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A simple and effective body-centric localization algorithm has been proposed in this paper using UWB wearable technology. The algorithm has been validated through measurement campaigns with a human subject volunteer in an indoor environment. The algorithm takes into account statistical channel parameter analysis, machine learning (ML) algorithms and time-of-arrival (TOA) based range estimation/data fusion techniques. Two channel parameters namely path loss magnitude and rms delay spread are proposed as classification features to be applied to the ML algorithm to accurately classify the off-body channel links into LOS, PNLOS and NLOS scenarios. Multi-class support vector machine (MC-SVM) classifier along with SMOTE algorithm to take into account class imbalance is applied with the channel classification accuracy of 98.63 %. Threshold based range estimation algorithms are applied in order to mitigate NLOS scenarios caused mainly due to the presence of the human subject. Results report human localization accuracy in 0.5-3 cm range using TDOA data fusion technique for target estimation. Further validation is presented considering wide range of Tx-Rx distance, presence of another obstruction between the Tx-Rx links and performance in different environment which shows the suitability of the proposed methodology.

Machine learning (ML) is playing an increasingly important role in processing large amounts of data generated by communication networks, since it can efficiently solve the problems of non-linearity and unstructured data. Recently, ML has been widely used in the processing of wireless channel data, as the noisy channel in real propagation environment is usually non-linear and unstructured. In this paper, a denoising method based on ML is presented. Two ML algorithms are used to classify and remove noise in channel impulse responses. Then, the results of the traditional noise threshold denoising are compared with ML denoising, and it is found that the denoising classifier using the bidirectional recurrent neural network has the better denoising performance. Finally, some channel parameters such as RMS delay spread are estimated based on measured channel data using different denoising methods. The results are evaluated and compared to explore the impact of denoising method on the extracted channel parameters.

In order to provide reliable and efficient connections between unmanned aerial vehicles (UAVs) and ground stations (GSs), realistic UAV-to-ground channel models are indispensable. In this article, we propose a novel 3-D nonstationary geometry-based stochastic model (GBSM) for UAV-to-ground multiple-input–multiple-output (MIMO) channels. Distinctive UAV-to-ground channel characteristics, such as time-domain nonstationarity, distinctions between different altitudes, spatial consistency, and 3-D arbitrary UAV movement trajectories, are taken into account. By adjusting parameter settings, the proposed channel model framework is sufficiently general to support multiple frequency bands and multiple scenarios, including millimeter wave (mmWave) and massive MIMO configurations. Statistical properties, including power delay profile (PDP), stationary interval, space–time correlation function (STCF), and root-mean-square (RMS) delay spread are derived and analyzed for different frequencies and scenarios. The accuracy of the proposed model is validated by comparing its statistical properties with corresponding available channel measurements. The proposed channel model will provide a fundamental support for the design, performance evaluation, and optimization of future UAV integrated sixth-generation (6G) wireless networks.

Industrial Internet of Things (IIoT) is an emerging area that fifth-generation (5G) mobile communication system penetrates industrial manufacturing applications. The indoor factory has larger space and there are a lot of metal machine tools distributed in it, which makes its radio propagation characteristics and corresponding channel models significantly different from those of the indoor office and indoor hotspot. To support the design and the evaluation of the IIoT techniques, the 3rd Generation Partnership Project (3GPP) released the first 5G IIoT standard model in October 2019. In this article, we give a detailed explanation of this IIoT model and compare it with other indoor models. First, we introduce the standardization of 3GPP IIoT channel model and its motivation. Second, four IIoT subscenarios, which are classified according to the clutter density and antenna height, are described. Third, the potential frequency bands of 5G IIoT are summarized. Fourth, the models of channel parameters, including the path loss and the line-of-sight (LOS) probability, the root mean-square (RMS) delay spread, and the angular spread, are given. Among them, the models of path loss and LOS probability take the antenna height and clutter density into consideration. The model of RMS delay spread changes from frequency-dependent to volume-dependent in order to catch the size variation of factories. Finally, two newly added key channel characteristics, dual mobility and absolute time of arrival, which help to describe the robot movement and positioning, are also presented.

Ultraviolet (UV) wireless communication has recently received much attention only for outdoor applications. Due to inherent nature of UV transmission, we believe that UV can also be considered for efficient and low-cost indoor communications. In this article, we present a novel UV indoor communication with an in-depth description of design implementation, channel modeling, and performance analysis. We consider a discrete Poisson channel with transmit power constraints. While focusing mainly on the development of a UV-based indoor communication, an indoor UV channel model is first proposed. Based on this, physical characteristics of the UV indoor channel using on–off keying modulation are analyzed with direct detection in terms of bit error rate, channel dc gain, and delay spread. As the proposed UV indoor communication exhibits some limitations, we provide a brief discussion on design implementation and challenges. From the performance analysis, it is found that the proposed UV indoor communication can provide ubiquitous link connectivity in indoor applications, while keeping network structure and management simple.

As a vital vertical industry empowered by the sixth-generation mobile communication system (6G), the vision of “smart rail mobility” requires a seamless wireless connectivity with the ultra high-data rate on the order of 100 Gbps or even more. This forms a strong driving force for exploiting the terahertz (THz) band where the available spectrum is massively abundant. In this paper, the smart rail mobility channel is characterized through ultra-wideband (UWB) channel sounding and ray tracing (RT) at 300 GHz band with an 8 GHz bandwidth in the five scenarios – Train-to-infrastructure (T2I), Inside station, Train-to-train (T2T), Infrastructure-to-infrastructure (I2I), and Intra-wagon. Corresponding channel characteristics such as path loss, shadow fading, Rician $K$ -factor, root-mean-square delay spread, azimuth/elevation angular spread of arrival/departure, and cross-polarization ratio are extracted and analyzed. Based on realistic channel information, the performance of THz communication is investigated in terms of channel capacity for all above five scenarios with various antenna patterns and weather conditions (except Intra-wagon) – sunny, rainy, and snowy. The results provide valuable insights into the system design and evaluation for THz communication enabled Smart Rail Mobility.

To meet the demands for the explosive growth of mobile data rates and scarcity of spectrum resources in the near future, the terahertz (THz) band has widely been regarded as a key enabler for the upcoming beyond fifth-generation (B5G) wireless communications. An accurate THz channel model is crucial for the design and deployment of the THz wireless communication systems. In this paper, a three-dimensional (3-D) dynamic indoor THz channel model is proposed by means of combining deterministic and stochastic modeling approaches. Clusters are randomly distributed in the indoor environment and each ray is characterized with consideration of molecular absorption and diffuse scattering. Moreover, we present the dynamic generation procedure of the channel impulse responses (CIRs). Statistical properties are investigated to indicate the non-stationarity and feasibility of the proposed model. Finally, by comparing with delay spread and K-factor results from the measurements, the utility of the proposed channel model is verified.

Vehicle-to-vehicle (V2V) wireless communications have many envisioned applications for ensuring traffic safety and for addressing traffic congestion. However, developing suitable communication systems and standards for this purpose requires developers to have accurate models for the V2V propagation channel. Likewise, the dynamic evolution of multipath components (MPCs) in V2V channels has not been well modeled in existing models. In this paper, we propose a geometry-based stochastic channel model for a lightly built-up urban environment and then parametrize the model from measurements. The MPCs are extracted based on a high-resolution parameter estimation; they are tracked and clustered through a joint algorithm. The identified clusters are classified as line-of-sight, reflections from static scatterers, reflections from mobile scatterers, multiple-bounce reflections, and diffuse scattering. Specifically, the multiple-bounce reflections are modeled as twin clusters that follow the COST 273/COST2100 approach. The paper gives a full parameterization of the channel model and supplies a step-by-step implementation recipe. We verify the model by comparing two second-order statistics, i.e., the root-mean-square (RMS) delay spread and the angular spreads of arrival/departure derived from the channel model, to the results obtained directly from the measurements. Furthermore, we also identify several key factors that strongly impact the synthetic channel performance.

In order to realize the vision of “smart rail mobility,” a seamless high-data rate wireless connectivity with up to dozens of gigahertz bandwidth will be required. This forms a strong motivation for exploring the underutilized millimeter wave (mmWave) and sub-mmWave bands. In this article, the wireless channel in one “smart rail mobility” scenario—the intrawagon scenario—is characterized through ultrawideband (UWB) channel sounding and ray tracing (RT) at mmWave and sub-mmWave bands. To begin with, a series of horizontal directional scan-sounding measurements are performed inside a real high-speed train wagon at 60 and 300 GHz frequency bands with a bandwidth of 8 GHz. Correspondingly, the channel characteristics such as Rician $K$ -factor, root-mean-square (rms) delay spread (DS), azimuth spread of arrival, and azimuth spread of departure are extracted and analyzed. Based on the measurements, a self-developed RT simulator is validated through the reconstruction of the three-dimensional wagon model and the calibration of the electromagnetic (EM) properties of the main materials. This gives the chance to physically interpret the measurement results and characterize the intrawagon mmWave and sub-mmWave channels more comprehensively through extensive RT simulations.

Designing a spectrally efficient wireless channel requires a comprehensive understanding of its time and frequency varying characteristics, making it a stochastic medium of communication. These characteristics become more challenging to cater at the receiving terminal in a multipath transmission. This is because of the fading effect and Doppler shift of the transmitted frequency, specifically in cellular mobile radio systems and vehicle to vehicle communications. This paper presents the modeling, simulation, and then characterization of a cellular mobile radio multipath channel over its time and frequency varying fading gain. For this purpose, a discrete-time Finite Impulse Response (FIR) type filter of such a channel is designed, modeled, and simulated using time and frequency varying characteristics of the received signal. The simulated channel response is further analyzed in terms of coherence bandwidth, coherence time, delay spread, Doppler spread, and symbol time.

Small cells are low-power and low-range radio access nodes that can be used to increase network capacity in reduced areas with high traffic demand and to provide coverage to small isolated zones. As their number is expected to be very high, connecting them to the aggregation point in a cost-efficient manner is a key challenge, and there is consensus that none of the current technologies is valid for all scenarios. Since lamp-posts are one of the most convenient locations for outdoor small cells, this work analyzes the use of power line communications (PLC) over outdoor public lighting networks (OPLN) as a backhaul technology for outdoor small cell deployments. To this end, the characteristics of the PLC channels established in OPLN are firstly assessed. The analysis combines noise measurements performed in existing OPLN and channel responses obtained from a multiconductor transmission line (MTL) model. The attenuation, delay spread and spatial correlation of the multiple-input multiple-output (MIMO) channels are investigated and their influence in the physical layer parameters of PLC systems is discussed. Afterward, the performance achieved by state-of-the-art PLC systems is assessed. To this end, estimations obtained by means of simulations and measurements taken in actual networks are included. Data throughput achieved by PLC systems based on the ITU-T G.hn standard, as well as the expected improvements obtained by $3\times 3$ MIMO systems, are given. Results indicate that PLC can be an interesting technology for coverage-driven small cell deployments with backhaul length shorter than 150 m, offering throughput values similar to existing Sub-6 GHz wireless solutions in non-line-of-sight (NLOS) conditions and wired ones like G.fast.

Nowadays, there is a need for wireless communications to operate over a variety of scenarios, including high mobility multiple-input multiple-output (MIMO) applications, that bring along a challenging problem. In channels where Doppler spread and delay spread are high, complexity of coherent detectors and pilot overhead are both raised. This work proposes a non-coherent reception technique, easily scalable to any number of antennas for the MIMO case, using simple coding and decoding structures which take advantage of channel diversity addition in three domains: time, frequency and space, by using virtual trajectories along with space time block-coding. Coarse analytics on the system performance in terms of the bit error rate are computed using Chernoff Boundaries as a function of the channel diversity and the order of the differential modulation, validating the efficiency of the proposed receiver.

Future automation and control units for advanced driver assistance systems (ADAS) will exchange sensor and kinematic data with nearby vehicles using wireless communication links to improve traffic safety. In this paper we present an accurate real-time system-level simulation for multi-vehicle communication scenarios to support the development and test of connected ADAS systems. The physical and data-link layer are abstracted and provide the frame error rate (FER) to a network simulator. The FER is strongly affected by the non-stationary doubly dispersive fading process of the vehicular radio communication channel. We use a geometry-based stochastic channel model (GSCM) to enable a simplified but still accurate representation of the non-stationary vehicular fading process. The propagation path parameters of the GSCM are used to efficiently compute the time-variant condensed radio channel parameters per stationarity region of each communication link during run-time. Five condensed radio channel parameters mainly determine the FER forming a parameter vector: path loss, root mean square delay spread, Doppler bandwidth, K -factor, and line-of-sight Doppler shift. We measure the FER for a pre-defined set of discrete grid points of the parameter vector using a channel emulator and a given transmitter-receiver modem pair. The FER data is stored in a table and looked up during run-time of the real-time system-level simulation. We validate our methodology using empirical measurement data from a street crossing scenarios demonstrating a close match in terms of FER between simulation and measurement.

The millimeter-wave (mm-wave) frequency band is projected to play a critical role in next-generation wireless networks owing to its large available bandwidth. Despite the theoretical potential for high data throughput, the mm-wave frequency faces numerous challenges—including severe path loss and high penetration loss. Therefore, a reliable understanding of channel propagation characteristics is required for the development of accurate and simple indoor communication systems. In this study, we conducted measurement campaigns with unique transmitter- receiver combinations using horn and tracking antennas, at 3.7 and 28 GHz in an indoor corridor environment on the $10^{th}$ floor of an IT building and the $3^{rd}$ floor of the main building of Chosun University, Gwangju, South Korea, and the details are presented herein. In both line-of-sight and non-line-of-sight scenarios, the large-scale path losses, and small-scale channel statistics, such as root mean square delay spread, and number of clusters, were obtained using the measurement results in a waveguide structure indoor corridor environment. We have proposed alternate methodologies beyond classical channel modeling to improve path loss models using artificial neural network (ANN) techniques—to alleviate channel complexity and avoid the time-consuming measurement process. The presented regression successfully assists the prediction of the path loss model in a new operating environment using measurement data from a specific scenario. The validated results suggest that the ANN large-scale path loss model used in this study outperforms the close-in reference distance and floating-intercept (alpha-beta) models. Additionally, our result shows that the number of time clusters follows an Erlang distribution.

Human body communications (HBCs), employing the human body as a signal transmission medium, can provide efficient and intuitive methods to form a network in the body. This article presents a comprehensive study for a highly reliable HBC system, including body channel modeling, transceiver design, and performance evaluation through implementation, in consideration of practical sensor network environments for wearable and implantable devices applicable to healthcare and biosignal acquisition. Body channel characteristics based on capacitive couplings, such as root mean square delay spread and mean path gain (MPG), were explored by measuring the body impulse responses under 12 experimental conditions, determined by the variation in body postures and device locations between the wrist and positions assumed under the scalp through a customized experimental setup with micropig-derived biomembranes (MBMs) used for wrapping the devices to emulate an implantable environment. The proposed transceiver design for digital transmission, including a preamble structure and signal modulation method supporting a maximum data rate of 1 Mb/s, was verified through the performance evaluations conducted for examining the frame detection probability and bit error rate (BER) in the body channel model at multiple operating frequencies of 32, 42, and 64 MHz. The proposed system reliability was demonstrated by the achievement of a BER of below ${4.7\,\times \, }{10}^{-8}$ through battery-powered implemented devices with dimensions of ${30\times 30 }\,\,{\text {mm}}^{2}$ , comprising a digital signal processing module (DSPM) for signal generation and detection processes, and an analog front-end module (AFEM) for recovering the received signal from signal deterioration by severe path loss and time-dispersive effect in the body channel.

With the dense deployment and wide applications of the Internet of Things in railway systems, the location-based security access control scheme is becoming increasingly important. In this study, the received signal strength (RSS) and channel state information (CSI) in railway communications are measured by AR9344 network interface card. Then, based on the measurement data, the authors propose trajectory-based, neural network-based (NN-based) and ray tracing-based (RT-based) localisation algorithms, serving for location-based security access control. Specifically, the trajectory-based algorithm combined with trajectory simulation, movement detection and dynamic time warping algorithms, realises passengers enter/exit pattern detection. The NN-based algorithm leverages back-propagation network (BPN) and constructs training sets with measurement-based RSS and CSI, finishing accurate localisation. Besides, they evaluate the algorithm performance under different layers of BPN. RT-based localisation algorithm combines measurement data and simulation analysis, leveraging simulated-based multiple-input multiple-output received power and delay spread to realise lightweight localisation. After evaluation, the RT-based algorithm can achieve the highest accuracy of localisation, up to 99.9% and is designed to be straightforward for integration with commercial access points and deployment to railway communications.

This paper presents a high performance circularly polarized multiple input multiple output microstrip patch antenna which is suitable for current high data rate requirements. Circular polarization has been achieved by dual feeding the signals in phase quadrature to the patch antenna. A polarization independent metamaterial has been designed. The designed metamaterial is used to enhance the gain of the antenna and used as a superstrate of this patch antenna. Using metamaterial superstrate, a gain as high as 13.6 dBi with a bandwidth of 15.4% has been achieved at 11 GHz. The structure has been fabricated and the simulated results are in good agreement with the measured results. Circular polarized antenna also reduces the delay spread due to multipath environment and provides high latency.

Human body communications (HBCs) have recently emerged as an innovative alternative to the current radio frequency communications for realizing wireless body area networks (WBANs) using the human body as a transmission channel without wired or wireless connections. This article addresses the provision of reliable modeling of the human body as a passage of the electric signal delivery based on the impulse response measurement through the proposal of a measurement setup and signal processing techniques applicable to wearable devices for healthcare and biosignal acquisition. In the experiments, customized impulse signals were applied to the body using battery-powered devices isolated to the earth ground for the operating environments of wearable devices. The impulse responses passed through the body were measured by considering 52 measurement conditions determined by the device locations from the head to ankle and the body postures. Body channel transfer functions (BCTFs) for the respective conditions were derived by an adaptive filter approach using an iterative algorithm to minimize the mean squared error between the measured and modeled impulse responses. The channel analysis parameters, such as mean path loss, root-mean-square delay spread, and mean and maximum excess delays, were analyzed based on the measured body impulse responses. In addition, the practical bit-error-rate performance for HBC based on the BCTFs reproducing intersymbol interference effects caused by the delay spreads of the body channels was explored to verify communication reliability in terms of the transmitter structures adopting digital transmission, sorts of human body channels, data rates, and operating frequencies.

Air-to-ground (AG) communications have attracted much attention for future advanced wireless communications. Unmanned aerial vehicle, as a critical enabler in AG communications, can be operated in various environments, such as over-water, hilly, and built-up environments. A better understanding of radio channels in various scenarios can immensely facilitate the deployment and design of wireless systems. Thus, in this letter, wideband characterizations of AG channels are performed based on the multienvironment channel measurements, where the center frequency is set to 6.5 GHz with the bandwidth of 500 MHz, which provides high delay resolution to capture significant multipath. Two key channel parameters, Rician K-factor and root-mean-square (rms) delay spread, are used as metrics to characterize AG channels. The positive Rician K-factor indicates the line-of-sight (LOS)-dominated characteristic of the AG channel. The discrepancy of the rms delay spread shows the obvious influence of multipaths from building on channel delay characteristics.

Stable and practical reception of visible light communication (VLC) signals at mobile devices necessitates optoelectronic receivers with large detection areas to attain wide field-of-view (FOV) as well as robustness against blockage. However, large detection (or aperture) area reduces the effective bandwidth of VLC receivers. We design and prototype a VLC receiver with multi-photodetector array followed by a multi-stage amplifier, capable of attaining high-speed data rates for white phosphorous LED light. The receiver array can be arranged conformal to the surface shape of mobile devices. We test the VLC system's performance under vibrations, characterize delay spread arising from movements and wide FOV of the receiver, design multi-symbol detection techniques based on time and spatial reception diversity, and evaluate the performance with real data transmissions.

This paper proposes a multi-feature fusion based propagation scene recognition model for high-speed railway (HSR) channels and presents the channel relevance analysis of HSR scenes. Extensive field measurement data in typical HSR scenes, including rural, station, suburban and multi-link scenes, are collected with the assist of railway long-term evolution (LTE) networks. The datasets of space-time-frequency channel features, involving Ricean K-factor, root mean square delay spread, Doppler spread, and angle spread, are generated for the model training and testing as well as the relevance analysis. The proposed model merges a weighted score fusion scheme into the deep neural network (DNN) in order to adaptively determine the optimal weights for each feature stream. This weighted score fusion based DNN model is implemented and evaluated in terms of accuracy, confusion matrix, F-score, and receiver operating characteristic (ROC) curve, which exhibits better performance than other machine learning models like random forest, support vector machine (SVM), $k$ -nearest neighbor (KNN), and weighted KNN. In addition, the channel relevance of HSR scenes is analyzed from perspectives of high-dimensional distribution distance and joint correlation of multiple features. Two metrics, Wasserstein distance and correlation matrix collinearity, are used in the analysis. Statistical results are provided, which reveals the relatively strong channel relevance between the multi-link and suburban scenes.

To guarantee shipping safety, it is crucial to build a reliable wireless communication network. This study presents characteristic analysis of shipping wireless channel based on measurements. The authors conduct five channel measurements for two important water mobile communications, covering inland river and sea scenarios. Channel characteristics, e.g. power delay profile, amplitude distribution, delay spread and shadow fading, are extracted and compared for the two scenarios. It is found that the main difference between the them lies in more obstacles and scatterers in inland river propagation environment. The results show that more obstacles and scatterers can result in richer multipath effect and larger shadow fading decorrelation distance. A triple Gaussian mixture distribution (TGMD) is proposed to characterize the wireless channel with LOS, obstructed LOS and non-LOS situations in the practical propagation. To verify the effectiveness of TGMD, the goodness of fit between measurement and analysis results in terms of Rician K-factor, root mean square (RMS) delay spread and RMS Doppler spread is calculated. Furthermore, the cross-correlation among shadow fading, Rician K-factor and RMS delay spread are studied. Larger cross-correlation can be found in inland river and sea than vehicular communication due to the open propagation environment.

PurposeWireless communication channel provides a wide area of applications in the field of communication, distributed sensor network and so on. The prominence of the wireless communication channel is because of its robust nature and the sustainability for the precise ranging and the localization. The precision and accuracy of the wireless communication channel largely depend on the localization. The development of the wireless communication channel with improved benefits needs the accurate channel model.Design/methodology/approachThis paper characterizes the tangential path loss model in the WINNER based wireless communication channel model. The measurements taken in the WINNER channel model are compared with the tangential path loss characterized WINNER Channel model.FindingsThe model operates well over the varying antenna orientations, measurement condition and the propagation condition. The proposed tangential path loss model is performing well over the various outdoor scenarios.Originality/valueThe proposed characterization shows change in the small-scale parameters (SSP), such as power, delay, angle of arrival and angle of departure as well as the large-scale parameters (LSP), such as RMS delay spread, shadowing, path loss and Ricean factor associated with the model.

This paper aims at simulating the electromagnetic environment inside an enclosed chamber with high conductivity and complicated structure, validating the feasibility of high-speed wireless communications inside aircraft cabins. It first built a characteristic model which represents the propagation scenario of an aircraft component, then simulated the propagation of 77 GHz millimeter wave source through ray tracing method and obtained wireless channel model including power distribution characteristics and delay spread model. Simulated results demonstrated a feature of standing wave distribution inside the structure, and a relatively large attenuation for millimeter wave propagation in such environment. Delay spread is normally less than 10 ns, with a typical characteristic of clustering. It proved that wireless communication at millimeter wave band in such configurations requires necessary channel coding technology to guarantee data transmission rate and system reliability.

Terahertz (THz) communication is a research hotspot in the future communication field. However, limited by the power of the THz source and various particles in the air, indoor THz wireless communication with short distance transmission has practical research value. Due to the strong directivity of THz beam, the line of sight (LOS) path occupies most of the energy of the signal. However, when the LOS path is blocked, the not line of sight (NLOS) path can be used as a supplement to ensure the stability of the communication link. In this paper, a 3D transmission model combining LOS path, primary reflection path and secondary reflection path was established by ray tracing method for indoor laboratory scenes with high demand for communication rate. The carrier frequency range is 220-330GHz. Through the results of power delay profile (PDP) and power angle profile (PAP) at the receiver, the correlation characteristics of important channel parameters such as Rician K-factor, root mean square (RMS) delay spread with different frequency points and different paths are analyzed. The results show that all the channel parameters are strongly correlated with frequency and transmission distance. These theoretical results lay a foundation for the subsequent communication experiments in real experimental condition.

Frequency offset transmit reference (FoTR)—a noncoherent spread spectrum technique—is considered in dense multipath fading environments, in the context of wideband communication. The interplay between system parameters and propagation effects is investigated. Analytical relations between key design parameters and the channel delay spread are derived, which provide a framework for determining reasonable system parameters that optimize the performance. An approximated closed-form expression for the outage probability is also obtained, which is shown to be fairly accurate for low outage probabilities. It is shown that FoTR suffers significantly from noise-enhancement, but, is nonetheless, robust against frequency-selective fading. A large value of frequency offset can significantly deteriorate the performance, particularly in environments with large channel delay spreads. This restricts the maximum data rate as well as the multiple-access capability of the scheme. Despite the limitations, FoTR can be a useful communication scheme for low data rate sensor networks deployed in dense multipath environments, particularly where the design demands a simple receiver and a low outage probability.

Owing to its several advantages over other wireless schemes, visible light communication (VLC) shall be at the forefront of optical wireless communication technology. However, due to multipath reflections and spatial distribution of light-emitting diode (LED) transmitters, there is an inherent delay spread in the VLC channels. We perform a comprehensive quantitative study on the effect of several practical factors like LED semi-angle, wall reflectivity, number of reflections, number of LED panels, room size, and user locations on the channel delay parameters, namely RMS delay spread and coherence bandwidth of the channel. We present the detailed derivation of the multipath VLC channel model and incorporate the effect of inter-symbol interference in bit error rate (BER) performance of the multipath VLC system. We analyze the average BER of the system under different practical scenarios and determine the penalty in signal to noise ratio entailed by a change in the system parameters mentioned above. We conclude that it is sufficient to model up to three reflections in the VLC channel to emulate the effect of multipath propagation on the channel characterization and BER analysis of the system. The results and analyses presented herein provide critical insights into the effect of multipath reflections in indoor VLC links, particularly the BER performance and channel delay characteristics. We also provide some key recommendations for the design of practical VLC systems by outlining the data rates that can be served under different system configurations.

Terahertz (THz) wireless data centers can provide low-latency networks and dynamic scalability that are vital for the next-generation cloud computing infrastructure. The knowledge of THz propagation characteristics in a data center environment is essential to the development of novel THz communication systems. However, a comprehensive characterization and modeling of THz propagation channels, which includes various obstructions in a data center is not available. This paper presents results from a THz channel measurement campaign conducted in a data center environment. Various propagation scenarios such as line-of-sight (LoS) link, non-LoS (NLoS) link using existing materials in a data center to redirect the beam, and obstructed-LoS (OLoS), -NLoS (ONLoS) links with common objects in data centers (cables and server racks’ mesh doors) serving as obstruction were investigated. Propagation channel parameters such as pathloss and root-mean-squared (RMS) delay spread were analyzed in the aforementioned scenarios while cluster-based modeling was implemented for some scenarios. The proposed model for THz propagation in a data center environment was validated with the measured data. The average inter-arrival time of clusters ( $1/\Lambda $ ) and rays ( $1/\lambda $ ) are estimated as 4.4 ns and 0.24 ns, respectively. We find that local scattering objects such as server-rack frames/pillars can be used to assist the NLoS type of link, and that cooling airflow in the data center has a negligible impact on THz propagation. Power cables and mesh doors of the server racks can cause additional attenuation of about 20 dB and 6 dB, respectively. Cluster model and other characterization results provided in this work are pertinent to THz wireless system design for data center environments.

International audience; We address channel characterization and modeling for medical wireless body-area networks (WBANs) based on the optical wireless technology. We focus on the intra-WBAN communication links, i.e., between a set of medical sensors and a coordination node, placed on the patient's body. We consider a realistic mobility model, e.g., inside a hospital room, which takes into account the effect of shadowing due to body parts movements and the variations of the underlying channels. To take into account the global and local user mobility, we consider a dynamic model based on a three-dimensional animation of a walk cycle, as well as walk trajectories based on an improved random way-point mobility model. Then, Monte Carlo ray-tracing simulations are performed to obtain the channel impulse responses for different link configurations at different instants of the walk scenarios. We then derive first-and second-order statistics of the channel parameters such as the channel DC gain, delay spread, and coherence time, and furthermore, propose best fit statistical models to describe the distribution of these parameters for a general scenario.

This paper introduces the design of a 41 GHz mmWave system dedicated for high-speed train communications between train and trackside. A novel frame structure is provided for the acquirement of channel state information as well as for the transmission of user data. Based on the proposed design principles, a system prototype has been established and employed in extensive measurement campaigns. The channel measurement results obtained from a recent measurement campaign under high-speed mobile conditions where the relative velocity between the transmitter and the receiver reaches 170 km/h are presented in this paper. Channel characteristics, including the power delay profile, RMS delay spread, fade depth, small-scale fading statistics, Ricean K factor, autocovariance function, coherence time, level crossing rate, and average fading duration are analyzed in detail. Moreover, the bit-error-rate performance for the proposed system under the channel whose characteristics are obtained from the measurements is simulated. Based on the simulation results, the key parameters for the proposed frame structure are determined to improve the system's robustness in fast varying channels and in the mean time achieve high spectrum efficiency. Besides, the throughput of the system prototype recorded during the transmission of three high-definition video streams is presented. Finally, the outage probability as a function of transmission distance and path loss exponent is estimated based on the channel measurement results.

Characterization and modeling of massive multiple-input multiple-output (MIMO) channel has been one of the research hotspots in the field of wireless communications. One important feature of the massive MIMO channel is the spatial non-stationarity. To statistically model the spatial non-stationary massive MIMO channels, a cluster-based channel model is proposed in this paper. The model incorporates both inter- and intra-cluster properties and the cluster evolution over the large-scale array. A hybrid data processing scheme is applied to extract the multipath components (MPCs) and clustering the MPCs over a large-scale antenna array. The global angular spread, cluster angular spread, and cluster delay spread are modeled with log-normal distributions. Observed cluster length and MPC length within clusters, which are introduced to describe the cluster existence over the array and MPCs existence within the cluster, respectively, are statistically modeled with the exponential distributions. Moreover, both the cluster and MPC arrival intervals, which are used, respectively, to describe the cluster occurrence position on the array and MPC occurrence position within the cluster, can be statistically modeled with the uniform distributions. Finally, the model implementation is validated by comparing with the different channel performance metrics between measurements and simulations.

This paper presents the propagation channel characteristics of a digital TV single-frequency network (SFN) obtained by carrying out field measurements using two synchronized transmitters. The measurements are performed at 31 reception points using both a directive reception antenna, which is typical of fixed reception scenarios, and an omnidirectional antenna, which is used to receive mobile signals. The characteristic parameters of the channel are obtained, including the average delay, the root mean square (RMS) delay spread, and the Rician K-factor, which are important for the design of SFN systems. An empirical expression is obtained for the prediction of the RMS delay spread as a function of the K factor and the distances to the transmission antennas.

It is essential to capture joint channel characteristics in cooperative multi-link systems in order to make realistic performance assessments and channel modeling. This paper investigates the joint statistical properties of large-scale parameters (LSPs) in high-speed railway (HSR) multi-link propagation scenarios. A dedicated long-term evolution (LTE) network-based multi-link channel sounding system is established, which breaks the constraints in HSR measurements and supports simultaneous time–frequency–space measurements for multiple links. To guarantee the effectiveness of multi-link measurements, a time-delay-window-based partition method is used to identify channel impulse responses from different links. Based on the processed multi-link data, the statistics of LSPs, involving shadow fading, K-factor, delay spread, and azimuth spread, is estimated and compared for the two links in a plain viaduct scenario on HSR. Then, auto-correlations and two kinds of cross correlations, such as intra-link correlation and inter-link correlation in the measured scenario, are calculated and analyzed. In addition, a simulation model of joint statistical characteristics for LSPs is proposed and validated according to the obtained measurement results. These results can be used to assess the actual performance of cooperative multi-link systems on HSR, and the proposed model can provide realistic inputs for channel models in HSR multi-link propagation scenarios.

The unmanned aerial vehicles (UAVs) have been widely applied in various fields due to their advantages like high mobility and low cost. Reliable communication is the premise to ensure the connectivity between UAV nodes. To provide reasonable references for the design, deployment, and operation of UAV communication systems, the precise prediction of radio channel parameters are required. In this study, the authors propose prediction methods for path loss and delay spread in air-to-ground millimetre-wave channels based on machine learning. Random forest and K-nearest-neighbours are the algorithms employed in the methods. Then, a feature selection scheme is proposed to further improve the prediction accuracy and generalisation performance of the machine-learning-based methods. Generally, machine learning algorithms require massive data for training purpose. However, measuring data is time-consuming and costly, especially when the scenario or frequency changes. Therefore, transfer learning methods are introduced to predict path loss with limited data. The proposed methods for path loss prediction are compared to Okumura-Hata and COST-231 Hata models. The lognormal distribution is the contrast model in delay spread prediction. Based on the data generated by ray-tracing software, the new methods have a smaller root mean square errors than contrast models.

We propose a multiple-access (MA) method in the uplink of a orthogonal time frequency space modulation-based wireless communication system where the channel has high Doppler and delay spread. Each user terminal (UT) is allocated delay-Doppler (DD) resource blocks which are spaced at equal intervals in the DD domain. This limits the corresponding time-frequency (TF) transmit signal to a sub-domain of the entire TF domain. By allocating non-overlapping portions to the TF transmit signal of different UTs, multi-user interference (MUI) is avoided. The proposed MA method is analytically shown to be MUI free and therefore has a significantly higher sum spectral efficiency when compared to other methods proposed in literature which utilize guard bands in the DD domain to reduce MUI.

Ultra-Reliable Low Latency Communications (URLLC), a key area of 5G, is designed to support dependable and time-sensitive communications. Yet when addressing Quality of Service (QoS) requirements, traditional 5G does not consider delay spread an interference metric reported back to the base station (as delay spread approaches the duration of the cyclic prefix, the channel capacity decreases due to inter-symbol interference). As IoT equipment may lack the processing capability to mitigate delay spread’s effects, not accounting for delay spread in reported channel condition metrics can result in resources not being assigned in an efficient manner.For out-of-coverage remote devices, such as in smart factories and Industrial Internet of Things [1] (IIoT), Non-Orthogonal Multiple Access (NOMA) small cells or Layer 3 User Equipment (UE) to Network (UE-to-Network) relays must be relied on to extend the network to localized areas. Due to power domain NOMA’s Resource Block (RB) multiplexing, in a multi-level NOMA system the impact of delay spread on the set of viable resource allocations becomes more evident as the interference generated can render 2nd level RBs unusable. Consequently, the likelihood of achieving URLLC’s low End-to-End Radio Latency requirements becomes more difficult in multi-level NOMA systems.In this paper we investigate a tractable methodology to mitigate the impact of delay spread and improve the End-to-End latency of IIoT devices via 5G NOMA multicast flow numerology migration for URLLC NOMA relays used in a non-public network. We derive a theoretically optimal integer linear programming (ILP) resource allocation algorithm and present a tractable low-complexity approximation algorithm, 5G Multicast Flow Migration over NOMA (5GMFMN). In terms of end-to-end radio latency, our evaluation shows 5GMFMN yields results similar to ILP, and both algorithms can yield over 4× improvement over traditional 5G at a max delay spread of 2.1µs.

Industrial automation is one of the key application scenarios of the fifth generation (5G) wireless communication network. The high requirements of industrial communication systems for latency and reliability lead to the need for industrial channel models to support massive multiple-input multiple-output (MIMO) and millimeter wave communication. In addition, due to the complex environment, huge communication equipment, and numerous metal scatterers, industrial channels have special rich dense multipath components (DMCs). Considering these characteristics, a novel three dimensional (3D) non-stationary geometry-based stochastic model (GBSM) for industrial automation wireless channel is proposed in this paper. Channel characteristics including the transfer function, time-varying space-time-frequency correlation function (STFCF), and root mean square (RMS) delay spread, model parameters including delay scaling factor and power decay factor are studied and analyzed. Besides, according to the indoor factory scenario classification of the 3rd Generation Partnership Project (3GPP) TR 38.901, two sub-scenarios considering the clutter density are simulated. Simulated cumulative distribution functions (CDFs) of RMS delay spread show a good consistency with the measurement data.

Wireless communication continuously gains in importance in the context of industrial automation due to its role as an enabling factor for flexibility. The number of mobile, wirelessly communicating devices in modern production facilities steadily rises. Knowledge about the signal propagation is central to the planning and maintenance of these wireless networks. Precise models enable users to supply sufficient communication capabilities to the factory of the future.Measurements of Power Delay Profiles (PDPs) were performed at the frequencies of 2.1,2.6,3.8 and 5.1GHz for three different scenarios in a modern and running production facility. The results are analyzed by means of multi-path components, delay spread and path loss. The results are compared to previous measurements. Thereby, further insights in propagation conditions in industrial scenarios are gained.

The path loss and wideband channel models for urban and suburban scenarios play a crucial role since they provide RF power estimations that allow the wireless network’s optimized design and performance. Although several propagation models can be found in the literature, it is always important to consider the particular characteristics of urbanization in each region where a 5G technology is deployed. In this contribution, we present narrowband and wideband measurements and channel modeling for at 2.4 GHz band in urban and suburban regions in Rio de Janeiro, Brazil. The results include the path loss dependence with distance, the average delay and the statistical distributions of the root mean square (RMS) delay spread, the number of multipath components, and multipath amplitudes.

This paper presents results of wideband channel measurements at 39 GHz and 70 GHz in a typical indoor office environment. Measurements were carried out using Durham University's multi-band frequency modulated continuous wave channel sounder. The propagation characteristics at different angular orientations are estimated and compared for both frequency bands. The effects of the antenna pattern on the propagation channel parameters such as the average power delay profile, root mean square delay spread, and angular spread, are analyzed. The results show similar propagation properties for both measured bands.

Safety driving is an essential requirement in the intelligent transportation system on expressways and urban roads. Particularly, identifying the presence of the visual connection between vehicle and vehicle, i.e., the non-line-of-sight (NLOS) identification, is important for many sensor systems on board such as optical radar, wireless positioning system and so forth. Usually NLOS identification can be done by checking the presence of the line-of-sight propagation path in wireless radio systems. In this paper, we present a study on the non-line-of-sight identification based on measurement data collected on expressways and urban intersections. Features of channel impulse response including skewness, kurtosis, root-mean-square delay spread, peak-to-average ratio and Rician-K factor are considered, and the identification accuracy of different features in different scenarios is presented. The results reveal that the skewness, kurtosis and peak-to-average ratio features are less affected by the environment, while the root-mean-square delay spread feature is obviously affected by the environment. Furthermore, it is found that the Rician-K factor is not suitable for identifying non-line-of-sight propagation in these two scenarios.

The emerging technology terahertz (THz) communication is envisioned to provide high-data-rate wireless links. The wide swath of the unused and unexplored spectrum makes it a significant candidate for the sixth-generation mobile communications (6G). In this paper, a series of channel measurements are conducted on an optical table to characterize the wireless channel on a desktop, which is an important use case for THz communications. The measured frequency range is from 75 GHz to 400 GHz, which has covered the main band planed for 6G within THz band. Eight frequency bands with ultrawide bandwidth are measured dividually in order to explore how the channel characteristics change along with frequency. By comparison of the power delay profiles (PDPs) between measurements and ray-tracing (RT) simulations, the measured multipaths can be physically interpreted. Moreover, with the aid of this self-developed RT simulator, electromagnetic (EM) property of the painted metal (which is the relevant material generating multi-order reflected paths in the measurements) is extracted, finding that the imaginary part of the relative permittivity is considerably small compared to the perfect conductor because of the painting. Last but not least, the key channel parameters, in terms of root-mean-square (RMS) delay spread and Ricain K-factor, are analyzed and modeled with frequency. In the future, with the help of RT simulations, the angular characteristics will be supplemented to complete the three-dimensional (3D) channel data towards a thorough understanding of channel characteristics for THz communications in the 6G era.

The primary synchronization signal (PSS) and secondary synchronization signal (SSS) transmitted in the 5G are used to perform a synchronization procedure. This paper proposes an effective residual frequency offset (RFO) estimation method in a 5G new radio (NR) system. The proposed RFO estimation method applies two branches correlation using PSS and SSS sequence. This paper shows via the simulation results that the inherent property of the PSS and SSS signals is exploited for a robust RFO estimation at various delay spread of wireless environments. It is demonstrated that the proposed RFO estimation scheme is efficient for the 5G NR system.

International audience; In this paper, we investigate the performance of vehicular visible light communications based on the radiation patterns of different commercial taillights (TLs) using non-sequential ray tracing simulations. Our simulation results indicate a significant variation in the path loss compared with Lambertian model. Based on the ray tracing results, we propose a new path loss model as a function of the propagation distance considering the asymmetrical radiation pattern of TLs. We use this model to derive the attainable transmission distance. We further present the delay spread for various vehicular communication scenarios to demonstrate the effect of neighboring vehicles.

In order to design and evaluate the performance of low Earth orbit (LEO) satellite communication systems for the sixth generation (6G) mobile communications, an accurate channel model is essential. In this paper, a three-dimensional (3D) geometry-based stochastic model (GBSM) for 6G LEO satellite communication channels is established. The proposed channel model extends the quasi deterministic radio channel generator (QuaDRiGa) model and takes unique property of LEO satellite communication, such as Faraday rotation effect into account. The paper presents a single-bounce channel model, taking the spatial consistency of parameters into account and supporting simultaneous movements of the transmitter (Tx) and receiver (Rx). Finally, simulation experiments are conducted under different environments, center frequencies, and heights of satellites. Based on the proposed model, we analyze statistical properties of the channel including time autocorrelation function and delay spread (DS), which are in accordance with theoretical analysis and verify the correctness of the proposed model. Additionally, simulation results prove that parameters mentioned earlier have a considerable influence on channel characteristics and can help with guiding the design of communication systems.

In traditional 5G latency-driven assignment methodologies, a radio carrier’s numerology is typically fixed for any given QoS flow, as directed by the QoS requirements. Unfortunately, a drawback to 5G’s radio carrier numerology assignment approach is that it does not account for the impact of multi-path/delay spread. As such 5G is unable to efficiently utilize the allocated radio spectrum in high delay spread radio environments, thus potentially limiting both massive Machine Type Communication (mMTC) and ultra Reliable Low Latency Communication’s (uRLLC) ability to meet each data flow’s Quality of Service (QoS) requirements; low latency flows are more sensitive to high delay spread. When considering power-domain NOMA resource allocation, the impact of delay spread can only be partially mitigated. In this research work we derive an optimal QoS to 5G radio carrier numerology mapping methodology for NOMA-enabled 5G Heterogeneous groupcast networks, subject to the constraints imposed by the UEs and UE-to-Network Relay. Compared to legacy multicast methodologies, our methodology can achieve up to a $$4.7\times $$ higher resource block capacity while minimizing each resource block’s latency deviation from its original latency requirements, i.e., compared to legacy methodologies, our methodology reduces QoS flow latency while minimizing resource block latency deviation.

The millimeter-wave (mmWave) is expected to deliver a huge bandwidth to address the future demands for higher data rate transmissions. However, one of the major challenges in the mmWave band is the increase in signal loss as the operating frequency increases. This has attracted several research interests both from academia and the industry for indoor and outdoor mmWave operations. This paper focuses on the works that have been carried out in the study of the mmWave channel measurement in indoor environments. A survey of the measurement techniques, prominent path loss models, analysis of path loss and delay spread for mmWave in different indoor environments is presented. This covers the mmWave frequencies from 28 GHz to 100 GHz that have been considered in the last two decades. In addition, the possible future trends for the mmWave indoor propagation studies and measurements have been discussed. These include the critical indoor environment, the roles of artificial intelligence, channel characterization for indoor devices, reconfigurable intelligent surfaces, and mmWave for 6G systems. This survey can help engineers and researchers to plan, design, and optimize reliable 5G wireless indoor networks. It will also motivate the researchers and engineering communities towards finding a better outcome in the future trends of the mmWave indoor wireless network for 6G systems and beyond.

For a long time, the development of maritime communication has been restricted by the low data rate, high-latency and high cost of the current communication systems. The upgrade of new generation mobile communication technologies is attracting more and more attention to conduct a shore-based broadband mobile communication network with high-latency and high reliability to serve the maritime industries. This paper presents a solution by means of building a ship-to-infrastructure (S2I) and a ship-to-ship (S2S) wireless communication networks for an offshore region. We characterize the S2I and S2S channels at 5.9 GHz band based on the channel measurements in realistic environments. The channel characteristics, including power delay profile, delay spread, propagation path loss, are extracted and analyzed. In view of the difference between marine and terrestrial communications, we analyze the influencing factors of the offshore water, including effective reflection, divergence and shadowing from the water surface, and diffraction loss caused by the earth curvature. We also predict the power coverage range and the channel capacity for S2I and S2S wireless communications. Finally, the communication performance is evaluated according to the channel measurement and characterization analysis. The research results can be a reference for the construction of maritime communication networks.

The radio wave is the carrier that transmits information in wireless communications. It propagates across space through a complex and dynamic mechanism. However, the radio waves are invisible, which makes it hard to design wireless communication systems. This demonstration presents a system architecture and implementation via virtual reality (VR) that can make people open the "eyes" to see the radio waves, and provide a novel method of using the radio waves designing and optimizing wireless communication systems. Users can see how the radio waves propagate in a 3D view. Furthermore, channel impulse responses (CIRs) and channel fading properties, e.g., path loss and delay spread, can be derived and visualized through the virtual interface. Also, this demo enables users to investigate the performance of base station (BS) deployment and hybrid beamforming (HBF) algorithms via VR. In a nutshell, this demo is helpful to feel, understand, and use the radio waves to improve the efficiency of wireless communication technologies and systems.

Ultraviolet (UV) wireless is very suitable for local area Non-line of sight(NLOS) dedicated covert communication. Overcoming the path loss and delay spread from NLOS channel is a critical mission for the UV NLOS transmitter. In the first part of this paper, the main recent short distance line of sight (LOS) and long distance NLOS UV communication transmitters are reviewed. Next, “UV NLOS acquisition tracking pointing (ATP)” is introduced. Then, “UV high speed modulation technology”, “high-power UV source” and etc. are analyzed and summarized. The prospect of “High repetition rate high power UV pulse modulation” and “High power sub-millisecond UV pulse OFDM modulation” is put forward in the end.