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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.

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.

The wireless communication system is one of the most favorable fields of communication in computer science because of its mobility and dynamicity. But it is very important to use some efficient techniques in terms of bandwidth and speed to cope with the wide range of user’s demands. In order to fulfill these demands, Orthogonal Frequency Division Multiplexing (OFDM) multicarrier technique holds some magnificent features namely multipath fading, delay spread, frequency selective fading, and inter channel interference (ICI). In this paper, the performance of OFDM system is analyzed to lessen the multipath fading and the inter symbol interference (ISI) over an Additive White Gaussian Noise (AWGN). We find out the variation of the output signal after removing unnecessary noise and bit error rate (BER) of the input signal using AWGN, and it shows better results for BER curve for Binary Phase Shift Keying (BPSK) in the OFDM system.

In this paper, the communication quality of an underwater acoustic link between two nodes is quantified by the predicted channel gain and delay spread using a stochastic and reinforcement learning model. The stochastic model generates an ensemble of time-varying channel characteristics by capturing the effect of known environmental changes including changes in sound speed profile, tides and bathymetry. Along with the stochastic model to capture the impact of unknown environmental parameters on channel quality a hidden Markov model is utilized to complement sparse channel measurements and predict the channel characteristics over a long time period spanning multiple days. In this work, the nodes are bottom mounted in a shallow turbulent water environment, with known tide cycles, physical oceanography conditions and channel geometry. As such, the channel characteristics can be estimated using a simulation software model at the remote nodes. While the simulation model is used to estimate the initial channel condition between the nodes in short-term deployment, as will be shown, the hidden Markov model provides an accurate channel characteristics prediction for long term deployment, which can be utilized by software-defined acoustic nodes such that they can adapt to the time varying acoustic channel.

Visible light communication (VLC) is a promising candidate that is expected to revolutionize indoor environment communications performance and fulfill fifth generation and beyond (5GB) technologies requirements. It offers high and free bandwidth, electromagnetic interference immunity, low-cost front end and low power consumption. Also, VLC has dual functions that could be utilized in both illumination and communication concurrently. The number of optical attocells (OAs) and their deployment in the room represent the main issue that should be taken into consideration in designing an optimal VLC system. In this paper, we have introduced a new model of five OAs in the typical room. In addition to an investigation of various optical attocells (OAs) deployment models, in which a multi-variable evaluation was performed in terms of received power, illumination, SNR and RMS delay spread in order to determine the optimal OAs model. Also, various modulation schemes performances were investigated which included NRZ-OOK, BPSK, and QPSK in order to improve the BER performance. Results indicated that BPSK modulation had superior BER performance when compared with all OAs models. Further, a comprehensive results analysis and comparison of all proposed models was conducted over various parameters, in which our new proposed OAs model achieved an optimal performance in comparison with the other models.

In this paper, we present characterization and measurement of a D-band (110-170 GHz) radiating near field channel. Assuming 2-ray path model, Channel Impulse Response (C.I.R) has been theoretically improvised for a bandlimited frequency response obtained from V.N.A. The change in CIR with increase in radiating near field distance between the transmitter and receiver has been studied using time delay statistical parameter i.e. root mean square (RMS) delay spread variation with distance. Furthermore, the effect of change in height of transmitter and receiver on RMS delay has been analyzed theoretically and experimentally validated using near field measurement setup. The experiment has been conducted using D- band 16dBi horn antennas working as the transmitter and receiver.

Mobile channel data results in a rural area are presented from measurements at 2 GHz over 50 MHz bandwidth The data were analyzed to derive an empirical relationship between rms delay spread and coherence bandwidth for correlation levels of 0.9 and 0.5 and the results are compared with those in the literature.

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.

A V2V radio channel measurement campaign with a maximum distance of 10 km was carried out during the congestion period in Wuhan city, China. In this paper, a short campaign description with the relevant measurement parameters is given. The received signal level is obtained from the measurement data and large variation is found. The mean excess delay and the RMS delay spread extracted from the averaged power-delay profiles, are found to be within 2 micro s and 1.5 micro s, respectively. The best-fit small-scale amplitude distribution is found to be Rayleigh distribution with the occurrence rate of 55.9%, while the TWDP and Rician distribution are estimated as the main best-fit distributions when the TX-RX distances are within 300m.

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.

Global navigation satellite system (GNSS) can provide us with three-dimensional coordinates information of any place on the earth. However, the multipath effects always cause a decrease in GNSS positioning accuracy. In this paper, we analyze and model the root mean square (RMS) delay spread (DS) in multipath channels and the GNSS pseudo-range error (PRE) based on channel measurements in an urban canyon scenario at both 1.575 GHz and 1.207 GHz. By constructing the probability density function (PDF) of RMS DS, it is found that the PDF can be well fitted by a lognormal distribution. In addition, compared with the International Telecommunication Union (ITU) standard, the mean value and standard deviation of RMS DS in the urban canyon are much smaller than those in the traditional urban micro-cellular scenario. Then, by modeling PRE as a function of the transmitter-receiver (Tx-Rx) elevation angle and RMS DS separately, the effect of the Tx-Rx elevation angle on PRE and the dependence of PRE on RMS DS are studied. It is found that the PRE increases linearly with the increases of the cotangent value of Tx-Rx elevation angle, and the fluctuation of PRE at 1.207 GHz is much larger than that at 1.575 GHz. Besides, there is a linear dependence of PRE on RMS DS, that is when RMS DS increases by 1 ns, PRE increases by 0.50 meters at 1.207 GHz and 0.53 meters at 1.575 GHz. These results are helpful for the research on multipath effects in urban canyon scenarios and the improvement of positioning accuracy for the GNSS.

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.

Terahertz (THz) communication is now being considered as one of possible technologies for the sixth generation (6G) wireless communication systems. In this paper, a novel three-dimensional (3D) space-time-frequency non-stationary theoretical channel model is first proposed for 6G THz wireless communication systems employing ultra-massive multiple-input multiple-output (MIMO) technologies with long traveling paths. Considering frequency-dependent diffuse scattering, which is a special property of THz channels different from millimeter wave (mmWave) channels, the relative angles and delays of rays within one cluster will evolve in the frequency domain. Then, a corresponding simulation model is proposed with discrete angles calculated using the method of equal area (MEA). The statistical properties of the proposed theoretical and simulation models are derived and compared, showing good agreements. The accuracy and flexibility of the proposed simulation model are demonstrated by comparing the simulation results of the relative angle spread and root mean square (RMS) delay spread with corresponding measurements.

In Multimedia Broadcast Multicast Service (MBMS)-dedicated cell, multipath aliasing is an inevitable challenge for CAS reception in long delay spread channels. Meanwhile, traditional Channel Estimation (CHE) algorithms may not work well in such scenarios. For overcoming this problem, an Aliasing-Elimination CHE (AE-CHE) algorithm was proposed. This novel algorithm utilizes the pre-decoded Physical Broadcast Channel (PBCH) to generate a full-symbol length multipath distribution. By using the multipath distribution, aliasing errors could be eliminated effectively. However, previous researches are mainly based on ideal factors such as perfect PBCH decoding, static channel without Doppler spread, which does not match the actual situation in practical receivers. This paper studies the effects of actual PBCH decoding ability and Doppler spread of time-variant channels on the performance of the AE-CHE algorithm. Analysis and simulation results show that the AE-CHE algorithm could also outperform the traditional algorithms even in the presence of non-ideal factors.

This paper proposes a three dimensional (3D) nonstationary geometry-based stochastic model (GBSM) for mobile-to-mobile (M2M) underwater acoustic (UWA) communication channels. In this proposed model, the border reverberations are modeled as a series of specular reflection paths and the volume reverberations are approximated as the twin-cluster birth-death model. Moreover, this model supports dual mobility both of transmitter (Tx) and receiver (Rx) in the 3D body of water. Based on the analytical model, the corresponding channel statistical properties such as the time-frequency correlation function (TF-CF), power delay profile (PDP), average delay, and root mean square delay spread (RMS- DS) are derived. The results show a good fit between the analytical model and the simulation model. Finally, the reliability of the model is validated by comparing the statistical characteristics with the measurement results.

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.

Orthogonal frequency division multiplexing (OFDM) has been widely adopted in underwater acoustic (UWA) communication due to its good anti-multipath performance and high spectral efficiency. For UWA-OFDM systems, channel state information (CSI) is essential for channel equalization and adaptive transmission, which can significantly affect the reliability and throughput. However, the time-varying UWA channel is difficult to estimate because of excessive delay spread and complex noise distribution. To this end, a novel Bayesian learning-based channel estimation architecture is proposed for UWA-OFDM systems. A clustered-sparse channel distribution model and a noise-resistant channel measurement model are constructed, and the model hyperparameters are iteratively optimized to obtain accurate Bayesian channel estimation. Accordingly, to obtain the clustered-sparse distribution, a partition-based clustered-sparse Bayesian learning (PB-CSBL) algorithm was designed. In order to lessen the effect of strong colored noise, a noise-corrected clustered-sparse channel estimation (NC-CSCE) algorithm was proposed to improve the estimation accuracy. Numerical simulations and lake trials are conducted to verify the effectiveness of the algorithms. Results show that the proposed algorithms achieve higher channel estimation accuracy and lower bit error rate (BER).

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.

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.

This paper proposes a novel joint channel estimation and beamforming approach for multicell wideband massive multiple input multiple output (MIMO) systems. With the proposed channel estimation and beamforming approach, we determine the number of cells $N_{c}$ that can utilize the same time and frequency resource while mitigating the effect of pilot contamination. The proposed approach exploits the multipath characteristics of wideband channels. Specifically, when the channel has a maximum of $L$ uncorrelated multipath taps (or correlated multipath taps satisfying modest criteria which is valid in most practical scenarios), it is shown that $N_{c}=L$ cells can estimate the channels of their user equipments (UEs) and perform beamforming while mitigating the effect of pilot contamination. The proposed approach can also be applied for general correlated multipath taps, and achieves good performance for this scenario as well. In a typical long term evolution (LTE) channel environment having delay spread $T_{d}=4.69\,\,\mu \text{s}$ and channel bandwidth $B=5$ MHz, we have found that $L=36$ cells can use this band. In practice, $T_{d}$ is constant for a particular environment and carrier frequency, and hence $L$ increases as the bandwidth increases. All the analytical expressions have been validated, and the superiority of the proposed design over the existing ones is demonstrated using extensive numerical simulations both for correlated and uncorrelated channels. The proposed channel estimation and beamforming design is linear and simple to implement.

Objectives: The scaling down of CMOS technology feature size may bring out many benefits in terms of area, performance, cost etc., but the undesirable effects such as variability in the parameters of the circuit and operating environment are increasing which in turn leads to uncertainty in the circuit performance and lowering of yield. In this study, the impact of variations has been analyzed, on the delay of standard cells. It is necessary to model variations to predict the performance. Methods: This analysis is performed by different Variation modeling techniques for Standard Cell Characterization. The Monte Carlo technique introduces randomness by changing the threshold voltage such that it is different for different transistors at the same time. In contrast, Liberty Variation Format used for lower technologies, gives the variation of a cell delay at 1 sigma of delay distribution per arc which covers all slew-load, arc and when conditions. Findings: The delay for every cell varies based on the active arc/input transition/output load. After running the simulations for Cell a using Monte Carlo and Liberty Variation Format technique, the result and delay spread for Monte Carlo simulations is obtained which is compared with the standard deviation values from the Liberty Variation Format simulations. After comparing them we can see the values almost tend to be equal. This way instead of running the Monte Carlo Simulations, which have a huge runtime we can also obtain the accurate standard deviation (sigma) values from the Liberty Variation Format simulations. Application: The simulation results demonstrate the variation in the delay of those cells from the nominal value and which modeling technique can be used for efficient Variation calculation for circuit parameters. Keywords: Liberty Variation Format, Monte Carlo Simulations, Process Variations, Standard Cells, Variations

As an important part of the intelligent transportation system (ITS), vehicle-to-vehicle (V2V) communication will improve the safety and efficiency of the transportation system by realizing the information transmission between vehicles. The underground parking garage is a typical scenario in V2V communication, but as an indoor environment, it is different from the conventional outdoor road scenarios significantly. Therefore, the purpose of this paper is to analyze and model the V2V channel characteristics of an underground garage. In this paper, a novel channel measurement carried out in the underground garage is first introduced. Considering that there are a lot of obstacles in an underground garage, the non-line-of-sight (NLoS) condition is taken into account during the measurement. Then, channel characteristic parameters, including large-scale fading, delay spread, and K-factor, are analyzed based on the measured data. In addition, we also carry out channel angle of arrival analysis, show the distribution of azimuth of arrival (AOA) and elevation of arrival (EOA) of multipath components (MPC), and conduct a statistical analysis of the angular spread. In the process of analysis and modeling, we focus on the differences between line-of-sight (LoS) and NLoS conditions. The analysis and conclusions presented in this paper will enrich the understanding of V2V channel and benefit the design of V2V communications.

In this paper, a massive multiple input multiple output (MIMO) channel measurement campaign with two setups is conducted in an indoor lobby environment. In the first setup, two types of 256-element virtual uniform rectangular arrays (URAs), i.e., the 4×64 virtual URA and the 64×4 virtual URA are used. The carrier frequency is 11 GHz; in the second setup, measurements are performed at 4, 6, 11, 13, 15, 18 GHz at two different user locations. The channel characterization is presented by investigating the typical channel parameters, including average power delay profile (APDP), K factor, root mean square (RMS) delay spread, and coherence bandwidth. Moreover, the channel characteristics in angular domain are investigated by applying the space-alternating generalized expectation-maximization (SAGE) algorithm. The extracted multipath components (MPCs) are preliminarily clustered by visual inspection, and related to the interacting objects (IOs) in physical environment. Multipath structures at multiple frequency bands are examined. Direction spread of departure is estimated to evaluate the directional dispersion at the base station (BS) side. The results in this paper can help to reveal the propagation mechanisms in massive MIMO channels, and provide a foundation for the design and application of the practical massive MIMO system.

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.

Light propagation in a downlink Optical Wireless Communication (OWC) system from above the sea surface to the underwater medium is influenced by wind generated surface waves, associated bubble layer, particulate absorption and scattering, and medium inhomogeneity. The present study aims to model the combined effects of these factors on the channel characteristics, power budget and channel impulse response of the OWC system using Monte-Carlo numerical simulation technique for two different water types (open-oceanic and coastal). The transmission of light across the air-sea interface is modelled by using a Bidirectional Transmittance Distribution Function (BTDF), whereas the medium inhomogeneity is taken into consideration by stratifying the underwater channel based on the in-situ measured IOPs. In order to examine the effect of stratification, the channel characteristics are estimated by considering the medium as homogenous as well as stratified and compared. Comparison results suggest that the medium stratification provides significant improvement in power estimation in comparison to a case where the medium is considered as homogeneous, for all depths. Similarly, the channel impulse responses estimated for these two conditions are notably different in terms of delay spread, suggesting that the medium stratification in clear and moderately turbid waters may be a vital necessity for precise estimation of channel characteristics. These results will be useful for design and implementation of a physical downlink optical wireless communication system.

In this study, based on channel measurements for a fifth generation (5G) hotspot of a large waiting hall of a high-speed railway station at 28 GHz, the channel modelling, simulation, and validation are performed. To investigate clustering sparse features at a millimetre-wave band, an adaptive kernel-power-density algorithm is used to identify clusters. Moreover, by using a quasi-deterministic radio channel generator (QuaDRiGa) simulation platform, the large-scale channel parameters such as delay spread, azimuth spread of arrival, and time-evolution characteristics are simulated and validated. The QuaDRiGa simulation results agree well with measurement data, which verifies the applicability of QuaDRiGa in a millimetre-wave band. The results could be very useful in millimetre-wave over-the-air testing and system performance evaluation in the 5G hotspot scenario.

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.

Starting from outdoor transmission, crossing vegetation, the wideband and narrowband characterization of the indoor mobile radio channel in the 700 MHz band is obtained from experiments carried out in the indoor environment of the Engineering building at Fluminense Federal University, and from the processed data, respectively, the power-delay profiles obtained permitted to calculate the time dispersion parameters and the envelope of the signal permitted to adjust probability density functions to the signal variability, concluding about the influence of vegetation on those characteristics.