Ordered statistics decoding (OSD) can achieve near maximum likelihood (ML) decoding performance for BCH codes. However, Gaussian elimination (GE) that delivers the systematic generator matrix of the code has an uncompromised latency. Addressing this challenge, this paper proposes a low-latency OSD (LLOSD) for BCH codes. Since BCH codes are binary subcodes of Reed-Solomon (RS) codes, codeword candidates can be produced using the RS systematic generator matrix, whose entries can be generated in parallel. By eliminating the non-binary codeword candidates and identifying the ML codeword, the LLOSD yields a lower latency as well as complexity than the OSD. It is shown that the LLOSD can be interpreted as generating the codeoword candidates through systematic encoding of a punctured BCH codeword, explaining its low-complexity feature. Moreover, the segmented variant is proposed to further facilitate the LLOSD. In order to decode long BCH codes, a hybrid soft decoding (HSD) is finally proposed. It integrates the LLOSD and the algebraic Chase decoding that can effectively provide extra TEPs for the LLOSD, enhancing the decoding performance. Both the complexity and performance of the proposed decoding are analyzed, demonstrating their advantage over the relevant state-of-the-art decoding.

This paper proposes a low-latency ordered statistics decoding (OSD) algorithm for BCH codes. The OSD latency is mainly caused by Gaussian elimination (GE) that produces a systematic generator matrix of the code. Considering BCH codes is binary subcodes of Reed-Solomon (RS) codes, we show that the BCH codeword candidates can be produced through the systematic generator matrix of the corresponding RS code. The systematic generator matrix of an RS code can be formed by generating the linearly independent RS codewords in parallel, replacing the GE process and enabling a low OSD latency. This paper further proposes a segmented variant that facilitates the decoding by reducing the number of test error patterns (TEPs). Complexity of the proposed OSD is also analyzed. Our simulation results show that the proposed decoding can achieve a similar performance as the conventional OSD, but with a lower decoding complexity. The decoding latency can be reduced over the conventional OSD substantially.

MuSeeCol is a collaborative music creation system that allows two users to jointly and playfully compose melodic or percussive music. Collaborative music is rendered when two face-to-face users interact with their respective side of a see-through multi-touch sensitive acrylic panel. We present user study findings from nine pairs of individuals who have used the MuSeeCol system collaboratively and summarize some general observations of what types of interaction designs make for effective face-to-face collaboration.