Reza Abdolee

California State University, Bakersfield



Ph.D, Postdoc and Visiting Scholars(Supervise/Co-Supervise):

Smart Irrigation and Automated Farming Using IoT Technologies:

Fatemeh Asghari Fatemeh Asghari Azhiri is working on sparse antenna array processing. The sparse array processing has well-known applications in many fields in- cluding communications. The purpose of this research is to design new struc- tures to achieve more degrees of freedom and increase accuracy and energy efficiency in growing applications of direction of arrival (DOA) estimation in wireless communications. Also, since base stations in space time coded Mas- sive MIMO systems utilize large antenna arrays, studying the effect of array processing on Massive MIMO transmitters is another goal of this research. It is desired to determine optimized antenna array selection techniques to improve performance of STBC Massive MIMO systems.

Smart Irrigation and Automated Farming Using IoT Technologies:

Majid Abrazi Majid Safari Abrazi works on IoT platforms and technologies for use in agriculture industry. While the popularity of the Internet of Things (IoT) continues to grow, and the need for wireless, connected, "smart" devices with it, not many agriculture industry are utilizing IoT solutions. The agriculture sector, specifically, could greatly benefit from this new technology. He is investigating the shortcomings of these products and technologies and then propose a solution to overcome such issues. His propoed solution will benefit from the current IoT hardware platform, software solution and cloud computing and virtual hardware.

Energy efficient hybrid massive MIMO structure for 5G:

Homeyra Rahbari The mmWave systems, operating in the frequency of 30-100GHz, have been introduced to fulfill the demands of large-capacity high-speed wireless services. However, the use of such a frequency band incurs severe signal attenuation and path loss, which is the dominant limiting factor for the coverage and robustness of mmWave communications. One of the promising solutions to resolve this issue is to utilize massive multiple-input multiple-output (MIMO) technology in mmWave transceivers, where a large number of antenna (e.g. hundreds or more) are used at the base station to transmit signal to multiple users. In such systems, as the number of antenna elements increases, not only hardware costs and size increase drastically, but also the computational complexity of the antenna array processing techniques becomes prohibitively high. In addition, large size massive MIMO transceivers may not fit well into small-cell wireless networks. To address this issue, Homeyra Rahbari proposes a new hardware architecture for mmWave massive MIMO systems that is significantly smaller in size and outperform the conventional massive MIMO in term of spectral and energy efficiency.

Super-Resolution Indoor/Outdoor Localization:

Dr. Mehdi Korki Dr. Mehdi Korki is working on super-resolution indoor/outdoor localization in Wirless Sensor Networks (WSN's). His research aims to substantially enhance the resolution and the accuracy of localization, and to reduce the bandwidth, communication resources, and computational complexity of the localization in WSNs. The project is expected to lay a solid foundation and make significant impacts to many modern applications and concepts, including Massive MIMO localization in 5G technology, localization for Internet of Things (IoT), smart cities, smart grids and energy control systems, wireless imaging sensor networks, etc.

Wireless Channel Modeling and Characterization for 5G systems:

Dr. Yaser Zahedi Dr. Yaser Zahdi is working on wireless channel characterization and modeling for mmWave frequency band and MIMO channels. His research includes, path loss channel modeling for outdoor mmWave communication channels, characterization of MIMO-UWB channel in outdoor environments, development of sparse wideband MIMO channel model, and mmWave channel characterization in indoor office environment.

Cognitive Radio and Non-gradiatent Based Learning Techniques in IoT systems:

Mohammadreza Ghavidel Mohammadreza Ghavidel is working on developing the spectrum agent-based cognitive radio schemes, and dealing with randomness use of learning techniques in IoT systems. In this Ph.D. research project, he proposes new models for spectrum evaluation in IoT using game theory to enhance energy efficiency of the system and reduce the data transmission latency. Considering the energy constraints in 5G systems, these new methods are very instrumental in increasing the lifetime of the sensor nodes in the system. Virtual wireless sensor networks and use of cognitive radio in this area are the other research avenues.