83 research outputs found
Wideband Spectrum Acquisition for UAV Swarm Using the Sparse Coding Fourier Transform
As the trend towards small, safe, smart, speedy and swarm development grows,
unmanned aerial vehicles (UAVs) are becoming increasingly popular for a wide
range of applications. In this letter, the challenge of wideband spectrum
acquisition for the UAV swarms is studied by proposing a processing method that
features lower power consumption, higher compression rates, and a lower
signal-to-noise ratio. Our system is equipped with multiple UAVs, each with a
different sub-sampling rate. That allows for frequency backetization and
estimation based on sparse Fourier transform theory. Unlike other techniques,
the collisions and iterations caused by non-sparsity environ-ments are
considered. We introduce sparse coding Fourier transform to address these
issues. The key is to code the entire spectrum and decode it through spectrum
correlation in the code. Simulation results show that our proposed method
performs well in acquiring both narrowband and wideband signals simultaneously,
compared to the other methods
Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications
Optical fiber communication industry has gained unprecedented opportunities and achieved rapid progress in recent years. However, with the increase of data transmission volume and the enhancement of transmission demand, the optical communication field still needs to be upgraded to better meet the challenges in the future development. Artificial intelligence technology in optical communication and optical network is still in its infancy, but the existing achievements show great application potential. In the future, with the further development of artificial intelligence technology, AI algorithms combining channel characteristics and physical properties will shine in optical communication. This reprint introduces some recent advances in optical fiber communication and optical network, and provides alternative directions for the development of the next generation optical fiber communication technology
Signal design and processing for noise radar
An efficient and secure use of the electromagnetic spectrum by different telecommunications
and radar systems represents, today, a focal research point, as the coexistence
of different radio-frequency sources at the same time and in the same frequency band
requires the solution of a non-trivial interference problem. Normally, this is addressed
with diversity in frequency, space, time, polarization, or code. In some radar applications,
a secure use of the spectrum calls for the design of a set of transmitted waveforms
highly resilient to interception and exploitation, i.e., with low probability of intercept/
exploitation capability. In this frame, the noise radar technology (NRT) transmits
noise-like waveforms and uses correlation processing of radar echoes for their optimal
reception. After a review of the NRT as developed in the last decades, the aim of this
paper is to show that NRT can represent a valid solution to the aforesaid problems
Compressed sensing based cyclic feature spectrum sensing for cognitive radios
Spectrum sensing is currently one of the most challenging design problems in cognitive radio. A robust spectrum sensing technique is important in allowing implementation of a practical dynamic spectrum access in noisy and interference uncertain environments. In addition, it is desired to minimize the sensing time, while meeting the stringent cognitive radio application requirements. To cope with this challenge, cyclic spectrum sensing techniques have been proposed. However, such techniques require very high sampling rates in the wideband regime and thus are costly in hardware implementation and power consumption. In this thesis the concept of compressed sensing is applied to circumvent this problem by utilizing the sparsity of the two-dimensional cyclic spectrum. Compressive sampling is used to reduce the sampling rate and a recovery method is developed for re- constructing the sparse cyclic spectrum from the compressed samples. The reconstruction solution used, exploits the sparsity structure in the two-dimensional cyclic spectrum do-main which is different from conventional compressed sensing techniques for vector-form sparse signals. The entire wideband cyclic spectrum is reconstructed from sub-Nyquist-rate samples for simultaneous detection of multiple signal sources. After the cyclic spectrum recovery two methods are proposed to make spectral occupancy decisions from the recovered cyclic spectrum: a band-by-band multi-cycle detector which works for all modulation schemes, and a fast and simple thresholding method that works for Binary Phase Shift Keying (BPSK) signals only. In addition a method for recovering the power spectrum of stationary signals is developed as a special case. Simulation results demonstrate that the proposed spectrum sensing algorithms can significantly reduce sampling rate without sacrifcing performance. The robustness of the algorithms to the noise uncertainty of the wireless channel is also shown
Digital Beamforming Applications and Demonstrations of an RF System-on-a-Chip
EM phased array system bandwidth is conventionally constrained by the use of phase shifters for beamsteering, which results in beam squint and pulse dispersion of wideband signals. Wideband antenna performance can be achieved through the use of element-level true time delay (TTD) units, but this is often impractical due to the complexities associated with TTD analog devices. The continued improvement of high-speed analog-to-digital converters (ADC) and digital-to-analog converters (DAC) places digital signal conversion at the element level. This allows TTD beamsteering to be accomplished digitally via a combination of integer-sample delays and fractional-sample delay finite impulse response (FIR) filters, enabling support for wideband communication and radar imaging operating modes.
As phased array systems rely on matched channel characteristics, accurate system calibration is paramount for optimum performance. Narrowband systems which implement beamforming via attenuators and phase shifters often employ lookup tables (LUT) containing a set of correction commands to be superimposed on the desired steering operation. These are commonly dependent on current and desired system characteristics, such as operating frequency, steering direction, power level, and/or temperature conditions. In contrast, wideband systems require higher fidelity compensation techniques capable of correcting imbalanced and dispersive channel effects from element-level electronics.
This dissertation examines deterministic and adaptive beamforming techniques and provides solutions to the aforementioned challenges by contributing the development and demonstration of a wideband digital beamformer with equalization on an RF system-on-a-chip (RFSoC). Performance metrics of the testbed match or exceed current publications of RFSoC based demonstrations. The RFSoC is a unique, state-of-the-art, highly integrated device that incorporates a field programmable gate array (FPGA), high speed ADCs and DACs with a system-on-a-chip (SOC) architecture onto the same silicon fabric. As much of the digital and analog RF circuitry is now integrated into a single package, these devices are revolutionizing radar and communication systems, reshaping phased array system design strategies. This enabling technology facilitates the development of compact all-digital arrays, massively increasing the available degrees of freedom in system control, a paradigm shift in industry and engineering communities.
The beamformer testbed is demonstrated on a sub-Nyquist-sampled 1.6 GHz S-band phased array system implemented using a Xilinx 8-channel 4 GSPS RFSoC. To enable TTD digital beamsteering, each channel is compensated via a conjugate symmetric fractional-sample delay FIR filter bank. By modifying the TTD filter structure to support complex coefficients, channel equalization is integrated with the fractional-sample delays to compensate undesired channel characteristics. To confirm the efficacy of this approach, results are provided for uncalibrated and calibrated system operation. Anechoic chamber measurements are presented as well as the FPGA floorplans showing RFSoC device utilization for both uncalibrated and calibrated configurations
Time and Frequency Transfer in a Coherent Multistatic Radar using a White Rabbit Network
Networks of coherent multistatic radars require accurate and stable time and frequency transfer (TFT) for range and Doppler estimation. TFT techniques based on global navigation satellite systems (GNSS), have been favoured for several reasons, such as enabling node mobility through wireless operation, geospatial referencing, and atomic clock level time and frequency stability. However, such systems are liable to GNSS-denial, where the GNSS carrier is temporarily or permanently removed. A denial-resilient system should consider alternative TFT techniques, such as the White Rabbit (WR) project. WR is an Ethernet based protocol, that is able to synchronise thousands of nodes on a fibre-optic based network with sub-nanosecond accuracy and picoseconds of jitter. This thesis evaluates WR as the TFT network for a coherent multistatic pulse-Doppler radar – NeXtRAD. To test the hypothesis that WR is suitable for TFT in a coherent multistatic radar, the time and frequency performance of a WR network was evaluated under laboratory conditions, comparing the results against a network of multi-channel GPS-disciplined oscillators (GPSDO). A WR-disciplined oscillator (WRDO) is introduced, which has the short-term stability of an ovenised crystal (OCXO), and long-term stability of the WR network. The radar references were measured using a dual mixer time difference technique (DMTD), which allows the phase to be measured with femtosecond level resolution. All references achieved the stringent time and frequency requirements for short-term coherent bistatic operation, however the GPSDOs and WRDOs had the best short-term frequency stability. The GPSDOs had the highest amount of long-term phase drift, with a peak-peak time error of 9.6 ns, whilst the WRDOs were typically stable to within 0.4 ns, but encountered transient phase excursions to 1.5 ns. The TFT networks were then used on the NeXtRAD radar, where a lighthouse, Roman Rock, was used as a static target to evaluate the time and frequency performance of the references on a real system. The results conform well to the laboratory measurements, and therefore, WR can be used for TFT in coherent radar
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COVERT COMMUNICATIONS IN CONTINUOUS-TIME SYSTEMS
This dissertation studies covert wireless communications where a transmitter (Alice) intends to transmit messages to a legitimate receiver (Bob) such that the presence of the message is hidden from an attentive warden (Willie). Here we consider pertinent aspects of covert communications that focus on moving such systems closer to implementation. For example, previous studies use the standard discrete-time communication model when analyzing covert communications, since this is commonly assumed without loss of generality in standard communication theory. However, it is not clear that such a model captures the salient aspects of the continuous-time covert communications problem. A power detector that is optimal for the warden in a discrete-time covert communications scenario may not be optimal on a continuous- time model. Thus, it is of interest to consider this more realistic model for physical channels. After analyzing a power optimization problem using the standard discrete-time model, we move to the key part of system implementation: the instantiation in true continuous-time systems of the discrete-time models studied to this point in the literature. A key goal is to examine Willie’s detection capability on a continuous-time model and study how the limits of covert communications change from the discrete-time case. In particular, we show that detectors for Willie can benefit from the continuous-time setting and outperform detectors based on the discrete-time model; not surprisingly, this has a significant impact on the true covert throughput of the system. Nevertheless, we establish constructions such that efficient covert communications can still be achieved in a continuous-time model, and prove the fundamental limit on the covert communication rate. After considering the continuous-time problem in detail, we then turn to addressing another limitation of previous work - the requirement for an intentional jammer to facilitate efficient covert communication. Instead, we consider how to exploit a pre-existing interference source – a radar - to achieve covert communication. We establish a covert communication scheme in such an environment, and analyze the corresponding covert rate. Finally, we consider the use of a detection technique similar to that in the covert communications problem, in the area of quantized signal detection
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