Blind adaptive MMSE equalization using prediction-based cross-correlation vector estimation

An adaptive blind MMSE channel equalization technique based on second-order statistics is investigated. We present an adaptive blind MMSE channel equalization using the multichannel linear prediction error method for estimating the cross-correlation vector. They can be implemented as RLS or LMS algorithms to recursively update the cross-correlation vector. Once the cross-correlation vector is available, it can be used for MMSE channel equalization. Unlike many known subspace methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch. The performance of our algorithms and comparisons with existing algorithms are shown.