Abstract | ||
---|---|---|
The ubiquitous location sensing trend has increased the demand for low-cost GPS receivers; but their energy needs are still too high. For delay-tolerant applications, investigations show that significant energy saving can be obtained by offloading a few milliseconds of raw signal samples and leveraging the greater processing power of the cloud for obtaining a position fix. In an attempt to reduce the energy cost of this data offloading operation, we propose SparseGPS+. Based on the sparse decomposition model, it overcomes many limitations of SparseGPS [1] to yield better signal-to-noise ratio and detection accuracy; which translates to 30% more energy savings compared to the state-of-the-art. |
Year | DOI | Venue |
---|---|---|
2016 | 10.1145/2994551.2996696 | SenSys |
Field | DocType | Citations |
White spaces,Efficient energy use,Computer science,Sparse approximation,Real-time computing,Millisecond,Global Positioning System,Wireless sensor network,Orthogonal frequency-division multiplexing,Cloud computing | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Prasant Misra | 1 | 134 | 18.86 |
Achanna Anil Kumar | 2 | 24 | 5.39 |
M. Girish Chandra | 3 | 112 | 24.49 |
P. Balamurali | 4 | 0 | 0.68 |