Vehicular communication has been widely concerned by academia and industry. Wireless channel characterization and modeling are the foundation of communication systems. Compared with typical road scenarios such as urban and suburban areas, wireless channel characterization in intersections is a challenging task. In this paper, channel measurements at 5.9 GHz in street intersection scenarios are carried out and provide data for the characterization and modeling of time-varying vehicular channels. This paper proposes a double-slope path loss model, which can accurately reflect the signal propagation loss at intersections. Further, the time-varying spatial characteristics of multipath are extracted and analyzed, and the azimuth and elevation spread of arrival are statistically characterized. The influence of obstacles on multipath spatial characteristics in intersection scenarios is investigated. Then we investigate the spatial stationarity of channels and analyze the possible reasons for the differences in spatial stationarity of different scenarios. In addition, based on multipath extraction, we quantitatively analyze the energy of dense multipath components in different propagation scenarios. The research in this paper can enrich the investigation of vehicular channels and enable the analysis and design of vehicular communication systems.

Obtaining angle-of-arrival (AOA) information is of great significance to improve the performance of communication systems. Real-time AOA recognition can reduce the complexity of beamforming design for massive multiple-input multiple-output (MIMO) systems, and can be used to construct an outer precoder to optimize the system and rate. However, for vehicular communications, AOA will change with environment and positions of vehicles, and it is difficult to obtain accurate AOA in real-time. Therefore, a fast AOA recognition method is needed to adapt to the rapid changes of channels. The traditional spectral- or parametric-based AOA estimation methods are difficult to obtain real-time AOA information because of the relatively high computational complexity. In order to solve this problem, this paper proposes a machine-learning-based fast AOA recognition approach. The proposed method includes off-line training and on-line estimation processes. In the off-line training process, an estimation model is obtained by using the support vector machine (SVM) based on a large number of actual measurement data in vehicular scenarios. Then, in the on-line estimation process, the obtained model is used to realize fast AOA recognition according to the channel snapshots collected by antenna array. Furthermore, the performance is verified under the different conditions of SVM parameters, training features, antenna numbers, and training data sizes. The experimental results show that the proposed method has satisfactory accuracy in real-time AOA recognition, and the optimal configuration and implementation scheme are also discussed.

A switchable multi-wavelength erbium-doped fiber laser (EDFL) based on parallel dual Lyot filters is experimentally demonstrated in this paper. A new type of parallel-structure fiber filter is designed and its spectrum is simulated. The structure is simple. The spectra of the filter changes when adjusting the polarization states of the polarization controllers (PCs). Due to the characteristics of the filter spectra and wavelength competition, the output wavelengths can be single wavelength, dual wavelengths and three wavelengths. When the output is single wavelength, the wavelength range is tunable with a tuning range of ~13 nm. The wavelength interval of dual wavelengths can be adjusted from 3.03 nm to 17.15 nm, which is a relatively wide range. The interval of three wavelengths also changes to some extent. Moreover, the optical signal-to-noise ratios (OSNRs) of the output wavelengths can up to 47 dB.

The emerging 6G network envisions integrated sensing and communication (ISAC) as a promising solution to meet growing demand for native perception ability. To optimize and evaluate ISAC systems and techniques, it is crucial to have an accurate and realistic wireless channel model. However, some important features of ISAC channels have not been well characterized, for example, most existing ISAC channel models consider communication channels and sensing channels independently, whereas ignoring correlation under the consistent environment. Moreover, sensing channels have not been well modeled in the existing standard-level channel models. Therefore, in order to better model ISAC channel, a cluster-based statistical channel model is proposed in this paper, which is based on measurements conducted at 28 GHz. In the proposed model, a new framework based on 3GPP standard is proposed, which includes communication clusters and sensing clusters. Clustering and tracking algorithms are used to extract and analyze ISAC channel characteristics. Furthermore, some special sensing cluster structures such as shared sensing cluster, newborn sensing cluster, etc., are defined to model correlation and difference between communication and sensing channels. Finally, accuracy of the proposed model is validated based on measurements and simulations.

A photonic-assisted approach for instantaneous frequency measurement based on optical power monitoring is proposed and demonstrated. Instead of using optical filter, a dual-polarization Mach-Zehnder modulator is used to modulate the unknown RF signal with a designed electrical time delay. Due to the property of electrical time delay, the frequency information is firstly converted to phase shift and then to the optical power. By monitoring the optical power, a monotonic relationship between the incident microwave frequency and optical power ratio can be easily established. A detailed theoretical analysis is carried out to illustrate the mechanism of the proposed instantaneous frequency measurement setup. Simulation has been performed to investigate the tuning of measurement range and the impact of imperfection devices. A proof-of-concept experiment has been carried out to verify the mechanism.

A novel individually switchable, widely tunable and interval-adjustable multi-wavelength erbium-doped fiber laser (EDFL) is experimentally demonstrated in this paper. It is based on the cascaded structure of SMF-TMF-SMF (STS) filter and Lyot filter with the assistance of nonlinear polarization rotation (NPR). The homemade STS filter is a comb filter that formed by splicing a section of two-mode fiber (TMF) and two segments of single-mode fiber (SMF) with core-offset structures. Compared with other multimode interferences, the spectrum of STS filter is more uniform. When inserted into the laser cavity, this comb filter functions as the wavelength selector with wavelength interval of ~0.8 nm. The insertion loss of the filter is only ~0.4 dB. By properly adjusting the polarization controllers (PCs) in the laser cavity, individually switchable wavelengths with different flexible lasing states can be obtained, such as tunable adjacent single-, dual-, triple-, quadruple- and quintuple-wavelength outputs. The tuning range can up to 30 nm, from 1530 nm to 1560 nm. When the number of output wavelengths is 1~3, the tuning process can keep the step size of 0.8 nm or 1.6 nm. The non-adjacent dual- and triple-wavelength outputs, as well as adjacent sextuple- and septuple-wavelength outputs can also be achieved. The output characteristics, such as flexible switchability and tunability, are difficult to implement by other methods.