To meet the required coverage and data rate demands of next-generation mobile communications, the coexistence of multiple radio frequency systems operating in well-separated frequency bands in precisely identified scenarios will be exploited in the long term. In this context, it is necessary to investigate frequency-dependent and environment-dependent channel characteristics by exploring the spatial and temporal correlations of multipath channels across different frequency bands and different environments. Traditional evaluation indexes, such as channel parameters and correlation coefficients, either do not enable direct derivation of the relationship between two channels or can only be evaluated from a certain dimension mathematically. Here, by combining large-scale and small-scale channel characteristics, a channel similarity index measure (CSIM) is proposed. This structural similarity index comprehensively considers several multipath parameters of two different channels, including amplitude, phase, delay, angle of arrival (AoA), and angle of departure (AoD). The results of ray tracing simulations and field measurement campaigns conducted across both centimeter wave (cmWave) and millimeter wave (mmWave) bands in typical indoor and outdoor scenarios verify that the proposed CSIM can effectively measure similarity from specific dimensions. Moreover, the statistical distributions of the CSIM, which reflect the similarities between channels of different frequencies, are also presented.

Empirical channel modeling is necessary for the deployment of the fifth-generation (5G) millimeter-wave (mmWave) cellular system in actual environments. In this paper, cluster-based analyses of mmWave channel characteristics in two typical dense urban environments are performed. First, radio propagation measurement campaigns are conducted at two primary 5G bands of 28 GHz and 39 GHz in a central business district and a dense residential area. The custom-designed channel sounder supports high-efficiency directional scanning sounding, which helps to collect sufficient data for statistical channel modeling. Next, using an improved autoclustering algorithm, multipath clusters and their scattering sources are identified. Mapping results show that multiple reflections from exterior walls and diffraction over building corners or rooftops enhance the coverage for non-line-of-sight (NLoS) links and the influences of these propagation mechanisms are intuitively embodied as changes in the topologies of deployment environments. Finally, an appropriate measure for cluster-level channel characteristics is provided including cluster number, Ricean K-factor, root mean squared (RMS) delay spread, RMS angular spread, and their correlations. Comparisons of these parameters across two mmWave bands are also given. The measurement and modeling results shed light on a fully understanding of mmWave channels in dense urban environments across multiple bands.

The clustered delay line channel model, in which each cluster consists of a number of rays, is widely used for link-level evaluations in mobile communications. Multiple parameters of each ray, including delay, amplitude, cross polarization ratio (XPR), initial phases of four polarization combinations and the azimuth and elevation angles of arrival and departure, shall be known. These parameters are measured using a channel sounder. The number of rays in every cluster is usually greater than the number of elements in the antenna array of the channel sounder, which represents a challenging issue in multipolarized channel measurements. A new subspace estimation method based on the broadband extended array response of an electromagnetic vector antenna array is proposed to resolve a large number of rays. The interelement spacing of the array can be greater than half the carrier wavelength, which reduces interelement coupling and simplifies the array design, especially for millimeter wave bands. First, the delay of each cluster is estimated using the reference antenna element. Then, the 2D angles of every ray are estimated using the classic rank-deficient multiple signal classification (MUSIC). Lastly, the initial phases, XPR and amplitude of every ray is estimated. Simulation results validate the proposed method.