Bin Nong

Single-channel blind separation of co-frequency communication signals has relied on real-valued networks or attention modules blind to complex structure, which cannot exploit the phase coupling between the I and Q rails. ComplexLightweightSepNet embeds a complex squeeze-and-excitation block in a complex convolutional encoder-decoder, scaling complex features with a real-valued channel weight that preserves phase, at 235,525 parameters. On 5 Hz co-frequency synthetic mixtures across four modulations it reaches a five-seed mean SDR of 2.31 dB with 0.62 dB standard deviation; paired Wilcoxon tests do not reach alpha = 0.05, so the result is positioned as a working point at the 235K scale, not an inferred advantage.

Single-channel blind separation of co-frequency communication signals has relied on real-valued networks or attention modules blind to complex structure, which cannot exploit the phase coupling between the I and Q rails. ComplexLightweightSepNet embeds a complex squeeze-and-excitation block in a complex convolutional encoder-decoder, scaling complex features with a real-valued channel weight that preserves phase, at 235,525 parameters. On 5 Hz co-frequency synthetic mixtures across four modulations it reaches a five-seed mean SDR of 2.31 dB with 0.62 dB standard deviation; paired Wilcoxon tests do not reach alpha = 0.05, so the result is positioned as a working point at the 235K scale, not an inferred advantage.