The impact of white gaussian noise mismatch on linear and decision feedback equalizers

Analyzes the sensitivity of equalizers to white gaussian noise mismatch, which exists whenever the noise power observed during training differs from that observed during detection. A closed-form solution for the mean-square error is obtained for linear and decision feedback equalizers as a function of the channel spectrum and degree of noise mismatch. The results show that increasing equalizer complexity may actually degrade performance in the presence of channel mismatch.<>