In decision feedback scheme, Forney's decision criterion (Forney's rule: FR) is optimal in the sense that the Neyman-Pearson's lemma is satisfied. Another prominent criterion called LR+Th was proposed by Hashimoto. Although LR+Th is suboptimal, its error exponent is shown to be asymptotically equivalent to that of FR by random coding arguments. In this paper, applying the technique of the DS2 bound, we derive an upper bound for the error probability of LR+Th for the ensemble of linear block codes. Then we can observe the new bound from two significant points of view. First, since the DS2 type bound can be expressed by the average weight distribution whose code length is finite, we can compare the error probability of FR with that of LR+Th for the fixed-length code. Second, the new bound elucidates the relation between the random coding exponents of block codes and those of linear block codes.

In channel decoding, a decoder with suboptimal metrics may be used because of the uncertainty of the channel statistics or the limitations of the decoder. In this case, the decoding metric is different from the actual channel metric, and thus it is called mismatched decoding. In this paper, applying the technique of the DS2 bound, we derive an upper bound on the error probability of mismatched decoding over a regular channel for the ensemble of linear block codes, which was defined by Hof, Sason and Shamai. Assuming the ensemble of random linear block codes defined by Gallager, we show that the obtained bound is not looser than the conventional bound. We also give a numerical example for the ensemble of LDPC codes also introduced by Gallager, which shows that our proposed bound is tighter than the conventional bound. Furthermore, we obtain a single letter error exponent for linear block codes.

Recently, Hof et al. extended the type-2 Duman and Salehi (DS2) bound to generalized decoding, which was introduced by Forney, with decision criterion FR. From this bound, they derived two significant bounds. One is the Shulman-Feder bound for generalized decoding (GD) with the binary-input output-symmetric channel. The other is an upper bound for an ensemble of linear block codes, by applying the average complete weight distribution directly to the DS2 bound for GD. For the Shulman-Feder bound for GD, the authors derived a condition under which an upper bound is minimized at an intermediate step and show that this condition yields a new bound which is tighter than Hof et al.'s bound. In this paper, we first extend this result for non-binary linear block codes used over a class of symmetric channels called the regular channel. Next, we derive a new tighter bound for an ensemble of linear block codes, which is based on the average weight distribution.