Lightweight initialization design for robust ICA-R algorithm using MMSE criterion

To enhance the blind signal separation performance of independent component analysis with reference (ICA-R) in communication spectrum-sharing applications and to reduce its hardware implementation complexity, a simplified non-random separation vector initialization method based on the minimum mean square error (MMSE) criterion was proposed, aiming at a lightweight design of a robust ICA-R algorithm. In this method, the observation signal matrix was directly multiplied by the reference signal to compute the initial value of the separation vector. Theoretical analysis and hardware simulation results show that, compared with existing methods, the proposed approach offers comprehensive advantages including high separation accuracy, strong robustness, fast convergence, and low hardware overhead. Experimental results on the separation and extraction of spectrally overlapped communication signals using the ICA-R algorithm demonstrate that the proposed method can still achieve efficient and robust target signal separation and extraction under strong co-channel interference, while effectively reducing the algorithm runtime. Thus, it is suitable for resource-constrained communication devices with stringent requirements for real-time performance, robustness, and computational efficiency.