3D vs. 2D channel models: Spatial correlation and channel capacity comparison and analysis

Three dimensional (3D) Multiple Input and Multiple Output (MIMO) is one of the most promising techniques for the 5th Generation (5G) mobile communication systems. Thus there is an urgent need for one reliable 3D MIMO channel model to research and evaluate 3D MIMO techniques. In this paper, we focus on the statistic characteristics of elevation angle in urban microcell (UMi) and propose a novel elevation angle modeling methodology. In order to capture enough 3D channel characteristics, field 3D channel measurements at 3.5 GHz with 100 MHz bandwidth are conducted in UMi scenario. Based on the existing 3D channel model frame, the proposed elevation angle model is introduced and the updated 3D channel model is used to perform channel capacity analysis. Comparisons among the updated 3D channel model, the traditional two dimensional (2D) channel model and the field 3D channel data are made. The updated 3D channel model obtains obvious capacity gain compared with 2D channel model. The proposed elevation angle model and the updated 3D channel model can optimally match the channel capacity of the real 3D channel data.

Multi-antenna techniques capable of exploiting the elevation dimension are anticipated to be an important air-interface enhancement targeted to handle the expected growth in mobile traffic. In order to enable the development and evaluation of such multi-antenna techniques, the 3rd generation partnership project (3GPP) has recently developed a 3-dimensional (3D) channel model. The existing 2-dimensional (2D) channel models do not capture the elevation channel characteristics lending them insufficient for such studies. This article describes the main components of the newly developed 3D channel model and the motivations behind introducing them. One key aspect is the ability to model channels for users located on different floors of a building (at different heights). This is achieved by capturing a user height dependency in modelling some channel characteristics including pathloss, line-of-sight (LOS) probability, etc. In general this 3D channel model follows the framework of WINNERII/WINNER+ while also extending the applicability and the accuracy of the model by introducing some height and distance dependent elevation related parameters.

Three dimensional (3D) Multiple Input and Multiple Output (MIMO) is one of the most promising techniques for the 5th generation (5G) mobile communication system. To support its research, the property of elevation angle in 3D channel model should be accurately modeled. Conventionally, 3D channel is modeled with an assumption that the mean elevation angle of multipaths is coincided with the line-of-sight (LOS) direction. In order to investigate its authenticity and give the reliable 3D channel model, extensive 3D multiple antenna field channel measurements with 100 MHz bandwidth are conducted in three typical scenarios, including outdoor to indoor(O2I), urban microcell (UMi) and urban macrocell (UMa). The statistical characteristics and parameters are extracted and analyzed based on the measurement data. It is found that the assumption holds in the LOS condition. However, for non-line-of-sight (NLOS) condition, a difference exists between the mean elevation angle and the direction connecting transmitter and receiver, which is defined as the elevation angle offset. Then, the eigenvalue distribution and capacity are compared between the reconstructed 3D channels with and without elevation angle offset. Results show that the performance of 3D channel with angle offset fits the measurement data better whereas that without angle offset is underestimated.

Elevation beamforming and Full Dimension MIMO (FD-MIMO) are currently active areas of research and standardization in 3GPP LTE-Advanced. FD-MIMO utilizes an active antenna array system (AAS), that provides the ability of adaptive electronic beam control over the elevation dimension, resulting in a better system performance as compared to the conventional 2D MIMO systems. FD-MIMO is more advantageous when amalgamated with massive MIMO systems, in that it exploits the additional degrees of freedom offered by a large number of antennas in the elevation. To facilitate the evaluation of these systems, a large effort in 3D channel modeling is needed. This paper aims at providing a summary of the recent 3GPP activity around 3D channel modeling. The 3GPP proposed approach to model antenna radiation pattern is compared with the ITU approach. A closed-form expression is then worked out for the spatial correlation function (SCF) for channels constituted by individual antenna elements in the array by exploiting results on spherical harmonics and Legendre polynomials. The proposed expression can be used to obtain correlation coefficients for any arbitrary 3D propagation environment. Simulation results corroborate and study the derived spatial correlation expression. The results are directly applicable to the analysis of future 5G 3D massive MIMO systems.

Three dimensional (3D) Multiple Input Multiple Output (MIMO) is considered as one key technology for 5th Generation mobile communication systems. However, can the capacity derived from a 3D channel impulse response (CIR) better approximate the corresponding capacity derived from the measured CIR? Is there a substantial improvement in the capacity of 3D MIMO system in comparison to the classical 2D case? To answer these questions, extensive field measurements were conducted for the outdoor to indoor scenarios in China and New Zealand. Key channel parameters are extracted from the measured channel impulse response via the space-alternating generalized expectation-maximization algorithm, followed by the reconstruction of the 32 × 56 CIR according to 2D and 3D channel model. Then CIRs are used to evaluate the channel capacity and comparative simulation results demonstrate that the 3D MIMO capacity closely approximates the capacity predicted with practical CIRs. Moreover, obvious enhancements in the capacity of 3D channel is observed in comparison to 2D case. In addition, the distribution of eigenvalues and the number of contributing eigenvalues are also investigated.

This paper provides the emulated channel transfer functions for the plane wave synthesis (PWS) and the prefaded signals synthesis (PFS) in 3D multi-probe anechoic chamber (MPAC) setups. Furthermore, the emulated spatial correlation functions (SCFs) for the two methods are deduced according to the respective channel transfer functions. The expressions derived in this paper are applicable for any spherical power spectrum. The target channel model utilized in this paper is 3D geometry-based stochastic channel models. The accuracies of the 3D emulated channel models with PWS and PFS in terms of the root mean square (rms) of the SCF error under different 3D channel settings are investigated. Some new conclusions about the two methods are obtained. Simulation results demonstrate that PWS proceeds PFS for most channel settings in 3D MPAC setups. Especially when the mean zenith angle of arrival of the cluster is not from the horizontal plane, PWS provides more accurate results. In addition, the relationship between the emulation accuracy and the zenith angle spread of arrival of the cluster is different from that between the emulation accuracy and the azimuth angle spread of arrival of the cluster.

The use of millimeter-wave (mmWave) and full-dimensional multiple-input multiple-output (FD-MIMO) antenna systems for 3D wireless communication is being exploited for enhanced network capacity improvement in the ongoing fifth-generation (5G) deployment.For adequate assessment of competing air interface, random access channelization, and beam alignment procedure in mmWave systems, adequate channel estimation and channel models for different use scenarios are necessary.Conventional pilot-based channel estimation methods are remarkably timeconsuming as the number of users or antennas tends toward large numbers.Channel reconstruction has been identified as one of the solutions to the above problem.In this work, a ray-tracing study was conducted using a Wireless Insite ray tracing engine to predict measured statistics for large-scale channel parameters (LSPs).Other LSP such as the shadow fading (SF) were generated using algorithm 1. Algorithm 2 was used to generate the small-scale channel parameters (SSP).The LSPs and SSPs were used as input in algorithm 3 to generate the channel coefficients used for the channel reconstruction in the MATLAB LTE toolbox.The results provided an accurate reconstructed downlink channel state information (CSI) for FDD-based mmWave massive-MIMO system in both the line-of sight (LOS) and non-line of sight scenarios.The results provide an opportunity to adapt the transmitted signal to the CSI and thereby optimize the received signal for spatial multiplexing or to achieve low bit error rates in wireless communication.

A 3D Massive MIMO Channel Model for Vehicle-to-Vehicle Communication Environments

Scalable Multi‐antenna systems are designed to gain improvement in energy and spectral efficiency under different propagation conditions by equipping the BSs with hundreds or even more antennas. A better understanding of such systems leads to overcome the essential challenges, which is important for the beneficial deployment in future networks. In wireless communication systems, channel models describe the main characteristics of the propagation environment and are essential for systems performance evaluation. This article considers a multi‐cell large scale multiuser MIMO (LS‐MU‐MIMO) system with a physical correlated channel model and linear‐based MMSE estimator and detector. A physical local scattering geometric‐based stochastic channel model for dense urban and suburban scenarios is presented in this article to illustrate the impact of propagation environment on signal transmission in a general framework of antenna spatial correlation. Also, a pilot signaling‐based channel estimation in the uplink scenario, the effect of pilot contamination (PC), and spatial correlation on the channel estimation are studied. The effect of PC and channel estimation on the performance of LS‐MU‐MIMO system is investigated by applying MMSE‐based channel estimator and detector over uniform linear arrays (ULA) of BS antennas in different scattering environments. Moreover, different pilot reuse patterns are considered, and their impact on the average sum SE has been investigated. The simulation results show that LS‐MU‐MIMO system can provide higher performance for dense urban scenarios where the user terminals (UTs) have limited mobility and higher coherence time than suburban scenarios. Furthermore, while higher spatial correlation will result in improvement in the channel estimation quality, it contributes imperfectly to the channel hardening effect.

Millimeter-wave (mmW) carrier frequencies offer new opportunities to build new antenna concepts, however these high frequencies make it nearly impossible to build an omnidirectional antenna. Therefore, it is important to model the position, the rotation of the UE and the surface orientation of the connected antennas. It is also important to consider the corresponding anisotropy in the channel modeling. Especially a three-dimensional (3D) channel model taking dual polarization effects into account is required and shall be illustrated in this communication. Therefore, Radio Frequency (RF) based pattern simulation is combined with the base band link-level simulator.

In the future work of long-term evolution for railway (LTE-R), a better understanding of the antenna array configu-rations is required. This paper primarily proposes the extension of 2D clustered channel model to 3D circumstance by getting elevation angle involved. Based on the presented 3D channel model, the attainable capacity/diversity gain is simulated by laying out different antenna arrays in 3D space. The impact of different antenna array configurations in 3D high speed railway scenario is studied. Our results show that antenna arrays which take advantage of elevation direction provide better MIMO system performance in high speed railway scenario.

It is envisioned that the sixth generation (6G) and beyond 6G (B6G) wireless communication networks will enable global coverage in space, air, ground, and sea. In such networks, both base stations and users can be mobile and will tend to move continuously in three-dimensional (3D) space. Therefore, obtaining channel state information (CSI) in 3D continuous-space is crucial for the design and performance evaluation of future 6G and B6G wireless systems. On the other hand, new 6G technologies such as integrated sensing and communications (ISAC) will also require prior knowledge of CSI in 3D continuous-space. In this paper, a 3D continuous-space electromagnetic channel model is proposed for tri-polarized multi-user communications, taking into account scatterers and spherical wavefronts. Scattered fields are calculated using the method of moments (MoM) with high accuracy. Spherical wave functions are utilized to decompose the dyadic Green’s functions that connect the transmitted source currents and the received electric fields. Simulation results demonstrate that transmit power, apertures, scatterers, and sample intervals have significant impacts on statistical properties and channel capacities, providing insights into the performance of continuous-space electromagnetic channel models and the design of future wireless systems.

Although the three-dimensional (3D) channel model considering the elevation factor has been used to analyze the performance of multiuser multiple-input multiple-output (MU-MIMO) systems, less attention is paid to the effect of the elevation variation. In this paper, we elaborate the sum rate of MU-MIMO systems with a 3D base station (BS) exploiting different elevations. To illustrate clearly, we consider a high-rise building scenario. Due to the floor height, each floor corresponds to an elevation. Therefore, we can analyze the sum rate performance for each floor and discuss its effect on the performance of the whole building. This work can be seen as the first attempt to analyze the sum rate performance for high-rise buildings in modern city and used as a reference for infrastructure.

The demand for optimization design and performance evaluation of wireless communication links in a mobile Internet of Things (IoT) motivates the exploitation of realistic and tractable channel models. In this paper, we develop a novel three-dimensional (3D) multiple-antenna channel model to adequately characterize the scattering environment for mobile IoT scenarios. Specifically, taking into consideration both accuracy and mathematical tractability, a 3D double-spheres model and ellipsoid model are introduced to describe the distribution region of the local scatterers and remote scatterers, respectively. Based on the explicit geometry relationships between transmitter, receiver, and scatterers, we derive the complex channel gains by adopting the radio-wave propagation model. Subsequently, the correlation-based approach for theoretical analysis is performed, and the detailed impacts with respect to the antenna deployment, scatterer distribution, and scatterer density on the vital statistical properties are investigated. Numerical simulation results have shown that the statistical channel characteristics in the developed simulation model nicely match those of the corresponding theoretical results, which demonstrates the utility of our model.

Insight into a wireless channel using a geometry-based three-dimensional (3D) channel model and its stochastic characterization is given in this paper. It is considered that the outdoor wireless channel is equipped with cooperative double (CODE), simultaneously transmitting and reflecting a reconfigurable intelligent surface (STAR-RIS). Other system elements include multiple-input multiple-output (MIMO) system realized using a transmitter (Tx), two distributed STAR-RISs and two users, U R and U T . To use the advantage of 360 0 coverage area of STAR-RIS, users are positioned on transmit-side ( U T ) and reflect-side ( U R ) of STAR-RIS. It is presumed that STAR-RIS operates with the energy splitting (ES) protocol as the underlying mechanism. Space-time cross-correlation function (ST-CCF) is an important time-domain performance measure to characterize a wireless channel. ST-CCF is estimated for parametric variations in the normalized antenna spacing of Tx, U R / U T , position of STAR-RIS, array size of the STAR-RIS and its orientation with respect to the azimuth plane. Simulation results are analyzed in terms of leverage from cooperative STAR-RIS deployment and its practical inferences.