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arxiv: 1004.5108 · v2 · pith:F43APGNZnew · submitted 2010-04-28 · 💻 cs.IT · cs.NI· math.DS· math.IT

Analyzing Random Network Coding with Differential Equations and Differential Inclusions

classification 💻 cs.IT cs.NImath.DSmath.IT
keywords differentialnetworkframeworkrandomanalyzingcodingdemonstrateequations
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We develop a framework based on differential equations (DE) and differential inclusions (DI) for analyzing Random Network Coding (RNC), as well as a nonlinear variant referred to as Random Coupon (RC), in a wireless network. The DEDI framework serves as a powerful numerical and analytical tool to study RNC. We demonstrate its versatility by proving theoretical results on multicast information flows in a wireless network using RNC or RC. We also demonstrate the accuracy and flexibility of the performance analysis enabled by this framework via illustrative examples of networks with multiple multicast sessions, user cooperation and arbitrary topologies.

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