My name is Parya Haji Mirzaee, I am a Ph.D. student at 5GIC&6GIC, University of Surrey, UK, under the supervision of Dr. Mohammad Shojafar and co-supervision of Dr. Haitham Cruickshank. From 2017 to 2019, I was the communication laboratory instructor and lecturer at Kurdistan University, Kurdistan, Iran. I received my master's degree from the University of Kurdistan. My project was on Smart Grid Communication Network and traffic engineering (2014-2016). I was a member of Rojdax research team and worked on the first project for Smart and Green transportation implementation in Sanandaj, Kurdistan, Iran. I did my bachelor's at Urmia University, Urmia, Iran, in communication Engineering (2010-2014).


Research interests


Parya Haji Mirzaee · Mohammad Fathi · Nooruldeen Nasih Qader (2017) Quality of service aware traffic scheduling in wireless smart grid
The next generation electrical power grid, known as smart grid (SG), requires a communication infrastructure to gather generated data by smart sensors and household appliances. Depending on the quality of service (QoS) requirements, this data is classified into event-driven (ED) and fixed-scheduling (FS) traffics and is buffered in separated queues in smart meters. Due to the operational importance of ED traffic, it is time sensitive in which the packets should be transmitted within a given maximum latency. In this paper, considering QoS requirements of ED and FS traffics, we propose a two-stage wireless SG traffic scheduling model, which results in developing a SG traffic scheduling algorithm. In the first stage, delay requirements of ED traffic is satisfied by allocating the SG bandwidth to ED queues in smart meters. Then, in the second stage, the SG rest bandwidth is going to the FS traffic in smart meters considering maximizing a weighted utility measure. Numerical results demonstrate the effectiveness of the proposed model in terms of satisfying latency requirement and efficient bandwidth allocation.
Farzad H. Panahi, Parya Haji Mirzaee, Fereidoun H. Panahi , Tomoaki Ohtsuki (2018) Smart Image-Processing based Energy Harvesting
for Green Internet of Things
 Internet of Things (IoT), as a widespread growing technology which connects various heterogeneous devices of wireless sensor networks (WSNs), plays a great role in sensing, monitoring, controlling of the covering environment. However, maximizing the lifetime of WSNs is still a major challenge. Although some approaches have been introduced to overcome the vital problem so far, research on this problem experiences a slow progress. Inspired by the promising performance of fuzzy-based Q-learning (FQL) algorithm to design practical smart sensors, this paper proposes a FQL-based approach that can maximize the lifetime of sensors and accelerate the process of wireless energy harvesting (EH) for mobile sensors which coexist with macro and small base stations (SBSs) deployed over a timevariant heterogeneous network (HetNet). The methodology is based on a centralized image-processing (IP) approach to scan and find the instant coverage map of the HetNet and then to localize red regions, i.e., regions with high levels of energy. Furthermore, mobile sensors attempt to access these regions during frequent movements. This will help to maximize the lifetime of the WSN. Simulation results confirm the effectiveness of the wireless EH process and smart aggregation of mobile sensors around the dense-coverage areas.