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To deal with the explosive growth of mobile traffic, millimeter-wave (mmWave) communications with abundant bandwidth resources have been applied to vehicular networks. As mmWave signal is sensitive to blockage, we introduce the unmanned aerial vehicle (UAV)-aided two-way relaying system for vehicular connection enhancement and coverage expansion. How to improve transmission efficiency and to reduce latency time in such a dynamic scenario is a challenging problem. In this paper, we formulate the joint optimization problem of relay selection and transmission scheduling, aiming to reduce transmission time while meeting the throughput requirements. To solve this problem, two schemes are proposed. The first one is the random relay selection with concurrent scheduling (RCS), a low-complexity algorithm implemented in two steps. The second one is the joint relay selection with dynamic scheduling (JRDS), which fully avoids relay contentions and exploits potential concurrent ability, to obtain further performance enhancement over RCS. Through extensive simulations under different environments with various flow numbers and vehicle speeds, we demonstrate that both RCS and JRDS schemes outperform the existing schemes significantly in terms of transmission time and network throughput. We also analyze the impact of threshold selection on achievable performance., Comment: 13 pages, 9 figures, IEEE TVT

We report on a novel weakly-coupled 6-LP-mode fiber that features a nanopore-assisted step-index core with double-cladding profile. The purpose of this fiber design is to alleviate modes coupling and bend sensitivity, thus simplifies the multiple-input multiple-output (MIMO) process and the environmental requirements in which the fiber is used. Through numerical simulations, we show that the minimum effective index difference (Δfleff) of larger than 1.8*10-3 among all LP-mode over C and L band can be achieved by a simple nanopore with 170 nm radius in the center of the core. Furthermore, the dependences of both bending loss and chromatic dispersion on fiber structures are investigated by the finite element method (FEM) to show the good broadband performance. The proposed fiber targets applications in simpler MIMO space division multiplexing (SDM) systems such as data center and short-reach large-capacity transmission.

With the emerging demands of new communication services, the contradiction between capacity demand and spectrum shortage of railway communication systems becomes more severe. How to provide broadband communication services has become the key goal of future smart high-speed railway (HSR) systems. Millimeter wave (mm-wave) frequency band has abundant spectrum resources and can provide communication services with large bandwidth. However, due to the high-speed of the train as well as the complexity and dynamics of environments, the communication link may be blocked randomly for a short time and will also lead to frequent handovers. In this paper, we adopt the promising intelligent reflecting surface (IRS) technology for a mm-wave HSR communication system. In order to improve system capacity, IRS is deployed to improve reflection transmission links, and optimization algorithms are designed for transceiver beamforming and IRS phase shift. In addition, given the specificity of the HSR scenario, we also formulate the average system ergodic capacity maximization problem and obtain upper bound on the average system ergodic capacity with statistical channel state information (CSI). Through extensive simulations, we verify that the proposed scheme performs significantly better than the other two baseline schemes in terms of average system throughput and average system ergodic capacity.

This two-part paper investigates the application of artificial intelligence (AI) and, in particular, machine learning (ML) to the study of wireless propagation channels. In Part I of this article, we introduced AI and ML and provided a comprehensive survey on ML-enabled channel characterization and antenna-channel optimization, and in this part (Part II), we review the state-of-the-art literature on scenario identification and channel modeling here. In particular, the key ideas of ML for scenario identification and channel modeling/prediction are presented, and the widely used ML methods for propagation scenario identification and channel modeling and prediction are analyzed and compared. Based on the state of the art, the future challenges of AI-/ML-based channel data processing techniques are given as well.

Herbal weight loss drugs are becoming more widely used in the fight against obesity, but ineffective regulation of these products have resulted in harmful additives. These products may contain adulterants such as sibutramine hydrochloride that may result in serious adverse health events including death. This work established a color precipitation reaction-based rapid screening method for illegal adulteration of sibutramine hydrochloride in natural herbal medicines (NHM) and dietary supplements (DS). While a variety of chromatography- and electrophoresis-based systems have been reported to measure this analyte, they generally suffer from high costs, complicated sample preparation, and a costly analytical infrastructure. In contrast, we present a simple, handheld kit to assay for sibutramine. The performance metrics of this tool include an average detection time of approximately 3 minutes, which is markedly shorter than conventional methods (HPLC or HPLC-MS, etc.), a detection limit of 0.1 mg per aliquot, and an accuracy of 99.02% (n = 820). More strikingly, the sensitivity is 100% (n = 278), and the specificity is 98.52% (n = 542). The rapid test kit developed from this screening method was evaluated by FDA. In summary, this screening method is a rapid, simple, and low-cost tool for the detection of sibutramine in NHM and DS with superior selectivity and sensitivity. For these reasons, this method is especially suitable for underdeveloped settings because it can be employed onsite without any instrumentation. In addition, this approach could rapidly exclude most of the negative samples to boost efficiency in large-scale samples assay. If necessary, positive samples can undergo further alternate testing methods to confirm the positive results of sibutramine hydrochloride content.

The Internet of Vehicles, previously referred to as Vehicular Ad Hoc Networks (VANETs), will be a collection of mobile ad hoc networks for vehicular communications to improve driving safety and traffic efficiency. Major categories include vehicle-to-vehicle (V2V) communications and vehicle-to-infrastructure (V2I) communications. Collectively these (and future categories) can be termed V2X communications. These two categories entail a variety of communication channels, network topologies, vehicle densities and communication scenarios, and in response to this, IEEE has released the IEEE 802.11p and IEEE 1609 protocols for VANETs. With the global commercial application of Long Term Evolution (LTE) mobile communication systems, LTE based vehicular (LTE-V) networks have been shown to offer advantages in V2I communications, coverage, high mobility and complicated communication scenarios. Therefore, in the 5th generation’s (5G) mobile communication networks, the 3GPP is discussing V2V communications as a device-to-device (D2D) communication application. As is well known, in high mobility scenarios, the wireless channel is rapidly time- varying, Doppler shifts and spreads can be much larger than in cellular, network topology can change quickly, and switching among base stations and vehicles is more frequent. All this presents formidable challenges to realizing reliable communications with low latency in 5G LTE-V systems.

As one of the most important candidate technologies for the fifth-generation wireless communication systems, massive MIMO technology has been widely studied recently because of the significant improvements it can provide in terms of spectrum efficiency and power efficiency. As the foundation of wireless communication, research on propagation characteristics for massive MIMO channels is of primary importance. This paper investigates the characteristics for massive MIMO channels in an indoor hall scenario at 6-GHz. Channel measurements were conducted with a bandwidth of 200 MHz in both line of sight (LOS) and non-LOS (NLOS) conditions. The statistical parameters in the delay domain were extracted to show the spatial variation along the large-scale antenna array. Based on the measured data, the spatial variation is first defined, and then characterized by using the spatial power delay profile correlation coefficient and spatial channel gain correlation matrix collinearity, and the quasi-stationarity region along the massive MIMO array is estimated. Furthermore, by using the space-alternating generalized expectation-maximization algorithm, the multipath components are extracted and classified according to the propagation environments, which provide more insights to the spatial variation of massive MIMO channels. Finally, the characteristics of the extracted angular parameters are investigated and the fluctuations are modeled, where the spatial variation phenomenon was clearly observed over the large-scale antenna array. The quasi-stationarity distance of the variation was found to range from 2.5 to 32.5 cm, and the LOS case differs from the NLOS case at 6 GHz. These results and discussions are useful for analysis and future modeling for massive MIMO channels, and may contribute to future definitions of channel spatial consistency.

Ambient backscatter, an emerging green communication technology, has aroused great interest from both academia and industry. One open problem for ambient backscatter communication (AmBC) systems is channel estimation for a massive-antenna reader. In this paper, we focus on channel estimation problem in AmBC systems with uniform linear array (ULA) at the reader which consists of large number of antennas. We first design a two-step method to jointly estimate channel gains and direction of arrivals (DoAs), and then refine the estimates through angular rotation. Additionally, Cramer-Rao lower bounds (CRLBs) are derived for both the modulus of the channel gain and the DoA estimates. Simulations are then provided to validate the analysis, and to show the efficiency of the proposed approach., 5 figures, submitted to IEEE Transactions on Vehicular Technology, 29 March, 2019

This paper evaluates the performances of channel emulation algorithms in the multiprobe anechoic chamber (MPAC) by using plane wave (PW) and spherical vector wave (SVW) theories. Channel emulation in MPAC enables the over-the-air (OTA) testing of performances of wireless devices under realistic propagation scenarios, through setting excitation voltages of probes and utilizing the polarized radiation patterns, locations, and orientations of probe antennas to emulate desired fields in test zone. Accurate emulation of radio wave propagation in target scenario guarantees that the device under test (DUT) be assessed fairly in the laboratory. Dynamic multipath scenario and orthogonal polarization can be emulated by exciting the multiple probes in such a way that the total fields from probes resemble the target impinging field in the test zone. The excitation voltages can be either calculated by PW or SVW theories. Despite the fact that PW and SVW are mathematically equal in the far field, different treatments on rotation and translation of waves as well as different linear equations used in two methods result in different computed voltages, hence, different emulated fields. The emulation performances of the two methods with different MPAC setups (e.g., test zone size, probe number, probe sphere radius, and probe directivity) are investigated. Both scenarios of the 2-D field emulation with the 2-D probe configuration and the 3-D (or 2.5-D) field emulation with the 3-D probe configuration are discussed, and instructions on how to wisely use the emulation algorithm are provided.

In this paper, the Gaussian mixture model (GMM) is introduced to the channel multipath clustering. In the GMM field, the expectation-maximization (EM) algorithm is usually utilized to estimate the model parameters. However, the EM widely converges into local optimization. To address this issue, a hybrid differential evolution (DE) and EM (DE-EM) algorithms are proposed in this paper. To be specific, the DE is employed to initialize the GMM parameters. Then, the parameters are estimated with the EM algorithm. Thanks to the global searching ability of DE, the proposed hybrid DE-EM algorithm is more likely to obtain the global optimization. Simulations demonstrate that our proposed DE-EM clustering algorithm can significantly improve the clustering performance.

In this paper, a novel target recognition based clustering algorithm is proposed for time-varying channels. Power angle spectrum (PAS) is extracted from measurement data by using Bartlett beamformer. Then the clusters in the PAS are separated from the background by using the proposed algorithm, where the amplitude distribution of the elements in the PAS is considered. Moreover, morphology operations are applied to further divide the clusters which are connected to each other. It is found that, the dominating clusters in both line-of-sight (LoS) and non-line-of-sight (NLoS) environments can be well recognized by the proposed algorithm with low computation cost. By using the proposed algorithm, the dynamic changes of the clusters in real-time channel measurement can be clearly observed, without using any high-resolution parameter estimation.

We analyze the nonwide-sense-stationarity (non-WSS) of vehicle-to-vehicle (V2V) radio channels using three metrics: 1) the correlation matrix distance (CMD); 2) the wideband spectral divergence (SD); and 3) the shadow fading correlation. The analysis is based on measurements carried out at 5.3 GHz using a ${\mathbf 30} \times {\mathbf 4}$ MIMO system in suburban, urban, and underground parking areas. Several factors such as the existence of a line-of-sight (LOS), the speed of cars, and the antenna array size and configuration are considered in the analysis of non-WSS. It is found that quasi-stationarity region ranges from 3 to 80 m in different V2V scenarios, and is strongly affected by the above factors. Based on the comparison of the equivalent quasi-stationarity region size estimated by the three metrics, it is suggested to use SD and shadowing correlation metrics for systems with small electrical array apertures and to use CMD metric only for arrays with large electrical apertures.

In reverberation chambers, the multipath channels with different delay characteristics can be generated by loading the chamber with different amounts of absorbers. This paper investigates the impacts of absorber loadings on the delay characteristics based on realistic measurements. An efficient method for estimating the root-mean-square (rms) delay spread in the chamber is presented. Furthermore, it is found that the chamber loadings also significantly affect the quality of a digitally modulated signal and the corresponding modulation quality measurements are performed.

In this letter, the fading statistics of wireless channels in high-speed railway cutting scenarios are characterized based on measurements. A multiple scattering model called second-order scattering fading (SOSF) is used to model the small-scale fading considering the influence of cuttings and bridges. The SOSF model can offer the possibility of analytical estimation for different fading severities via a simple moment-based estimator. It is demonstrated that Ricean fading is the dominant fading distribution in cutting scenarios, but deep fades also occur. The fading process is therefore described by a hidden Markov model, which is validated statistically by measurement data.

Discovering clusters from a dataset with different shapes, densities, and scales is a known challenging problem in data clustering. In this paper, we propose the RElative COre MErge (RECOME) clustering algorithm. The core of RECOME is a novel density measure, i.e., Relative $K$ nearest Neighbor Kernel Density (RNKD). RECOME identifies core objects with unit RNKD, and {partitions} non-core objects into atom clusters by successively following higher-density neighbor relations toward core objects. Core objects and their corresponding atom clusters are then merged through $\alpha$-reachable paths on a KNN graph. We discover that the number of clusters computed by RECOME is a step function of the $\alpha$ parameter with jump discontinuity on a small collection of values. A fast jump discontinuity discovery (FJDD) method is proposed based on graph theory. RECOME is evaluated on both synthetic datasets and real datasets. Experimental results indicate that RECOME is able to discover clusters with different shapes, densities, and scales. It outperforms six baseline methods on both synthetic datasets and real datasets. Moreover, FJDD is shown to be effective to extract the jump discontinuity set of parameter $\alpha$ for all tested datasets, which can ease the task of data exploration and parameter tuning., Comment: The manuscript has been updated to the latest version. The official version please see https://www.sciencedirect.com/science/article/pii/S0020025518300215 The code has been released in https://github.com/gyla1993/RECOME-A-new-density-based-clustering-algorithm-using-relative-KNN-kernel-density

This paper describes an extensive propagation channel measurement campaign in a warehouse environment for line-of-sight (LOS) and nonline-of-sight (NLOS) scenarios. The measurement setup employs a vector network analyzer operating in the 2–8-GHz frequency band combined with an $8 \times 8$ virtual multiple-input multiple-output (MIMO) antenna array. We develop a comprehensive statistical propagation channel model based on high-resolution extraction of multipath components and subsequent spatiotemporal clustering analysis. The intracluster direction of departure (DoD), direction of arrival (DoA), and the time of arrival (ToA) are independent, both for the LOS and NLOS scenarios. The intracluster DoD and DoA can be approximated by the Laplace distribution, and the intracluster ToA can be approximated by an exponential mixture distribution. The intercluster analysis, however, shows a dependency between the cluster DoD, DoA, and ToA. To capture this dependency, we separately model the clusters caused by single and multiple bounce scattering along the aisles in the warehouse. The intercluster DoD distribution follows a Laplace distribution, while the cluster DoA conditioned on the DoD is approximated by a Gaussian mixture distribution. The model was validated using the capacity and delay-spread values.

The indoor radio channels at 15 GHz are investigated based on measurements. The large- and small-scale fading behaviors as well as the delay dispersion characteristics are discussed. It is found that the large-scale fading, RiceanK-factor, and delay spread can be described by log-normal distributions. Furthermore, both autocorrelation and cross correlation properties of the above parameters are analyzed and modeled. These parameters characterize fading and delay behaviors as well as their mutual dependency and can be used as empirical values for future wireless system design and simulation in 15 GHz short-range indoor channels.

Vehicle-to-vehicle (V2V) communications have received a lot of attention due to their numerous applications in traffic safety. The design, testing, and improvement of the V2V system hinge critically on the understanding of the propagation channels. An important feature of the V2V channel is the time variance. To statistically model the time-variant V2V channels, a dynamic wideband directional channel model is proposed in this paper, based on measurements conducted at 5.3 GHz in suburban, urban, and underground parking environments. The model incorporates both angular and delay domain properties and the dynamic evolution of multipath components (MPCs). The correlation matrix distance is used to determine the size of local wide-sense stationary (WSS) region. Within each WSS time window, MPCs are extracted using the Bartlett beamformer. A multipath distance-based tracking algorithm is used to identify the “birth” and “death” of such paths over different stationarity regions, and the lifetime of MPC is modeled with a truncated Gaussian distribution. Distributions for the number of multipaths and their positions are statistically modeled. Within each path lifetime, the initial power is found to depend on the excess delay, and a linear polynomial function is used to model the variations within the lifetime. In addition, a Nakagami distribution is suggested to describe the fading behavior. Finally, the model implementation is validated by comparison of second-order statistics between measurements and simulations.

This paper presents a detailed description of a propagation channel measurement campaign performed in a warehouse environment and provide a comprehensive channel model for this environment. Using a vector network analyzer (VNA), we explored both Line-of-sight(LOS) and Non-Line-of-sight (NLOS) scenarios over a 2-8 GHz frequency range. We extracted both small-scale and large-scale channel parameters such as distance-dependent pathloss exponent (n), frequency-dependent pathloss exponent (k), shadowing variance, and amplitude fading statistics of the channel. We also provide the clustering analysis of the channel impulse responses by using a modified Saleh-Valenzuela approach. Our model is validated by comparing the distributions of the root-mean-square (RMS) delay spread obtained from our model and measurement data, respectively. The model developed can be used for realistic performance evaluations of ultrawideband (UWB) communications and localization systems in warehouse environments.

Radio wave propagation scene partitioning is necessary for wireless channel modeling. As far as we know, there are no standards of scene partitioning for high-speed rail (HSR) scenarios, and therefore we propose the radio wave propagation scene partitioning scheme for HSR scenarios in this paper. Based on our measurements along the Wuhan-Guangzhou HSR, Zhengzhou-Xian passenger-dedicated line, Shijiazhuang-Taiyuan passenger-dedicated line, and Beijing-Tianjin intercity line in China, whose operation speeds are above 300 km/h, and based on the investigations on Beijing South Railway Station, Zhengzhou Railway Station, Wuhan Railway Station, Changsha Railway Station, Xian North Railway Station, Shijiazhuang North Railway Station, Taiyuan Railway Station, and Tianjin Railway Station, we obtain an overview of HSR propagation channels and record many valuable measurement data for HSR scenarios. On the basis of these measurements and investigations, we partitioned the HSR scene into twelve scenarios. Further work on theoretical analysis based on radio wave propagation mechanisms, such as reflection and diffraction, may lead us to develop the standard of radio wave propagation scene partitioning for HSR. Our work can also be used as a basis for the wireless channel modeling and the selection of some key techniques for HSR systems.

Along with the increase of the use of working frequencies in advanced radio communication systems, the near-region inside tunnels lengthens considerably and even occupies the whole propagation cell or the entire length of some short tunnels. This paper analytically models the propagation mechanisms and their dividing point in the near-region of arbitrary cross-sectional tunnels for the first time. To begin with, the propagation losses owing to the free space mechanism and the multimode waveguide mechanism are modeled, respectively. Then, by conjunctively employing the propagation theory and the three-dimensional solid geometry, the paper presents a general model for the dividing point between two propagation mechanisms. It is worthy to mention that this model can be applied in arbitrary cross-sectional tunnels. Furthermore, the general dividing point model is specified in rectangular, circular, and arched tunnels, respectively. Five groups of measurements are used to justify the model in different tunnels at different frequencies. Finally, in order to facilitate the use of the model, simplified analytical solutions for the dividing point in five specific application situations are derived. The results in this paper could help deepen the insight into the propagation mechanisms in tunnels.

The delay caused by the reflected ray in broadband communication has a great influence on the communications in subway tunnel. This paper presents measurements taken in subway tunnels at 2.4 GHz, with 5 MHz bandwidth. According to propagation characteristics of tunnel, the measurements were carried out with a frequency domain channel sounding technique, in three typical scenarios: line of sight (LOS), Non-line-of-sight (NLOS) and far line of sight (FLOS), which lead to different delay distributions. Firstly IFFT was chosen to get channel impulse response (CIR) h(t) from measured three-dimensional transfer functions. Power delay profile (PDP) was investigated to give an overview of broadband channel model. Thereafter, a long delay caused by the obturation of tunnel is observed and investigated in all the scenarios. The measurements show that the reflection can be greatly remained by the tunnel, which leads to long delay cluster where the reflection, but direct ray, makes the main contribution for radio wave propagation. Four important parameters: distribution of whole PDP power, first peak arriving time, reflection cluster duration and PDP power distribution of reflection cluster were studied to give a detailed description of long delay characteristic in tunnel. This can be used to ensure high capacity communication in tunnels.