Matalgah, and A. Abu-Abed "Enhanced cooperative coding for relay-based MIMO-
OFDM systems," IEEE 21st International Symposium on Personal Indoor and Mobile Radio Commu-
nications (PIMRC), pp. 2299–2303, 26-30 Sep, 2010.
C 2008 I. Abualhaol
and M. Matalgah "Subchannel-Division Adaptive Resource Allocation Technique for
Cooperative Relay-Based MIMO-OFDM Wireless Systems," IEEE Wireless Communications and
Networking Conference (WCNC), pp. 1002–1007, March 31- April 3, 2008.
C 2008 I. Abualhaol
and M. Matalgah "Capacity Analysis of MIMO System Over Nakagami-
m
Fading Chan-
nels Using Finite Mixture with Expectation Maximization Algorithm," IEEE International Conference
on Computer Systems and Applications (AICCSA), pp. 309–316, March 31- April 4, 2008.