FIR-SIMO channel order determination by invariant-signal-subspace matching

Wax, M.; Adler, Amir

doi:10.1016/j.dsp.2023.103914

Cited by 1 publication

(2 citation statements)

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“…However, the information-theorycriterion-based approaches often underestimate or overestimate the channel order. Various channel order identification methods have been proposed in the literature to obtain the channel order with the higher identification accuracy [30]- [35]. For example, the subspace [30]- [32], the autocorrelation function [33], the hypothesis test [34], [35], and the cumulant features [36] are exploited to identify the unknown channel order.…”

Section: A Related Workmentioning

confidence: 99%

“…Various channel order identification methods have been proposed in the literature to obtain the channel order with the higher identification accuracy [30]- [35]. For example, the subspace [30]- [32], the autocorrelation function [33], the hypothesis test [34], [35], and the cumulant features [36] are exploited to identify the unknown channel order. Despite a variety of schemes for the channel order identification, they can only operate in a single-antenna transmitter.…”

Section: A Related Workmentioning

confidence: 99%

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Joint Identification for Number of Transmit Antennas and Channel Order

Wang,

He,

Wang

2023

IEEE Access

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Identifying the number of transmit antennas and the channel order is an important step in recovering the original information for a non-cooperative communication system. Traditional methods overestimate the number of transmit antennas and the channel order due to the coupling effect. This paper proposes a novel joint identification scheme to determine the number of transmit antennas and the channel order, which consists of two stages. Specifically, in the first stage, an improved weighted Gerschgorin disk identifier is developed to obtain the number of transmit antennas using frequency domain signals. In the second stage, we first derive an equivalent time-domain model to improve the utilization of the receiver antenna, and then a novel test statistic following F distribution is constructed to perform the sequential binary hypothesis testing. Finally, the channel order is obtained using the estimated number of transmit antennas in the first stage. The simulation results show that the proposed joint identification scheme significantly outperforms the existing approaches.

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