New research led by Associate Professor Peng Cheng has demonstrated how artificial intelligence (AI) can help future wireless networks manage unprecedented demand.
“Connected devices such as smartphones, sensors and autonomous vehicles are expected to exceed 30 billion worldwide by the end of the decade,” he says. “This is going to place enormous pressure on wireless networks to deliver a reliable, high-quality service.”
Associate Professor Cheng’s study, published in IEEE Transactions in Communications, explored how AI can be used to guide complex network decisions to support this huge increase in users.
“Currently, when demand exceeds network capacity, networks must make difficult decisions about access and resource allocation. Most existing approaches struggle to scale to this level of complexity,” he explains.
“Our research showed that AI can learn from network conditions and user demand and use this information to help networks make smarter decisions about who to serve when resources are limited.”
Associate Professor Cheng says this means that AI-driven decision-making can “reduce network congestion, improve user experience and increase overall system efficiency without immediate hardware expansion.”
The next step will be to translate this research into practical solutions through industry collaboration.
“Future work will test this research in more realistic, dynamic network conditions, helping bridge the gap between theory and real-world operation.”
“We also hope these ideas will be relevant to other large-scale digital systems, including smart cities and industrial automation, where efficient and fair resource allocation is essential.”
