Abstract:

An improved equalization is proposed. Based on the principle of minimum mean square error (MMSE), the algorithm minimums the mean square error between the output of the equalization and the training codes. The objective function is transformed to the second order cone programming (SOC), which is solved by the standard interior point method. Comparing with traditional adaptive algorithms equalization based on least mean squares (LMS) and recursive least squares (RLS), the algorithm which does not need iterative process is not affected by the contradiction between convergent speed and precision. Therefore it overcomes the difficulty of parameters setting in adaptive equalization. Furthermore, the algorithm only needs shorter training codes to achieve the same equilibrium effect and is a guide to improve the communication efficiency.