Sparse Identification of Volterra Models for Power Amplifiers Without Pseudoinverse Computation

Abstract

We present a new formulation of the doubly orthogonal matching pursuit (DOMP) algorithm for the sparse recovery of Volterra series models. The proposal works over the covariance matrices by taking advantage of the orthogonal properties of the solution at each iteration and avoids the calculation of the pseudoinverse matrix to obtain the model coefficients. A detailed formulation of the algorithm is provided along with a computational complexity assessment, showing a fixed complexity per iteration compared with its previous versions in which it depends on the iteration number. Moreover, we empirically demonstrate the reduction in computational complexity in terms of runtime and highlight the pruning capabilities through its application to the digital predistortion of a class J power amplifier operating under 5G-NR signals with the bandwidth of 20 and 30 MHz, concluding that this proposal significantly outperforms existing techniques in terms of computational complexity.

A Crest Factor Reduction Technique for LTE Signals with Target Relaxation in Power Amplifier Linearization

“…To handle the baseband waveforms, digital multiplexing formats such as orthogonal frequency division multiplexing (OFDM) require an extensive range of data to signals used in wide code division multiple access (W-CDMA), and long-term evolution (LTE), which is the standard used for broadband 5G New Radio (NR) communication networks [ 4 ], or as the proposed predistortion algorithm for peak to average power ratio (PAPR) reduction in OFDM transmission, as in [ 5 ] without a feedback loop. Due to the demand for high bandwidth efficiency from 20 to 30-MHz [ 6 ], and the need for power efficiency, the usage of the DPD techniques offer digital flexibility to linearize the undesired behavior of the PAs. Applications in the 2 GHz band is a current topic, whose techniques are migrating towards 5G NR, applications for 10-MHz LTE bandwidths, so it is essential to develop methodologies that evaluate the error vector magnitude (EVM) and adjacent channel power ratio (ACPR) achieved [ 7 ].…”

A General Order Reduction Method of Wideband Digital Predistortion Model Using Attention Mechanism

“…At present, the most common and popular predistortion models are the full Volterra (FV) series models. Since these models' parameters are linear with respect to the output of the system, these models can be easily identified by the classical regression theory [9]. However, the complex nonlinear behaviors (including nonlinearity and memory effects [6]) caused by the increase of the signal bandwidth and complex modulation modes will lead to the curse of dimensionality of the FV models [9].…”

“…Since these models' parameters are linear with respect to the output of the system, these models can be easily identified by the classical regression theory [9]. However, the complex nonlinear behaviors (including nonlinearity and memory effects [6]) caused by the increase of the signal bandwidth and complex modulation modes will lead to the curse of dimensionality of the FV models [9]. Therefore, the order reduction of the FV model has become an effective means to improve the availability of the model and reduce the cost [10,11].…”

“…To solve the ill-condition of the equation system caused by the high correlation between the basis function terms, a doubly OMP (DOMP) algorithm uses Gram-Schmidt orthogonalization to eliminate the correlation between the selected and unselected basis function spaces after each iteration [17]. However, the pseudo inverse calculation and the Kronecker product calculation in the orthogonalization process lead to the high computational complexity of the algorithm [9]. To this end, the simplified sparse parameter identification DOMP (SSPI DOMP) algorithm is proposed to implement the pseudo inverse computation through the recursive process [19], which effectively reduces the computational complexity.…”

“…To this end, the simplified sparse parameter identification DOMP (SSPI DOMP) algorithm is proposed to implement the pseudo inverse computation through the recursive process [19], which effectively reduces the computational complexity. Reference [9] also proposed to realize the pseudo inverse calculation by processing the covariance matrix by the orthogonal properties, to reduce the calculation cost further. In addition, a predistortion model pruning algorithm based on adaptive principal component analysis (PCA) was proposed in reference [14].…”