Characterization and Linearization of 5G mm-Wave Power Amplifiers Using Reduced-Sampling Observation Receiver

Abstract

In this work, an advanced calibration routine is proposed to determine the frequency response of a feedback receiver over a targeted linearization bandwidth, when only sub-Nyquist (aliased) samples are available. A new approach is then devised to apply a direct learning algorithm along with the proposed receiver calibration routine, and thus linearize a millimeter wave power amplifier (PA), driven by a modulated signal, using digital pre-distortion (DPD) with a reduced feedback sampling rate. The proposed new calibration routine and DPD approach are successfully applied to linearize a PA under test, operating at 24 GHz and driven by single carrier 16-QAM and carrier aggregated LTE signals of 200MHz modulation bandwidth using a feedback receiver with sampling rates of 2 Gsps, 1 Gsps and 500 Msps. Adjacent channel power ratio of about 49 dBc and normalized mean square error of about 2% are obtained at the linearized PA output using the three sampling rates.