The integration of sub-6 GHz, centimeter-wave, and millimeter-wave bands through cross-band coordination is recognized as a pivotal approach to optimize system performance in the sixth generation (6G) research. The existing standard channel models, e.g., 3GPP TR 38.901 and QuaDRiGa, support cross-band channel simulations. However, both models assume that multipath components observed at different bands are identical, which is inconsistent with channel measurements. In this paper, we propose a general cross-band channel model, which considers the birth and death of clusters across different bands. The evolution of clusters in temporal and spatial domains is also incorporated, where the common clusters observed at different bands are modeled to undergo identical birth-death processes. Furthermore, the frequency-dependent blockage losses caused by obstacles are embedded in the proposed model. A comprehensive analysis of channel statistical properties is conducted, including the delay/angular/Doppler spreads and stationary times/distances. Moreover, the similarities of cross-band channels in angular and delay domains are analyzed. To validate the accuracy of the proposed model, cross-band channel measurements across 0.7 to 39 GHz are conducted by time-domain channel sounders, which are capable of simultaneously measuring channels at two bands. Comparisons of simulation results from the proposed model, enhanced 6G pervasive channel model, and 3GPP TR 38.901 with measurement data reveal that the proposed model demonstrates the best alignment with measurements.

Millimeter-wave (mmWave) communications have a wide range of applications in indoor scenarios. However, the mmWave channel characteristics such as high path loss (PL), blockage effect, and temporal non-stationarity for indoor multiscenarios are not fully studied by using the same channel sounder, especially in the moving conditions. In this paper, indoor mmWave channel measurements are conducted at 28 GHz band in an office lounge and a lobby, considering both stationary and moving states of transmitter. Channel characteristics including PL, delay power spectral density (PSD), angular PSD, root mean square (RMS) delay spread (DS), and RMS angular spread (AS) for different scenarios are compared and analyzed. The relationships between channel characteristics and environments are thoroughly investigated. Measurement results confirm the clusters birth-death process and the channel temporal nonstationary properties. Multipath components (MPCs) caused by multiple-order reflections from walls are observed to show a significant impact on channel characteristics in the lobby.

Reconfigurable intelligent surfaces (RISs) are considered as one of the potential technologies for the sixth generation (6 G) wireless communication systems. Research on RIS channels is crucial for future RIS-assisted communication systems. However, current RIS channel measurements are only conducted when the receiver (Rx) is stationary, lacking moving channel measurements. In this paper, RIS is used as the transmitter (Tx) antenna in a hall environment to measure the 28 GHz RIS channel. We use near-field coding and far-field coding to measure the RIS channel during the movement process, respectively. The channel characteristics, including path loss, delay spread (DS), Ricean K-factor (KF), temporal autocorrelation function (TACF), and channel capacity are analyzed. It is found that in the hall environment, the coding mode of RIS exerted significant influences on path loss and channel capacity, whereas their impacts on DS, KF, and TACF were relatively minor.

Partition-based clustering algorithms like K-Means, KPowerMeans (KPM) and fuzzy c-means (FCM) have drawbacks for identifying arbitrarily sized non-spherical clusters in supporting wireless channel modeling. In this paper, we improve the Mahalanobis distance metric and propose a novel space-transformed and weighted fuzzy c-means (STW-FCM) algorithm for clustering multipath components (MPCs). The proposed STW-FCM algorithm imposes more relaxed assumptions on cluster shapes, allowing better accommodation of irregularly shaped clusters. Both synthetic and channel measurement data are utilized for validating the proposed STW-FCM algorithm, demonstrating its superior performance compared to existing clustering algorithms.

The performance evaluation of sixth generation (6G) communication systems is anticipated to be a controlled and repeatable process in the lab, which brings up the demand for wireless channel emulators. However, channel emulation for 6G space-time-frequency (STF) non-stationary channels is missing currently. In this paper, a non-stationary multiple-input multiple-output (MIMO) geometry-based stochastic model (GBSM) that accurately characterizes the channel STF properties is introduced firstly. Then, a subspace-based method is proposed for reconstructing the channel fading obtained from the GBSM and a channel emulator architecture with frequency domain processing is presented for 6G MIMO systems. Moreover, the spatial time-varying channel transfer functions (CTFs) of the channel simulation and the channel emulation are compared and analyzed. The Doppler power spectral density (PSD) and delay PSD are further derived and compared between the channel model simulation and subspace-based emulation. The results demonstrate that the proposed channel emulator is capable of reproducing the non-stationary channel characteristics.

Vehicle-to-vehicle (V2V) is an important sixth generation (6G) communication scenario, and we need to measure the performance of V2V communication systems in a controlled and repeatable channel environment. Hence, a corresponding channel emulator is required. In this paper, we first introduce a non-stationary V2V geometry-based stochastic model (GBSM) that takes into account the birth-death process of clusters and adapts to changes of the V2V scenario. Furthermore, the adaptive non-stationary V2V channel emulator with the birth-death process of clusters is constructed on a field-programmable gate array (FPGA) hardware platform. This channel emulator uses the fading channel generation algorithm of sum-of-frequency-modulation (SoFM) and the sine wave generation algorithm of the look-up table (LUT). Moreover, the important statistical properties of the channel under the theoretical simulation and hardware platform emulation are studied through simulations, e.g., temporal autocorrelation function (TACF), spatial cross-correlation function (SCCF), and delay power spectral density (delay PSD). Results show that the proposed channel emulator and the corresponding theoretical channel model fit well.

As a promising key technology for the sixth generation (6G) wireless communication systems, the reconfigurable intelligent surface (RIS) is able to intelligently control the propagation environments. In order to investigate the properties of RIS-assisted channels, related channel measurements are necessary. However, the channel parameter estimation (CPE) work in RIS-assisted channel measurements is challenging since the RIS can only tune part of the channel. In this paper, we present a novel channel sounding procedure firstly where channels are observed through different RIS transmission modes. Then a space-alternating generalized expectation-maximization (SAGE) based CPE scheme for 6G RIS-assisted channel measurements is proposed, which is realized by the multipath components (MPCs) tracking and detection, the maximum likelihood (ML) estimation, and other procedures. It is capable of detecting whether MPCs interact with RIS and estimating all important channel parameters, including the angle parameters at the RIS side. Finally, the proposed scheme is evaluated through synthetic channels. The impacts of the RIS size, the number of transmission modes, and the phase quantization on its performance are investigated. Simulation results show a good performance of the proposed scheme.

The reconfigurable intelligent surface (RIS) is regarded as a promising technology for the future networks, since it has the ability to manipulate the randomly behaving wireless communication environment. However, due to the large number of the passive RIS elements, the pilot overhead of channel estimation in the RIS-assisted communication system is huge. To address this issue, we propose a three-step orthogonal matching pursuit (OMP) based algorithm which can further improve the channel estimation accuracy compared to the existing pilot-saving schemes. The proposed algorithm can overcome the effect of noise by expanding the number of training samples for the estimation of the same channel parameters. Specifically, the joint sparsity structure of the cascaded channels associated with different users is fully revealed and exploited in this paper. Based on this sparsity structure, the classical OMP algorithm is modified to jointly estimate channel parameters. Simulation result shows that, to achieve the same channel estimate accuracy, the pilot overhead of channel estimation of the proposed algorithm is lower than the existing schemes.