Capacity of wireless erasure networks

By Amir F. Dana, Radhika Gowaikar, Ravi Palanki, Babak Hassibi, Michelle Effros. IEEE Transactions on Information Theory, 2006

402 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/7aecc7d3dc185fdecd7a8e92a95f33126a5b068a

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

The Importance of Being Opportunistic: Practical Network Coding for Wireless Environments (2005, background): “A few papers extended some of these results to wired and wireless networks with lossy links [10,20,21].”
Stochastic geometry and random graphs for the analysis and design of wireless networks (2009, background): “…approach is the increasing popularity of erasure channels and erasure networks to model the performance of links that are occasionally in outage [101] Although this has never been done, one can envision combining emerging results on the capacity of wireless erasure networks with outage…”
Noisy Network Coding (2010, background): “Dana, Gowaikar, Palanki, Hassibi, and Effros [6] studied the multiple-source multicast erasue network as a simple model for a wireless March 15, 2010 DRAFT 3 data network with packet loss.”
Full length article: On coding for reliable communication over packet networks (2008, neutral): “rks, in [17] for data dissemination, in [18] for data storage, and in [19] for content distribution over peer-to-peer overlay networks. Other coding schemes for lossy packet networks are described in [7] and [20]; the scheme described in the former requires placing in the packet headers side informa”
Wireless Network Information Flow: A Deterministic Approach (2009, methodology): “The research of S. Diggavi was supported in part by the Swiss National Science Foundation NCCR-MICS center.”
Byzantine modification detection in multicast networks using randomized network coding (2004, background): “Interest in network coding has grown following demonstrations of its various advantages: in network capacity [1], robustness to nonergodic network failures [2] and ergodic packet erasures [3], [4], and distributed network operation [5].”