研究目的
To characterize transmitters by multiple input multiple output (MIMO) Volterra series and identify the dominant effects in the transmitter structure for designing behavioral models and compensation techniques.
研究成果
The proposed technique using input signals of different periodicity effectively decomposes the MIMO Volterra series into self and cross kernels, identifying the dominant structure in a MIMO transmitter. This can be exploited in designing efficient behavioral models and digital compensation techniques.
研究不足
The technique's effectiveness is dependent on the choice of input signal periodicities and may be limited by the measurement noise and the relative level of the cross-kernel compared to self-kernels.
