Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
On length adaptation for the least mean square adaptive filters
Signal Processing - Fractional calculus applications in signals and systems
Adaptive carrier recovery systems for digital data communications receivers
IEEE Journal on Selected Areas in Communications
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Based on the least mean square (LMS) algorithm, an improved compensation method for finite impulse response-adaptive line enhancer (FIR-ALE) method has been proposed. In order to compare these two compensation methods, their power spectrums, bit error rate-signal-to-noise ratios (BER-SNR), learning curves, and signal constellations have been studied through Matlab simulations, while taking the 8PSK modulation signal as an example. The results of the comparison illustrate that the improved method enhances the compensation ability of the FIR-ALE method by 18 and 25 dB, when the jitter amplitude is 5^o and 15^o, respectively. Some factors influencing the compensation ability are studied by theoretical analysis and simulation under the condition of one-sinusoidal jitter and multiple-sinusoidal jitter. These factors include the phase jitter amplitude, the phase jitter frequency, the number of the filter taps, and the number of the pilot symbols. The results indicate that the compensation ability is unrelated to the phase jitter frequency and that the system becomes useless when the geometric sum of sinusoidal jitter amplitudes exceeds the hard decision distance.