20 research outputs found
Dual operative radar for vehicle to vehicle and vehicle to infrastructure communication
The research presented in this Thesis deals with the concepts of joint radar and communication system for automotive application. The novel systems developed include a joint radar and communication system based on the fractional Fourier transform (FrFT) and two interference mitigation frameworks.
In the joint radar and communication system the FrFT is used to embed the data information into a radar waveform in order to obtain a signal sharing Linear Frequency Modulation (LFM) characteristics while allowing data transmission. Furthermore, in the proposed system multi user operations are allowed by assigning a specific order of the FrFT to each user. In this way, a fractional order division multiplexing can be implemented allowing the allocation of more than one user in the same frequency band with the advantage that the range resolution does not depend on the number of the users that share the same frequency band but only from the assigned of the FrFT. Remarkably, the predicted simulated radar performance of the proposed joint radar and communication system when using Binary Frequency Shift Keying (BFSK) encoding is not significantly affected by the transmitted data.
In order to fully describe the proposed waveform design, the signal model when the bits of information are modulated using either BFSK or Binary Phase Shift Keying (BPSK) encoding is derived. This signal model will result also useful in the interference mitigation frameworks.
In multi user scenarios to prevent mutual radar interference caused by users that share the same frequency band at the same time, each user has to transmit waveforms that are uncorrelated with those of other users. However, due to spectrum limitations, the uncorrelated property cannot always be satisfied even by using fractional order division multiplexing, thus interference is unavoidable. In order to mitigate the interference, two frameworks are introduced. In a joint radar communication system, the radar also has access to the communication data. With a near-precision reconstruction of the communication signal, this interference can be subtracted. In these two frameworks the interfering signal can be reconstructed using the derived mathematical model of the proposed FrFT waveform.
In the first framework the subtraction between the received and reconstructed interference signals is carried out in a coherent manner, where the amplitude and phase of the two signals are taken into account. The performance of this framework is highly depend on the correct estimation of the Doppler frequency of the interfering user. A small error on the Doppler frequency can lead to a lack of synchronization between the received and reconstructed signal. Consequently, the subtraction will not be performed in a correct way and further interference components can be introduced.
In order to solve the problem of the lack of the synchronization an alternative framework is developed where the subtraction is carried out in non-coherent manner. In the proposed framework, the subtraction is carried out after that the received radar signal and the reconstructed interference are processed, respectively. The performance is tested on simulated and real signals. The simulated and experimental results show that this framework is capable of mitigating the interference from other users successfully.The research presented in this Thesis deals with the concepts of joint radar and communication system for automotive application. The novel systems developed include a joint radar and communication system based on the fractional Fourier transform (FrFT) and two interference mitigation frameworks.
In the joint radar and communication system the FrFT is used to embed the data information into a radar waveform in order to obtain a signal sharing Linear Frequency Modulation (LFM) characteristics while allowing data transmission. Furthermore, in the proposed system multi user operations are allowed by assigning a specific order of the FrFT to each user. In this way, a fractional order division multiplexing can be implemented allowing the allocation of more than one user in the same frequency band with the advantage that the range resolution does not depend on the number of the users that share the same frequency band but only from the assigned of the FrFT. Remarkably, the predicted simulated radar performance of the proposed joint radar and communication system when using Binary Frequency Shift Keying (BFSK) encoding is not significantly affected by the transmitted data.
In order to fully describe the proposed waveform design, the signal model when the bits of information are modulated using either BFSK or Binary Phase Shift Keying (BPSK) encoding is derived. This signal model will result also useful in the interference mitigation frameworks.
In multi user scenarios to prevent mutual radar interference caused by users that share the same frequency band at the same time, each user has to transmit waveforms that are uncorrelated with those of other users. However, due to spectrum limitations, the uncorrelated property cannot always be satisfied even by using fractional order division multiplexing, thus interference is unavoidable. In order to mitigate the interference, two frameworks are introduced. In a joint radar communication system, the radar also has access to the communication data. With a near-precision reconstruction of the communication signal, this interference can be subtracted. In these two frameworks the interfering signal can be reconstructed using the derived mathematical model of the proposed FrFT waveform.
In the first framework the subtraction between the received and reconstructed interference signals is carried out in a coherent manner, where the amplitude and phase of the two signals are taken into account. The performance of this framework is highly depend on the correct estimation of the Doppler frequency of the interfering user. A small error on the Doppler frequency can lead to a lack of synchronization between the received and reconstructed signal. Consequently, the subtraction will not be performed in a correct way and further interference components can be introduced.
In order to solve the problem of the lack of the synchronization an alternative framework is developed where the subtraction is carried out in non-coherent manner. In the proposed framework, the subtraction is carried out after that the received radar signal and the reconstructed interference are processed, respectively. The performance is tested on simulated and real signals. The simulated and experimental results show that this framework is capable of mitigating the interference from other users successfully
Timing and Carrier Synchronization in Wireless Communication Systems: A Survey and Classification of Research in the Last 5 Years
Timing and carrier synchronization is a fundamental requirement for any wireless communication system to work properly. Timing synchronization is the process by which a receiver node determines the correct instants of time at which to sample the incoming signal. Carrier synchronization is the process by which a receiver adapts the frequency and phase of its local carrier oscillator with those of the received signal. In this paper, we survey the literature over the last 5 years (2010–2014) and present a comprehensive literature review and classification of the recent research progress in achieving timing and carrier synchronization in single-input single-output (SISO), multiple-input multiple-output (MIMO), cooperative relaying, and multiuser/multicell interference networks. Considering both single-carrier and multi-carrier communication systems, we survey and categorize the timing and carrier synchronization techniques proposed for the different communication systems focusing on the system model assumptions for synchronization, the synchronization challenges, and the state-of-the-art synchronization solutions and their limitations. Finally, we envision some future research directions
5G PRS-Based Sensing: A Sensing Reference Signal Approach for Joint Sensing and Communication System
The emerging joint sensing and communication (JSC) technology is expected to
support new applications and services, such as autonomous driving and extended
reality (XR), in the future wireless communication systems. Pilot (or
reference) signals in wireless communications usually have good passive
detection performance, strong anti-noise capability and good auto-correlation
characteristics, hence they bear the potential for applying in radar sensing.
In this paper, we investigate how to apply the positioning reference signal
(PRS) of the 5th generation (5G) mobile communications in radar sensing. This
approach has the unique benefit of compatibility with the most advanced mobile
communication system available so far. Thus, the PRS can be regarded as a
sensing reference signal to simultaneously realize the functions of radar
sensing, communication and positioning in a convenient manner. Firstly, we
propose a PRS based radar sensing scheme and analyze its range and velocity
estimation performance, based on which we propose a method that improves the
accuracy of velocity estimation by using multiple frames. Furthermore, the
Cramer-Rao lower bound (CRLB) of the range and velocity estimation for PRS
based radar sensing and the CRLB of the range estimation for PRS based
positioning are derived. Our analysis and simulation results demonstrate the
feasibility and superiority of PRS over other pilot signals in radar sensing.
Finally, some suggestions for the future 5G-Advanced and 6th generation (6G)
frame structure design containing the sensing reference signal are derived
based on our study
Mobile node-aided localization and tracking in terrestrial and underwater networks
In large-scale wireless sensor networks (WSNs), the position information of individual
sensors is very important for many applications. Generally, there are a small number
of position-aware nodes, referred to as the anchors. Every other node can estimate its
distances to the surrounding anchors, and then employ trilateration or triangulation for
self-localization. Such a system is easy to implement, and thus popular for both terrestrial
and underwater applications, but it suffers from some major drawbacks. First, the density
of the anchors is generally very low due to economical considerations, leading to poor
localization accuracy. Secondly, the energy and bandwidth consumptions of such systems
are quite significant. Last but not the least, the scalability of a network based on fixed
anchors is not good. Therefore, whenever the network expands, more anchors should be
deployed to guarantee the required performance. Apart from these general challenges,
both terrestrial and underwater networks have their own specific ones. For example, realtime
channel parameters are generally required for localization in terrestrial WSNs. For
underwater networks, the clock skew between the target sensor and the anchors must
be considered. That is to say, time synchronization should be performed together with
localization, which makes the problem complicated.
An alternative approach is to employ mobile anchors to replace the fixed ones. For
terrestrial networks, commercial drones and unmanned aerial vehicles (UAVs) are very
good choices, while autonomous underwater vehicles (AUVs) can be used for underwater
applications. Mobile anchors can move along a predefined trajectory and broadcast beacon
signals. By listening to the messages, the other nodes in the network can localize themselves
passively. This architecture has three major advantages: first, energy and bandwidth consumptions can be significantly reduced; secondly, the localization accuracy can be much
improved with the increased number of virtual anchors, which can be boosted at negligible
cost; thirdly, the coverage can be easily extended, which makes the solution and the network
highly scalable.
Motivated by this idea, this thesis investigates the mobile node-aided localization and
tracking in large-scale WSNs. For both terrestrial and underwater WSNs, the system
design, modeling, and performance analyses will be presented for various applications,
including: (1) the drone-assisted localization in terrestrial networks; (2) the ToA-based
underwater localization and time synchronization; (3) the Doppler-based underwater localization;
(4) the underwater target detection and tracking based on the convolutional
neural network and the fractional Fourier transform. In these applications, different challenges
will present, and we will see how these challenges can be addressed by replacing
the fixed anchors with mobile ones. Detailed mathematical models will be presented, and
extensive simulation and experimental results will be provided to verify the theoretical
results. Also, we will investigate the channel estimation for the fifth generation (5G) wireless
communications. A pilot decontamination method will be presented for the massive
multiple-input-multiple-output communications, and the data-aided channel tracking will
be discussed for millimeter wave communications. We will see that the localization problem
is highly coupled with the channel estimation in wireless communications
Signal Reconstruction From Nonuniform Samples Using Prolate Spheroidal Wave Functions: Theory and Application
Nonuniform sampling occurs in many applications due to imperfect sensors, mismatchedclocks or event-triggered phenomena. Indeed, natural images, biomedical responses andsensor network transmission have bursty structure so in order to obtain samples that correspondto the information content of the signal, one needs to collect more samples when thesignal changes fast and fewer samples otherwise which creates nonuniformly distibuted samples.On the other hand, with the advancements in the integrated circuit technology, smallscale and ultra low-power devices are available for several applications ranging from invasivebiomedical implants to environmental monitoring. However the advancements in the devicetechnologies also require data acquisition methods to be changed from the uniform (clockbased, synchronous) to nonuniform (clockless, asynchronous) processing. An important advancementis in the data reconstruction theorems from sub-Nyquist rate samples which wasrecently introduced as compressive sensing and that redenes the uncertainty principle. Inthis dissertation, we considered the problem of signal reconstruction from nonuniform samples.Our method is based on the Prolate Spheroidal Wave Functions (PSWF) which can beused in the reconstruction of time-limited and essentially band-limited signals from missingsamples, in event-driven sampling and in the case of asynchronous sigma delta modulation.We provide an implementable, general reconstruction framework for the issues relatedto reduction in the number of samples and estimation of nonuniform sample times. We alsoprovide a reconstruction method for level crossing sampling with regularization. Another way is to use projection onto convex sets (POCS) method. In this method we combinea time-frequency approach with the POCS iterative method and use PSWF for the reconstructionwhen there are missing samples. Additionally, we realize time decoding modulationfor an asynchronous sigma delta modulator which has potential applications in low-powerbiomedical implants
Spectrally efficient FDM communication signals and transceivers: design, mathematical modelling and system optimization
This thesis addresses theoretical, mathematical modelling and design issues of Spectrally Efficient
FDM (SEFDM) systems. SEFDM systems propose bandwidth savings when compared to
Orthogonal FDM (OFDM) systems by multiplexing multiple non-orthogonal overlapping carriers.
Nevertheless, the deliberate collapse of orthogonality poses significant challenges on the
SEFDM system in terms of performance and complexity, both issues are addressed in this work.
This thesis first investigates the mathematical properties of the SEFDM system and reveals the
links between the system conditioning and its main parameters through closed form formulas
derived for the Intercarrier Interference (ICI) and the system generating matrices. A rigorous
and efficient mathematical framework, to represent non-orthogonal signals using Inverse Discrete
Fourier Transform (IDFT) blocks, is proposed. This is subsequently used to design simple
SEFDM transmitters and to realize a new Matched Filter (MF) based demodulator using the
Discrete Fourier Transforms (DFT), thereby substantially simplifying the transmitter and demodulator
design and localizing complexity at detection stage with no premium at performance.
Operation is confirmed through the derivation and numerical verification of optimal detectors
in the form of Maximum Likelihood (ML) and Sphere Decoder (SD). Moreover, two new linear
detectors that address the ill conditioning of the system are proposed: the first based on
the Truncated Singular Value Decomposition (TSVD) and the second accounts for selected ICI
terms and termed Selective Equalization (SelE). Numerical investigations show that both detectors
substantially outperform existing linear detection techniques. Furthermore, the use of the
Fixed Complexity Sphere Decoder (FSD) is proposed to further improve performance and avoid
the variable complexity of the SD. Ultimately, a newly designed combined FSD-TSVD detector
is proposed and shown to provide near optimal error performance for bandwidth savings of 20%
with reduced and fixed complexity.
The thesis also addresses some practical considerations of the SEFDM systems. In particular,
mathematical and numerical investigations have shown that the SEFDM signal is prone to high
Peak to Average Power Ratio (PAPR) that can lead to significant performance degradations.
Investigations of PAPR control lead to the proposal of a new technique, termed SLiding Window
(SLW), utilizing the SEFDM signal structure which shows superior efficacy in PAPR control
over conventional techniques with lower complexity. The thesis also addresses the performance
of the SEFDM system in multipath fading channels confirming favourable performance and
practicability of implementation. In particular, a new Partial Channel Estimator (PCE) that
provides better estimation accuracy is proposed. Furthermore, several low complexity linear
and iterative joint channel equalizers and symbol detectors are investigated in fading channels
conditions with the FSD-TSVD joint equalization and detection with PCE obtained channel
estimate facilitating near optimum error performance, close to that of OFDM for bandwidth
savings of 25%. Finally, investigations of the precoding of the SEFDM signal demonstrate a
potential for complexity reduction and performance improvement.
Overall, this thesis provides the theoretical basis from which practical designs are derived to
pave the way to the first practical realization of SEFDM systems
Passive Synthetic Aperture Radar Imaging Using Commercial OFDM Communication Networks
Modern communication systems provide myriad opportunities for passive radar applications. OFDM is a popular waveform used widely in wireless communication networks today. Understanding the structure of these networks becomes critical in future passive radar systems design and concept development. This research develops collection and signal processing models to produce passive SAR ground images using OFDM communication networks. The OFDM-based WiMAX network is selected as a relevant example and is evaluated as a viable source for radar ground imaging. The monostatic and bistatic phase history models for OFDM are derived and validated with experimental single dimensional data. An airborne passive collection model is defined and signal processing approaches are proposed providing practical solutions to passive SAR imaging scenarios. Finally, experimental SAR images using general OFDM and WiMAX waveforms are shown to validate the overarching signal processing concept