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Low-density parity-check (LDPC) codes are very powerful error correction codes for bit-interleaved coded modulation (BICM) schemes. In BICM schemes the bits of one symbol have unequal error protection. In this paper, we show how to improve the performance of given LDPC codes by mapping the variable nodes of certain degree in a special way to the different(More)
Irregular low-density parity-check (LDPC) codes constructed from small protographs are one of the most powerful LDPC block codes. In this paper, we introduce the convolutional version of these codes. LDPC convolutional codes constructed from protographs have some advantages in comparison to LDPC block codes constructed from protographs, e.g., an effective(More)
In this paper the broadband wireless access system provided by the IEEE 802.16 wireless MAN air interface with its amendment to mobile users (IEEE 802.16e) is addressed. We exclusively consider data transmission in the uplink based on scalable OFDMA. We provide performance results for the most important forward error correcting (FEC) schemes intended for(More)
OF THE DISSERTATION The Use of Arti cial Intelligence to Improve the Numerical Optimization of Complex Engineering Designs by Mark A. Schwabacher Dissertation Directors: Thomas Ellman and Andrew Gelsey Gradient-based numerical optimization of complex engineering designs promises to produce better designs rapidly. However, such methods generally assume that(More)
In this paper, we describe a method, how to optimize the asymptotic puncturing distributions for low-density parity-check codes constructed with different algorithms. Therefore, we generalize the discretized density evolution such that we can take care of the structure of the code. We show by density evolution and by simulations that even for the same(More)
It is well known that search-space reformulation can improve the speed and reliability of numerical optimization in engineering design. We argue that the best choice of reformulation depends on the design goal, and present a technique for automatically constructing rules that map the design goal into a reformulation chosen from a space of possible(More)