An Energy-Efficient Multi-Level Sleep Strategy for Periodic Uplink Transmission in Industrial Private 5G Networks.

This paper proposes an energy-efficient multi-level sleep mode control for periodic transmission (MSC-PUT) in private fifth-generation (5G) networks. In general, private 5G networks meet IIoT requirements but face rising energy consumption due to dense base station (BS) deployment, particularly impacting operating expenses (OPEX). An approach of BS sleep mode has been studied to reduce energy consumption, but there has been insufficient consideration for the periodic uplink transmission of industrial Internet of Things (IIoT) devices. Additionally, 5G New Reno's synchronization signal interval limits the effectiveness of the deepest sleep mode in reducing BS energy consumption. By addressing this issue, the aim of this paper is to propose an energy-efficient multi-level sleep mode control for periodic uplink transmission to improve the energy efficiency of BSs. In advance, we develop an energy-efficient model that considers the trade-off between throughput impairment caused by increased latency and energy saving by sleep mode operation for IIoT's periodic uplink transmission. Then, we propose an approach based on proximal policy optimization (PPO) to determine the deep sleep mode of BSs, considering throughput impairment and energy efficiency. Our simulation results verify the proposed MSC-PUT algorithm's effectiveness in terms of throughput, energy saving, and energy efficiency. Specifically, we verify that our proposed MSC-PUT enhances energy efficiency by nearly 27.5% when compared to conventional multi-level sleep operation and consumes less energy at 75.21% of the energy consumed by the conventional method while incurring a throughput impairment of nearly 4.2%. Numerical results show that the proposed algorithm can significantly reduce the energy consumption of BSs accounting for periodic uplink transmission of IIoT devices.

Energy-Efficient AP Selection Using Intelligent Access Point System to Increase the Lifespan of IoT Devices.

With the emergence of various Internet of Things (IoT) technologies, energy-saving schemes for IoT devices have been rapidly developed. To enhance the energy efficiency of IoT devices in crowded environments with multiple overlapping cells, the selection of access points (APs) for IoT devices should consider energy conservation by reducing unnecessary packet transmission activities caused by collisions. Therefore, in this paper, we present a novel energy-efficient AP selection scheme using reinforcement learning to address the problem of unbalanced load that arises from biased AP connections. Our proposed method utilizes the Energy and Latency Reinforcement Learning (EL-RL) model for energy-efficient AP selection that takes into account the average energy consumption and the average latency of IoT devices. In the EL-RL model, we analyze the collision probability in Wi-Fi networks to reduce the number of retransmissions that induces more energy consumption and higher latency. According to the simulation, the proposed method achieves a maximum improvement of 53% in energy efficiency, 50% in uplink latency, and a 2.1-times longer expected lifespan of IoT devices compared to the conventional AP selection scheme.

Cascaded Stokes and anti-Stokes laser based on an optical resonator with a self-assembled organic monolayer.

Due to their high circulating intensities, ultra-high quality factor dielectric whispering gallery mode resonators have enabled the development of low threshold Raman microlasers. Subsequently, other Raman-related phenomena, such as cascaded stimulated Raman scattering (CSRS) and stimulated anti-Stokes Raman scattering (SARS), were observed. While low threshold frequency conversion and generation have clear applications, CSRS and SARS have been limited by the low Raman gain. In this work, the surface of a silica resonator is modified with an organic monolayer, increasing the Raman gain. Up to four orders of CSRS are observed with sub-milliwatt (mW) input power, and the SARS efficiency is improved by three orders of magnitude compared to previous studies with hybrid resonators.

Raman-Kerr frequency combs in Zr-doped silica hybrid microresonators.

Resonant cavity-enhanced Kerr frequency combs have been demonstrated using a range of cavity materials. Regardless of cavity type, one fundamental challenge is achieving low or flat dispersion while maintaining high-efficiency four-wave mixing (FWM). Here we demonstrate a Raman-Kerr frequency comb using a Zr-doped silica hybrid toroidal microcavity. The Zr-doped layer both flattens the dispersion and increases the stimulated Raman scattering efficiency. This enhancement enables the generation of FWM around both the Stokes and anti-Stokes Raman scattering emissions. As a result, the Raman-Kerr frequency comb spans more than 300 nm in the near-IR region with less than 5.2 mW of input power.

Densely packed siloxane barrier for blocking electron recombination in dye-sensitized solar cells.

A challenge in developing photovoltaic devices is to minimize the loss of electrons, which can seriously deteriorate energy conversion efficiency. In particular, minimizing this negative process in dye-sensitized solar cells (DSCs) is imperative. Herein, we use three different kinds of siloxanes, which are adsorbable to titania surfaces and polymerizable in forming a surface passivation layer, to reduce the electron loss. The siloxanes used are tetraethyl orthosilicate (TEOS or compound A), 1-(3-(1H-imidazol-1-yl)propyl)-3-(3-triethoxysilyl) propyl) urea (compound B), and N-(3-triethoxysilylpropyl)-N'[3-(3-methyl-1H-imidazol-3-ium) propyl] urea iodide (compound C). Titania surface passivation by either compound B or C was comparatively more effective in increasing the electron lifetime than TEOS. In the case of small-sized TEOS combined with either large-sized compound B or C, a thinner and denser passivation layer was presumably developed, thus increasing electron lifetime further. Intriguingly, device AB shows the longest electron lifetime, whereas device AC has the highest energy conversion efficiency among these experimental conditions. These results suggest that, in this special case, the electron lifetime may not be a dominant parameter in determining the energy conversion efficiency.

Tetrathiafulvalene as an electron acceptor for positive charge induction on the surface of silver nanoparticles for facilitated olefin transport.

Tetrathiafulvalene (TTF), a well-known electron donor, can also behave as an electron acceptor after being adsorbed on the surface of silver nanoparticles (Ag NPs), thereby inducing a partial positive charge on the Ag NPs surface. The Ag NPs activated by TTF help propylene transport much faster than propane, i.e., facilitated olefin transport, resulting in extremely high separation performance for propylene-propane mixtures.