LZn uses a spectral intersection driven synchronization scheme to achieve robust LoRa frame detection under collisions and ultra-low SNR, improving sensitivity by up to 10 dB and real-world decoding by up to 3.46x versus prior collision-tolerant methods.
Haenggi,Stochastic Geometry for Wireless Networks
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The Rao-Blackwellized Hybrid Estimator combines exact sampling of K dominant interferers with analytical marginalization of the Poisson tail to produce an unbiased coverage estimator whose bias decays as O(K^{1-η/2}) and delivers up to 90x variance reduction.
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LZn : Robust LoRa Frame Synchronization Under Frame Collisions and Ultra-Low SNR Conditions
LZn uses a spectral intersection driven synchronization scheme to achieve robust LoRa frame detection under collisions and ultra-low SNR, improving sensitivity by up to 10 dB and real-world decoding by up to 3.46x versus prior collision-tolerant methods.
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Rao-Blackwellized Coverage Estimation in Poisson Networks: A High-Fidelity Hybrid Framework
The Rao-Blackwellized Hybrid Estimator combines exact sampling of K dominant interferers with analytical marginalization of the Poisson tail to produce an unbiased coverage estimator whose bias decays as O(K^{1-η/2}) and delivers up to 90x variance reduction.