Reliable Wireless Broadcasting with Near-Zero Feedback

We examine the problem of minimizing feedbacks in reliable wireless broadcasting, by pairing rateless coding with extreme value theory. Our key observation is that, in a broadcast environment, this problem resolves into estimating the maximum number of packets dropped among many receivers rather than for each individual receiver. With rateless codes, this estimation relates to the number of redundant transmissions needed at the source in order for all receivers to correctly decode a message with high probability. We develop and analyze two new data dissemination protocols, called Random Sampling (RS) and Full Sampling with Limited Feedback (FSLF), based on the moment and maximum likelihood estimators in extreme value theory. Both protocols rely on a single-round learning phase, requiring the transmission of a few feedback packets from a small subset of receivers. With fixed overhead, we show that FSLF has the desirable property of becoming more accurate as the receivers's populati...

• Type: Journal
• Year: 2010
• Where: INFOCOM
• Authors: Weiyao Xiao, Sachin Agarwal, David Starobinski, Ari Trachtenberg
• Keywords: Communications, Data Dissemination Protocols, Extreme Value Theory, INFOCOM 2010, Reliable Wireless Broadcasting