Massive MIMO channel estimation taking into account spherical waves

Together with millimiter waves (mmWaves), massive multiple-input multiple-output (MIMO) systems are key technological components of fifth generation (5G) wireless communication systems. In such a context, geometric considerations show that the largely adopted plane wave model (PWM) of the channel potentially loses its validity. An alternative is to consider the more accurate but more complex spherical wave model (SWM). This paper introduces an intermediate parabolic wave model (ParWM), more accurate than the PWM while less complex than the SWM. The validity domains of those three physical models are assessed in a novel way. Finally, estimation algorithms for the SWM and ParWM are proposed and compared with classical algorithms, showing a promising performance complexity trade-off

Channel Capacity Investigation of a Linear Massive MIMO System using Spherical Wave Model in LOS Scenarios

Massive multiple-input multiple-output (MIMO) is a key technology for the 5th generation (5G) of wireless communication systems. The traditional plane wave channel model (PWM) is often not suitable for the large antenna structure, and in certain cases should be replaced by the more accurate spherical wave model (SWM). By using the spherical wave characterization method, this paper investigates the channel capacity performance of a linear massive MIMO system in line-of-sight (LOS) scenarios. Two types of access settings, the point to point (PTP) system and multi-user (MU) system, are considered. In the PTP setting, a geometrical optimization is performed to obtain configurations that are able to generate a full rank channel matrix for a linear massive MIMO system, which yields full spatial diversity even in LOS scenarios. Compared with the approximate and commonly applied rank-1 PWM, this is very useful for fixed wireless access and radio relay systems requiring high throughput. For the MU case, we compare the eigenvalue distributions of the LOS channels using the plane wave and spherical wave characterization method, and sum rate results are obtained by Monte Carlo simulations. The results show that MU systems using the more realistic and accurate SWM can achieve a higher sum rate than results from the PWM. This is beneficial and informative when designing massive MIMO wireless networks