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Optimizing Energy Efficiency in Wireless Links Through Optimal Ratios and Reconfigurable Intelligent Surfaces

Time: Mon 2024-03-04 13.00

Location: Amiga, Kistagången 16, Kista

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Language: English

Subject area: Information and Communication Technology

Doctoral student: Anders Enqvist , Kommunikationssystem, CoS, Communication Systems

Opponent: Associate Professor Yuanwei Liu, Queen Mary University of London, London, UK

Supervisor: Professor Emil Björnson, Kommunikationssystem, CoS, Department of Computer Science, KTH Royal Institute of Technology, Kista, Sweden; Associate Professor Ozlem Tugfe Demir, Kommunikationssystem, CoS, Department of Electrical and Electronics Engineering, TOBB University of Economics and Technology, Ankara, Turkey; Associate Professor Cicek Cavdar, Kommunikationssystem, CoS

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QC 20240215


This thesis explores the optimization of energy efficiency (EE) in the radiolink of wireless communication systems, focusing on both the user equipment (UE) and the base station (BS). The first part of the study examines strategies to minimize the energy consumption of the UE when transmitting short data payloads, utilizing a reconfigurable intelligent surface (RIS) controlled by the BS, to improve the channel conditions. The challenge lies in balancing the increased energy consumption due to additional pilot signals needed toconfigure the RIS against the energy savings during data transmission. We propose an innovative approach where the RIS is divided into subarrays of controllable sizes to shorten the pilot length. The analytical results provide a unique energy-minimizing solution in terms of pilot length and power which depends on an interplay between the payload size and path loss conditions between the UE, BS, and RIS. In the second part, the focus shifts to the EE of a multi-antenna BS. A comprehensive power consumption model is employed, accounting for both active and passive components of the transceiver circuitry. By treating the transmit power, bandwidth, and number of antennas as optimization variables, we derive novel closed-form solutions to the optimal value of these variables and propose an algorithm for their joint optimization. This part of the study not only optimizes the variables for maximum EE but also uncovers a new relationship between radiated power and passive transceiver power consumption, offering insights into the trade-offs between using maximum power and bandwidth. Together, these studies provide an updated view of EE optimization in wireless communication systems, offering novel theoretical insights for both UE and BS configurations.