QuaDRiGa: A 3-D Multi-Cell Channel Model With Time Evolution for Enabling Virtual Field Trials

Abstract

Channel models are important tools to evaluate the performance of new concepts in mobile communications. However, there is a tradeoff between complexity and accuracy. In this paper, we extend the popular Wireless World Initiative for New Radio (WINNER) channel model with new features to make it as realistic as possible. Our approach enables more realistic evaluation results at an early stage of algorithm development. The new model supports 3-D propagation, 3-D antenna patterns, time evolving channel traces of arbitrary length, scenario transitions and variable terminal speeds. We validated the model by measurements in a coherent LTE advanced testbed in downtown Berlin, Germany. We then reproduced the same scenario in the model and compared several channel parameters (delay spread, path gain, K-factor, geometry factor and capacity). The results match very well and we can accurately predict the performance for an urban macro-cell setup with commercial high-gain antennas. At the same time, the computational complexity does not increase significantly and we can use all existing WINNER parameter tables. These artificial channels, having equivalent characteristics as measured data, enable virtual field trials long before prototypes are available.

Millimeter Wave Communications for Future Mobile Networks

“…5) QuaDRiGa Model [107]: As an open source implementation of the 3GPP-3D channel model, the QuaDRiGa channel model is further extended with the features of spatial consistency (to accurately evaluate the performance of massive MIMO) and multi-cell transmissions by exploiting the approach in SCM-E and COST 273.…”

Robust full-dimension MIMO transmission based on limited feedback angular-domain CSIT

“…In these simulations we consider a simple Rician-fading channel model, which allows to easily control the compressibility of the CSI in the angular domain via the Rician K-factor. In Section 6.3, we then utilize the more realistic QUADRIGA channel model [76] to compare the proposed leakage-bounded angular precoding methods to the interference-aware precoding methods summarized in Section 5.2 4 . We first of all evaluate the compressibility of the channel realizations obtained from QUADRIGA in the angular domain.…”

Phase Noise Effect on MIMO-OFDM Systems with Common and Independent Oscillators

“…Nevertheless, the conclusion also holds for spatially correlated MIMO channels. To demonstrate this, we assume a uniform linear array with half-wavelength interelement distance at both Tx and Rx and introduce antenna correlations at both sides using the Kronecker channel model with the Bessel correlation function 0 (2 / ) [34], where 0 is the zeroth-order Bessel function of the first kind, is the distance between the th and th antenna elements in the Tx (or Rx) array, and is the wavelength. The corresponding results are shown in Figure 4(c).…”