Attack-aware Synchronization-free Data Timestamping in LoRaWAN

Low-power wide-area network technologies such as long-range wide-area network (LoRaWAN) are promising for collecting low-rate monitoring data from geographically distributed sensors, in which timestamping the sensor data is a critical system function. This article considers a synchronization-free approach to timestamping LoRaWAN uplink data based on signal arrival time at the gateway, which well matches LoRaWAN’s one-hop star topology and releases bandwidth from transmitting timestamps and synchronizing end devices’ clocks at all times. However, we show that this approach is susceptible to a frame delay attack consisting of malicious frame collision and delayed replay. Real experiments show that the attack can affect the end devices in large areas up to about 50,000, m 2 . In a broader sense, the attack threatens any system functions requiring timely deliveries of LoRaWAN frames. To address this threat, we propose a LoRaTS gateway design that integrates a commodity LoRaWAN gateway and a low-power software-defined radio receiver to track the inherent frequency biases of the end devices. Based on an analytic model of LoRa’s chirp spread spectrum modulation, we develop signal processing algorithms to estimate the frequency biases with high accuracy beyond that achieved by LoRa’s default demodulation. The accurate frequency bias tracking capability enables the detection of the attack that introduces additional frequency biases. We also investigate and implement a more crafty attack that uses advanced radio apparatuses to eliminate the frequency biases. To address this crafty attack, we propose a pseudorandom interval hopping scheme to enhance our frequency bias tracking approach. Extensive experiments show the effectiveness of our approach in deployments with real affecting factors such as temperature variations.

Implementation of a Noise-Shaped Signaling System through Software-Defined Radio

Along with the development of electromagnetic weapons, Electronic Warfare (EW) has been rising as the future form of war. Especially in the area of wireless communications, high security defense systems such as Low Probability of Detection (LPD), Low Probability of Interception (LPI), and Low Probability of Exploitation (LPE) communication algorithms are being studied to prevent military force loss. One LPD, LPI, and LPE communication algorithm, physical-layer security, has been discussed and studied. We propose a noise signaling system, a type of physical-layer security, which modifies conventionally modulated I/Q data into a noise-like shape. To suggest the possibility of realistic implementation, we use Software-Defined Radio (SDR). Since there are certain hardware limitations, we present the limitations, requirements, and preferences of practical implementation of the noise signaling system. The proposed system uses ring-shaped signaling, and we present a ring-shaped signaling system algorithm, SDR implementation methodology, and performance evaluations of the system using the metrics of Bit Error Rate (BER) and Probability of Modulation Identification (PMI), which we obtain by using a Convolutional Neural Network (CNN) algorithm. We conclude that the ring-shaped signaling system can perform high LPI/LPE communication functioning because an eavesdropper cannot obtain the correct modulation scheme information. However, the performance can vary with the configurations of the I/Q data-modifying factors.

Toward Polymorphic Internet of Things Receivers Through Real-Time Waveform-Level Deep Learning

Wireless systems such as the Internet of Things (IoT) are changing the way we interact with the cyber and the physical world. As IoT systems become more and more pervasive, it is imperative to design wireless protocols that can effectively and efficiently support IoT devices and operations. On the other hand, today's IoT wireless systems are based on inflexible designs, which makes them inefficient and prone to a variety of wireless attacks. In this paper, we introduce the new notion of a deep learning-based polymorphic IoT receiver, able to reconfigure its waveform demodulation strategy itself in real time, based on the inferred waveform parameters. Our key innovation is the introduction of a novel embedded deep learning architecture that enables the solution of waveform inference problems, which is then integrated into a generalized hardware/software architecture with radio components and signal processing. Our polymorphic wireless receiver is prototyped on a custom-made software-defined radio platform. We show through extensive over-the-air experiments that the system achieves throughput within 87% of a perfect-knowledge Oracle system, thus demonstrating for the first time that polymorphic receivers are feasible.

SDR-Implemented Passive Bistatic SAR System Using Sentinel-1 Signal and Its Experiment Results

A fixed-receiver mobile-transmitter passive bistatic synthetic aperture radar (MF-PB-SAR) system, which uses the Sentinel-1 SAR satellite as its non-cooperative emitting source, has been developed by using embedded software-defined radio (SDR) hardware for high-resolution imaging of the targets in a local area in this study. Firstly, Sentinel-1 and the designed system are introduced. Then, signal model, signal pre-processing methods, and effective target imaging methods are presented. At last, various experiment results of target imaging obtained at different locations are shown to validate the developed system and the proposed methods. It was found that targets in a range of several kilometers can be well imaged.

Modeling and Fabrication of a Reconfigurable RF Output Stage for Nanosatellite Communication Subsystems

Current small satellite platforms such as CubeSats require robust and versatile communication subsystems that allow the reconfiguration of the critical operating parameters such as carrier frequency, transmission power, bandwidth, or filter roll-off factor. A reconfigurable Analog Back-End for the space segment of a satellite communication subsystem is presented in this work. This prototype is implemented on a 9.5 cm2 6-layer PCB, and it operates from 0.070 to 6 GHz and complies with CubeSat and IPC-2221 standards. The processing, control, and synchronizing stages are carried out on a Software-Defined Radio approach executed on a baseband processor. Results showed that the signal power at the output of the proposed Analog Back-End is suitable for feeding the following antenna subsystem. Furthermore, the emitted radiation levels by the transmission lines do not generate electromagnetic interference.

5G F-OFDM Waveform Based Software-Defined Radio Technology

Filtered-orthogonal frequency division multiplexing (F-OFDM) is a quasi-orthogonal waveform candidate for the applications of the fifth generation (5G) communication system. In this study, an F-OFDM waveform with unequal sub-band sizes is proposed to improve the spectrum efficiency (SE) of the 5G system. The proposed waveform is modeled with the Blackman window-sinc filter and is developed based on the software-defined radio (SDR) technology for practical implementation. The result shows that the F-OFDM performance of the simulation and hardware implementation is approximately the same. The SE using the proposed F-OFDM waveform is 6% and 5.8% higher than the SE using the conventional OFDM waveform under the simulation in the LabVIEW NXG simulator and under the practical use in the universal software radio peripheral (USRP) platform, respectively.

ADS-B Signal Verification Using a Coherent Receiver

Automatic Dependent Surveillance-Broadcast (ADS-B) enables aircraft to periodically broadcast their flight states such as position and velocity. Compared to classical radar surveillance, it increases update rate and accuracy. Currently, Mode S Extended Squitter is the most common implementation for ADS-B. Due to the simplicity of Mode S design, ADS-B signals are prone to injections. This study proposes a cost-effective solution that verifies the integrity of ADS-B signals using coherent receivers. We design the verification approach by combining the signal’s direction of arrival, estimated from the multi-channel data, with the target bearing calculated from ADS-B messages. By using another high-performance software-defined radio transceiver, we also conduct real signal injection experiments to validate our approaches.