Description

We propose a new approach, TuneSCode, for tunable sparse network coding as a key enabler towards efficient resource management in wireless networks. This approach seeks to attain the benefits of sparse codes, which reduce end users’ computational effort, while preserving network coding’s ability to recode at intermediate nodes, which is crucial for achieving capacity in wireless networks. Going a step further, TuneSCode proposes techniques to tune the sparseness of the code to strike a balance between throughput and complexity in the presence of devices with heterogeneous capabilities. We will maintain a close collaboration with MIT via the co-supervision of a PhD student at Aalborg University. TuneSCode will deliver theoretical analysis and implementations on commercial mobile platforms. The latter will empower our students to develop real products with socio-economic impact for Denmark.
AcronymTuneSCode
StatusFinished
Effective start/end date01/09/201331/08/2016

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ID: 214678283