Public defence, Communications Engineering, MSc Maliha Jada

Title of the thesis: Techniques for Energy Efficient Radio Access Networks

Thesis defender: Maliha Jada
Opponent: Prof. Kimmo Kansanen, NTNU, Norway
Custos: Prof. Jyri Hämäläinen, Aalto University School of Electrical Engineering 

The scarcity of global resources is a fundamental challenge of our time, impacting everything from clean air to livable land. Garrett Hardin’s concept of the "Tragedy of the Commons" illustrates how shared resources are often overexploited for short-term gains, resulting in environmental imbalances like climate change. Today, energy has emerged as another critically limited resource facing ever-increasing demand, a surge driven heavily by the exponential growth of data storage and communication required for Artificial Intelligence (AI) applications.

While mobile networks are the vital backbone enabling this AI revolution, their rapid expansion comes with a significant environmental footprint. Mobile networks currently account for roughly 10% of the greenhouse effect attributed to Information and Communication Technology (ICT), representing about 2.5% of global CO2 emissions. Curbing these emissions requires a drastic shift toward energy efficiency, where power consumption is directly tied to how efficiently network resources are managed.

Cellular networks are traditionally engineered to handle peak traffic during peak hours, deploying all available assets to guarantee service quality. However, during periods of low traffic, many of these resources remain active but underutilized, leading to substantial energy waste. This doctoral thesis addresses this critical environmental and economic challenge by developing strategies to dynamically scale down or switch off underutilized network elements during low-traffic periods without compromising user experience.

The research investigates, optimizes, and evaluates energy-saving techniques across multiple generations of mobile communication:

3G & 4G/4G+ networks: The work establishes baseline modeling for base station power consumption and proposes a novel network management approach based on dynamic base station and carrier switching. It introduces a multi-dimensional, traffic-aware optimization framework using meta-heuristic approaches, offering scalable solutions for energy-conscious network planning.

5G-Advanced and 6G networks: Moving into state-of-the-art architectures, the thesis explores energy-efficient radio resource adaptation techniques, with a specific focus on massive MIMO systems. By analyzing antenna and transmit power adaptation both individually and jointly, the study demonstrates substantial energy savings under low-to-medium loads, while maintaining robust performance during peak demands.

This doctoral work provides understanding and results that can be used to design flexible, adaptive and energy efficient mobile networks. Work is bridging the gap between high-performance connectivity and environmental sustainability as the industry transitions toward 6G.

Thesis available for public display 7 days prior to the defence at Aalto University's public display page.