Reducing Channel Estimation and Feedback Overhead in IRS-Aided Downlink System: A Quantize-Then-Estimate Approach
Channel state information (CSI) acquisition is essential for the base station (BS) to fully reap the beamforming gain in intelligent reflecting surface (IRS)-aided downlink communication systems. Recently, Wang et al. (2020) revealed a strong correlation in different users' cascaded channels st...
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| Vydáno v: | IEEE transactions on wireless communications Ročník 24; číslo 2; s. 1325 - 1338 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
IEEE
01.02.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1536-1276, 1558-2248 |
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| Abstract | Channel state information (CSI) acquisition is essential for the base station (BS) to fully reap the beamforming gain in intelligent reflecting surface (IRS)-aided downlink communication systems. Recently, Wang et al. (2020) revealed a strong correlation in different users' cascaded channels stemming from their common BS-IRS channel component, and leveraged such a correlation to significantly reduce the pilot transmission overhead in IRS-aided uplink communication. In this paper, we aim to exploit the above channel property to reduce the overhead for both pilot and feedback transmission in IRS-aided downlink communication. Note that in the downlink, the distributed users merely receive the pilot signals containing their own CSI and cannot leverage the correlation in different users' channels, which is in sharp contrast to the uplink counterpart considered in Wang et al. (2020). To tackle this challenge, this paper proposes a novel "quantize-then-estimate" protocol in frequency division duplex (FDD) IRS-aided downlink communication. Specifically, the users quantize and feed back their received pilot signals, instead of the estimated channels, to the BS. After de-quantizing the pilot signals received by all the users, the BS estimates all the cascaded channels by leveraging their correlation, similar to the uplink scenario. Under this protocol, we manage to propose efficient user-side quantization and BS-side channel estimation methods. Moreover, we analytically quantify the pilot and feedback transmission overhead to reveal the significant performance gain of our proposed scheme over the conventional "estimate-then-quantize" scheme. |
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| AbstractList | Channel state information (CSI) acquisition is essential for the base station (BS) to fully reap the beamforming gain in intelligent reflecting surface (IRS)-aided downlink communication systems. Recently, Wang et al. (2020) revealed a strong correlation in different users’ cascaded channels stemming from their common BS-IRS channel component, and leveraged such a correlation to significantly reduce the pilot transmission overhead in IRS-aided uplink communication. In this paper, we aim to exploit the above channel property to reduce the overhead for both pilot and feedback transmission in IRS-aided downlink communication. Note that in the downlink, the distributed users merely receive the pilot signals containing their own CSI and cannot leverage the correlation in different users’ channels, which is in sharp contrast to the uplink counterpart considered in Wang et al. (2020). To tackle this challenge, this paper proposes a novel “quantize-then-estimate” protocol in frequency division duplex (FDD) IRS-aided downlink communication. Specifically, the users quantize and feed back their received pilot signals, instead of the estimated channels, to the BS. After de-quantizing the pilot signals received by all the users, the BS estimates all the cascaded channels by leveraging their correlation, similar to the uplink scenario. Under this protocol, we manage to propose efficient user-side quantization and BS-side channel estimation methods. Moreover, we analytically quantify the pilot and feedback transmission overhead to reveal the significant performance gain of our proposed scheme over the conventional “estimate-then-quantize” scheme. |
| Author | Zhang, Shuowen Wang, Zhaorui Liu, Liang Jin, Shi Wang, Rui |
| Author_xml | – sequence: 1 givenname: Rui orcidid: 0000-0001-5937-5876 surname: Wang fullname: Wang, Rui email: rui-eie.wang@connect.polyu.hk organization: Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China – sequence: 2 givenname: Zhaorui orcidid: 0000-0003-2973-1555 surname: Wang fullname: Wang, Zhaorui email: wangwang2020channel@cuhk.edu.cn organization: FNii and SSE, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), Shenzhen, China – sequence: 3 givenname: Liang orcidid: 0000-0002-6509-9609 surname: Liu fullname: Liu, Liang email: liang-eie.liu@polyu.edu.hk organization: Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China – sequence: 4 givenname: Shuowen orcidid: 0000-0002-4511-4154 surname: Zhang fullname: Zhang, Shuowen email: shuowen.zhang@polyu.edu.hk organization: Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China – sequence: 5 givenname: Shi orcidid: 0000-0003-0271-6021 surname: Jin fullname: Jin, Shi email: jinshi@seu.edu.cn organization: National Mobile Communications Research Laboratory, Southeast University, Nanjing, China |
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| SubjectTerms | Beamforming Channel estimation channel feedback Channels Communication Communications systems Correlation distributed source coding Downlink Downlinking Feedback Feedback control systems Feeds Frequency division duplexing Information systems Intelligent reflecting surface (IRS) Protocols Quantization (signal) Reconfigurable intelligent surfaces Transmitting antennas Uplink Uplinking Vectors Wireless communication |
| Title | Reducing Channel Estimation and Feedback Overhead in IRS-Aided Downlink System: A Quantize-Then-Estimate Approach |
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