Multi-Input Multi-Output MLP/BP-based Decision Feedback Equalizers for Overcoming Intersymbol Interference and Co-Channel Interference in Band-Limited Channels
نویسندگان
چکیده
This paper presents a multi-input multi-output (MIMO) multi-layered perceptron neural network with backpropagation algorithm (MLP/BP). The proposal is a waveform equalizer for distorted nonreturn-to-zero (NRZ) data recovery in band-limited channels with co-channel interference (CCI). From the simulation results, we note that the proposed design can recover severe distorted NRZ data as well as suppress intersymbol interference (ISI) and co-channel interference. As a result, the better performance as compared to LMS DFEs is achieved in the band-limited channels where the data rate is ten times as much as the channel bandwidth. Key-Words: Co-Channel Interference (CCI), Decision-Feedback Equalizer (DFE), Intersymbol Interference (ISI), Minimum Mean Square Error (MMSE), Multi-Layered Perceptron Neural Network with Backpropagation Algorithm (MLP/BP), and Nonreturn-to-Zero (NRZ).
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MLP/BP-based Decision Feedback Equalizers with High Skew Tolerance in Band-Limited Channels
A multi-layered perceptron neural network with backpropagation algorithm (MLP/BP) is realized as a waveform equalizer for distorted nonreturn-to-zero (NRZ) data recovery in band-limited channels. Moreover, the proposed approach can tolerate sampling clock skew and channel response variance. According to simulation results, the proposed design can recover severe distorted NRZ data with better pe...
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