We revisit the linear programming bounds for the size vs. distance trade-off for binary codes, focusing on the bounds for the almost-balanced case, when all pairwise distances are between $d$ and $n-d$, where $d$ is the code distance and $n$ is the block length. We give an optimal solution to Delsarte's LP for the almost-balanced case with large distance $d \geq (n - \sqrt{n})/2 + 1$, which shows that the optimal value of the LP coincides with the Grey-Rankin bound for self-complementary codes. We also show that a limitation of the asymptotic LP bound shown by Samorodnitsky, namely that it is at least the average of the first MRRW upper bound and Gilbert-Varshamov bound, continues to hold for the almost-balanced case.
翻译:我们重新审视了二进制码的大小与距离权衡的线性编程界限, 重点是几乎平衡的情况的界限, 当所有对称的距离在美元与美元之间, 美元是代码距离, 美元是块长度。 我们给德尔萨特的LP 以最佳的解决方案, 用于大距离的几乎平衡的案例 $d\ geq (n -\ sqrt{n}/2 + 1 美元, 这表明 LP 的最佳值与 灰兰金 的自补充代码的界限相吻合。 我们还显示, Samorodnitsky 显示的无药LP 约束的局限性, 即至少是第一个MRRW上界和Gilbert- Varshamov 的平均值, 继续维持在几乎平衡的情况下。