Experimental Comparison of Digital Beamforming Interference Cancellation Algorithms using a Software Defined Radio Array

Digital beamforming (DBF) is the holy grail of antenna array technology. However, very few DBF arrays have been demonstrated due to the high cost of implementation. Here we report on a cost-effective platform for DBF using a software-defined radio array and present experimental results on interference cancellation using the DBF platform. We transmitted digital data modulated with 4-QAM from a single-element transmitter to the 4-element DBF array while a single-element interferer disrupted the transmission. Digital beamforming interference cancellation was then implemented with three different algorithms, namely, least mean squares, sample matrix inversion, and recursive least squares. The bit error rates in each case are compared for several interference power levels. The results indicate that all adaptive methods provide significant improvements over unit weights, with sample matrix inversion outperforming recursive least squares and recursive least squares outperforming least mean squares.