Power Amplifier Predistortion Using Reduced Sampling Rates in the Forward and Feedback Paths
Author:
Ahmed Serien1, Ahmed Majid1, Bensmida Souheil2ORCID, Hammi Oualid1ORCID
Affiliation:
1. Department of Electrical Engineering, College of Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates 2. Institute of Sensors, Signals and Systems, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburg EH14 4AS, UK
Abstract
The feasibility of implementing digital predistortion for next-generation wireless communication is faced with a dilemma due to the ever-increasing demand for faster data rates. This causes the utilized bandwidth to increase significantly, as seen in the 5G NR standard in which bandwidths as high as 400 MHz are utilized. Hence, the development of new predistortion techniques in which the forward and feedback paths operate at lower sampling rates is of utmost importance to realize efficient and practical predistortion solutions. In this work, a novel predistortion technique is presented by which the predistortion is divided between the digital and analog domains. The predistorter is composed of a memoryless AM/AM gain function that is implementable in the analog domain, and a nonlinear model with memory effects in the digital domain to relax the sampling rate requirements on both the forward and feedback paths. Experimental validation was carried out with a 20 MHz and a 40 MHz 5G signal, and the results indicate minimal linearization degradation with a sampling rate reduction of 50% and 30%, respectively. This sampling rate reduction is concurrently applied in the digital-to-analog converter of the forward path and the analog-to-digital converter of the feedback path.
Funder
American University of Sharjah
Reference32 articles.
1. A Comprehensive Survey on 5G-and-Beyond Networks with UAVs: Applications, Emerging Technologies, Regulatory Aspects, Research Trends and Challenges;Banafaa;IEEE Access,2024 2. Devi, D.H., Duraisamy, K., Armghan, A., Alsharari, M., Aliqab, K., Sorathiya, V., Das, S., and Rashid, N. (2023). 5G Technology in Healthcare and Wearable Devices: A Review. Sensors, 23. 3. Kakkavas, G., Diamanti, M., Stamou, A., Karyotis, V., Bouali, F., Pinola, J., Apilo, O., Papavassiliou, S., and Moessner, K. (2022). Design, Development, and Evaluation of 5G-Enabled Vehicular Services: The 5G-HEART Perspective. Sensors, 22. 4. Predistortion-Based Linearization for 5G and Beyond Millimeter-Wave Transceiver Systems: A Comprehensive Survey;Haider;IEEE Commun. Surv. Tutor.,2022 5. Liu, X., Zhai, J., Zhang, Z., Ning, D., Chen, P., and Yu, C. (IEEE Microw. Wirel. Compon. Lett., 2024). High-Precision Digital Predistortion for Sub-6-GHz GaN Power Amplifiers Excited by a Signal with 400-MHz Modulation Bandwidth, IEEE Microw. Wirel. Compon. Lett., in press.
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