Dynamic Analysis of Least Squares Estimation on Equalization Using a Systemic Approach

摘要

The observed growth trend of the wireless communications market will drive the development of new wireless systems, including equalizers. Linear equalization is still a relatively low computational demand and easy-to- implement solution that may increase reliability in low data rate devices such as the ones required for IoT systems and wireless sensor networks. However, the relationship between the mean squared error (MSE) and the matrix correlation of the Least Squares (LS) estimation procedure, with the bit error rate (BER) of the system, has not been fully investigated. This paper presents a description of the simulated BER behavior, caused by the influence of the matrix correlation and MSE, through a causal analysis derived from a systems thinking approach. Then, it is proposed a descriptive hypothesis of the main cause and effect relationships involved in the generation of the BER behavior, using different training sequences in the LS optimization procedure.