الفهرس | Only 14 pages are availabe for public view |
Abstract Over the past 100 years, great advances have been made in the wireless communication technology. Personal communication devices now enable communications to and from virtually anywhere on the planet, and even outside. To improve performance, coverage and efficiency, modern wireless communication systems utilize digital signaling techniques. With digital signaling, it is possible to use error control coding. Recently, a new coding scheme called ”turbo coding” has generated tremendous interest in channel coding of digital communication systems due to its high error correcting capability. Two key innovations in turbo coding are parallel concatenated encoding and iterative decoding. A soft-in soft-out component decoder can be implemented using the maximum a posteriori (MAP) or the maximum likelihood (ML) decoding algorithm. While the MAP algorithm offers better performance than the ML algorithm, the computation is complex and not suitable for hardware implementation. The log-MAP algorithm, which performs necessary computations in the logarithm domain, greatly reduces hardware complexity. With the proliferation of the battery powered devices, power dissipation, along with speed and area, is a major concern in VLSI design. The near optimum performance of turbo codes and/or the performance gains realized via iterative decoding is conditioned upon reliable knowledge of the channel side information. Lack of this knowledge can severely degrade the performance of turbo codes and/or offset any gains that may otherwise have been realized via turbo processing. Therefore, the need for reliable channel knowledge necessitates some form of channel estimation at the receiver. The aim of this thesis is to design and implement an iterative decoder with a channel estimator then employ and exploit the estimator to take a decision of terminating the iterations of the turbo III (iterative) decoder to optimize the decoder power consumption. The iterative decoder based on the MAP decoding algorithm (which is categorized as a Trellis-based symbol by symbol estimation algorithm) uses the channel information given by the estimator to make a termination operation of the decoding process. The designs of the decoder and the estimator are combined into one embedded design. The thesis demonstrates that an adaptive number of iterations calculated depending on the channel state offers a power efficient system than that depending on a fixed number of decoding iterations. |