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Adaptive thu phát không dây P11

RBF Turbo Equalization This chapter presents novel turbo equalization scheme, a which employs a RBF equaliser instead of the conventional trellis-based equaliserDouillard et al. [ 1.531. The basic principles of of turbo equalization will be highlighted. Structural, computational cost and performance comparisons of the RBF-based and trellis-based turbo equalisers areprovided. A novel element of our design isthat in order to reduce the computational complexity the RBF turbo of equaliser (TEQ), we propose invoking further iterations only, if the decoded symbol has a high error probability | Adaptive Wireless Tranceivers L. Hanzo C.H. Wong M.S. Yee Copyright 2002 John Wiley Sons Ltd ISBNs 0-470-84689-5 Hardback 0-470-84776-X Electronic Chapter 11 RBF Turbo Equalization This chapter presents a novel turbo equalization scheme which employs a RBF equaliser instead of the conventional trellis-based equaliser of Douillard et al. 153 . The basic principles of turbo equalization will be highlighted. Structural computational cost and performance comparisons of the RBF-based and trellis-based turbo equalisers are provided. A novel element of our design is that in order to reduce the computational complexity of the RBF turbo equaliser TEQ we propose invoking further iterations only if the decoded symbol has a high error probability. Otherwise we curtail the iterations since a reliable decision can be taken. Let us now introduce the concept of turbo equalization. 11.1 Introduction to Turbo equalization In the conventional RBF DFE based systems discussed in Chapter 10 equalization and channel decoding ensued independently. However it is possible to improve the receiver s performance if the equaliser is fed by the channel outputs plus the soft decisions provided by the channel decoder invoking a number of iterative processing steps. This novel receiver scheme was first proposed by Douillard et al. 153 for a convolutional coded binary phase shift keying BPSK system using a similar principle to that of turbo codes and hence it was termed turbo equalization. This scheme is illustrated in Figure 11.1 which will be detailed during our forthcoming discourse. Gertsman and Lodge 308 extended this work and showed that the iterative process of turbo equalization can compensate for the performance degradation due to imperfect channel estimation. Turbo equalization was implemented in conjunction with turbo coding rather than conventional convolutional coding by Raphael and Zarai 309 demonstrating an increased performance gain due to turbo coding as well as with advent of .