Mitigating the Impact of Channel Aging in Cell-Free MIMO Systems Using a Channel Predictor Based on Extended Kalman Filter

Several previous works have pointed out that the channel aging effect may severely degrade the performance of wireless systems. This effect may be more pronounced in cell-free networks due to two main reasons. First, designing centralized precoders for cell-free (CF) systems requires the exchange of...

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Vydáno v:IEEE transactions on vehicular technology Ročník 74; číslo 6; s. 8544 - 8560
Hlavní autoři: Paiva, A. Regilane L., Freitas, Walter C., Antonioli, Roberto P., Silva, Yuri C. B., Fodor, Gabor
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.06.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Aging
Autoregressive processes
cell-free
Central processing units
channel aging
Clustering
Correlation
CPUs
Delays
Extended Kalman filter
Impact analysis
Information systems
Kalman filters
Millimeter wave communication
MIMO communication
non-isotropic scattering
Precoding
Predictive models
Rayleigh channels
Symbols
ISSN:0018-9545, 1939-9359, 1939-9359
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Shrnutí:Several previous works have pointed out that the channel aging effect may severely degrade the performance of wireless systems. This effect may be more pronounced in cell-free networks due to two main reasons. First, designing centralized precoders for cell-free (CF) systems requires the exchange of a large amount of channel state information (CSI) data between access points and a central processing unit, which may cause considerable processing delays. Secondly, the CF architecture requires keeping track of multiple aging channels, since user equipment devices are served by multiple cell sites. In this paper, we consider a CF multiple input multiple output (MIMO) system that uses joint coherence transmission and operates in the presence of channel propagation clustering under high Doppler frequencies. Unlike previous works, which focus on analyzing the impact of channel aging, this paper proposes a Kalman filter-based directional CSI prediction scheme that relies on a set of underlying <inline-formula><tex-math notation="LaTeX">P</tex-math></inline-formula>-th order autoregressive processes that correspond to the active links of the CF system. The extended Kalman filter is chosen with the purpose of predicting the channel path parameters. Using the predicted directional CSI, we design centralized hybrid precoding. Our results indicate that the proposed CSI prediction and precoding schemes outperform related benchmarks schemes and a 3rd order AR process model is a good engineering trade-off between model complexity and CSI prediction performance in practically relevant CF scenarios.
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ISSN:0018-9545
1939-9359
1939-9359
DOI:10.1109/TVT.2025.3533969