Energy-Efficient Transmission Strategies for Multiantenna Systems

Thesis event information

Date and time of the thesis defence

Place of the thesis defence

Lecture Hall L10

Topic of the dissertation

Energy-Efficient Transmission Strategies for Multiantenna Systems

Doctoral candidate

Master of Engineering (M.Eng.) Kien-Giang Nguyen

Faculty and unit

University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, Centre for Wireless Communications - Radio Technologies

Subject of study

Wireless Communications

Opponent

Associate Professor Bruno Clerckx, Imperial College London, United Kingdom

Custos

Professor Markku Juntti, University of Oulu

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Energy-Efficient Transmission Strategies for Multiantenna Systems

The rapid evolution of wireless networks to meet the requirements of explosive data traffic demand is escalating energy consumption beyond sustainable limits. This vision poses ever-critical concerns over not only global climate change but also operating costs of mobile networks. As a result, energy efficiency, measuring how many information bits can be transmitted by a unit of energy, has been identified as a key performance indicator for future wireless networks to address the increasing concern over greenhouse gas emissions and sustainable economic growth. The use of multiple antennas at transceivers greatly boosts achievable data rate for wireless communications systems. Therefore, multiantenna transmission has been identified as the key element enabling the current and future mobile networks, i.e., 4G, 5G and beyond. However, this technique requires remarkable amount of energy to operate a large number of electronic circuits involved. Energy-efficient multiantenna techniques are thus deemed important for wireless systems. This thesis aims at developing transmission strategies optimizing the energy efficiency metric of multiantenna wireless systems. The proposed transmission schemes outperform existing methods in terms of achieving energy efficiency, as well as are low-complexity and attractive for practical implementation.
Last updated: 1.3.2023