ISI and Noise is always a great problem in wireless communication. It causes error in received signal at receiver side and removing it to get error free signal is always a challenging job. The signal distortion is unavoidable in wireless communication so lot of methods have been proposed to remove distortion mainly caused by ISI and delay spread. One of the method to combat ISI is to introduce cyclic prefix (CP) between the transmitted symbols. CP provides immunity against ISI and delay spread. So as long as dispersion of channel is shorter than length of CP, the performance of channel is good. So to keep performance of channel good, we have to shorten the channel so that length of CP must be larger than channel impulse response. Indeed, the insertion of cyclic Prefix (CP) through symbols offers greater immunity against deadlines broadcast and interference. Accordingly, as channel dispersion is no longer than the CP, the system performance does not degrade and need of time-domain equalization is usually not immediate. However, time-dispersive channel reduces the data transmission at meaningful rate since the received signal is corrupted by interference between the two carriers and inter symbol. To avoid degradation of performance, technique for shortened channel, commonly known as the time domain equalizer (TEQ) is introduced. The only price to pay for the insertion of a CP is the meaningful reduction of the transmission rate, which turns out to be negligible if the duration of CP is negligible compared to the transmitted symbol. In practice, length of CP cannot be also increased excessively. Therefore, if the CP is not long enough, the received signal is corrupted by Inter-Carrier and the inter-symbol interference (ISI and ICI) which decreases considerably the system performance. To avoid interference, we need to insert an equalizer in the time domain (TEQ) at the receiver front end to shorten the channel IR of the CP length. There is large complexity associated with channel shortening. Because of large size of channel matrices, it’s very difficult job to find channel shortener at every time instant, as channel shortener calculation involves matrix inversion. So in this research we will discuss method to reduce complexity of wireless channel shortening. By reducing complexity we save time but we v sacrifice efficiency. So we will keep balance between efficiency of shortener and complexity associated with its calculation.

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