Propagation Characteristics of Suburban Environments Using Hybrid Ray-Tracing Simulation

Comparisons of outdoor Urban Microcell (UMi) large-scale path loss models, root mean square (RMS) delay spreads (DS), angular spreads (AS), and the number of spatial beams for extensive measurements performed at 28, 38, 73, and 142 GHz are presented in this letter. Measurement campaigns were conducted from 2011–2020 in downtown Austin, Texas, Manhattan (New York City), and Brooklyn, New York with communication ranges up to 930 m. Key similarities and differences in outdoor wireless channels are observed when comparing the channel statistics across a wide range of frequencies from millimeter-wave to sub-THz bands. Path loss exponents (PLEs) are remarkably similar over all measured frequencies, when referenced to the first meter free space path loss, and the RMS DS and AS decrease as frequency increases. The similar PLEs from millimeter-wave to THz frequencies imply that spacing between cellular base stations will not have to change as carrier frequencies increase towards THz, since wider bandwidth channels at sub-THz or THz carrier frequencies will cover similar distances because antenna gains increase quadratically with increasing frequency when the physical antenna area remain constant.

Channel measurement is the most direct and accurate method to analyze the characteristics of wireless channel. In this paper, four channel measurements with different transmitter antenna (Tx) heights of 2 m, 3 m, 5.5 m and 8 m were conducted in an urban micro-cell (UMi) scenario at 3.7 GHz. The measurements include line-of-sight (LOS) and non-line-of-sight (NLOS) propagation. The transmitter of the measuring system consisting of a vector signal transceiver (VST), a high speed switch, a power amplifier (PA) and a planar antenna array (PLA). While the receiver is composed of a VST, a high speed switch, a low noise amplifier (LNA) and a uniform circular antenna array (UCA). Statistical results and comparative analysis are presented, including power delay profiles (PDPs), pathloss (PL), root mean square (RMS) delay spread (DS), elevation/azimuth of arrival (EOA/AOA) and corresponding elevation/azimuth RMS spread of arrival (ESA/ASA). The alpha-beta-gamma (ABG) model and close-in (CI) free space reference distance model are adopted. We use multiple signal classification (MUSIC) algorithm to estimate the EOA /AOA of the channel and analyzed the variation of relevant EAS/ASA. It can be seen from the results that the pathloss exponent decreases with the increasing of the Rx heights. The delay spread, on the contrary, increases as the antenna heights increase. The ASA decreases with the antenna goes higher and ESA has an opposite trend.

This paper analyzes channel characteristics of millimeter-wave (mm-wave) at 39 GHz in indoor environments based on channel measurements in a conference room and a lobby. Statistical results of channel large-scale fading characteristics including path loss (PL), shadow fading (SF) and small-scale fading characteristics like K-factor, root mean square (RMS) delay spread (DS) and RMS angular spread (AS) are presented. Furthermore, effects of different environments on the channel characteristics are investigated. In addition, differences between our measurement-based channel model parameters and those of the 3GPP channel model are discussed. The comparative analysis results reveal that channel characteristics are highly related with the measured environments; a complex environment with abundant reflectors has large RMS DS and RMS AS but small K-factor due to rich scattering.

Sub-1 GHz bands have been used for many years and now some of them will be reallocated for new applications, including the fifth generation (5G) wireless communication systems and beyond, Internet of Things (IoT), smart grid, etc. As the well-known path-loss (PL) models are mainly applicable in 2-6-GHz frequency range, a new channel measurement campaign is needed to study the propagation characteristics at sub-1 GHz bands. In this article, we conduct fixed-to-mobile wideband channel measurements at 400-600-MHz bands in urban and suburban scenarios using the time domain channel sounder. As the interference and noise signals are severe, the transmitted waveform is carefully designed to enlarge the system dynamic range. Meanwhile, ray tracing simulation is applied to construct the measurement environments and do the mutual verification with measurement results. The two-slope PL model and lognormal shadowing fading model are proposed for large-scale fading channel modeling. The root mean square (RMS) delay spread (DS), number of paths, and diffraction characteristics are also analyzed. The results will have great importance for the coming new applications at sub-1 GHz bands.

In this paper, an outdoor massive MIMO (Multiple-Input and Multiple-Output) system with $40\times 40$ planer array is simulated based on the SBR (Shooting and Bouncing Ray) method. The propagation characteristics, including PAP (Power Angle Profile), receive power, delay spread and PDP (Power Delay Profile), are studied in both LoS (line-of-sight) and NLoS (non-line-of-sight) links. The near-field effect is also discussed.

This paper presents wideband indoor channel measurements in three of the millimeter wave (mmWave) bands for the fifth generation (5G) and beyond 5G (B5G) wireless systems. Measurements were conducted at the Ka‐band (36–41 GHz) and V‐band (50–75 GHz) in office and factory/industrial environments, using Durham University's custom‐designed channel sounder. Recently, several channel measurements at different mmWave bands have been reported in various indoor environments. However, few studies have explored the impact of the processing bandwidth (BW) on the estimated channel parameters. Therefore, the aim of this paper is to investigate the effects of the analysis BW on different propagation channel characteristics, such as power delay profile, root mean square delay spread, Rician K‐factor, coherence BW (), and path loss. These wideband channel parameters are measured and estimated with a BW of 0.5, 1, 1.5, and 2 GHz. The results are presented for both line‐of‐sight and non‐line‐of‐sight scenarios.

The industrial scenario is indispensable for ubiquitous 6G coverage, which demands hyper-reliable and low-latency communication for full automation, control, and operation. To meet these demands, it is widely believed that it is necessary to introduce not only the conventional sub-6 GHz bands but also high-frequency technologies, such as millimeter wave (mmWave), terahertz (THz), and visible light bands. In this paper, we conduct a channel characterization and comparison in the industrial scenario from the sub-6 GHz to visible light bands. The channel characteristics, including the path loss (PL), root mean square (RMS) delay spread (DS), and angle spread (AS), were analyzed with respect to the frequency dependence and the distance dependence. On the one hand, the visible light band exhibited significant differences in channel characteristics compared to the electronic wave band. Due to the line-of-sight transmission of VLC, the visible light band had a higher path loss, and the path loss exponent reached 3.84. Due to the Lambertian radiation pattern, which has a wide range of reflection angles, the AS of the visible light band was much larger than that of the electronic wave band, which were 1.73 and 0.80 for the visible light and THz bands, respectively. On the other hand, the blockage effect of the metal instruments in the industrial scenario will greatly affect the channel characteristics. As the transceiver distance grows large, signals from both sides of the receiver will be blocked by metal instruments, resulting in a decreasing trend in the RMS DS for the electronic wave band. Moreover, the statistical characteristics of the channel properties were modeled and compared with the 3GPP TR 38.901 standard. It was found that the height of the receiver caused the difference between the proposed model and the 3GPP model and needs to be taken into account when modeling. Furthermore, we extended the 3GPP model to the THz and VLC bands and provided the statistical parameters of the channel characteristics for all frequency bands. This study can provide insights for the evaluation and standardization of multi-frequency communication technology in the industrial scenario.

Intravehicular wireless sensor network (IVWSN) is a cutting edge research topic that delivers cost reduction, assembly, and maintenance efficiency by removing the wiring harnesses within the vehicle and enables the integration of new sensors into the locations inside a vehicle where cable connection is not possible. Providing energy efficiency through the low-duty-cycle operation and high reliability by exploiting the large bandwidth, ultrawideband (UWB) has been determined to be the most appropriate technology for IVWSNs. We investigate the UWB channel model for IVWSNs within the engine compartment of a vehicle by collecting an extensive amount of data for 19 × 19 links for different types and conditions of the vehicle. These include a Fiat Linea with engine off, Fiat Linea with engine on, and Peugeot Bipper with engine off. The path-loss exponent is estimated to be around 3.5 without exhibiting much variation when the engine is turned on and for different types of vehicles. The power variation around the expected path loss has lognormal distribution with zero mean and standard deviation in the range of [5.5, 6.3] dB for different types of vehicles with almost no variation when the engine of the same vehicle is turned on. The clustering phenomenon in the power delay profile (PDP) is well represented by a modified Saleh-Valenzuela (SV) model. The interarrival times of the clusters are modeled using a Weibull distribution. The cluster-amplitude and ray-amplitude decay functions are represented with a dual-slope linear model with breakpoint around 26.6 and 5.5 ns, respectively. The parameters of the Weibull distribution and these dual-slope linear models do not vary significantly for different types and conditions of the vehicle. The variations of the observed PDPs around the SV model is well modeled by independent normal random variables with zero mean and with a variance independent of the delay bin, and the type and condition of the vehicle. We propose a simulation model for the UWB channel within the engine compartment based on these findings and validate it by comparing the received energy and root mean square (RMS) delay spread of the generated and observed PDPs.

In this paper, the application of AI and machine learning (ML) to the study of wireless propagation channels is investigated in two parts: first, an artificial neural network model is used to improve path loss prediction, and then, a pattern recognition model using multilayer perceptron (MLP) networks is used to identify and remove impulsive noise in power delay profiles (PDP). These studies were conducted based on field measurements in the 2400 MHz band in a public square with vegetation. The results are analyzed and compared with ordinary least squares (OLS) nonlinear regression results and results from similar studies. The Root Mean Square Error (RMSE) values between the experimental results of mean path loss and those provided by each propagation model are presented. The adjustment performed by OLS nonlinear regression and ANN significantly reduced the RMSE. The best results are those presented by artificial neural networks, with RMSE of 0.39 when using four neurons in the hidden layer of the ANN. The ANN used to identify and remove impulsive noise in power delay profiles (PDP) through pattern recognition proved to be more efficient than the CFAR technique. ANN technique found a larger number of valid multipaths compared to the CFAR technique.

This paper focused on differences of vehicle-to-vehicle (V2V) radio channel characteristics in the same region but different traffic density and speeds (congestion and non-congestion) at 5.9 GHz. Continuous measurement campaign was conducted on a city expressway through the complex dense urban area in Wuhan, China. Small-scale channel characteristics including power delay profile (PDP), amplitude fading distribution, K-factor, delay spread and doppler shift were obtained, respectively. Specifically, the cumulative distribution function (CDF) of root mean square (RMS) delay spreads and RMS doppler spreads in non-congestion scenario and congestion scenario were all fitted well with Lognormal distribution. We also found that different intensity of traffic and speed of vehicles have little effect on RMS delay spreads, but have a big impact on RMS doppler spreads. According to estimation outcomes, the V2V channel characteristics in Chinese urban scenario were different from the previous measured results in European cities. All of these conclusions in this paper can provide references to design the wireless communication system for V2V channel.

In the next generation of mobile communication systems, high data rates and high capacity will be possible if multiple antennas are used at new frequencies. This paper presents the correlations between channel parameter path loss (PL), root mean square delay spread (DS), angular spread (AS), and K-factor established based on channel measurements. The channel measurements were performed in a 781MHz LOS/NLOS environment. To avoid interference from Korean DTV broadcasting, we measured the channel characteristics in urban/rural/suburban areas on Jeju Island using a channel sounder and 4×4 antennas. The correlations between channel parameter show that the wireless channel characteristics can be determined and effective communication system design can be produced for use in similar environments.

In this study, radio channel measurements were conducted in an urban inland river environment at 5.9GHz. The measurements consisted of both the line of sight (LOS) and non-line of sight (NLOS) cases. We estimate and model channel characteristics based on the measured data. For small-scale fading properties, best fit small-scale fading distribution is determined. Statistical models of the Ricean K-factors and Weibull shape parameters are provided. In addition, a distance-dependent Ricean K-factor model for the urban inland river environment is proposed. For the power delay profile (PDP), we perform cluster identification and obtain the cumulative distribution function (CDF) of the inter-cluster interval. A statistical model of the intracluster decay time constant is also presented, and an exponential decay model is applied for modeling the inter-cluster decay of the PDP. For delay spread and Doppler spread, the root mean square (RMS) delay spreads in the LOS case are compared with those in the NLOS case. Moreover, we estimate and analyze RMS Doppler spreads in both the LOS and NLOS cases. Finally, a bimodal Gaussian mixture distribution (BGMD) is employed to characterize the RMS delay spreads and RMS Doppler spreads. The BGMDs exhibit good matching levels.

To establish reliable wireless communication systems in underground mines, accurate channel modeling plays an indispensable role in the design phase. In this paper, we propose ray tracing-based channel modeling in room-and-pillar mines. Specifically, the propagation paths of signals are firstly determined in the horizontal plane of a room-and-pillar mine using the ray tracing method. Then, the two-dimensional (2D) propagation paths are converted into their corresponding three-dimensional (3D) counterparts by deriving the heights of intersection points at obstacles and the locations of reflection points on mine ceilings and floors. Since the roughness of mine surfaces has a non-negligible influence on radio propagation properties, it is also taken into account when the electric fields of propagation paths are calculated. To validate the accuracy of the proposed ray tracing-based room-and-pillar channel model, we compare simulation results with experimental measurements conducted in an actual mine in terms of mean excess delay and root mean square (RMS) delay spread. The comparisons show simulation results have a good consistency with measurement data.

Applications of unmanned aircraft systems (UAS) are expected to expand dramatically in the coming decades. In order to provide safe and reliable links for UAS, NASA Glenn Research Center sponsored a measurement campaign in 2013 to characterize air-ground (AG) channels. In the first three of our AG channel characterization series papers, path loss, small scale fading, stationarity distance, root mean square (RMS) delay spread, spatial correlations, and tapped delay line models were presented for a range of ground site environment. In this paper, we expand the results to a unique and little-studied characteristic of the AG channels—airframe shadowing—for a medium-sized aircraft. Airframe shadowing occurs when the line-of-sight signal is obstructed by the airplane itself in some specific maneuvers. Based on over 200 aircraft wing/engine shadowing events in both C-band (5060 MHz) and L-band (968 MHz) collected in the measurement campaign, shadowing depth, duration, multiple antenna diversity gain, and small scale fading results and their statistics are reported. Algorithms are proposed to simulate a random shadowing event based upon shadowing depth and duration cumulative density functions. Airframe shadowing characteristics are independent of the local ground site conditions and link distance. The shadowing loss is modeled as a function of aircraft roll angle, but shadowing loss and duration are essentially uncorrelated. The maximum shadowing loss measured was over 35 dB and the duration was up to 74 s. As expected, deployment of multiple aircraft antennas is shown helpful to mitigate this shadowing.

The effect of human body and indoor environment in the ultra wide band (UWB) radio propagation channel is presented. Time domain measurements are performed in the body-centric wireless sensor laboratory, Queen Mary, University of London. In order to characterize the on-body radio channel, the transmitter has been placed on the belt, and the receiver is moved on 33 different Line of Sight (LOS) positions on the human candidate. Statistical path loss, and time domain parameters [mean delay and root mean square (RMS) delay spread] are extracted from measurement data. Due to multipath effect, the path loss exponent is smaller than the one measured in an anechoic chamber. Three different thresholds have been applied to calculate the time dispersion parameters. Results show reduction of delay spread if higher threshold is used. (4 pages)