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Blind equalization based on adaptive forgetting factor, recursive least squares(RLS) with constant modulus algorithm(CMA), is investigated. The cost function of CMA is simplified to meet the second norm form to ensure the stability of RLS-CMA, and thus an improved RLS-CMA(RLS-SCMA) is established. To further improve its performance, a new adaptive forgetting factor RLS-SCMA(ARLS-SCMA) is proposed. In ARLS-SCMA, the forgetting factor varies with the output error of the blind equalizer during the iterative process, which leads to a faster convergence rate and a smaller steady-state error. The simulation results prove the effectiveness under the condition of the underwater acoustic channel.
Blind equalization based on adaptive forgetting factor, recursive least squares (RLS) with constant modulus algorithm (CMA), is investigated. The cost function of CMA is simplified to meet the second norm form to ensure the stability of RLS-CMA, and thus To further improve its performance, a new adaptive forgetting factor RLS-SCMA (ARLS-SCMA) is proposed. In ARLS-SCMA, the forgetting factor varies with the output error of the blind equalizer during the iterative process, which leads to a faster convergence rate and a smaller steady-state error. The simulation results prove the effectiveness under the condition of the underwater acoustic channel.