Joint Power Amplifiers and I/Q Modulator Impairments Modelling and Compensation for LTE Transmitters Using Artificial Neural Networks

This work introduces joint power amplifier (PA) and I/Q modulator modelling and compensation for LongTerm Evolution (LTE) transmitters using artificial neural networks (ANNs). The proposed solution util-izes a powerful nonlinear autoregressive with exogenous inputs (NARX) ANN architecture, which yieldsnoticeable results for high peak to average power ratio (PAPR) LTE signals. Given the ANNs learning capa-bilities, this one-step solution, which includes the mitigation of both PA nonlinearity and I/Q modulatorimpairments, is both accurate and adaptable

Evaluation of nonlinear distortion in MIMO transmitters

In this paper, an evaluation of unwanted effects in Multiple Input Multiple Output (MIMO) transmitters is described. Complete 2×2 and 4×4 MIMO Orthogonal Frequency Division Multiplex (OFDM) transmitters are simulated for the purpose of quantifying all potential unwanted effects such as Power Amplifiers' (PAs) nonlinearity, linear and nonlinear crosstalk, and IQ modulator imperfections. An experimental analysis of a 2×2 MIMO transmitter using two-tones and WCDMA signal is presented.