TY - GEN
T1 - Decentralized expected consistent signal recovery for quantization measurements
AU - Wang, Chang Jen
AU - Wen, Chao Kai
AU - Tsai, Shang-Ho
AU - Jin, Shi
N1 - Publisher Copyright:
© 2020 IEEE
PY - 2020/5
Y1 - 2020/5
N2 - Signal recovery through coarse quantization of a linear transform output has many applications in engineering, such as channel estimation and signal detection in massive MIMO systems. A recently proposed scheme, known as generalized expectation consistent signal recovery (GEC-SR), can achieve Bayesian inference and exhibit better robustness than many existing methods. However, recovering signals with large transform matrices continue to present a computational burden for GEC-SR. In this study, we develop a novel decentralized architecture by leveraging the core framework of GEC-SR called “deGEC-SR.” deGEC-SR offers excellent performance as GEC-SR and runs tens of times faster than GEC-SR. We derive the theoretical state evolution of deGEC-SR and demonstrate its accuracy using numerical results.
AB - Signal recovery through coarse quantization of a linear transform output has many applications in engineering, such as channel estimation and signal detection in massive MIMO systems. A recently proposed scheme, known as generalized expectation consistent signal recovery (GEC-SR), can achieve Bayesian inference and exhibit better robustness than many existing methods. However, recovering signals with large transform matrices continue to present a computational burden for GEC-SR. In this study, we develop a novel decentralized architecture by leveraging the core framework of GEC-SR called “deGEC-SR.” deGEC-SR offers excellent performance as GEC-SR and runs tens of times faster than GEC-SR. We derive the theoretical state evolution of deGEC-SR and demonstrate its accuracy using numerical results.
KW - Bayes-optimal inference
KW - Decentralized algorithm
KW - Expectation consistent
KW - Quantization measurement
UR - https://www.scopus.com/pages/publications/85091189579
U2 - 10.1109/ICASSP40776.2020.9054602
DO - 10.1109/ICASSP40776.2020.9054602
M3 - Conference contribution
AN - SCOPUS:85091189579
SN - 978-1-7281-5090-1
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 5620
EP - 5624
BT - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Y2 - 4 May 2020 through 8 May 2020
ER -