Precomputed Ionospheric Propagation for HF Wireless Sensor Transmission Scheduling

Global communications without reliance on an engineered communications network make the ionosphere an attractive medium for wireless sensors in remote deployments. However, ionospheric circuits’ temporary availability is a challenge in scheduling transmissions for a sensor with limited power, communications and computational capacity, particularly where cost and antenna constraints limit operation to a single frequency. We describe a technique for scheduling transmissions based on precomputed propagation models. The models predict the time-varying Signal to Noise Ratio (SNR) at the receiver. We describe methods to determine threshold SNR values, using the Weak Signal Propagation Reporter (WSPR) database to determine if a time slot is suitable for transmission.Two techniques are investigated to quantify the failed receptions: the Inverse Square Law method uses a statistical approach and a sampling measurement technique called Goldilocks. The two approaches yielded threshold SNR values of −21 dB and −19 dB, respectively, for a time slot with a 90% successful reception goal. Applying these thresholds to the modelled SNR, we generate a precomputed hourly transmission schedule. With the schedule determined monthly, a 12-month plan requires 36 bytes of wireless sensor storage. A six-day experiment, using a 1677 km path, found that the schedule resulted in an 83% reception rate when used with a power level of 200 mW.