Researchers develop algorithm to increase energy efficiency

MUMBAI: A team of researchers from the Indian Institute of Technology-bombay (IIT-B) and Monash University, Australia developed a new algorithm that identifies the right amount of power level required to enhance energy efficiency of wireless communication systems.

Radio frequency (RF) signals are electromagnetic radiations used in wireless communication that transmit information and carry an inherent small electrical energy component. Emerging technology harvests this electrical energy, called RF energy, to power many wireless devices in various sectors such as medical implants or Internet of Things.

RF energy is harvested either by scavenging the ambient energy or by having a dedicated energy source. Such a system facilitates the continuous charging of the nodes’ batteries, enhances their life and overcomes the energy limitations of conventional battery-powered wireless devices. It also reduces the need for frequent battery replacement.

“RF energy harvesting networks consume high energy for both energy and information transmission. Therefore, optimising energy losses is a crucial and active research area for future wireless communication networks,” said Manjesh Hanawal, associate professor, industrial engineering and operations research (IEOR), IIT-B, who was one of the researchers involved in the project.

The algorithm developed by researchers at IIT-B uses a statistical tool that aids the source in identifying the optimal power output without having to depend on other parameters. The performance results of the algorithm were published in the journal IEEE Wireless Communications Letters in June.

Wireless nodes detect, monitor and report the energy harvesting status to the energy source. Based on the feedback, the source regulates the right power level to meet the demand and avoid power wastage.

Researchers use statisticsbased algorithms driven by artificial intelligence to automate power optimising process. Current algorithms are designed on a metric called channel state information — the feedback from receivers, such as how good the link is or how much of the received energy they could use.

In such smart systems, power sources act as both transmitters and receivers of information. The power source has to assess how much energy has to be transmitted so that all the nodes get enough energy to transmit the information.

However, more energy to the nodes does not translate to more information transmission. Hence, it is important to evaluate the overall energy efficiency of the RF energy harvesting network.

The project is funded by the Department of Science and Technology and Science and Engineering Research Board, Government of India, through the Innovation in Science Pursuit for Inspired Research Faculty Fellowship and Early Career Research Award; and the Australian Research Council’s Discovery Early Career Researcher Award scheme.

“An actual transmission system is a complex network with several receivers spread over a region receiving different amounts of energy for harvesting. Also, they will require different amounts of energy for successfully transmitting the information,” said Hanawal, lead author of the study.

As the environment is uncertain, reinforcing algorithms with sequential decision making can quickly ascertain status of the harvested energy, thereby improving the system’s energy efficiency, he said.

“The rate at which nodes could transmit the information is treated as the reward and is directly coupled with the amount of energy harvested,” said Debamita Ghosh, first author of the study and a research scholar at IEOR and Monash University.