Font Size: 

In wireless channels there are Non-idealities that cause distortion to the mobile signalsuch as long distance, multipath and the noise that the channel added to the transmittedsignal. This paper utilizes adaptive filtering techniques to solve this channel distortion.Consequently, an adaptive FIR blind identification architecture is developed using fouradaptive algorithms to estimate wireless time invariant as well as time varying channels.The four adaptive algorithms are least mean square (LMS), normalized least square(NLMS), recursive least square (RLS) and affine projection algorithm (AFP). The resultsshows that the RLS outperforms other algorithm in wireless time-invariant channel withleast mean square error of (0.0116), and AFA outperforms other algorithms in wirelesstime-variant channel with least square error of (0.433) and fastest convergence rate. Theimplications of this wireless channel identification architecture are feasible in detectingnext-generation 5G channels and underwater acoustic channel to provide the channelinformation for further signal processing.