Turbo coding is a powerful coding technique that can provide highly reliable data transmission at extremely low signal-to-noise ratios. Owing to the computational complexity of the employed decoding algorithm, the realization of turbo decoders usually takes a large amount of memory space and potentially long decoding delay. Therefore, an efficient memory management strategy becomes one of the key factors toward successfully implementing turbo decoders. This paper focuses on the development of general structures for efficient memory management of turbo decoders employing the sliding-window (Log-) MAP algorithm. Three different structures and the associated mathematic representations are derived to evaluate the required memory size, average decoding rate, and latency based on the speed and the number of the adopted processors. Comparative results show the dependency of the resulting performance based on a set of parameters; thus provide useful and general information on practical implementations of turbo decoders.

Because of non-negligible ISI due to the Gaussian filter and delay spread in the GSM system, an equalizer is required. In this letter, a joint sliding window channel estimation and timing adjustment method is proposed for maximum likelihood sequence equalizer. And also a smoothing algorithm is presented in order to improve the equalizer performance. This smoothing scheme utilizes a variant of LMS algorithm to tune the channel coefficient estimates. Simulation results show that the proposed scheme is adequate for channel estimation of the adaptive equalizer.