Abstract
The performance of a multi-user multiple-input multiple-output (MIMO) system is mainly determined by the correlation of user channels. Applying channel models without spatial correlation or spatially inconsistent channel models for performance analysis leads to an under-estimation of spatial correlation and therefore to overly optimistic system performance. This is especially pronounced when the wireless channel is modeled as i.i.d. Rayleigh fading for users in a rich scattering environment, for example, for indoor users. To analyze the spatial channel correlation in massive MIMO systems, we performed wireless channel measurements in three different scenarios. In each scenario, we measure 148 receiver positions, spread over a length of almost 9m. Since the wireless channel statistics change with receiver position, we perform a stationarity analysis. We provide a statistical analysis of the measured channel in terms of amplitude distribution and user-side spatial correlation within the region of stationarity. This analysis shows that, even for a deep-indoor user location, the spatial correlation is significantly higher compared to a Rician channel model with the same $K$ factor. We model the measured channel by means of a Rician channel model and a spatially consistent channel model, which is based on the scenario geometry, to provide an insight for the observed propagation phenomena. Results show that the user correlation is not negligible for massive MIMO in outdoor-to-indoor scenarios. The achievable spectral efficiency with linear precoding is 20% lower compared to the Rician channel model, even for large inter-user distances of 6m.
Highlights
The challenge to meet all requirements of envisioned future mobile communications networks is manifold
We show that the achievable spectral efficiency of two users in an outdoorto-indoor massive multiple-input multiple-output (MIMO) system is 20% lower compared to a Rician channel model with the same K factor, even at large inter-user distances of 6 m
The amount of spatial correlation and the decorrelation behavior with distance are mainly determined by the location of scattering objects visible to the receiver
Summary
The challenge to meet all requirements of envisioned future mobile communications networks is manifold. Typical use cases for 5th generation (5G) mobile communications and beyond are: ultra-reliable low-latency communication (uRLLC) for mission critical applications such as vehicularto-vehicular (V2V) communication, enhanced mobile broadband (eMBB) to meet the steadily increasing demand for data volume and data rate, and massive machine type communication (mMTC) for the implementation of the Internet of things (IoT). Challenges is enhancing the well-established technology of MIMO communication to a large-scale, which is referred to as massive MIMO [1], [2]. Since a large-scale antenna array at the BS leads to channel hardening in a wireless fading channel, the reliability and latency are enhanced when scaling up a MIMO system with respect to the number of BS antennas [6]. For indoor mobile users, an uncorrelated i.i.d. channel model
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