5 research outputs found

    High-rate self-synchronizing codes

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    Self-synchronization under the presence of additive noise can be achieved by allocating a certain number of bits of each codeword as markers for synchronization. Difference systems of sets are combinatorial designs which specify the positions of synchronization markers in codewords in such a way that the resulting error-tolerant self-synchronizing codes may be realized as cosets of linear codes. Ideally, difference systems of sets should sacrifice as few bits as possible for a given code length, alphabet size, and error-tolerance capability. However, it seems difficult to attain optimality with respect to known bounds when the noise level is relatively low. In fact, the majority of known optimal difference systems of sets are for exceptionally noisy channels, requiring a substantial amount of bits for synchronization. To address this problem, we present constructions for difference systems of sets that allow for higher information rates while sacrificing optimality to only a small extent. Our constructions utilize optimal difference systems of sets as ingredients and, when applied carefully, generate asymptotically optimal ones with higher information rates. We also give direct constructions for optimal difference systems of sets with high information rates and error-tolerance that generate binary and ternary self-synchronizing codes.Comment: 9 pages, no figure, 2 tables. Final accepted version for publication in the IEEE Transactions on Information Theory. Material presented in part at the International Symposium on Information Theory and its Applications, Honolulu, HI USA, October 201

    Optimal large linear complexity frequency hopping patterns derived from polynomial residue class rings

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    We construct new sequences over finite rings having optimal Hamming correlation properties. These sequences are useful in frequency hopping multiple-access (FHMA) spreadspectrum communication systems. Our constructions can be classified into linear and nonlinear categories, both giving optimal Hamming correlations according to Lempel-Greenberger bound. The nonlinear sequences have large linear complexity and can be seen as a generalized version of GMW sequences over field
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