Research  Funded by University of Bahrain

Project name: Wireless Space Time MIMO technology for Broadband Communication systems "MIMO@UOB"

Starting date: 15 / 10 / 2009

Ending date: 1 / 7 /2011



Digital communications using multiple-input–multiple-output (MIMO) wireless link that uses multiple transmitter and receiver antennas, has recently emerged as one of the most significant technical breakthroughs in modern wireless communications with a chance of resolving the bottleneck of traffic capacity in future Internet-intensive wireless networks. This technique also solves the problem of the limited data rates achievable over wireless links because of the fading problems that improve the system performance. As shown in fig 1, MIMO systems gives high speed date rates compared to current technologies with single antennas, SISO.


In this project an overview of recent progress in the area of multiple-input–multiple-output (MIMO) wireless systems. After some background on the research leading to the discovery of the enormous potential of MIMO wireless links. The state of the art in MIMO channel modelling leading to a better understanding of actual MIMO gains will be presented. The different classes of techniques and algorithms proposed which attempt to realize the various benefits of MIMO including spatial multiplexing, space–time coding schemes and integration with OFDM will be numerically simulated.

Finally, the project addresses current questions regarding the integration of MIMO links in practical wireless systems and standards. A practical objective of this project will be to measure the channel and model the hot spot in EE department building within University of Bahrain campus with high speed LAN local area wireless network using the latest standard IEEE802.11-n that uses MIMO technology,  as shown in fig 2.




Fig. 1: Comparison between routers performance for single antenna versus MIMO technology

for home network applications


Fig. 2: Block diagram of a space-time coded MIMO-OFDM system, IEEE802.11n.


Dr. Mohab Mangoud is the primarily investigator of the project, he is an associate professor at the Electrical and Electronics Engineering Department, University of Bahrain. He received his Ph.D. in 2001 from the University of Bradford in United Kingdom. His main area of expertise is on wireless communications and satellite systems. He has significant international collaborative experience on several research projects through US/European Union joint funding and funding through private telecommunications companies in United Kingdom. Dr. Mangoud has already conducted research on MIMO and recently co-advised a graduate student at the Master’s level. Last year 2 new papers were published in this topic and the project will be a continue for this research efforts.


[1] M. A. Mangoud, “Capacity Investigations of MIMO Systems in Correlated Rician Fading Channel Using Statistical Multi-Clustered Modelling”, Proceeding of the 8th International Conference of Intelligent Transport Systems (ITS), Thailand , October 2008.


[2] M. A. Mangoud, “Optimization of Antenna Geometry to Increase Channel Capacity for Indoor MIMO Systems” Proceeding of The International Conference on Intelligent Systems, Bahrain, December 2008.




The primary objective for this project, various features of MIMO technology that gives high-performance broadband wireless backhaul solution will be investigated.  The aim is to have a greater effective throughput, increased link availability and operating distances in both LOS and NLOS conditions for modern wireless communication systems. Thus the project will have the following objectives:


1.     Ergodic Capacity investigations and improved channel models for MIMO wireless technology and special attention will be given to IEEE802.11n standards. Statistical channel modelling for wireless MIMO systems [4] and comparing it with ray tracing channel modelling (using commercial software package. As a case study: channel will be modelled for a wireless local area network within the building of the University of Bahrain (realistic environment). 


2.     The impact of Antennas on MIMO systems performance will be studied in this project as an extension to the work started in [5] by Dr. Mangoud. Also, finding the array geometry that maximizes capacity over a variety of propagation channels and different symbol error rates. The optimizing channel capacity for indoor MIMO systems will be performed using GA and SWARM. This study will include the effects of: Element Radiation Pattern, Array Configuration, Element Polarization and Mutual Coupling


3.  Broadband MIMO System Simulation: Computer simulation is a very important tool for wireless communication systems R&D. the project will develop a standard 802.11n compatible simulation system to facilitate advanced 802.11n MIMO platform development. The system can be used to verify system algorithms and to evaluate the performance in a short time. MATLAB and Lab View have been chosen to be used to build this system and the simulation system has been well defined as stated in the specifications. Simulations MIMO-OFDM Systems using both programs. Also, Space-Time Block Coding will be included and compared with Layered architecture with a thorough performance analysis.


4.   MIMO Channel models in objective 1 will be validated against channel measurement. Indoor channel measurements for statistical models for test case of WLAN within UOB will be examined for different setups with various positions and orientations of the antenna arrays. The measured data and present results for path loss, power delay profiles, spatial correlation and temporal correlation will be analyze.




Phase  Title




  1. Literature survey, review and comparison of system performance of Space-Time wireless MIMO systems and current channel models and challenges to be addressed in details.



Nov 2009


Dec 2009




  1. Channel modeling and building the new MIMO model for IEEE802.11n.

(Ray tracing simulation if possible)


Jan 2010

April 2010


  1. Simulations STC-OFDM/MIMO Systems with layered architecture.

(Matlab, Labview, software).


May 2010

Dec 2010


  1. Performance evaluation of Multiple-Input Multiple-Output Wireless Communication Systems


Jan 2011

April 2011

  1. Writing report


May 2010

June 2011