Performance Analysis and Transmission Block Size Optimization for Massive MIMO Vehicular Network with Spatially and Temporally Correlated Channels
Journal article, 2024

We investigate the effect of spatially and temporally correlated channels on the transmission performance of multi-cell multi-user massive multiple-input multiple-output (MIMO) vehicular networks in generic non-isotropic scattering environments. A new channel model is established to evaluate the harmfulness of the non-isotropic-scattered angle-of-departure/angle-of-arrival (AoD/AoA) spread and the high mobility of users on the uplink transmission. We derive the expressions of achievable spectral efficiency (SE), taking into account the effects of line-of-sight propagation, channel aging, and pilot contamination. Specifically, two novel receive combining schemes, namely the aging-aware maximum ratio combining and the aging-aware minimum mean square error combining, are presented to mitigate the SE decline caused by outdated channel state information. A low-complexity pilot assignment algorithm is proposed to suppress pilot contamination. We find that the quasi-static assumption of the channel may be unsafe for the system design of the vehicular networks even within a single transmission block period lasting from hundreds of microseconds to a few milliseconds. We observe that there exists an optimal block size Copt that maximizes area spectral efficiency. Especially, Copt can be expressed as a function of movement speed, AoD spread, and AoA spread. Numerical results are presented to validate the efficacy of the proposed schemes and highlight the importance of correct performance evaluation for practical massive MIMO system designs.

channel aging

Contamination

Aging

space-time correlation

Massive MIMO

non-isotropic

Channel estimation

Massive MIMO

Correlation

Scattering

vehicular network

Channel models

Author

Huafu Li

Harbin Institute of Technology

Liqin Ding

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Yang Wang

Harbin Institute of Technology

Chenyang Sun

Harbin Institute of Technology

Zhenyong Wang

Harbin Institute of Technology

IEEE Internet of Things Journal

23274662 (eISSN)

Vol. 11 5 8989-9003

Subject Categories

Telecommunications

Communication Systems

Signal Processing

DOI

10.1109/JIOT.2023.3321728

More information

Latest update

3/9/2024 4