This paper investigates an approach for speaker identification in a remote access system based on coded speech signals. The aim of using the coding process is to decrease the amount of transmitted data via the channel. In this proposed system, the speech signal is coded by two different coding techniques. It can be coded either by linear predictive coding or compressive sensing. The coded speech signal is transmitted into the receiver via the wireless communication channel. At the receiver, the received signal is decoded, and then speaker identification system is applied on the decoded signal. During the transmission process, the channel errors affect on the transmitted signal, so they should be taken into account. The speaker identification process is used to achieve the security needed for the remote access system. In speaker identification system, the feature vectors are captured from different discrete transforms such as discrete wavelet transform, discrete cosine transform, and discrete sine transform, besides the time domain. The recognition rate for all transforms is computed to evaluate the effect of coded signals on the performance of the speaker identification system. The results proved that the discrete cosine transform and discrete wavelet transform are the best. In addition to the proposed system gives close recognition results to those obtained from real speech signals revealing a simple degradation effect due to the speech coding.