In essence, channel tracking is formulated as a compressive sensing problem with the proposed sensing matrix over the delay domain, which enables low complexity irrespective of the number of available subcarriers, resulting in a new tracking algorithm based on the exact top-k feature selection.
To elaborate, the proposed method is based on a novel sensing matrix that exploits the time evolution models of angle of arrivals (AoAs) and angle of departures (AoDs), where the time-varying channel is effectively approximated with a few discrete AoA and AoD candidates. Moreover, the proposed tracking algorithm is refined by introducing multiple sub-sensing subsets, which further improve the tracking performance. Numerical results and complexity analyses in terms of floating operations (FLOPs) confirm that the proposed approaches achieve better trade-offs between complexity and tracking gain than the conventional Bayesian estimator approaches.
Full abstract in IEEEXplore DOI: 10.1109/TVT.2024.3373821
Authors
Sota Uchimura, Koji Ishibashi – Advanced Wireless and Communication Research Center (AWCC), University of Electro-Communications, Japan
Hiroki Iimori, Paulo Valente Klaine, Szabolcs Malomsoky – Ericsson Research, Japan
Published in IEEE Transactions on Vehicular Technology ( Volume: 73, Issue: 8)
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