Enhancing the Resolution of the Spectrogram of Non-Stationary Mobile Radio Channels by Using Massive MIMO Techniques

Abstract

This paper is concerned with the enhancement of the resolution of the spectrogram of non-stationary mobile radio channels using massive multiple-input multiple-output (MIMO) techniques. By starting from a new generic geometrical model for a non-stationary MIMO channel, we derive the complex MIMO channel gains under the assumption that the mobile station (MS) moves with time-variant speed. Closed-form solutions are derived for the spectrogram of the complex MIMO channel gains by using a Gaussian window. It is shown that the window spread can be optimized subject to the MS's speed change. Furthermore, it is shown that the spectrogram can be split into an auto-term and a cross-term. The auto-term contains the useful time-variant spectral information, while the cross-term can be identified as a sum of spectral interference components, which restrict considerably the time-frequency resolution of the spectrogram. Moreover, it is shown that the effect of the cross-term can be drastically reduced by using massive MIMO techniques. The proposed method is not only important for estimating timevariant Doppler power spectra with high resolution, but it also pioneers the development of new passive acceleration/deceleration estimation methods and the development of new non-wearable fall detection systems.