Recently Bleichenbacher et al. proposed a decoding algorithm for interleaved (N, K) Reed-Solomon codes, which allows close to N-K errors to be corrected in many cases. We discuss the application of this decoding algorithm to concatenated codes

We derive lower bounds on the distance and error exponent of the coding scheme described in the title. The bounds are compared to the parameters and error performance of a concatenated code family with varying inner codes of equal rates and a fixed minimum-distance separable (MDS) code as the outer code, letting the inner and outer code lengths approach infinity.

The minimum distance of concatenated codes with Reed-Solomon outer codes and convolutional inner codes is studied. For suitable combinations of parameters the minimum distance can be lower-bounded by the product of the minimum distances of the inner and outer codes. For a randomized ensemble of concatenated codes a lower bound of the Gilbert-Varshamov type is proved.>

Error-correcting capabilities of concatenated codes with maximum distance separable (MDS) outer codes and time-varying inner codes, used on memoryless discrete channels with maximum-likelihood decoding, are investigated. It is proved that, asymptotically, the Gallager random coding theorem can be obtained for all rates by such codes. Further, the expurgated coding theorem, as well, is proved to be valid for all rates on regular channels. The latter result implies that the Gilbert-Varshamov bound for block codes over any finite field can be obtained asymptotically for all rates by linear concatenated codes.

Binary linear concatenated codes with Reed-Solomon codes as the outer code and varying nonsystematic inner codes are investigated. It is shown that codes exist in this class which asymptotically meet the Gilbert-Varshamov bound.

Binary unit memory codes, originally introduced by Lee, are investigated. A few examples of constant unit memory codes are given and bounds on the distance profile and the free distances are discussed. For time-varying codes asymptotic lower bounds on the distance profile and the free distance are given. The error probability for the codes, used on a memoryless binary-input, output-symmetric channel, is asymptotically upper bounded. The asymptotic results for the free distance and the error probability, which are in some respects better than for conventional convolutional codes, are interpreted by Forney's inverse concatenation construction.