Pilot-Free Predictive Multi-User Beamforming via Sensing Management in Cell-Free Networks
Eren Berk Kama, Murat Babek Salman, Isaac Skog, and Emil Bj\"ornson

TL;DR
This paper introduces a sensing management framework for cell-free MIMO systems that reduces pilot overhead by tracking user locations with EKF and predictive beamforming, maintaining high spectral efficiency.
Contribution
It proposes a novel state-based architecture and sensing protocol that minimizes pilot training by leveraging user tracking and predictive beamforming in cell-free networks.
Findings
EKF-based tracking supports near-perfect CSI spectral efficiency.
Sensing operations are minimized, only performed when necessary.
The approach is robust and practical in cell-free massive MIMO setups.
Abstract
This paper presents a sensing management frame- work for integrated sensing and communications (ISAC) within cell-free massive multiple-input multiple-output (MIMO) systems to reduce pilot-based channel state information (CSI) acquisition overhead. Conventional communication systems rely on frequent channel estimation procedures that impose significant signaling overhead, consuming valuable time-frequency resources. To ad- dress this inefficiency, we propose a state-based architecture that partitions users into communication and sensing groups based on service requirements. When users are not requesting data, the system utilizes sensing capabilities to track their location. Upon receiving a communication request, the system transitions to communication mode, leveraging the tracked state for predictive beamforming to eliminate the need for uplink pilot training. We develop an extended…
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