Blind channel identification and equalization in dense wireless sensor networks with distributed transmissions

In densely deployed wireless sensor networks, signals of adjacent sensors can be highly cross-correlated. This property is utilized for blind channel identification and equalization. Blind equalization can be performed with linear complexity and with robustness to all channel conditions. Transmissions are more power and bandwidth efficient, which is especially important for wideband sensor networks. The cross-correlation property and the finite sample effect are analyzed. Simulations demonstrate the superior performance of the proposed method.