Insufficiency of linear coding for the network coding problem was first proved by providing an instance which is solvable only by nonlinear network coding (Dougherty et al., 2005).Based on the work of Effros, et al., 2015, this specific network coding instance can be modeled as a groupcast index coding (GIC)instance with 74 messages and 80 users (where a message can be requested by multiple users). This proves the insufficiency of linear coding for the GIC problem. Using the systematic approach proposed by Maleki et al., 2014, the aforementioned GIC instance can be cast into a unicast index coding (UIC) instance with more than 200 users, each wanting a unique message. This confirms the necessity of nonlinear coding for the UIC problem, but only for achieving the entire capacity region. Nevertheless, the question of whether nonlinear coding is required to achieve the symmetric capacity (broadcast rate) of the UIC problem remained open. In this paper, we settle this question and prove the insufficiency of linear coding, by directly building a UIC instance with only 36users for which there exists a nonlinear index code outperforming the optimal linear code in terms of the broadcast rate.
翻译:网络编码问题的线性编码不足首先通过提供仅通过非线性网络编码(Dougherty等人,2005年,2005年)可溶解的例子,证明了网络编码问题的线性编码不足。根据Effros等人的工作,2015年,根据Effros等人,2015年,这一特定的网络编码实例可以模拟成一个有74条消息和80个用户(多用户可以请求发出信息)的分组计算索引编码(GIC),这证明GIC问题的线性编码不足。利用Maleki等人建议的系统化方法,2014年,上述GIC实例可以投放到一个有200多个用户的单线性索引编码(UIC)实例中,每个用户都希望得到一个独特的信息。这证实了非线性编码对于UIC问题的必要性,但对于实现整个能力区域而言,也是唯一需要非线性编码来达到UIC问题的对称能力(宽带率)的问题。在本文中,我们解决了这个问题,并证明线性编码是充分的,通过直接建立UIC系统化指数,只有36个最佳的版本。