In this paper, a novel three-dimensional (3D) geometry-based stochastic model (GBSM) and a beam domain channel model (BDCM) for sixth-generation (6G) millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) systems are proposed. The spherical wavefront and space-time-frequency non-stationarity introduced by massive MIMO, movements of the user and clusters, and large bandwidth of mmWave communications are incorporated. The shared clusters between the sensing channel and communication channel caused by the scattering characteristics are also considered. Based on the proposed channel model, important statistical properties are derived and simulated, including the space-time-frequency correlation function (STF-CF), root mean square (RMS) beam spread, RMS delay spread, RMS Doppler spread, coherence time, and channel capacity. By comparing the statistical properties of the sensing channel and the communication channel, it is found that the sensing channel exhibits more significant temporal non-stationarity. Moreover, the distribution of clusters for the sensing channel and communication channel shows significant difference, which is confirmed by the simulation results of RMS beam spread and RMS delay spread.

Integrated sensing and communication (ISAC) has attracted wide attention as an emerging application scenario for the sixth generation (6G) wireless communication system. In this paper, a novel three-dimensional (3D) non-stationary localization-assisted ISAC geometry-based stochastic model (GBSM) is proposed. The locations of the first-bounce scatterer and last-bounce scatterer in the communication channel can be estimated by the particle filter with the assistance of backscattering sensing. The important channel statistical properties of the proposed channel model are simulated and compared with the ray tracing (RT) results, including the delay spread, azimuth angle of departure/arrival (AAoD/AAoA) spread, and elevation angle of departure/arrival (EAoD/EAoA) spread. The simulation results of the proposed channel model show a good agreement with the RT results, which proves the correctness of the proposed channel model. Utilizing the localization parameters of scatterers, the proposed ISAC channel model can better map the real environment.

The integrated sensing and communication (ISAC) refers to the integration of radio sensing and wireless communications to realize the multiplexing of space, time, and frequency resources. In the sixth generation (6G) wireless networks, ISAC is considered as one of the most promising technologies. In this paper, a novel ISAC channel model combining forward and backward scattering is proposed. In addition to the non-stationarity caused by motions, the correlations between sensing and communication channels are investigated. The channel characteristics of sensing such as forward scattering and backward scattering are introduced into the communication channel model. Utilizing the correlations between sensing and communication channels, the communication channel model is divided into line-of-sight (LOS), forward scattering, and backward scattering components. These three components are summed according to probability weighting to obtain a more accurate channel model for sensing assisted communication systems. Moreover, important statistical properties of the proposed ISAC channel model are derived and simulated. The analytical and simulation results match well, demonstrating the correctness of derivations and simulations. Some derived/simulated statistical properties are verified by corresponding measurement data, which indicates the utility of the proposed ISAC channel model.

Orbital angular momentum (OAM) is regarded as a key technology of the sixth generation (6G) wireless communication systems. The vortex wave is a typical application of OAM. In this paper, a novel time-varying three-dimensional (3D) geometry-based stochastic model (GBSM) for a multiple-input multiple-output (MIMO) system employing the vortex wave is proposed. This model supports all kinds of OAM antennas that generate the vortex wave and introduces a spiral phase term to represent the helical wavefront of the vortex wave. To better reveal characteristics of the OAM-based MIMO system, some important statistical properties like temporal autocorrelation function (ACF) and spatial cross-correlation function (CCF) are derived and analyzed. Non-negligible impacts on the temporal ACF caused by OAM antennas are revealed. The results illustrate that the OAM-based MIMO system can help decrease spatial CCF, especially in the environment that angular spreads are small. Characteristics analyzed in this paper are important for future OAM communication systems.

A general three-dimensional (3D) non-stationary massive multiple-input multiple-output (MIMO) geometry-based stochastic model (GBSM) for the sixth generation (6G) communication systems is proposed in the paper. The novelty of the model is that the model is designed to cover a variety of channel characteristics, including space-time-frequency (STF) non-stationarity, spherical wavefront, spatial consistency, channel hardening, etc. Firstly, the introduction of the twin-cluster channel model is given in detail. Secondly, the key statistical properties such as space-time-frequency correlation function (STFCF), space cross-correlation function (CCF), temporal autocorrelation function (ACF), frequency correlation function (FCF), and performance indicators, e.g., singular value spread (SVS), and channel capacity are derived. Finally, the simulation results are given and consistent with some measurements in relevant literatures, which validate that the proposed channel model has a certain value as a reference to model massive MIMO channel characteristics.