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Title: Bridging the Capacity Gap Between Interactive and One-Way Communication
We study the communication rate of coding schemes for interactive communication that transform any two-party interactive protocol into a protocol that is robust to noise. Recently, Haeupler [11] showed that if an ∊ > 0 fraction of transmissions are corrupted, adversarially or randomly, then it is possible to achieve a communication rate of Furthermore, Haeupler conjectured that this rate is optimal for general input protocols. This stands in contrast to the classical setting of one-way communication in which error-correcting codes are known to achieve an optimal communication rate of 1 In this work, we show that the quadratically smaller rate loss of the one-way setting can also be achieved in interactive coding schemes for a very natural class of input protocols. We introduce the notion of average message length, or the average number of bits a party sends before receiving a reply, as a natural parameter for measuring the level of interactivity in a protocol. Moreover, we show that any protocol with average message length ℓ = Ω(poly(1/∊)) can be simulated by a protocol with optimal communication rate 1 - Θ(Η(∊)) over an oblivious adversarial channel with error fraction e. Furthermore, under the additional assumption of access to public shared randomness, the more » optimal communication rate is achieved ratelessly, i.e., the communication rate adapts automatically to the actual error rate e without having to specify it in advance. This shows that the capacity gap between one-way and interactive communication can be bridged even for very small (constant in e) average message lengths, which are likely to be found in many applications. « less
Award ID(s):
1527110 1618280 1750808
Publication Date:
Journal Name:
ACM-SIAM Symposium on Discrete Algorithms
Page Range or eLocation-ID:
2123 to 2142
Sponsoring Org:
National Science Foundation
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