Blind equalization of single-input multi-output channels has practical value for inverse problems encountered in communications, sonar, and seismic data processing. Relying on diversity (sufficient number of multiple outputs), we bypass the channel estimation step and derive direct blind FIR equalizers of co-prime FIR channels. There are no constraints on the inaccessible input, apart from a minimum persistence of excitation condition; the input can be deterministic or random with unknown color or distribution. At moderate SNR (>20 dB), the resulting algorithms remain operational even with very short data records (<100 samples), which makes them valuable for equalization of rapidly fading multipath channels. Complexity, persistence of excitation order, and mean-square error performance tradeoffs are delineated for equalizers of singleshift (semi-blind), pair, or, multiple shifts estimated separately or simultaneously. Optimum and suboptimum combinations of the equalizers' outputs are also studied. Simulations illustrate the proposed algorithms and compare them with dual deterministic channel identification algorithms.
- Multichannel system identification