Parameter Design for Channel Knowledge Map Assisted Channel Estimation

Muhammad Awais; Yun Hee Kim

doi:10.1109/ICTC66702.2025.11388376

Parameter Design for Channel Knowledge Map Assisted Channel Estimation

Muhammad Awais
, Yun Hee Kim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Efficient channel estimation in massive multiple-input multiple-output (mMIMO) with limited pilot resources remains a key challenge. Recently, the concept of a channel knowledge map (CKM) has been proposed to enable location and environment-aware estimation. For a CKM referred to as channel angle-distance map (CADM) proposed for near-field channels, we investigate the sensitivity of the CADM-assisted channel estimation to the number of stored multipath components for a given location. We explore how variations in the number of multipath components in CADM affect the mean squared error (MSE) performance in different signal-to-noise ratio (SNR) conditions. Simulation results reveal that a moderate overestimation of multipath components in CADM can improve the MSE performance in high SNR regimes, whereas excessive multipath data degrades the performance in low SNR regimes.

Original language	English
Title of host publication	2025 16th International Conference on Information and Communication Technology Convergence, ICTC 2025
Publisher	IEEE Computer Society
Pages	1541-1542
Number of pages	2
ISBN (Electronic)	9798331556785
DOIs	https://doi.org/10.1109/ICTC66702.2025.11388376
Publication status	Published - 2025
Event	16th International Conference on Information and Communication Technology Convergence, ICTC 2025 - , Korea, Republic of Duration: 14 Oct 2025 → 17 Oct 2025

Publication series

Name	International Conference on ICT Convergence
ISSN (Print)	2162-1233
ISSN (Electronic)	2162-1241

Conference

Conference	16th International Conference on Information and Communication Technology Convergence, ICTC 2025
Country/Territory	Korea, Republic of
Period	14/10/25 → 17/10/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Keywords

channel estimation
Channel knowledge map (CKM)
massive MIMO
near-field channels

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10.1109/ICTC66702.2025.11388376

Cite this

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title = "Parameter Design for Channel Knowledge Map Assisted Channel Estimation",

abstract = "Efficient channel estimation in massive multiple-input multiple-output (mMIMO) with limited pilot resources remains a key challenge. Recently, the concept of a channel knowledge map (CKM) has been proposed to enable location and environment-aware estimation. For a CKM referred to as channel angle-distance map (CADM) proposed for near-field channels, we investigate the sensitivity of the CADM-assisted channel estimation to the number of stored multipath components for a given location. We explore how variations in the number of multipath components in CADM affect the mean squared error (MSE) performance in different signal-to-noise ratio (SNR) conditions. Simulation results reveal that a moderate overestimation of multipath components in CADM can improve the MSE performance in high SNR regimes, whereas excessive multipath data degrades the performance in low SNR regimes.",

keywords = "channel estimation, Channel knowledge map (CKM), massive MIMO, near-field channels",

author = "Muhammad Awais and Kim, \{Yun Hee\}",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 16th International Conference on Information and Communication Technology Convergence, ICTC 2025 ; Conference date: 14-10-2025 Through 17-10-2025",

year = "2025",

doi = "10.1109/ICTC66702.2025.11388376",

language = "English",

series = "International Conference on ICT Convergence",

publisher = "IEEE Computer Society",

pages = "1541--1542",

booktitle = "2025 16th International Conference on Information and Communication Technology Convergence, ICTC 2025",

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Awais, M & Kim, YH 2025, Parameter Design for Channel Knowledge Map Assisted Channel Estimation. in 2025 16th International Conference on Information and Communication Technology Convergence, ICTC 2025. International Conference on ICT Convergence, IEEE Computer Society, pp. 1541-1542, 16th International Conference on Information and Communication Technology Convergence, ICTC 2025, Korea, Republic of, 14/10/25. https://doi.org/10.1109/ICTC66702.2025.11388376

Parameter Design for Channel Knowledge Map Assisted Channel Estimation. / Awais, Muhammad; Kim, Yun Hee.
2025 16th International Conference on Information and Communication Technology Convergence, ICTC 2025. IEEE Computer Society, 2025. p. 1541-1542 (International Conference on ICT Convergence).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Parameter Design for Channel Knowledge Map Assisted Channel Estimation

AU - Awais, Muhammad

AU - Kim, Yun Hee

PY - 2025

Y1 - 2025

N2 - Efficient channel estimation in massive multiple-input multiple-output (mMIMO) with limited pilot resources remains a key challenge. Recently, the concept of a channel knowledge map (CKM) has been proposed to enable location and environment-aware estimation. For a CKM referred to as channel angle-distance map (CADM) proposed for near-field channels, we investigate the sensitivity of the CADM-assisted channel estimation to the number of stored multipath components for a given location. We explore how variations in the number of multipath components in CADM affect the mean squared error (MSE) performance in different signal-to-noise ratio (SNR) conditions. Simulation results reveal that a moderate overestimation of multipath components in CADM can improve the MSE performance in high SNR regimes, whereas excessive multipath data degrades the performance in low SNR regimes.

AB - Efficient channel estimation in massive multiple-input multiple-output (mMIMO) with limited pilot resources remains a key challenge. Recently, the concept of a channel knowledge map (CKM) has been proposed to enable location and environment-aware estimation. For a CKM referred to as channel angle-distance map (CADM) proposed for near-field channels, we investigate the sensitivity of the CADM-assisted channel estimation to the number of stored multipath components for a given location. We explore how variations in the number of multipath components in CADM affect the mean squared error (MSE) performance in different signal-to-noise ratio (SNR) conditions. Simulation results reveal that a moderate overestimation of multipath components in CADM can improve the MSE performance in high SNR regimes, whereas excessive multipath data degrades the performance in low SNR regimes.

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KW - Channel knowledge map (CKM)

KW - massive MIMO

KW - near-field channels

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DO - 10.1109/ICTC66702.2025.11388376

M3 - Conference contribution

AN - SCOPUS:105035071150

T3 - International Conference on ICT Convergence

SP - 1541

EP - 1542

BT - 2025 16th International Conference on Information and Communication Technology Convergence, ICTC 2025

PB - IEEE Computer Society

T2 - 16th International Conference on Information and Communication Technology Convergence, ICTC 2025

Y2 - 14 October 2025 through 17 October 2025

ER -

Parameter Design for Channel Knowledge Map Assisted Channel Estimation

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