Li, K., Ghazi, A., Tarver, C. et al. J Sign Process Syst (2017) 89: 417. https://doi.org/10.1007/s11265-017-1233-y
Parallel digital predistortion design on mobile GPU and embedded multicore CPU for mobile transmitters
|Author:||Li, Kaipeng1; Ghazi, Amanullah2; Tarver, Chance1;|
1Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
2Department of Computer Science and Engineering, University of Oulu, Oulu, Finland
3Department of Electronics and Communication Engineering, Tampere University of Technology, Tampere, Finland
|Online Access:||PDF Full Text (PDF, 1 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019060719445
|Publish Date:|| 2019-06-07
Digital predistortion (DPD) is a widely adopted baseband processing technique in current radio transmitters. While DPD can effectively suppress unwanted spurious spectrum emissions stemming from imperfections of analog RF and baseband electronics, it also introduces extra processing complexity and poses challenges on efficient and flexible implementations, especially for mobile cellular transmitters, considering their limited computing power compared to basestations. In this paper, we present high data rate implementations of broadband DPD on modern embedded processors, such as mobile GPU and multicore CPU, by taking advantage of emerging parallel computing techniques for exploiting their computing resources. We further verify the suppression effect of DPD experimentally on real radio hardware platforms. Performance evaluation results of our DPD design demonstrate the high efficacy of modern general purpose mobile processors on accelerating DPD processing for a mobile transmitter.
Journal of signal processing systems for signal image and video technology
|Pages:||417 - 430|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported by the US NSF under grants EECS-1408370, CNS-1265332, ECCS-1232274, and the Finnish Agency of Innovation, Tekes.
© Springer Science+Business Media New York 2017. This is a post-peer-review, pre-copyedit version of an article published in Journal of Signal Processing Systems. The final authenticated version is available online at: https://doi.org/10.1007/s11265-017-1233-y.