Iterative Hard Thresholding with Memory-based Dynamic Sparse Wireless Channel Estimator

Oyerinde, Olutayo O.; Flizikowski, Adam; Marciniak, Tomasz

doi:10.1109/icspcs50536.2020.9310035

Cited by 1 publication

(18 citation statements)

References 27 publications

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“…The authors in [36] proposed a decision-directedbased sparse adaptive predictor that works in the delay-Doppler domain for dynamic UWA channels. To track the dynamic sparse wireless communication channels, the authors in [37] exploited associated temporal correlations of channels to develop the proposed iterative hard thresholding with memory (IHT_wM)-based estimator for broadband communication systems. A summary of some of the above reviewed relevant works is presented in Table 1.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, the work presented in [37] is revisited. As an extension of this work, the main contributions of this paper are summarized as follows.…”

Section: Introductionmentioning

confidence: 99%

“…Though the channel estimator proposed in this paper is built on the same traditional Iterative Hard Thresholding algorithm employed in [37], however, the main distinctions between this work and the one presented in [37] include the following. In 37, a constant step size parameter is employed in the operation of the channel estimator.…”

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confidence: 99%

“…Consequently, reference [37] employed variable momentum step size in combination with fixed step size in the dynamic channel estimation procedure. On the other hand, the proposed IHT-wCVSSnM-based estimator's operation is based on the combined variable step size and variable momentum step size mechanisms.…”

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confidence: 99%

“…On the other hand, the proposed IHT-wCVSSnM-based estimator's operation is based on the combined variable step size and variable momentum step size mechanisms. Insight about time to computation in terms of CPU running time for all the estimators is presented in this paper but not in [37]. Reference Contributions [11] The paper focused on estimation technique for underwater acoustic (UWA) channels where the channels impulses' responses are said to possess large delays and Doppler spreads with few significant echoes.…”

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confidence: 99%

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Iterative Hard Thresholding with Combined Variable Step Size & Momentum-Based Estimator for Wireless Communication Systems with Dynamic Sparse Channels

2021

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The channel of the broadband wireless communications system can be modeled as a dynamic sparse channel. Such a channel is difficult to reconstruct by using linear channel estimators that are normally employed for dense channels’ estimation because of their lack of capacity to use the inherent channel’s sparsity. This paper focuses on reconstructing this type of time-varying sparse channel by extending a recently proposed dynamic channel estimator. Specifically, variable step size’s mechanism and variable momentum parameter are incorporated into traditional Iterative Hard Thresholding-based channel estimator to develop the proposed Iterative Hard Thresholding with Combined Variable Step Size and Momentum (IHT-wCVSSnM)-based estimator. Computer simulations carried out in the context of a wireless communication system operating in a dynamic sparse channel, show that the proposed IHT-wCVSSnM-based estimator performs better than all the other estimators significantly. However, the computational complexity cost of the proposed estimator is slightly higher than the closely performing channel estimator. Nevertheless, the inherent complexity cost of the proposed estimator could be compromised in a situation where the system’s performance is of higher priority when compared with the computational complexity cost.

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Section: Introductionmentioning

confidence: 99%

“…In this paper, the work presented in [37] is revisited. As an extension of this work, the main contributions of this paper are summarized as follows.…”

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%

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