With the growing demands for marine environmental monitoring, collaborative operations, and marine resource development, high-speed and reliable Internet of Things (IoT) communication has become essential for maritime activities. This paper presents a wideband channel measurement campaign at 3.3 GHz in complex nearshore environments to investigate ship-to-ship (S2S) channel characteristics. The study systematically examines time-frequency stationarity, large-scale fading (LSF), dispersion, and small-scale fading (SSF). Results show that the mean stationarity distance reaches 22.48 m, with an average stationarity bandwidth exceeding 39.95 MHz. The statistical close-in (CI) model provides superior accuracy for path loss modeling, while the shadow fading autocorrelation exhibits a periodic oscillatory pattern, captured by a proposed improved model. Time–frequency–angular analysis indicates weak overall dispersion, with stronger dispersion in complex nearshore environments compared to open sea. Furthermore, RMS delay spread, Doppler spread, and angular spread are accurately modeled by Lognormal, Weibull, and Lognormal distributions, respectively. The Rician distribution dominates SSF envelope modeling, with the K-factor following a Normal distribution (mean 14.28–16.03 dB). These findings provide valuable insights for the design and evaluation of maritime IoT communication systems in nearshore environments.

As a key technology of future communication systems, reconfigurable intelligent surfaces (RISs) can intelligently control wireless signal reflections, thereby optimizing propagation channels and enhancing communication performance. However, the indoor channel characteristics and communication performance of RISs in real-world deployment environments remain insufficiently studied. In this paper, we develop a RIS-based measurement platform for simultaneous channel measurement and link-level performance analysis, followed by verification and validation in a laboratory environment. Utilizing this platform, we conduct wideband channel measurement and performance analysis work in indoor scenarios at 2.6 GHz band. Multiple RIS phase shift codebooks are employed, including the 1-bit discrete Fourier transform (DFT) codebook, the Ring-type codebook, and the conditional sample mean (CSM) codebook. Based on these measurements, two empirical path loss (PL) models, namely the floating-intercept (FI) model and the close-in (CI) model, are fitted to the measured data. Furthermore, we comprehensively analyze and compare the channel characteristics of RIS-assisted communications, including shadow fading (SF), multipath components (MPCs) statistics, the Rician K-factor (KF), and root mean square (RMS) delay spread. Finally, we evaluate and compare the wireless coverage and link-level performance of various RIS reflection schemes. The findings on propagation characteristics and communication performance provide essential insights that can support the future application and deployment of RIS-assisted communication systems.

As next-generation wireless communication systems need to be able to operate in high-frequency bands and high-mobility scenarios, delay-Doppler (DD) domain multicarrier (DDMC) modulation schemes, such as orthogonal time frequency space (OTFS), demonstrate superior reliability over orthogonal frequency division multiplexing (OFDM). Accurate DD domain channel modeling is essential for DDMC system design. However, since traditional channel modeling approaches are mainly confined to time, frequency, and space domains, the principles of DD domain channel modeling remain poorly studied. To address this issue, we propose a systematic DD domain channel measurement and modeling methodology in high-speed railway (HSR) scenarios. First, we design a DD domain channel measurement method based on the long-term evolution for railway (LTE-R) system. Second, for DD domain channel modeling, we investigate quasi-stationary interval, statistical power modeling of multipath components, and particularly, the quasi-invariant intervals of DD domain channel fading coefficients. Third, via LTE-R measurements at 371 km/h, taking the quasi-stationary interval as the decision criterion, we establish DD domain channel models under different channel time-varying conditions in HSR scenarios. Fourth, the accuracy of proposed DD domain channel models is validated via bit error rate comparison of OTFS transmission. In addition, simulation verifies that in HSR scenario, the quasi-invariant interval of DD domain channel fading coefficient is on millisecond (ms) order of magnitude, which is much smaller than the quasi-stationary interval length on 100 ms order of magnitude. This study could provide theoretical guidance for DD domain modeling in high-mobility environments, supporting future DDMC and integrated sensing and communication designs for 6G and beyond.

Reconfigurable intelligent surface (RIS) has garnered significant attention in wireless communications due to its electromagnetic wave manipulation capabilities. In order to ensure the effectiveness of various transmission designs in practical environment, the channel characteristics of RIS-assisted wireless communication systems warrant thorough investigation. While substantial research has been conducted on large-scale channel characteristics, there remains a lack of measurement-based studies on channel small-scale characteristics. This paper conducts channel measurement campaigns, analyzing delay characteristics and multi-cluster properties in multiple indoor and outdoor environments, including square, corridor, and classroom scenarios. The measurement results indicate that the RIS-assisted path (i.e. the virtual line-of-sight (VLOS) path) makes the channels exhibit two-cluster characteristics analogous to conventional line-of-sight channels. Moreover, in classroom scenario, VLOS path generates reflected echoes that degrade the channel delay characteristics. Building on these findings, this paper proposes a small-scale channel modeling framework comprising a two-cluster-based channel impulse response (CIR) model and a K-factor-based CIR model. The simulation and measurement results demonstrate satisfactory agreement, validating the effectiveness and practicality of the proposed framework. Two types of CIR models that are unified with the traditional CIR model form, along with an optional echo component, make this framework flexible and easy to use. The proposed small-scale modeling framework can effectively characterize the power delay profiles of RIS-assisted channels, providing References for future research on RIS-assisted wireless communications.

Reconfigurable intelligent surface (RIS) holds significant potential to enhance wireless communications by offering good performance, high security, and great efficiency. In particular, RIS provides notable benefits in improving wireless location accuracy for user equipments (UEs), which are often overlooked. In this paper, we utilize RIS for received signal strength (RSS)-based indoor fingerprinting localization. To improve positioning accuracy, we propose a two-stage RIS configuration selection approach. Specifically, in the first stage, we select the RIS configuration that contributes significantly to positioning. In the second stage, a supervised learning approach is used to select features, effectively reducing the large state space of the RIS. The effectiveness of the proposed RIS-assisted RSS fingerprinting localization technique is validated through simulation and field test results.

This paper presents a measurement of dynamic wireless channels between ultra-low altitude unmanned aerial vehicle (UAV) and vehicle in a semi-urban scenario, with the UAV acting as the transmitter and the vehicle as the receiver. Through quantitative analysis of the delay and doppler domains, we observe significant dynamic changes in the channel state as the vehicle passes through a T-shaped intersection. We compare the root-mean-square delay spread (RMS DS) and root mean square doppler spread (RMS DPS) of the vehicle as it approaches, passes through, and moves away from the intersection, and conduct modeling analysis based on the time-frequency domain dispersion. To describe the channel characteristics at the intersection, we develop a tap delay line (TDL) channel model based on markov birth-death process. This study aims to deepen the understanding of UAV-to-vehicle (U2V) channel characteristics, with a particular focus on the intersection scenario. The findings provide important theoretical foundations and practical guidance for the development, optimization, performance evaluation, and resource allocation strategies of low-altitude communication systems.

In this paper, a measurement campaign is conducted to investigate unmanned surface vehicle (USV) communication channels in complex nearshore environments. The experiment setup includes a fixed offshore platform as the transmitter and a mobile vessel as the receiver. Based on the collected data, this study analyzes and models the stationarity and fading characteristics of the channel. The results show that the values for the 1st percentile, 50th percentile, and 90th percentile of the channel’s stationary distance (threshold=0.8) are 0.412 m, 5.99 m, and 23.19 m, respectively. Path loss analysis indicates that the close-in free-space reference path loss with a path loss exponent of 2.407 provides an accurate representation, while shadow fading follows a normal distribution with a mean of zero and a standard deviation of 4.55 dB. To better capture the autocorrelation of shadow fading, a novel model is proposed, improving accuracy by 35% compared to the conventional exponential model. Additionally, small-scale fading envelope analysis using the Akaike information criterion (AIC) confirms that the Rician distribution is the most suitable model. The K-factor of the Rician distribution can be statistically modeled as a bimodal Gaussian distribution, with a goodness-of-fit (GoF) value of 0.026.

Reconfigurable intelligent surface (RIS) has emerged as a promising key technology for sixth-generation (6G) wireless communication systems, primarily due to its capability to intelligently manipulate the propagation environment. In this paper, we conduct comprehensive measurements of the wireless channel and link-level performance of an RIS-assisted communication system in indoor corridor scenarios. We analyze the time dispersion characteristics and channel capacity under both RIS intelligent reflection (RIS-IR) and without RIS (WR) cases for comparative evaluation. The results demonstrate that wideband channel characteristics have a notable impact on the performance of RIS-assisted communications. Specifically, we model the fading distribution of the visual-line-of-sight (VLoS) path introduced by the RIS and establish a corresponding tapped-delay-line (TDL) channel model. The insights derived from this study offer theoretical foundations and practical guidelines for the deployment and performance evaluation of RIS-assisted communication systems.

In satellite communication systems, the Doppler effect caused by the high-speed motion of satellites significantly impacts the stability and performance of communication links. This is especially evident in pseudo-random code modulation systems, where the Doppler effect induces a frequency offset in the pseudo-code rate, thereby degrading signal demodulation performance. Focusing on the code Doppler effect in satellite communication scenarios, this paper investigates a channel simulation method adapted to the code Doppler effect and verifies its effectiveness.

A channel measurement system for accurate modeling of the millimeter-wave (mmWave) band air-to-ground (A2G) wireless channel is presented. The measurement system consists of a ground station on a small cart and an air station installed on a custom-made octocopter unmanned aerial vehicle (UAV). Channel sounders at 26 GHz mmWave band with a bandwidth of 1 GHz are mounted on the air station and the ground station. In contrast to the on-the-shelf drones, the custom-made UAV offers the advantages of greater payload capacity and extended flight endurance. The measurement campaign was conducted in a university campus scenario, providing valuable measurement data for further analyses of the A2G channel. To analyze multipath effects in the A2G channel, simulation result of a ray tracing (RT) model is used to identify the principal propagation effects in the actual measurements. Subsequently, the path-loss exponent and the standard deviation of shadowing are calculated based on the measurement. Furthermore, sparsity of the A2G mmWave channel is evaluated through analyses of the Gini index and the Rician$K$factor. By comparing with the measurement results in the different propagation scenarios presented in the related work, e.g., industrial Internet-of-Things (IIoT), vehicular urban, and laboratory room, unique characteristics of the A2G mmWave channel are discussed.

The Industrial Internet of Things (IIoT) enables machines to communicate robustly. High reliability, high throughput, and low latency are the critical capabilities of IIoT, which have posed great challenges to existing wireless solutions for industrial applications. Due to the vast available bandwidth, the emerging millimeter-wave (mmWave) technology is promising to address this bottleneck. However, the propagation behaviors at such high frequencies in the harsh industrial environment have yet been well understood. In this work, extensive measurements have been conducted in a representative industrial application scenario using a 2-GHz wideband directional channel sounder in the 28-GHz mmWave band. By exploiting the measurement with excellent resolution, the multipath components’ (MPCs) delay-angular space is transformed onto the scatter points (SPs) in the propagation environment. An effective clustering algorithm is then proposed to cluster the SPs without prior knowledge and iterations. Through a geometrical optics analysis, the SP clusters are classified corresponding to the reflectors. By doing this, the cluster-generating reflectors are reduced to a quasi-deterministic (QD) channel model that ensures spatial consistency and MPCs’ stochastic dispersion. Finally, it is shown that the measurement data agrees well with the proposed QD model, indicating the high fidelity of the proposed model.

With the emergence of various IoT applications, a large-scale IoT system is set to revolutionize the various industry. Massive machine type communication will play a crucial role in providing robust support to this system. However, in mMTC, implementing user access control to block malicious users remains a critical issue that needs to be addressed. To this end, this paper proposes a user access control scheme based on resource hopping multiple access (RHMA). This scheme utilizes the unique resource hopping patterns of different users to control user access. The controllability of these resource hopping patterns effectively prevents malicious users from intruding into the system. Moreover, the proposed user access control scheme is implemented in practice with USRP platform. The experimental results confirm the reliability and effectiveness of the proposed access control system.

Orthogonal time frequency space (OTFS) modulation is an emerging technology to tackle time-frequency (TF) selective channel in high mobility scenarios. In OTFS, resource is multiplexed in the delay-Doppler (DD) domain. Based on the potential sparsity, separability, stability and compactness of the channel spreading function, OTFS is able to realize lower complexity of channel estimation, higher diversity and higher reliability compared with orthogonal frequency division multiplexing (OFDM). However, the channel spreading function for practical communication systems is rarely considered in the current OTFS-related literature. High-speed railway (HSR) is a typical high mobility scenario with trains travelling at over 200km/h, which has the potential to employ OTFS. To this end, the HSR channel spreading function is characterized and the performance of OTFS in HSR is evaluated based on the realistic channel measurement in this article. Firstly, the HSR channel in TF domain is measured based on the long term evolution railway (LTE-R) network. Then, the characteristics of the channel spreading function are analyzed. In particular, the impact of time domain channel fading on the spreading function is investigated. The characteristics of the measured spreading function are analyzed with the proposed metrics in railway viaduct and tunnel scenarios. Based on the above analysis, an algorithm for generating the channel spreading function is proposed. Feasibility of the proposed DD domain channel generation algorithm is verified through comparing metrics of which to those of the measured channel. By simulating the bit error rate (BER) and mean square channel estimation error performances of OTFS modulation in the practical band-limited systems, it is shown that the impacts of Doppler shift, delay, SFFT and time domain channel fading need be considered for the application of OTFS modulation, in contrast to the state-of-art DD domain channel generation scheme based on tap delay link (TDL) model. For example, compared to OTFS modulation under the ideal channel spreading function, OTFS modulation requires a signal gain greater than 5 dB under the practical channel spreading function affected by above factors, to achieve the same BER less than 10−2 under parameters defined in simulation.

Intelligent Transportation System (ITS) is more and more crucial in the modern transportation field, such as the applications of autonomous vehicles, dynamic traffic light sequences, and automatic road enforcement. As the upcoming fifth-generation mobile network (5G) is entering the deployment phase, the idea of cellular vehicle-to-everything (C-V2X) is proposed. The same 5G networks, coming to mobile phones, will also allow vehicles to communicate wirelessly with each other. Hence, 3.5 GHz, as the main sub-6 GHz band licensed in 5G, is focused in our study. In this paper, a comprehensive study on the channel characteristics for vehicle-to-infrastructure (V2I) link at 3.5 GHz frequency band is conducted through channel measurements and ray-tracing (RT) simulations. Firstly, the channel parameters of the V2I link are characterized based on the measurements, including power delay profile (PDP), path loss, root-mean-square (RMS) delay spread, and coherence bandwidth. Then, the measurement-validated RT simulator is utilized to conduct the simulations in order to supplement other channel parameters, in terms of the Ricean K-factor, angular spreads, the cross-correlations of abovementioned parameters, and the autocorrelation of each parameter itself. This work is aimed at helping the researchers understand the channel characteristics of the V2I link at 3.5 GHz and support the link-level and system level design for future vehicular communications of 5G.

Long Term Evolution (LTE) is expected to substitute the Global System for Mobile Communications (GSM) as the radio access technology for railway communications. Recently, especial attention has been devoted to high-speed trains since this particular environment poses challenging problems in terms of performance simulation and measurement. In order to severely decrease the cost and complexity of high-speed measurement campaigns, we have proposed a technique to induce effects caused by highly-time varying channels on Orthogonal Frequency-Division Multiplexing (OFDM) signals while conducting measurements at low speeds. In this work, we employ this technique to evaluate LTE transmissions in a Time-Division Duplex (TDD) fashion, which is more convenient for the railway environment due to a number of reasons (e.g., better flexibility in frequency choice and the importance of the uplink transmissions for railway control communications). We assess the performance obtained in high- speed scenarios up to 500 km/h.

Massive MIMO has been chosen as one of the candidate technologies of the fifth-generation mobile communication system (5G), and channel modeling of massive MIMO is of great importance. The most direct and effective approach to investigate the propagation characteristics of massive MIMO channels is channel measurements. However, there are only few measurements of massive MIMO channels, and there still lacks deep investigations of massive MIMO channel characteristics. In this paper, we present a measurement campaign of indoor massive MIMO channels, by using a linear large-scale array with 64 elements. The measurements are conducted at 2 GHz, 4 GHz, and 6 GHz, respectively, with a bandwidth of 200 MHz. Both LOS and NLOS propagation scenarios are considered in the measurements. The basic channel parameters are extracted, including path loss, delay spread, and coherence bandwidth. The non-stationarity of radio channels, which is reflected by the variations of delay spread and coherence bandwidth over different array locations, is discussed. The impact of carrier frequency on the above channel parameters is further discussed. The results would be useful for the design of massive MIMO system in the indoor environments.