Abstract
Finite-length multiple-input multiple-output (MIMO) decision feedback equalizers (DFEs) that optimize the decision delays are investigated herein. The mean square error (MSE) of each output with respect to the decision delays is derived to form the basis of the optimization cost function. A genetic algorithm (GA) is implemented to reduce the computational burden of the search. Simulation results show that the GA successfully tracks the optimum decision delays with only a fraction of the computational complexity of the global search. Moreover, the use of optimized decision delays in the MIMO DFE for simulated fading MIMO channels provides an average improvement of 4.1 dB for the combined output MSE.
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