TY - GEN
T1 - The cube coefficient subspace architecture for nonlinear digital predistortion
AU - Herman, Matthew
AU - Miller, Benjamin A.
AU - Goodman, Joel
PY - 2008
Y1 - 2008
N2 - In this paper, we present the cube coefficient subspace (CCS) architecture for linearizing power amplifiers (PAs), which divides the overparametrized Volterra kernel into small, computationally efficient subkernels spanning only the portions of the full multidimensional coefficient space with the greatest impact on linearization. Using measured results from a Q-Band solid state PA, we demonstrate that the CCS predistorter architecture achieves better linearization performance than state-of-the-art memory polynomials and generalized memory polynomials.
AB - In this paper, we present the cube coefficient subspace (CCS) architecture for linearizing power amplifiers (PAs), which divides the overparametrized Volterra kernel into small, computationally efficient subkernels spanning only the portions of the full multidimensional coefficient space with the greatest impact on linearization. Using measured results from a Q-Band solid state PA, we demonstrate that the CCS predistorter architecture achieves better linearization performance than state-of-the-art memory polynomials and generalized memory polynomials.
UR - http://www.scopus.com/inward/record.url?scp=70349678519&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2008.5074750
DO - 10.1109/ACSSC.2008.5074750
M3 - Conference contribution
AN - SCOPUS:70349678519
SN - 9781424429417
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1857
EP - 1861
BT - 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
T2 - 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
Y2 - 26 October 2008 through 29 October 2008
ER -