Multiple-input-multiple-output (MIMO) has been a promising technology in wireless communication systems. Channel models are of great importance for the development and assessment of system. With the increase of carrier frequency and MIMO size, the channel model needs to consider near-field spherical wave and spatial non-stationary characteristics, which is different from conventional far-field planar-wave-based geometry-based stochastic model (GBSM) in the 3rd Generation Partnership Project (3GPP). This paper focuses on comparing the channel characteristics and modeling in the far- and near-field region. In this work, we design the measurement campaign in the 6 GHz band (5.9-6.1 GHz) involving the unlicensed spectrum. The uniform planar array (UPA) is adopted from far-field to near-field, where the communication distance is decreasing from 21 m to 6 m (Rayleigh distance is about 14.8 m). Compared to the far-field, the spatial non-stationary phenomenon of channel parameters can be more clearly observed along the array in the near-field region. Then, we propose the extension channel model based on the channel modeling of 3GPP TR 38.901. The array domain is introduced to characterize the spatial non-stationarity of channel parameters (e.g., power, delay, angle). Subsequently, the channel characteristic parameters along the array are analyzed in the near-field range, and the non-stationary model related to the antenna array is established, including power, path loss, delay spread, angular spread, and Ricean K-factor. Finally, the model validation and parametrization are presented in detail with the actual indoor near-field MIMO channel measurements in the 6 GHz band, such as power, angle, and so on. The design and scheme of antenna array spacing are given under the influence of spatial non-stationary characteristics. These work will be helpful for the development and operation of MIMO technology in unlicensed spectra for wireless communication systems.

Extremely large-scale massive multiple-input multiple-output (XL-MIMO) is a potential enabling technology for 6th-generation (6G) communication. The XL-MIMO channel research will be important for XL-MIMO system development. In this paper, the measurement of XL-MIMO channels from 32 to 512 transmitting antenna elements in the 6 GHz band is carried out in an indoor corridor scenario. The delay spread, angular spread, and channel capacity are investigated. The results are compared with the indoor channel model in the Third Generation Partnership Project (3GPP) TR 38.901. We find that the number of antenna elements has a small impact on the delay spread and angular spread. So the spatial non-stationary effect does not need to be considered specifically in the far-field range in this scenario. In addition, the special structure of the corridor leads to a difference in the comparison of the angular spread with the 3GPP model in each dimension. The closed environment of the corridor also results in a significant gap in channel capacity performance from the i.i.d. channel. This work can provide insights into XL-MIMO applications in the 6G era.

Extremely Large-Scale Multiple-Input-Multiple-Output (XL-MIMO) communication, is recognized as a potential enabling technology for sixth-generation (6G) communication. Due to the large antenna aperture of XL-MIMO, spatial non-stationary (SnS) phenomena may occur on the array domain during deployment. This paper, relying on Ray-tracing (RT) simulations, analyzes the SnS phenomena from various perspectives of channel characteristics. Meanwhile, to accurately model the SnS phenomenon, this paper proposes a method for stationary sub-interval partitioning based on channel characteristics. It is assumed that the channel is stationary within each sub-interval, while it is non-stationary across different intervals. The method comprehensively considers factors such as channel correlation, delay spread (DS), azimuth angle spread of departure (ASD), and multipath components (MPCs) birth-death for sub-interval partitioning. By analyzing the independence of sub-intervals, this paper demonstrates that the proposed method performs better in sub-interval partitioning compared to the traditional averaging approach.

Extremely-large-scale multiple-input multiple-output (XL-MIMO) technology, offering vast spatial degrees of freedom by deploying a huge number of antennas, is a promising enabling technology to empower sixth-generation mobile networks (6G). The XL-MIMO channel model is a prerequisite of XL-MIMO technology optimization, system design, and performance evaluation. In this paper, we provide an overview of challenges and ongoing research in XL-MIMO channel measurement, characterization, and modeling. In particular, characterizing and modeling near-field effects and spatial non-stationarity (SnS) are discussed. Also, the channel modeling methods that can describe these new channel characteristics are surveyed. Furthermore, open issues in XL-MIMO channel measurement, characterization, and modeling are presented to give insights into future XL-MIMO channel research.