We investigate the fundamental limits of reliable communication over multi-view channels, in which the channel output is comprised of a large number of independent noisy views of a transmitted symbol. We consider first the setting of multi-view discrete memoryless channels and then extend our results to general multi-view channels (using multi-letter formulas). We argue that the channel capacity and dispersion of such multi-view channels converge exponentially fast in the number of views to the entropy and varentropy of the input distribution, respectively. We identify the exact rate of convergence as the smallest Chernoff information between two conditional distributions of the output, conditioned on unequal inputs. For the special case of the deletion channel, we compute upper bounds on this Chernoff information. Finally, we present a new channel model we term the Poisson approximation channel -- of possible independent interest -- whose capacity closely approximates the capacity of the multi-view binary symmetric channel for any fixed number of views.

翻译：我们研究了在多视图信道上进行可靠通信的基本极限，其中信道输出由大量独立的、带有噪声的传输符号视图构成。我们首先考虑多视图离散无记忆信道的设置，然后将结果推广到一般多视图信道（使用多字母公式）。我们证明，此类多视图信道的信道容量和色散分别随着视图数量的增加以指数速度收敛至输入分布的熵和变熵。我们确定了收敛的确切速率，即基于不等输入条件下两个输出条件分布之间的最小切诺夫信息。对于删除信道这一特例，我们计算了该切诺夫信息的上界。最后，我们提出一种新的信道模型——泊松近似信道（可能具有独立的研究价值），其容量在任意固定视图数量下能紧密逼近多视图二进制对称信道的容量。