<title>Adaptive equalization techniques for indoor dynamic wireless communication channels</title>

Abstract

A modified constant modulus algorithm (MCMA) algorithm for adaptive channel equalization for QAM signals is proposed. The proposed algorithm minimizes a cost function that consists of amplitude- and phase-dependent terms. The phase term complements the amplitude-dependent term that is provided by the conventional constant modulus algorithm (CMA). This term should satisfy several properties that guarantee extremum values at the QAM signal levels and at maximum deviations from these levels. Further, the properties should allow symmetry and uniformity across all alphabets. It is shown that the even power co-sinusoidal functions are appropriate for phase term representations. The MCMA is compared with the CMA and the Stop-and-Go Algorithm (SGA) for blind equalization. The performance is evaluated for indoor wireless channels using both transient and steady-state behaviors of the mean square error (MSE). A channel model is developed based on spectral observations of the unlicensed U-NII frequency band, and shown to be time-varying and to exhibit frequency selective fading. While the CMA is successful in achieving good performance, it is shown that both MCMA and SGA are superior and more robust in low SNR environments. The paper also presents a performance comparison of symbol-spaced and sample-spaced equalizations for a single and two-antenna receiver. Simulation results demonstrate that using multi-antenna receiver can effectively improve adaptive channel equalizations by increasing convergence rate and decreasing steady-state mean square error.