The CTR has two major research groups namely wireless communications research group and fiber optics research group. The centre is led by Dr.Udesh Oruthota and in addition has five academic staff members currently.
The wireless communication research group cover a broad range of research initiatives related to telecommunications engineering, with our key research related to 5G wireless communication & networking such as simultaneous wireless information and power transfer (SWIPT), machine learning based wireless communication, underwater visible light communications (VLC), unmanned aviation vehicle (UAV) assisted communications and non-orthogonal multiple access (NOMA) technologies for 5G, internet of things (IoT), etc.
The fiber optic research group is working on the non-linear phase noise compensation techniques, developing dispersion measurement techniques and free space optics (FSO). Further, this research group conducted a feasibility study in fiber network infrastructure development to implement SEA-ME-WE traffic routing via Sri Lanka.
Research areas
Radio-based localization and sensing
Radio-based localization and sensing involve using radio signals to determine the position and movement of objects within a specific area. This technology is crucial in various applications, such as autonomous vehicles, indoor navigation, and smart home systems. In this research, new algorithms and system architectures are proposed to enhance the accuracy and reliability of radio-based localization systems. These advancements leverage multi-path signal analysis, time-of-arrival measurements, and advanced signal processing techniques to improve localization accuracy in challenging environments, such as those with high signal interference or dense obstacles.
AI/ML-based communication systems design
AI/ML-based communication systems design focuses on integrating artificial intelligence and machine learning algorithms into communication networks to optimize performance and efficiency. This approach is increasingly relevant in the era of 5G and beyond, where network environments are dynamic and complex. In this research, novel AI/ML models are developed to enhance network resource management, improve signal processing, and enable adaptive communication protocols. These models use data-driven techniques to predict network conditions and optimize routing, thus ensuring higher data throughput, reduced latency, and improved overall network reliability.
AI/ML-Based IoT Systems Design
AI/ML-based IoT systems design involves incorporating artificial intelligence and machine learning into Internet of Things (IoT) applications to enhance their functionality, security, and scalability. This approach is critical for smart cities, industrial automation, and healthcare systems, where vast amounts of data are generated and need to be processed in real-time. In this research, innovative AI/ML algorithms are proposed to analyze IoT data streams, detect anomalies, and predict maintenance needs, thereby optimizing system performance and ensuring robust security. These algorithms utilize deep learning, reinforcement learning, and federated learning to process data locally on IoT devices, reducing the need for centralized processing and enhancing the overall system efficiency.
Average age of information in the URLLC based wireless networks
Age of Information (AoI) measures the freshness of the received data in mission critical Internet-of-Things (IoT) applications i.e., industrial internet, intelligent transportation systems etc. In this research , new system models are proposed to estimate the average AoI (AAoI) in an ultra-reliable low latency communication (URLLC) enabled wireless communication system.
Non orthogonal multiple access (NOMA)
NOMA is the sophisticated multiple access scheme proposed for 5G wireless networks and it provides high spectral efficiency and massive connectivity in the cellular networks. Moreover, the concept of NOMA is used in low power wireless networks, for instance internet of things (IoT) to support multiple low power devices with the same resources. Further, NOMA scheme is used parallely with many existing wireless technologies such as visible light communication and physical layer network coding etc. thereby it further enhance the performance of the wireless networks.
Soft information relaying
The soft information relaying (SIR) is a recently proposed relay protocol for cooperative communication for wireless networks. It reduces the drawbacks and the shortcomings of traditional protocols, such as error propagation to the destination (DF) and noise amplification at the relay (AF). In contrast to DF, in SIR the performance of decoding at the destination is not degraded under a poor channel condition improving transmit diversity and spectral efficiency.
UAV assisted wireless communication
UAVs are commonly called drones which have a wide range of applications. At the beginning of time, its application was limited to military, surveillance, media coverage and photography. Thanks to the continuous development of low-cost energy efficient UAVs that are embedded with artificial intelligence, they open the way to many other promising applications. Such as Data Collection, Road traffic monitoring, smart agriculture, surveying, vehicle to vehicle communication, etc.
In that way, the wireless communication industry is also attracted towards embedding UAVs to achieve the requirements of the future generation of communication systems. Considering 5G and beyond, it comes with diverse requirements. Includes low latency, high data rate, massive connectivity, etc. Among those Need for Resilience networks, on-demand deployment and dynamic architecture can be exploited via UAV assisted wireless communication.
With that background, we focus on various fields of applied research in the application of UAV in wireless communication. We focus on algorithms to place UAV base stations in an emergency scenario to increase the spectral efficiency of the system. Some of our works are related to UAV enabled mobile edge computing. Also, we are focusing on wireless power transfer enabled UAVs for data collection. Moreover, there are several other branches that are focused under UAV assisted wireless communication.
