We propose a general framework for the specification of a sparse representation of millimeter wave vehicular propagation channels and apply this to both synthetic data and real-world observations from channel sounding experiments. The proposed framework is based on the c-LASSO (complex Least Absolute Shrinkage and Selection Operator) which minimizes the mean squared error of the sparse representation for a given number of degrees of freedom. By choosing the number of degrees of freedom, we balance the numerical complexity of the representation in the channel emulation against its accuracy in terms of the mean squared error. A key ingredient is the choice of basis of the representation and we discuss two options: the Fourier basis and its projection onto a given subband. The results indicate that the subband-projected Fourier basis is a low-complexity choice with high fidelity for representing clustered channel impulse responses. Finally, a sequential estimator is formulated which enforces a consistent temporal evolution of the geometry of the interacting objects in the propagation environment. We demonstrate the performance of our approach using both synthetic data and measured 60 GHz vehicular channel traces.
Millimeter Wave Vehicular Channel Emulation: A Framework for Balancing Complexity and Accuracy
