AMP-Based Joint Activity Detection and Channel Estimation for Massive Grant-Free Access in OFDM-Based Wideband Systems

To realize orthogonal frequency division multiplexing (OFDM)-based grant-free access for wideband systems under frequency-selective fading, existing device activity detection and channel estimation methods need substantial accuracy improvement or computation time reduction. In this paper, we aim to resolve this issue. First, we present an exact time-domain signal model for OFDM-based grant-free access under frequency-selective fading. Then, we present a maximum a posteriori (MAP)-based device activity detection problem and two minimum mean square error (MMSE)-based channel estimation problems. The MAP-based device activity detection problem and one of the MMSE-based channel estimation problems are formulated for the first time. Next, we build a new factor graph that captures the exact statistics of time-domain channels and device activities. Based on it, we propose two approximate message passing (AMP)-based algorithms, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AMP-A-EC</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AMP-A-AC</i>, to approximately solve the MAP-based device activity detection problem and two MMSE-based channel estimation problems. Both proposed algorithms alleviate the AMP’s inherent convergence problem when the pilot length is smaller or comparable to the number of active devices. Then, we analyze <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AMP-A-EC</i>’s error probability of activity detection and mean square error (MSE) of channel estimation via state evolution and show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AMP-A-AC</i> has the lower computational complexity (in dominant term). Finally, numerical results show the two proposed AMP-based algorithms’ superior performance and respective preferable regions, revealing their significant values for OFDM-based grant-free access.

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Publication Details

Journal
IEEE Transactions on Wireless Communications
Published
2025-09-01
DOI
https://doi.org/10.1109/twc.2025.3598367
Primary Topic
Power Line Communications and Noise
Type
article
Field-Weighted Citation Impact
0.00

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article

AMP-Based Joint Activity Detection and Channel Estimation for Massive Grant-Free Access in OFDM-Based Wideband Systems

Danny H. K. Tsang, Ying Cui, Zhiyan Li
IEEE Transactions on Wireless Communications
Power Line Communications and Noise
article

AMP-Based Joint Activity Detection and Channel Estimation for Massive Grant-Free Access in OFDM-Based Wideband Systems

Danny H. K. Tsang, Ying Cui, Zhiyan Li
article en

Abstract

To realize orthogonal frequency division multiplexing (OFDM)-based grant-free access for wideband systems under frequency-selective fading, existing device activity detection and channel estimation methods need substantial accuracy improvement or computation time reduction. In this paper, we aim to resolve this issue. First, we present an exact time-domain signal model for OFDM-based grant-free access under frequency-selective fading. Then, we present a maximum a posteriori (MAP)-based device activity detection problem and two minimum mean square error (MMSE)-based channel estimation problems. The MAP-based device activity detection problem and one of the MMSE-based channel estimation problems are formulated for the first time. Next, we build a new factor graph that captures the exact statistics of time-domain channels and device activities. Based on it, we propose two approximate message passing (AMP)-based algorithms, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AMP-A-EC</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AMP-A-AC</i>, to approximately solve the MAP-based device activity detection problem and two MMSE-based channel estimation problems. Both proposed algorithms alleviate the AMP’s inherent convergence problem when the pilot length is smaller or comparable to the number of active devices. Then, we analyze <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AMP-A-EC</i>’s error probability of activity detection and mean square error (MSE) of channel estimation via state evolution and show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AMP-A-AC</i> has the lower computational complexity (in dominant term). Finally, numerical results show the two proposed AMP-based algorithms’ superior performance and respective preferable regions, revealing their significant values for OFDM-based grant-free access.

IEEE Transactions on Wireless CommunicationsVol. 25
Hong Kong University of Science and Technology (HK), University of Hong Kong (HK)
National Natural Science Foundation of China
Openalex Percentile: Top 78%
Power Line Communications and Noise
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