Po-Chih Chen received the B.S. and M.S. degrees in electrical engineering and communication engineering from National Taiwan University (NTU), Taiwan, in 2015 and 2017, respectively. He received the Ph.D. degree in electrical engineering at the California Institute of Technology (Caltech), USA, in 2024. Starting from 2024, he has been a faculty member of the Institute of Communications Engineering, National Yang Ming Chiao Tung University, Taiwan, where he is currently an assistant professor. His recent research interests are in signal processing, array processing, sparse arrays, distributed algorithms for arrays, and millimeter-wave (mmWave) MIMO communications.

Personal Information:

• Google Scholar: https://scholar.google.com/citations?user=IHMnu0UAAAAJ

N/A

o Array Signal Processing
o Signal Processing for Communications
o Digital Signal Processing
o Distributed Algorithms

1. P.-C. Chen and P. P. Vaidyanathan, “Channel estimation for mmWave using the convolutional beamspace approach,” IEEE Trans. Signal Process., accepted for publication.
2. P.-C. Chen and P. P. Vaidyanathan, “Distributed algorithms for array signal processing,” IEEE Trans. Signal Process., vol. 69, pp. 4607-4622,  2021.
3. P.-C. Chen and P. P. Vaidyanathan, “Convolutional beamspace for linear arrays,” IEEE Trans. Signal Process., vol. 68, pp. 5395-5410,  2020.
4. P.-C. Chen, B. Su, and Y. Huang, “Matrix characterization for GFDM systems: Low- complexity MMSE receivers and optimal prototype filters,” IEEE Trans. Signal Process., vol. 65, no. 18 pp. 4940-4955,  Sep. 2017.

1. P.-C. Chen and P. P. Vaidyanathan, “Hybrid Convolutional Beamspace Method for mmWave MIMO Channel Estimation,” Asilomar Conf. on Signal, Syst., Comput., 2023.
2. P.-C. Chen and P. P. Vaidyanathan, “Cram´er–Rao Bound for Convolutional Beamspace Method,” Asilomar Conf. on Signal, Syst., Comput., 2023.
3. P.-C. Chen and P. P. Vaidyanathan, “Unitary ESPRIT for coprime arrays,” Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., 2023, pp. 1-5.
4. P.-C. Chen and P. P. Vaidyanathan, “Error analysis of convolutional beamspace algorithms,” Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., 2023, pp. 1-5.
5. P.-C. Chen and P. P. Vaidyanathan, “Hybrid convolutional beamspace for DOA estimation of millimeter wave sources,” Asilomar Conf. on Signal, Syst., Comput., 2022, pp. 86-90.
6. P.-C. Chen and P. P. Vaidyanathan, “Convolutional beamspace using IIR filters,” Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., 2022, pp. 5003-5007.
7. P.-C. Chen and P. P. Vaidyanathan, “Sliding-Capon based convolutional beamspace for linear arrays,” Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., 2021, pp. 4565-4569.
8. P.-C. Chen and P. P. Vaidyanathan, “Rank properties of manifold matrices of sparse arrays,” Asilomar Conf. on Signal, Syst., Comput., 2021, pp. 1628-1633.
9. P.-C. Chen and P. P. Vaidyanathan, “Distributed root-MUSIC using finite-time average consensus,” Asilomar Conf. on Signal, Syst., Comput., 2021, pp. 539-543.
10. P.-C. Chen and P. P. Vaidyanathan, “Convolutional beamspace and sparse signal recovery for linear arrays,” Asilomar Conf. on Signal, Syst., Comput., 2020, pp. 929-933.
11. P. P. Vaidyanathan and P.-C. Chen, “Convolutional beamspace for array signal processing,” Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., 2020, pp. 4707-4711.
12. P.-C. Chen and P. P. Vaidyanathan, “On ESPRIT with multiple coprime-invariances,” Asilomar Conf. on Signal, Syst., Comput., 2019, pp. 148-152.
13. C.-L. Tai, B. Su, and P.-C. Chen, “Optimal filter design for GFDM that minimizes PAPR under performance constraints,” Proc. IEEE Wireless Commun. Netw. Conf., 2018, pp. 1-6.
14. P.-C. Chen, B. Su, “Filter optimization of out-of-band radiation with performance constraints for GFDM systems,” in the 18th IEEE Int. Workshop on Signal Process. Advances in Wireless Commun. (SPAWC), 2017, pp. 1-5.