The integration of Wake-Up Radios (WURs) into Wi-Fi presents a powerful paradigm for enabling multi-year battery life in power-constrained devices. However, existing approaches, such as the IEEE 802.11ba standard, rely on dedicated, spectrally-inefficient transmissions that consume valuable channel resources. This paper introduces AuraWake, a novel technique that creates a spectrally-efficient control plane by superimposing control signals directly onto ongoing Wi-Fi data packets, leveraging the primary link’s existing signal-to-noise ratio margin. We first present a detailed simulation model and a low-complexity architecture for the AuraWake receiver. Through comprehensive link-level simulation, we conduct a rigorous performance evaluation of its reliability and quantify its minimal, controllable impact on the primary data communication. We then demonstrate the utility of this superimposed control plane by applying it to solve critical, practical challenges in modern Wi-Fi. Our system-level analysis and simulation studies confirm that using AuraWake to mitigate clock drift for long-sleeping Target Wake Time (TWT) stations, enforce quiet periods to protect Restricted TWT (R-TWT) transmissions, and dynamically adapt TWT schedules significantly enhances the reliability and efficiency of these next-generation energy-saving features.

The variety of low latency applications in 6G makes the issue of maintaining data freshness increasingly important. However, due to battery life limitations, User Equipment (UE) should also apply power-saving procedures, such as Discontinuous Reception (DRX), which may result in additional latency. Therefore, this paper aims to study the relationship between data freshness and power-saving performance. To capture the information freshness, we use Age of Information (AoI) as the performance metric. To the best of our knowledge, unlike previous studies that primarily focus on the trade-off between power saving and delay, this is the first study to consider the impact of DRX on the Age of Information (AoI). We have derived the closed-form solutions for both the peak-average AoI (PAoI) and time-average AoI (TAoI) under the DRX mechanism, along with their respective parameter adjustment strategies. Based on our simulation validation, these proposed strategies enable the UE to maintain the average AoI close to the theoretical lower bound while simultaneously achieving high power-saving efficiency. This positions our approach at the forefront of balancing information freshness and energy conservation in mobile and IoT networks.

As the feature size decreases, leakage power consumption becomes an important target in the design. Using multiple threshold voltages (VTs) in cell-based designs is a popular technique to simultaneously optimize circuit timing and minimize leakage power. However, an arbitrary cell placement result of a multi-VT design may suffer from many design rule violations induced by the Minimum-Implant-Area (MIA) rule, and thus it is necessary to take the MIA rules into consideration during the detailed placement stage. The state-of-the-art works on detailed placement comprehensively tackling MIA rules either disallow VT change or only allow reducing cell VTs to avoid timing degradation. However, these limitations may either result in larger cell displacement or cause overhead in leakage power. In this paper, we propose an optimization framework of VT reassignment and detailed placement to simultaneously consider MIA rules and leakage power minimization under timing constraints. Experimental results show that compared with the state-of-the-art works, the proposed framework can efficiently achieve better trade-off between leakage power and cell displacement.

Reducing the power consumption of User Equipment (UE) has always been a crucial issue in communication systems. As a result, Discontinuous reception (DRX) is introduced in today's New Radio (NR) networks as a power-saving strategy. In addition, the variety of low latency applications in 6G makes the issue of maintaining data freshness increasingly important. This paper aims to study the relationship between freshness and power-saving. To capture the information freshness, we use Age of Information (AoI) as the performance metric. To our best knowledge, unlike previous studies focusing on power saving and delay trade-offs, this is the first study considering the impact of DRX on AoI. We solve the closed-form solution of the peak average AoI with the DRX mechanism. Moreover, we propose a parameters adjustment strategy. Based on the simulation validation, our proposed strategy can enable the UE to keep the AoI close to the theoretical lower bound AoI while achieving high power-saving efficiency.