Azad, Ehsan M., Quaglia, Roberto  ORCID: https://orcid.org/0000-0003-3228-301X, Chadhary, Kauser, Bell, James J.  ORCID: https://orcid.org/0000-0002-4815-2199 and Tasker, Paul J.  ORCID: https://orcid.org/0000-0002-6760-7830
      2022.
      
      Cardiff model utilization for predicting the response of multiple-input power amplifiers.
      Presented at: Mediterrannean Microwave Symposium (MMS),
      Pizzo Calabro, Italy,
      9-13 May 2022.
      
      Proceedings of Microwave Mediterranean Symposium (MMS).
      
      
      
       
      
      
      IEEE,
      
      10.1109/MMS55062.2022.9825516
    
  
    
       
    
    
  
  
         | 
      
Preview  | 
          
            
PDF
 - Accepted Post-Print Version
 Download (1MB) | Preview  | 
        
Abstract
This paper explores the use of the Cardiff non-linear behavioral model to characterize the response of multiple-input power amplifiers. In particular, a case study is presented on a 300 W load modulated balanced amplifier operating at 2.1 GHz. The model mathematical formulation is presented, and the comparison between original data and model shows an error below 3%. More importantly, it is shown that the model can accurately interpolate between characterization points allowing a reduction of up to 96% of the points needed to accurately predict the model behavior. This significantly reduces the simulation and measurement time for multiple-input PA's whilst attempting to determine the optimal driving conditions.
| Item Type: | Conference or Workshop Item (Paper) | 
|---|---|
| Date Type: | Publication | 
| Status: | Published | 
| Schools: | Schools > Engineering | 
| Publisher: | IEEE | 
| ISBN: | 9781665471114 | 
| ISSN: | 2157-9822 | 
| Funders: | Ampleon | 
| Date of First Compliant Deposit: | 22 July 2022 | 
| Date of Acceptance: | 15 April 2022 | 
| Last Modified: | 30 Nov 2022 08:22 | 
| URI: | https://orca.cardiff.ac.uk/id/eprint/151420 | 
Actions (repository staff only)
![]()  | 
              Edit Item | 

							


    
    
  
  
        
 Altmetric
 Altmetric