The fifth generation (5G) mobile communication systems will be in use around 2020. The aim of 5G systems is to provide anywhere and anytime connectivity for anyone and anything. Several new technologies are being researched for 5G systems, such as massive multiple-input multiple-output (MIMO) communications, vehicle-to-vehicle (V2V) communications, high-speed train (HST) communications, and millimeter wave (mmWave) communications. Each of these technologies introduces new propagation properties and sets specific requirements on 5G channel modeling. Considering the fact that channel models are indispensable for system design and performance evaluation, accurate and efficient channel models covering various 5G technologies and scenarios are urgently needed. This paper first summarizes the requirements of the 5G channel modeling, and then provides an extensive review of the recent channel measurements and models. Finally, future research directions for channel measurements and modeling are provided.

Millimeter wave (mmWave) bands have been utilized for the fifth generation (5G) communication systems and will no doubt continue to be deployed for beyond 5G (B5G). However, the underlying channels are not fully investigated at multi-frequency bands and in multi-scenarios by using the same channel sounder, especially for the outdoor, multiple-input multiple-output (MIMO), and vehicle-to-vehicle (V2V) conditions. In this paper, we conduct multi-frequency multi-scenario mmWave MIMO channel measurements with 4×4 antennas at 28, 32, and 39 GHz bands for three cases, i.e., the human body and vehicle blockage measurements, outdoor path loss measurements, and V2V measurements. The channel characteristics, including blockage effect, path loss and coverage range, and non-stationarity and spatial consistency, are thoroughly studied. The blockage model, path loss model, and time-varying channel model are proposed for mmWave MIMO channels. The channel measurement and modeling results will be of great importance for further mmWave communication system deployments in indoor hotspot, outdoor, and vehicular network scenarios for B5G.

In order to provide reliable and efficient connections between unmanned aerial vehicles (UAVs) and ground stations (GSs), realistic UAV-to-ground channel models are indispensable. In this article, we propose a novel 3-D nonstationary geometry-based stochastic model (GBSM) for UAV-to-ground multiple-input-multiple-output (MIMO) channels. Distinctive UAV-to-ground channel characteristics, such as time-domain nonstationarity, distinctions between different altitudes, spatial consistency, and 3-D arbitrary UAV movement trajectories, are taken into account. By adjusting parameter settings, the proposed channel model framework is sufficiently general to support multiple frequency bands and multiple scenarios, including millimeter wave (mmWave) and massive MIMO configurations. Statistical properties, including power delay profile (PDP), stationary interval, space-time correlation function (STCF), and root-mean-square (RMS) delay spread are derived and analyzed for different frequencies and scenarios. The accuracy of the proposed model is validated by comparing its statistical properties with corresponding available channel measurements. The proposed channel model will provide a fundamental support for the design, performance evaluation, and optimization of future UAV integrated sixth-generation (6G) wireless networks.

In fifth generation (5G) wireless communications, high-speed train (HST) communications is one of the most challenging scenarios. By adopting massive multiple-input multiple-output (MIMO) and millimeter wave (mmWave) technologies into HST communications, the underlying communication system design becomes more challenging and some new channel characteristics have to be studied, such as the non-stationarities in space, time, and frequency domains. This paper proposes a novel three-dimensional space-time-frequency non-stationary mmWave massive MIMO theoretical model, as well as a corresponding simulation model for 5G HST wireless channels based on WINNER II and Saleh-Valenzuela channel models. Cluster evolutions in space, time, and frequency domains are proposed and analyzed to ensure the models' non-stationarities in three domains. Moreover, based on the proposed channel models, important time-variant channel statistical properties are investigated, such as the time autocorrelation function, space cross-correlation function, delay power spectrum density (PSD), angular PSD, and frequency correlation function. Results indicate that the statistical properties of the simulation model, verified by simulation results, can match well with those of the theoretical model.