Interference Gaussianization: Time-Domain Inter-Symbol Spreading for Blind Adaptive Array Signal Source Identification

This paper proposes a novel blind adaptive array (BAA) interference suppression scheme incorporated with a time-domain symbol spreading (TISS). It can expand an operational region of BAA irrespective of input signal-to-interference power ratio (SIR) conditions. Independent component analysis (ICA) and constant modulus algorithm (CMA) are expected as the promising BAA approaches to suppress unknown interference which is extensively caused due to the small cell densification and spectrum superposing between a plurality of wireless communication systems. These BAA algorithms basically require an input SIR to be larger than 0 dB to suppress interference by capturing the desired signal appropriately. The proposed scheme applies TISS to the transmission signal for the desired user and then de-spreads it at the receiver side. It Gaussianizes statistical inherence of the interference signals and can bring beneficial effects; reducing the kurtosis for ICA as well as collapsing the constant envelope properties for CMA. Such intentional modification to the interference signals can improve the capture performance of the desired signal and realize its effective identification even at SIR <; 0 dB. Its fundamental effectiveness is presented through various perspectives such as input SIR, symbol amount, and modulation orders.