Numerical analysis of an infrared gas sensor utilizing an indium-tin-oxide-based plasmonic slot waveguide

Plasmonic waveguides have attracted much attention owing to the associated high field intensity at the metal–dielectric interface and their ability to confine the modes at the nanometer scale. At the same time, they suffer from relatively high propagation loss, which is due to the presence of metal. Several alternative materials have been introduced to replace noble metals, such as transparent conductive oxides (TCOs). A particularly popular TCO is indium tin oxide (ITO), which is compatible with standard microelectromechanical systems (MEMS) technology. In this work, the feasibility of ITO as an alternative plasmonic material is investigated for infrared absorption sensing applications: we numerically design and optimize an ITO-based plasmonic slot waveguide for a wavelength of 4.26 µm, which is the absorption line of CO2. Our optimization is based on a figure of merit (FOM), which is defined as the confinement factor divided by the imaginary part of the effective mode index (i.e., the intrinsic damping of the mode). The obtained optimal FOM is 3.2, which corresponds to 9 µm and 49 % for the propagation length (characterizing the intrinsic damping) and the confinement factor, respectively.

A study on the Delta-Bullington irregular terrain radiofrequency propagation model : assessing model suitability for use in decision support tools

Modeling the propagation of radiofrequency signals over irregular terrain is both challenging and critically important in numerous Army applications. One application of particular importance is the performance and radio connectivity of sensors deployed in scenarios where the terrain and the environment significantly impact signal propagation. This report investigates both the performance of and the algorithms and assumptions underlying the Delta-Bullington irregular terrain radiofrequency propagation model discussed in International Telecommunications Union Recommendation P.526-15. The aim is to determine its suitability for use within sensor-planning decision support tools. After reviewing free-space, spherical earth diffraction, and terrain obstacle diffraction losses, the report dis-cusses several important tests of the model, including reciprocity and geographic continuity of propagation loss over large areas of rugged terrain. Overall, the Delta-Bullington model performed well, providing reasonably rapid and geographically continuous propagation loss estimates with computational demands appropriate for operational use.

Image polaritons in van der Waals crystals

Polaritonic modes in low-dimensional materials enable strong light–matter interactions and the manipulation of light on nanometer length scales. Very recently, a new class of polaritons has attracted considerable interest in nanophotonics: image polaritons in van der Waals crystals, manifesting when a polaritonic material is in close proximity to a highly conductive metal, so that the polaritonic mode couples with its mirror image. Image modes constitute an appealing nanophotonic platform, providing an unparalleled degree of optical field compression into nanometric volumes while exhibiting lower normalized propagation loss compared to conventional polariton modes in van der Waals crystals on nonmetallic substrates. Moreover, the ultra-compressed image modes provide access to the nonlocal regime of light–matter interaction. In this review, we systematically overview the young, yet rapidly growing, field of image polaritons. More specifically, we discuss the dispersion properties of image modes, showcase the diversity of the available polaritons in various van der Waals materials, and highlight experimental breakthroughs owing to the unique properties of image polaritons.

Power Allocation and Energy Cooperation for UAV-Enabled MmWave Networks: A Multi-Agent Deep Reinforcement Learning Approach

Unmanned Aerial Vehicle (UAV)-assisted cellular networks over the millimeter-wave (mmWave) frequency band can meet the requirements of a high data rate and flexible coverage in next-generation communication networks. However, higher propagation loss and the use of a large number of antennas in mmWave networks give rise to high energy consumption and UAVs are constrained by their low-capacity onboard battery. Energy harvesting (EH) is a viable solution to reduce the energy cost of UAV-enabled mmWave networks. However, the random nature of renewable energy makes it challenging to maintain robust connectivity in UAV-assisted terrestrial cellular networks. Energy cooperation allows UAVs to send their excessive energy to other UAVs with reduced energy. In this paper, we propose a power allocation algorithm based on energy harvesting and energy cooperation to maximize the throughput of a UAV-assisted mmWave cellular network. Since there is channel-state uncertainty and the amount of harvested energy can be treated as a stochastic process, we propose an optimal multi-agent deep reinforcement learning algorithm (DRL) named Multi-Agent Deep Deterministic Policy Gradient (MADDPG) to solve the renewable energy resource allocation problem for throughput maximization. The simulation results show that the proposed algorithm outperforms the Random Power (RP), Maximal Power (MP) and value-based Deep Q-Learning (DQL) algorithms in terms of network throughput.

Graphene on Silicon Photonics: Light Modulation and Detection for Cutting-Edge Communication Technologies

Graphene—a two-dimensional allotrope of carbon in a single-layer honeycomb lattice nanostructure—has several distinctive optoelectronic properties that are highly desirable in advanced optical communication systems. Meanwhile, silicon photonics is a promising solution for the next-generation integrated photonics, owing to its low cost, low propagation loss and compatibility with CMOS fabrication processes. Unfortunately, silicon’s photodetection responsivity and operation bandwidth are intrinsically limited by its material characteristics. Graphene, with its extraordinary optoelectronic properties has been widely applied in silicon photonics to break this performance bottleneck, with significant progress reported. In this review, we focus on the application of graphene in high-performance silicon photonic devices, including modulators and photodetectors. Moreover, we explore the trend of development and discuss the future challenges of silicon-graphene hybrid photonic devices.

Weighted Direct Position Determination via the Dimension Reduction Method for Noncircular Signals

This work studies the direct position determination (DPD) of noncircular (NC) signals with multiple arrays. Existing DPD algorithms of NC sources ignore the impact of path propagation loss on the performance of the algorithms. In practice, the signal-to-noise ratios (SNRs) of different observation stations are often different and unstable when the NC signal of the same radiation target strikes different observation locations. Besides, NC features of the target signals are applied not only to extend the virtual array manifold but also to bring high-dimensional search. For the sake of addressing the above problems, this study develops a DPD method of NC sources for multiple arrays combing weighted subspace data fusion (SDF) and dimension reduction (RD) search. First, NC features of the target signals are applied to extend the virtual array manifold. Second, we assign a weight to balance the error and obtain higher location accuracy with better robustness. Then, the RD method is used to eliminate the high computational complexity caused by the NC phase search dimension. Finally, the weighted fusion cost function is constructed by using the eigenvalues of the received signal covariance matrixes. It is verified by simulation that the proposed algorithm can effectively improve the location performance, get better robustness, and distinguish more targets compared with two-step location technology and SDF technology. In addition, without losing the estimation performance, the proposed algorithm can significantly reduce the complexity caused by the NC phase search dimension.

The influence of single layer MoS2 flake on the propagated surface plasmons of silver nanowire

We demonstrate the enhancement of both excitation and transmission efficiency of the propagated surface plasmon (SP) of Ag nanowire (Ag NW) in hybrid Ag-MoS2 structure by contrasting the SP propagation of the same Ag NW on different substrates including silicon substrate, monolayer MoS2, or partially overlapping the Ag NW on MoS2 flake. The simulation results indicate that with the assistance of MoS2, the leaky radiation of the hybrid plasmonic modes of the H1 and H2 can be prominently suppressed by the high refractive index dielectric layer of the MoS2, which provides an optical barrier blocking the leaky radiation, resulting in the reduced propagation loss. Our work provides a feasible and effective method to enhance the SP propagation length.

Study and Analysis of a Multilayer Multipair Electret-Based Thin-Film Mechanical Antenna

Very low-frequency (VLF) and ultralow-frequency (ULF) electromagnetic waves have the advantage of high penetration and low propagation loss in wireless communication systems and are mainly used for underwater and underground communications, as well as for earthquake and lightning forecasting. At present, VLF and ULF antennas are mostly bulky and require hundreds of antennas and more to be set up, which is costly and inefficient. In this paper, we propose to generate VLF and ULF signals by rotating a multilayer multipair electret thin-film electret driven by an excitation device, which improves the problem of low radiation efficiency of VLF and ULF signals and the large size of conventional low-frequency transmitting antennas. Based on a multilayer, multipair electret film mechanical antenna, a magnetic field propagation model is developed, and the relationship between the magnetic flux density mode and the number of layers of electret films, as well as the relationship between the antenna emission frequency and the motor rotation frequency and the number of pairs of electret films, is analyzed. The selection of a suitable model for practical situations based on conditions such as antenna size and propagation distance is illustrated. The research work is of great importance for guiding the design of mechanical antennas and optimizing antenna structures.

Terrain-based adaption of propagation model loss parameters using non-linear square regression

Reliable and real-time propagation loss modeling play a significant role in the efficient planning, development, and optimization of macrocellular communication networks in a given terrain. Thus, the need to adapt or tune an existing model to enhance its signal prediction accuracy in a specified terrain becomes imperative. In this paper, we proposed and applied a non-linear square regression method based on the Levenberg-Marquart (LM) algorithm to adapt and improve the empirical propagation loss estimation accuracy of the Egli model for two major cities in Nigeria. A comprehensive propagation loss measurement acquired over Long Term Evolution (LTE) mobile broadband networks operating at 2630 MHz for four different cities was collected using TEMS investigation tools to achieve the Egli model adaption. Results indicate that the adapted Egli model displays a high estimation accuracy over the Gauss-Newton (GN) algorithm leveraging the non-linear regression method employed to benchmark the propagation loss estimation. Using six standard statistical indicators, the adapted Egli model displayed lower estimation errors than the classical Egli model across the tested locations in the two cities investigated. Finally, the LM-adapted Egli model was compared with extensive measurements from another eNodeB in Port Harcourt different from the initial four eNodeBs investigated. The results indicate that the adapted model is suitable for deployment in related macrocellular environments.

Nonlinear loss characterization of continuous wave guiding in silicon wire waveguides

Accurate propagation loss characterization of silicon waveguides is increasingly demanded for silicon-photonics-(Si-Ph) applications with high-power continuous-wave-(CW) light sources. We report on nonlinear loss parameters of silicon wire waveguides for 1.31-μm-wavelength CW light extracted from transmission data measured for different lengths and polarizations. Such parameters were, so far, unavailable, although they are required for accurately modeling Si-Ph optical circuits. More-than-ten-times enhancement of two-photon absorption from prior results for short pulse light was observed at power densities ranging up to 4.7×1011 W/m2 while free carrier absorption was suppressed. We estimate the nonlinear loss of the waveguide using the parameter values obtained