In this paper, we propose a pipelined architecture for an equalizer based on the Multilevel Modified Constant Modulus Algorithm (MMCMA). We also provide the correction factor that mathematically converts the proposed pipelined adaptive equalizer into an equivalent non-pipelined conventional MMCMA based equalizer. The proposed method of pipelining uses modules with 6 filter coefficients, resulting in an overall latency of a single sampling period, along the main transmission line. The basic concept of the proposed architecture is to implement the Finite Impulse Response (FIR) filter and the algorithm portion of the adaptive equalizer, such that the critical path of the whole circuit has a maximum of three complex multipliers and three adders.

In this paper, we propose an adaptive algorithm for an IIR adaptive line enhancer (ALE) based on constrained FIR ADF. The two constraints that are considered are the unit norm constraint and zeros constraint. By incorporating these two constraints, we show that the effect of a white disturbance signal on the convergence of the ALE is eliminated in the mean sense. The mathematical analysis for exact modeling also indicates that there exists a solution, which gives perfect estimation of the frequencies of the sinusoidal signals. Furthermore, by using a sufficiently small step size and introducing a control mechanism, the convergence of a second order ALE is guaranteed even if there is a sudden change in the frequency of the input sinusoidal signal. Simulation results that are presented, verify these properties.