The bi-orthogonal codes for embedding Side-Information (SI) in data-based blind SLM (BSLM) proposed in Joo et al. (2012) produce better bit error rate (BER) and SI error rate (SIER) performance compared to binary codes. However, the authors do not provide details for code generation; instead, they list some codes with a length of / and a minimum Hamming distance of / . The suggested bi-orthogonal code does not work for any value of the maximum iteration number other than = ⌈ / ⌉. Therefore, this paper proposes two algorithms for generating codes for any value of . The proposed methods maintain the normalized minimum Hamming distance between generated codes to . . However, the second proposed algorithm, which works in the case of < ⌊ ⌋, is also able to only consider codes with a maximum Hamming distance, allowing it to improve SIER performance. Thus, the second proposed algorithm improves SIER performance by up to 1 dB at Eb/No=3dB. Furthermore, the proposed algorithms are able to generate a multiple set of codes that deliver same performance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.