Suppression of intermittent interference using smart antenna with distributed training scheme
Fayyaz Ahmad Siddiqui, V. Sreng, Florence Danilo-Lemoine, David D. Falconer · 2014
In this paper, an adaptive antenna arrays processing based on Sample Matrix Inversion (SMI) algorithm with a novel training scheme is presented. The training scheme used is known as distributed training scheme [1]. The scheme uses distributed placement of the training symbols throughout the packet. The channel estimation, along with this particular training scheme, is designed to track intermittent interference. This type of interference arises due to an uncontrolled and unpredictable environment such as that of a license-exempted case. In this work, we show the comparison between the performance of distributed scheme with pre-amble training method and also with some iterative based adaptation algorithms like LMS and CMA. A lower bound theoretical analysis is made to compare its result to the simulation results. Moreover, analytical expression for the excess MSE are derived for both distributed and preamble training schemes. Short blocks scenario for the creation of intermittent interference is created by using a batch Poisson traffic model.