Analytical Foundations of Energy-Efficient Wireless Communication: RIS Control and Sleep Mode Management

QC 20260819

Abstract

This thesis explores the optimization of energy efficiency (EE) and practical configuration overhead in wireless communication systems, focusing on both the user equipment (UE) and the base station (BS).

The first part of the study examines minimizing the UE's energy consumption when transmitting short data payloads via a BS-controlled reconfigurable intelligent surface (RIS). To balance the energy cost of the additional pilot signals needed to configure the RIS against the energy savings during data transmission, we propose dividing the RIS into controllable subarrays. This yields a unique energy-minimizing configuration determined by payload size and path loss conditions. Building on the practical challenges of RIS implementation, we then address the wireless control signaling overhead required to feed back these phase-shift configurations to the RIS. We propose a novel quantization codebook that guarantees minimal signal-to-noise ratio (SNR) loss while reducing feedback overhead from linear to logarithmic scaling with the number of RIS elements, and we introduce an efficient differential feedback scheme for mobility scenarios.

The second part focuses on the EE of multi-antenna BSs using an active and passive transceiver model. By jointly optimizing transmit power, bandwidth, and the number of antennas, we derive novel closed-form solutions that uncover a fundamental relationship between radiated power and passive circuitry consumption. This optimization framework is extended to incorporate Quality-of-Service constraints and advanced sleep modes, leading to a dynamic scheduling algorithm that optimizes hardware configurations to minimize total energy consumption for bursty traffic.

Finally, the thesis investigates the fundamental EE limits of a dual-band BS site combining a coverage-oriented sub-6 GHz carrier with a high-bandwidth, capacity-oriented secondary carrier. By jointly optimizing hardware parameters and sleep-mode activity across both bands, we identify four distinct operational regions that govern EE-optimal behavior. We derive analytical thresholds dictating precisely when the secondary capacity band should awaken from sleep and how much traffic it should carry, demonstrating that its utilization becomes EE-optimal only when the power cost of the bandwidth-limited primary band exceeds the static power penalty of activating the secondary circuitry.

Together, these studies provide a comprehensive view of EE optimization and resource management, offering novel theoretical insights and actionable design guidelines for UE and BS configurations, RIS control signaling, sleep-mode management, and multi-band integration.

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