Optimization-based mode selection scheme for OAM millimeter wave system in the off-axis misalignment case

Millimeter-wave transmission combined with Orbital Angular Momentum(OAM)has the advantage of reducing the loss of beam power and increasing the system capacity.However,to fulfill this advantage,the antennas at the transmitter and receiver must be parallel and coaxial;otherwise,the accuracy of mode detection at the receiver can be seriously influenced.In this paper,we design an OAM millimeter-wave communication system for overcoming the above limitation.Specifically,the first contribution is that the power distribution between different OAM modes and the capacity of the system with different mode sets are analytically derived for performance analysis.The second contribution lies in that a novel mode selection scheme is proposed to reduce the total interference between different modes.Numerical results show that system performance is less affected by the offset when the mode set with smaller modes or larger intervals is selected.

Modeling and Performance Analysis of UAV-Aided Millimeter Wave Cellular Networks with Stochastic Geometry

UAV-aided cellular networks,millimeter wave(mm-wave) communications and multi-antenna techniques are viewed as promising components of the solution for beyond-5G(B5G) and even 6G communications.By leveraging the power of stochastic geometry,this paper aims at providing an effective framework for modeling and analyzing a UAV-aided heterogeneous cellular network,where the terrestrial base stations(TBSs) and the UAV base stations(UBSs) coexist,and the UBSs are provided with mm-wave and multi-antenna techniques.By modeling the TBSs as a PPP and the UBSs as a Matern hard-core point process of type Ⅱ(MPH-Ⅱ),approximated but accurate analytical results for the average rate of the typical user of both tiers are derived through an approximation method based on the mean interference-to-signal ratio(MISR) gain.The influence of some relevant parameters is discussed in detail,and some insights into the network deployment and optimization are revealed.Numerical results show that some trade-offs are worthy of being considered,such as the antenna array size,the altitude of the UAVs and the power control factor of the UBSs.

Off-Grid Compressed Channel Estimation with Parallel Interference Cancellation for Millimeter Wave Massive MIMO

Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capacity.However,channel estimation has become very challenging due to the use of massive MIMO antenna array.Fortunately,the mmWave channel has strong sparsity in the spatial angle domain,and the compressed sensing technology can be used to convert the original channel matrix into the sparse matrix of discrete angle grid.Thus the high-dimensional channel matrix estimation is transformed into a sparse recovery problem with greatly reduced computational complexity.However,the path angle in the actual scene appears randomly and is unlikely to be completely located on the quantization angle grid,thus leading to the problem of power leakage.Moreover,multiple paths with the random distribution of angles will bring about serious interpath interference and further deteriorate the performance of channel estimation.To address these off-grid issues,we propose a parallel interference cancellation assisted multi-grid matching pursuit(PIC-MGMP)algorithm in this paper.The proposed algorithm consists of three stages,including coarse estimation,refined estimation,and inter-path cyclic iterative inter-ference cancellation.More specifically,the angular resolution can be improved by locally refining the grid to reduce power leakage,while the inter-path interference is eliminated by parallel interference cancellation(PIC),and the two together improve the estimation accuracy.Simulation results show that compared with the traditional orthogonal matching pursuit(OMP)algorithm,the normalized mean square error(NMSE)of the proposed algorithm decreases by over 14dB in the case of 2 paths.

High-Accuracy NLOS Identification Based on Random Forest and High-Precision Positioning on 60 GHz Millimeter Wave

60 GHz millimeter wave(mmWave)system provides extremely high time resolution and multipath components(MPC)separation and has great potential to achieve high precision in the indoor positioning.However,the ranging data is often contaminated by non-line-of-sight(NLOS)transmission.First,six features of 60GHz mm Wave signal under LOS and NLOS conditions are evaluated.Next,a classifier constructed by random forest(RF)algorithm is used to identify line-of-sight(LOS)or NLOS channel.The identification mechanism has excellent generalization performance and the classification accuracy is over 97%.Finally,based on the identification results,a residual weighted least squares positioning method is proposed.All ranging information including that under NLOS channels is fully utilized,positioning failure caused by insufficient LOS links can be avoided.Compared with the conventional least squares approach,the positioning error of the proposed algorithm is reduced by 49%.

Compressive near-field millimeter wave imaging algorithm based on Gini index and total variation mixed regularization

A compressive near-field millimeter wave(MMW)imaging algorithm is proposed.From the compressed sensing(CS)theory,the compressive near-field MMW imaging process can be considered to reconstruct an image from the under-sampled sparse data.The Gini index(GI)has been founded that it is the only sparsity measure that has all sparsity attributes that are called Robin Hood,Scaling,Rising Tide,Cloning,Bill Gates,and Babies.By combining the total variation(TV)operator,the GI-TV mixed regularization introduced compressive near-field MMW imaging model is proposed.In addition,the corresponding algorithm based on a primal-dual framework is also proposed.Experimental results demonstrate that the proposed GI-TV mixed regularization algorithm has superior convergence and stability performance compared with the widely used l1-TV mixed regularization algorithm.

Non-intrusive soil carbon content quantification methods using machine learning algorithms:A comparison of microwave and millimeter wave radar sensors

Agricultural and forestry biomass can be converted to biochar through pyrolysis gasification,making it a significant carbon source for soil.Applying biochar to soil is a carbon-negative process that helps combat climate change,sustain soil biodiversity,and regulate water cycling.However,quantifying soil carbon content conventionally is time-consuming,labor-intensive,imprecise,and expensive,making it difficult to accurately measure in-field soil carbon’s effect on storage water and nutrients.To address this challenge,this paper for the first time,reports on extensive lab tests demonstrating non-intrusive methods for sensing soil carbon and related smart biochar applications,such as differentiating between biochar types from various biomass feedstock species,monitoring soil moisture,and biochar water retention capacity using portable microwave and millimeter wave sensors,and machine learning.These methods can be scaled up by deploying the sensor in-field on a mobility platform,either ground or aerial.The paper provides details on the materials,methods,machine learning workflow,and results of our investigations.The significance of this work lays the foundation for assessing carbon-negative technology applications,such as soil carbon content accounting.We validated our quantification method using supervised machine learning algorithms by collecting real soil mixed with known biochar contents in the field.The results show that the millimeter wave sensor achieves high sensing accuracy(up to 100%)with proper classifiers selected and outperforms the microwave sensor by approximately 10%–15%accuracy in sensing soil carbon content.

Artificial Intelligence Based Multi-Scenario mmWave Channel Modeling for Intelligent High-Speed Train Communications

A large amount of mobile data from growing high-speed train(HST)users makes intelligent HST communications enter the era of big data.The corresponding artificial intelligence(AI)based HST channel modeling becomes a trend.This paper provides AI based channel characteristic prediction and scenario classification model for millimeter wave(mmWave)HST communications.Firstly,the ray tracing method verified by measurement data is applied to reconstruct four representative HST scenarios.By setting the positions of transmitter(Tx),receiver(Rx),and other parameters,the multi-scenarios wireless channel big data is acquired.Then,based on the obtained channel database,radial basis function neural network(RBF-NN)and back propagation neural network(BP-NN)are trained for channel characteristic prediction and scenario classification.Finally,the channel characteristic prediction and scenario classification capabilities of the network are evaluated by calculating the root mean square error(RMSE).The results show that RBF-NN can generally achieve better performance than BP-NN,and is more applicable to prediction of HST scenarios.

An ISGW Filtering Antenna with Spurious Modes and Surface Wave Suppression for Millimeter Wave Communications

In this paper,an integrated substrate gap waveguide(ISGW)filtering antenna is proposed at millimeter wave band,whose surface wave and spurious modes are simultaneously suppressed.A secondorder filtering response is obtained through a coupling feeding scheme using one uniform impedance resonator(UIR)and two stepped-impedance resonators(SIRs).To increase the stopband width of the antenna,the spurious modes are suppressed by selecting the appropriate sizes of the ISGW unit cell.Furthermore,the ISGW is implemented to improve the radiation performance of the antenna by alleviating the propagation of surface wave.And an equivalent circuit is investigated to reveal the working principle of ISGW.To demonstrate this methodology,an ISGW filtering antenna operating at a center frequency of 25 GHz is designed,fabricated,and measured.The results show that the antenna achieves a stopband width of 1.6f0(center frequency),an out-of-band suppression level of 21 dB,and a peak realized gain of 8.5 dBi.

Cubature Kalman Filter Based Millimeter Wave Beam Tracking for OTFS Systems

In this paper,a Millimeter wave(mmWave)beam tracking problem is studied in orthogonal time frequency space(OTFS)systems.Considering the nonlinearity of beamforming and the constraints of existing Kalman-filtering based beam tracking schemes,we propose a novel Cubature Kalman Filter(CKF)framework tracking the channel state information(CSI)to manage the challenge of highspeed channel variation in single-user moving scene for OTFS systems.Aiming for low complexity for mobile settings,this paper trains only one beam pair to track a path to maintain the reliable communication link in the analog beamforming architecture.Simulation results show that our proposed method has better tracking performance to improve the accuracy of the estimated beam angle compared with prior work.

Radio Propagation and Wireless Coverage of LSAA-Based 5G Millimeter-Wave Mobile Communication Systems

Millimeter-wave(mm Wave) communications will be used in fifth-generation(5G) mobile communication systems, but they experience severe path loss and have high sensitivity to physical objects, leading to smaller cell radii and complicated network architectures. A coverage extension scheme using large-scale antenna arrays(LSAAs) has been suggested and theoretically proven to be cost-efficient in combination with ultradense small cell networks. To analyze and optimize the LSAA-based network deployments, a comprehensive survey of recent advances in statistical mmWave channel modeling is first presented in terms of channel parameter estimation, large-scale path loss models, and small-scale cluster models. Next, the measurement and modeling results at two 5G candidate mmWave bands(e.g., 28 GHz and 39 GHz) are reviewed and compared in several outdoor scenarios of interest, where the propagation characteristics make crucial contributions to wireless network designs. Finally, the coverage behaviors of systems employing a large number of antenna arrays are discussed, as well as some implications on future mmWave cellular network designs.

Quantized Hybrid Precoding Design for Millimeter-Wave Large-Scale MIMO Systems

Millimeter wave(mmWave) and large-scale multiple input multiple output(MIMO) are two emerging technologies in fifth-generation wireless communication systems. The power consumption and hardware cost of radio frequency(RF) chains increase exponentially with the bit resolution of analog-to-digital converters(ADCs) and digital-to-analog converters(DACs). One promising solution is to employ few RF chains with low-bit ADCs and DACs. In this paper, we consider mmWave large-scale MIMO systems with low bits DACs and ADCs. Leveraging on the Bussgang theorem and the additive quantization noise model(AQNM), a closed-form expression of the achievable rate is derived to show the effect of the ADCs? and DACs? resolution. Moreover, an orthogonal matching pursuit(OMP) based hybrid precoding algorithm is proposed to increase the achievable rate. Our results show that the impact of DACs is more pronounced than the impact of ADCs. Furthermore, 5-bit ADCs and DACs are sufficient at the transceiver to operate without a significant performance loss.

A Low Power,High Sensitivity SiGe HBT Static Frequency Divider up to 90 GHz for Millimeter-Wave Application

A layout and connection optimization for static frequency divider is presented. The layout optimization provides a new circle topology transistors placement and reasonable connection structure, which reduces the parasitic effectively and enables self-oscillation frequency enhancement. Besides, bandwidth enhancement techniques based on a center-tap capacitor in input balun design and inductive peaking in latch design are adopted to improve further high frequency performance with low power consumption. As a proof of concept, design of a divide-by-2 static frequency divider in 0.13 μm SiGe BiCMOS technology is reported. With single-ended input clock signal, the divider is measured to be operated from 40 to 90 GHz. Phase noise measurements of a 90 GHz input clock signal indicate ideal behavior with no measurable noise contribution from the divider. The divider followed by a buffer that can deliver more than-10 dBm output power, which is sufficient to drive succeeding stage. To the author's knowledge, the divider exhibits a competitive power dissipation and the highest FOM among silicon based frequency dividers that operating higher than 70 GHz.

User Association and Wireless Backhaul Bandwidth Allocation for 5G Heterogeneous Networks in the Millimeter-Wave Band

The user association and wireless backhaul bandwidth allocation for a two-tier heterogeneous network （HetNet） in the mil- limeter wave （mmWave） band is proposed in this article. The two-tier HetNet is built up with a macro base station （MBS） and several small cell SBSs, where the MBS is assumed to be equipped with large-scale antenna arrays but the SBSs only have single-antenna capa- bility and they rely on the wireless link to the MBS for backhaul. The sum of logarithmic user rate, which is established according to the result of multi-user Multiple Input Mul- tiple Output （MIMO） downlink employing Zero-Force Beamforming （ZFBF）, is chosen as the network utility for the objective func- tion. And a distributed optimization algorithm based on primal and dual decomposition is used to jointly optimize the user association variable xj,z and the wireless backhaul band- width factor α. Simulation results reveal that the distributed optimization algorithm jointly optimizing two variables outperforms the con- ventional SINR-based user association strate- gies.

Super-resolution processing of passive millimeter-wave images based on adaptive projected Landweber algorithm

Passive millimeter wave （PMMW） images inherently have the problem of poor resolution owing to limited aperture dimension. Thus, efficient post-processing is necessary to achieve resolution improvement. An adaptive projected Landweber （APL） super-resolution algorithm using a spectral correction procedure, which attempts to combine the strong points of all of the projected Landweber （PL） iteration and the adaptive relaxation parameter adjustment and the spectral correction method, is proposed. In the algorithm, the PL iterations are implemented as the main image restoration scheme and a spectral correction method is included in which the calculated spectrum within the passband is replaced by the known low frequency component. Then, the algorithm updates the relaxation parameter adaptively at each iteration. A qualitative evaluation of this algorithm is performed with simulated data as well as actual radiometer image captured by 91.5 GHz mechanically scanned radiometer. From experiments, it is found that the super-resolution algorithm obtains better results and enhances the resolution and has lower mean square error （MSE）. These constraints and adaptive character and spectral correction procedures speed up the convergence of the Landweber algorithm and reduce the ringing effects that are caused by regularizing the image restoration problem.

Super-resolution processing of passive millimeter-wave images based on conjugate-gradient algorithm

This paper designs a 3 mm radiometer and validate with experiments based on the principle of passive millimeter wave （PMMW） imaging. The poor spatial resolution, which is limited by antenna size, should be improved by post data processing. A conjugate-gradient （CG） algorithm is adopted to circumvent this drawback. Simulation and real data collected in laboratory environment are given, and the results show that the CG algorithm improves the spatial resolution and convergent rate. Further, it can reduce the ringing effects which are caused by regularizing the image restoration. Thus, the CG algorithm is easily implemented for PMMW imaging.

A Concise Model and Analysis for Heat-Induced Withdrawal Reflex Caused by Millimeter Wave Radiation

In this study, we consider the heat-induced withdrawal reflex caused by exposure to an electromagnetic beam. We propose a concise dose-response relation for predicting the occurrence of withdrawal reflex from a given spatial temperature profile. Our model is distilled from sub-step components in the ADT CHEETEH-E model developed at the Institute for Defense Analyses. Our model has only two parameters: the activation temperature of nociceptors and the critical threshold on the activated volume. When the spatial temperature profile is measurable, the two parameters can be determined from test data. We connect this dose-response relation to a temperature evolution model for electromagnetic heating. The resulting composite model governs the process from the electromagnetic beam deposited on the skin to the binary outcome of subject’s reflex response. We carry out non-dimensionalization in the time evolution model. The temperature solution of the non-dimensional system is the product of the applied power density and a parameter-free function. The effects of physical parameters are contained in non-dimensional time and depth. Scaling the physical temperature distribution into a parameter-free function greatly simplifies the analytical solution, and helps to pinpoint the effects of beam spot area and applied power density. With this formulation, we study the theoretical behaviors of the system, including the time of reflex, effect of heat conduction, biological latency in observed reflex, energy consumption by the time of reflex, and the strategy of selecting test conditions in experiments for the purpose of inferring model parameters from test data.

A millimeter and sub-millimeter wave frequency selective surface beamsplitter for geostationary orbit microwave radiometers

We report the design of three frequency selective surface （FSS） filters used on the FengYun-4 （FY-4） microwave satellite, which separate five-frequency bands in the frequency range of 50-429 GHz with the insertion loss less than 0.4 dB, and separation between adjacent channels more than 20 dB for either TE or TM incidence. Firstly, we briefly introduce the disadvantages of two types of FSS filter： waveguide-array FSS and printed FSS, which are commonly employed in the millimeter and sub-millimeter wave band. In order to meet the insertion loss requirement and specified spectral transmission response, we adopt a filter composed of two closely spaced freestanding metal plates, which con- tains an array of resonant ring slot elements. Computer simulation technology （CST） is used to optimize the structural dimensions of the resonant unit and interlayer separation. Numerical results show that these FSS filters exhibit trans- mission loss of less than 0.4 dB and separation between adjacent channels of more than 20 dB. Simulated transmission coefficients are in close agreement with the required specification, and even exceed the performance specifications.

Millimeter Wave and THz Propagation Channel Modeling for High-Data Rate Railway Connectivity--Status and Open Challenges

In the new era of railways, infrastructure, trains and travelers will be interconnected. In order to realize a seamless high-data rate wireless connectivity, up to dozens of GHz bandwidth is required. This motivates the exploration of the underutilized millimeter wave （mmWave） as well as the largely unexplored THz band. In this paper, we first identify relevant communication scenarios for railway applications. Then the specific challenges and estimates of the bandwidth requirements for high-data rate railway connec-tivity in these communication scenarios are described. Finally, we outline the major challenges on propagation channel modeling and provide a technical route for further studies.

Millimeter-Wave Absorption Properties of Thin Wave Absorber in Free Space with New Porous Carbon Material

In this paper, we focus on PHYTOPOROUS, a porous carbon material made entirely from plant-based ingredients, as a new broadband-wave absorber material that acts in the millimeter wave band. We created prototypes of thin rubber-sheet wave absorbers that contain porous carbon (PHYTOPOROUS) made from rice chaff and soybean hulls, which are both agricultural residue products that are generated in large quantities. We investigated the permittivity and reflectance characteristics of this material using the free-space time-domain method. The thin rubber-sheet wave absorber that contained PHYTOPOROUS made from soybean hulls exhibited a frequency band that was approximately 18 GHz wide and centered at 90 GHz. The return loss for this material was greater than −20 dB. This demonstrates that the material provides nearly constant reflection absorption over a wide frequency band.

Cell-type continuous electromagnetic radiation system generating millimeter waves for active denial system applications

The cell-type continuous electromagnetic radiation system is a demonstration device capable of generating high-power millimeter electromagnetic waves of a specific wavelength and observing their effects on living organisms.It irradiates a biological sample placed in a 30×30×50 cm^(3)cell with electromagnetic waves in the 3.15-mm-wavelength region(with an output of≥1 W)and analyzes the temperature change of the sample.A vacuum electronic device-based coupled-cavity backward-wave oscillator converts the electron energy of the electron beam into radiofrequency(RF)energy and radiates it to the target through an antenna,increasing the temperature through the absorption of RF energy in the skin.The system causes pain and ultimately reduces combat power.A cell-type continuous electromagnetic radiation system consisting of four parts—an electromagnetic-wave generator,a highvoltage power supply,a test cell,and a system controller—generates an RF signal of≥1 W in a continuous waveform at a 95-GHz center frequency,as well as a chemical solution with a dielectric constant similar to that of the skin of a living organism.An increase of 5°C lasting approximately 10 s was confirmed through an experiment.