This paper presents a receiving scheme to combat intersymbol interference (ISI) in digital transmissions protected by convolutional codes. The receiver performs two successive soft-output decisions through an iterative process, involving a symbol detector and a channel decoder. At each iteration, extrinsic information is extracted from the detection and decoding steps and used in the next iteration, similar to turbo-decoding. The receiver can be structured in a modular way, with performance directly related to the number of modules used. Simulation results show that turbo-equalization effectively mitigates multipath effects on Gaussian channels and partially on Rayleigh channels. The transmission channel is modeled as an equivalent discrete-time channel, with the modulator, transmission channel, and demodulator represented by a discrete-time model. Symbol detection is based on Maximum-Likelihood Sequence Estimation (MLSE) using the Viterbi algorithm. The detection and decoding modules are associated similarly to turbo-decoding. Soft outputs are provided by the symbol detector, and the samples from the equivalent discrete-time channel are processed iteratively. Turbo-equalization is based on the iterative exchange of extrinsic information between the symbol detector and the channel decoder. The principle involves using soft-output decisions from the channel decoder to improve the performance of the symbol detector. The extrinsic information is used in a feedback loop to refine the estimates of the symbols. Simulation results show that turbo-equalization achieves significant improvements in bit error rate (BER) compared to traditional methods. On Gaussian channels, turbo-equalization completely compensates for multipath effects, achieving performance similar to a non-selective Gaussian channel. On Rayleigh channels, while partial compensation is achieved, the BER remains close to that of a Gaussian channel without ISI. The results indicate that turbo-equalization is an effective method for overcoming multipath effects in digital transmissions. The paper concludes that turbo-equalization is a promising technique for combating ISI in multipath channels.This paper presents a receiving scheme to combat intersymbol interference (ISI) in digital transmissions protected by convolutional codes. The receiver performs two successive soft-output decisions through an iterative process, involving a symbol detector and a channel decoder. At each iteration, extrinsic information is extracted from the detection and decoding steps and used in the next iteration, similar to turbo-decoding. The receiver can be structured in a modular way, with performance directly related to the number of modules used. Simulation results show that turbo-equalization effectively mitigates multipath effects on Gaussian channels and partially on Rayleigh channels. The transmission channel is modeled as an equivalent discrete-time channel, with the modulator, transmission channel, and demodulator represented by a discrete-time model. Symbol detection is based on Maximum-Likelihood Sequence Estimation (MLSE) using the Viterbi algorithm. The detection and decoding modules are associated similarly to turbo-decoding. Soft outputs are provided by the symbol detector, and the samples from the equivalent discrete-time channel are processed iteratively. Turbo-equalization is based on the iterative exchange of extrinsic information between the symbol detector and the channel decoder. The principle involves using soft-output decisions from the channel decoder to improve the performance of the symbol detector. The extrinsic information is used in a feedback loop to refine the estimates of the symbols. Simulation results show that turbo-equalization achieves significant improvements in bit error rate (BER) compared to traditional methods. On Gaussian channels, turbo-equalization completely compensates for multipath effects, achieving performance similar to a non-selective Gaussian channel. On Rayleigh channels, while partial compensation is achieved, the BER remains close to that of a Gaussian channel without ISI. The results indicate that turbo-equalization is an effective method for overcoming multipath effects in digital transmissions. The paper concludes that turbo-equalization is a promising technique for combating ISI in multipath channels.