ACPR prediction of multi-carrier systems through behavioural modelling of power amplifiers using measured two-tone transfer characteristics and statistical techniques

Behavioural models for power amplifiers (PA) have traditionally been developed based on conventional AM-AM and AM-PM curves from one-tone measurements, which discounts the presence of memory in the system. However, as signal bandwidth increases particularly in multicarrier spread spectrum systems, memory effects become more severe. These effects result from the frequency response of matching networks, nonlinear capacitances of the transistors and the response of the bias networks. Multi-stage high power amplifiers require a more accurate behavioural model to provide a better description of memory effects and highly nonlinear characteristics than the memoryless models based on single-tone transfer characteristics. This is achieved using measured two-tone transfer characteristics of the amplitude and phase of the fundamental, IM3 and IM5 components, which includes highly nonlinear components that represent the amplifier's significant memory. A statistical technique is then applied to predict spectral regrowth of a multicarrier signal due to the nonlinearity of the PA using the autocorrelation moments of the signal and the derived behavioural model. This statistical method allows accurate, fast and efficient prediction of the adjacent channel power ratio (ACPR) of the communication system without time-consuming time-domain simulations.