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We consider a new inference-centric application for a distributed sensor network. Consider multiple signal sources, i.e., acoustic sources, in the field being monitored. Governed by physics law each sensorpsilas measurement can be modeled as a linear combination of the original multiple signal sources, corrupted by the additive measurement noise. In a non-cooperative communication scenario, each sensor...
This work studies the performance of a data-driven reduced rank scheme for rapid timing acquisition in multiple access communications. Our results show that when only a limited amount of preamble bits are available, instead of the true second-order statistics (SOS), the reduced rank scheme provides reliable timing information. Exploiting the structure of the multiple access interference, the data...
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