Abstract: A LoRa device for communicating sensor signals in a low power wide area network (LPWAN) includes a physical layer using Hamming encoding and Gray indexing with chirp spread signal (CSS) modulation to encode and modulate the sensor signals and a medium access layer (MAC) including a compressive sensing sub-layer which reduces encoded, modulated signals to sparse vectors. A transmission packet is formed by combining the sparse vectors with a selected set of sparse vectors representing past measurements and the incoming velocity of the sensor signals. A receiver decompresses the transmission packet by reconstructing, at a sparse recovery sub-layer of a receiver MAC layer, the encoded, modulated sensor signals. A decoder path removes the CSS modulation and Gray indexing, and Hamming decodes the sensors signals.

Abstract: Methods and apparatuses are provided for estimating a path of an aerial vehicle engaged in attacking network devices in a wireless communication network. A distance function corresponding to the aerial vehicle and a boundary node is determined based on an initial coordinate location of the aerial vehicle and an initial coordinate location of the boundary node. A function of jamming power received at the boundary node from the aerial vehicle is determined based at least on the first distance function and a transmission power of the boundary node. The function of jamming power represents a power associated with a jamming signal received from the aerial vehicle at the boundary node. A trajectory of the aerial vehicle at a plurality of time periods is estimated by the boundary node with an extended Kalman filter. The extended Kalman filter is determined based on the function of jamming power.

Abstract: Devices, methods, and non-transitory computer readable media perform steps for securing communications in a Multi-User (MU), Massive, Multiple Input Multiple Output (MIMO) network. The base station estimates an initial precoding matrix based on a first estimated value of a signal to interference plus noise ratio (SINR) and determines a kth user device outage probability value and an eavesdropper device outage probability value associated with the eavesdropper device. An optimized beamformer weight matrix is determined based on the user device outage probability value and the eavesdropper device outage probability value. The base station determines whether the optimized beamformer weight matrix satisfies at least one outage condition. When the outage condition is satisfied, the base station transmits the optimized beamformer weight matrix to each remote radio head, which transmits downlink signals using a kth beamformer vector of the optimized beamformer weight matrix.

Abstract: A LoRa device for communicating sensor signals in a low power wide area network (LPWAN) includes a physical layer using Hamming encoding and Gray indexing with chirp spread signal (CSS) modulation to encode and modulate the sensor signals and a medium access layer (MAC) including a compressive sensing sub-layer which reduces encoded, modulated signals to sparse vectors. A transmission packet is formed by combining the sparse vectors with a selected set of sparse vectors representing past measurements and the incoming velocity of the sensor signals. A receiver decompresses the transmission packet by reconstructing, at a sparse recovery sub-layer of a receiver MAC layer, the encoded, modulated sensor signals. A decoder path removes the CSS modulation and Gray indexing, and Hamming decodes the sensors signals.

Abstract: A LoRa device for communicating sensor signals in a low power wide area network (LPWAN) includes a physical layer using Hamming encoding and Gray indexing with chirp spread signal (CSS) modulation to encode and modulate the sensor signals and a medium access layer (MAC) including a compressive sensing sub-layer which reduces encoded, modulated signals to sparse vectors. A transmission packet is formed by combining the sparse vectors with a selected set of sparse vectors representing past measurements and the incoming velocity of the sensor signals. A receiver decompresses the transmission packet by reconstructing, at a sparse recovery sub-layer of a receiver MAC layer, the encoded, modulated sensor signals. A decoder path removes the CSS modulation and Gray indexing, and Hamming decodes the sensors signals.

Abstract: A LoRa device for communicating sensor signals in a low power wide area network (LPWAN) includes a physical layer using Hamming encoding and Gray indexing with chirp spread signal (CSS) modulation to encode and modulate the sensor signals and a medium access layer (MAC) including a compressive sensing sub-layer which reduces encoded, modulated signals to sparse vectors. A transmission packet is formed by combining the sparse vectors with a selected set of sparse vectors representing past measurements and the incoming velocity of the sensor signals. A receiver decompresses the transmission packet by reconstructing, at a sparse recovery sub-layer of a receiver MAC layer, the encoded, modulated sensor signals. A decoder path removes the CSS modulation and Gray indexing, and Hamming decodes the sensors signals.

Abstract: A method and system for regenerating free space optical (FSO) signal pulses over free space optical (FSO) links. The FSO signal pulses are received over a first FSO link by a receiver telescope. The FSO signal pulses are split into a first part and a second part. The first part of the FSO signal pulses is converted to an electrical signal. The electrical signal is low pass filtered, amplified, and inverted to generate a negative electric voltage. The amplitude of the second part of the FSO signal pulses is attenuated by an optical absorber based on the negative electric voltage, thus regenerating the FSO signal pulses. The regenerated FSO signal pulses are amplified and bandpass filtered. The amplified and filtered regenerated FSO signal pulses are transmitted on a second FSO link.

Abstract: A LoRa device for communicating sensor signals in a low power wide area network (LPWAN) includes a physical layer using Hamming encoding and Gray indexing with chirp spread signal (CSS) modulation to encode and modulate the sensor signals and a medium access layer (MAC) including a compressive sensing sub-layer which reduces encoded, modulated signals to sparse vectors. A transmission packet is formed by combining the sparse vectors with a selected set of sparse vectors representing past measurements and the incoming velocity of the sensor signals. A receiver decompresses the transmission packet by reconstructing, at a sparse recovery sub-layer of a receiver MAC layer, the encoded, modulated sensor signals. A decoder path removes the CSS modulation and Gray indexing, and Hamming decodes the sensors signals.

Abstract: A LoRa device for communicating sensor signals in a low power wide area network (LPWAN) includes a physical layer using Hamming encoding and Gray indexing with chirp spread signal (CSS) modulation to encode and modulate the sensor signals and a medium access layer (MAC) including a compressive sensing sub-layer which reduces encoded, modulated signals to sparse vectors. A transmission packet is formed by combining the sparse vectors with a selected set of sparse vectors representing past measurements and the incoming velocity of the sensor signals. A receiver decompresses the transmission packet by reconstructing, at a sparse recovery sub-layer of a receiver MAC layer, the encoded, modulated sensor signals. A decoder path removes the CSS modulation and Gray indexing, and Hamming decodes the sensors signals.