Low Complexity Joint OMP Methods for FDD Channel Estimation in Massive MIMO Systems

In this paper, for a cell-free massive multi-input multi-output (MIMO) system assisted with intelligent reflective surface (IRS) panels, a generalized superimposed pilot (GSP) training scheme is proposed, where the available number of pilots are equal to the coherence time slots, and the transmitting data symbols are spread over the coherence time with the help of simple precoding. Further, in order to keep the system scalable, a low complexity approach is employed for processing, and the corresponding rate components are analyzed. It is shown that with careful design of precoding and number of data symbols, the GSP symbols can provide much better channel estimation and data detection performance, as compared to the regular pilot scheme and the conventional superimposed scheme. These results, verified via simulations, shows that the centralized processing improves the data detection performance than localized processing. The pilot contamination effect, is significantly reduced due to the availability of larger number of pilots, as compared to the regular pilots transmission. For four IRS panels in the system, the proposed scheme is shown to reduce the channel estimation errors by 74% approximately.

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“…The notation G + lk denotes plus one value, that is, G + lk = G lk + 1. The steering vector can be given as [47]…”

Section: A Channel Model For User To Ap (G Lk )mentioning

confidence: 99%

Generalized Superimposed Training Scheme in IRS-Assisted Cell-Free Massive MIMO Systems

Garg

Ratnarajah

2022

IEEE J. Sel. Top. Signal Process.

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CSI acquisition in RIS-assisted mobile communication systems

Han

Tang

et al. 2023

National Science Review

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Reconfigurable intelligent surface (RIS)-assisted mobile communication is a promising technological paradigm thanks to the attractive advantages of low cost and flexible control of electromagnetic waves. However, the low-cost features of RISs entail some fundamental challenges to the acquisition of channel state information (CSI), which is essential for the optimal RIS design. To tackle this problem, there have been extensive studies on CSI acquisition in RIS-assisted mobile communication systems, from the perspective of architectural improvement as well as specific mathematical solutions. This article aims to overview the existing works on CSI acquisition in RIS-assisted mobile communication systems.

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Knowledge-Driven Deep Learning Based Channel Estimation for Terahertz Extra-Large MIMO Systems

Wang,

Gao,

Zhang

et al. 2023

2023 IEEE 23rd International Conference on Communication Technology (ICCT)

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Low Complexity Joint OMP Methods for FDD Channel Estimation in Massive MIMO Systems

Cited by 4 publications

References 9 publications

Generalized Superimposed Training Scheme in IRS-Assisted Cell-Free Massive MIMO Systems

Generalized Superimposed Training Scheme in IRS-Assisted Cell-Free Massive MIMO Systems

CSI acquisition in RIS-assisted mobile communication systems

Knowledge-Driven Deep Learning Based Channel Estimation for Terahertz Extra-Large MIMO Systems

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