267 research outputs found

    Joint Location Sensing and Channel Estimation for IRS-Aided mmWave ISAC Systems

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    In this paper, we investigate a self-sensing intelligent reflecting surface (IRS) aided millimeter wave (mmWave) integrated sensing and communication (ISAC) system. Unlike the conventional purely passive IRS, the self-sensing IRS can effectively reduce the path loss of sensing-related links, thus rendering it advantageous in ISAC systems. Aiming to jointly sense the target/scatterer/user positions as well as estimate the sensing and communication (SAC) channels in the considered system, we propose a two-phase transmission scheme, where the coarse and refined sensing/channel estimation (CE) results are respectively obtained in the first phase (using scanning-based IRS reflection coefficients) and second phase (using optimized IRS reflection coefficients). For each phase, an angle-based sensing turbo variational Bayesian inference (AS-TVBI) algorithm, which combines the VBI, messaging passing and expectation-maximization (EM) methods, is developed to solve the considered joint location sensing and CE problem. The proposed algorithm effectively exploits the partial overlapping structured (POS) sparsity and 2-dimensional (2D) block sparsity inherent in the SAC channels to enhance the overall performance. Based on the estimation results from the first phase, we formulate a Cram\'{e}r-Rao bound (CRB) minimization problem for optimizing IRS reflection coefficients, and through proper reformulations, a low-complexity manifold-based optimization algorithm is proposed to solve this problem. Simulation results are provided to verify the superiority of the proposed transmission scheme and associated algorithms

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Waveform Design for 4D-Imaging mmWave PMCW MIMO Radars with Spectrum Compatibility

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    4D-imaging mmWave radars offer high angular resolution in both azimuth and elevation, but achieving this requires a large antenna aperture size and a significant number of transmit and/or receive channels. This presents a challenge for designing transmit waveforms that are both orthogonal and separable on the receive side, as well as have low auto-correlation sidelobes. This paper focuses on designing an orthogonal set of sequences for 4D-imaging radar sensors based on PMCW technology. We propose an iterative optimization framework based on Coordinate Descent, which considers the Regions Of Interest (ROI) and optimizes a phase-modulated constant modulus waveform set based on weighted integrated sidelobe level on the required ROI and spectrum shaping. The optimization also accounts for the radar working adjacent to communication systems and other radar sensors. Simulation results are provided to demonstrate the effectiveness of the proposed method, which achieves low sidelobe levels and is compatible with spectrum constraints

    Coherent FDA Receiver and Joint Range-Space-Time Processing

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    When a target is masked by mainlobe clutter with the same Doppler frequency, it is difficult for conventional airborne radars to determine whether a target is present in a given observation using regular space-time adaptive processing techniques. Different from phased-array and multiple-input multiple-output (MIMO) arrays, frequency diverse arrays (FDAs) employ frequency offsets across the array elements, delivering additional range-controllable degrees of freedom, potentially enabling suppression for this kind of clutter. However, the reception of coherent FDA systems employing small frequency offsets and achieving high transmit gain can be further improved. To this end, this work proposes an coherent airborne FDA radar receiver that explores the orthogonality of echo signals in the Doppler domain, allowing a joint space-time processing module to be deployed to separate the aliased returns. The resulting range-space-time adaptive processing allows for a preferable detection performance for coherent airborne FDA radars as compared to current alternative techniques.Comment: 11 pages, 9 figure

    In-band-full-duplex integrated access and backhaul enabled next generation wireless networks

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    In sixth generation (6G) wireless networks, the severe traffic congestion in the microwave frequencies motivates the exploration of the large available bandwidth in the millimetre-wave (mmWave) frequencies to achieve higher network capacity and data rate. Since large-scale antenna arrays and dense base station deployment are required, the hybrid beamforming architecture and the recently proposed integrated access and backhaul (IAB) networks become potential candidates for providing cost and hardware-friendly techniques for 6G wireless networks. In addition, in-band-full-duplex (IBFD) has been recently paid much more research attention since it can make the transmission and reception occur in the same time and frequency band, which nearly doubles the communication spectral efficiency (SE) compared with state-of-the-art half-duplex (HD) systems. Since 6G will explore sensing as its new capability, future wireless networks can go far beyond communications. Motivated by this, the development of integrated sensing and communications (ISAC) systems, where radar and communication systems share the same spectrum resources and hardware, has become one of the major goals in 6G. This PhD thesis focuses on the design and analysis of IBFD-IAB wireless networks in the frequency range 2 (FR2) band (≥ 24.250 GHz) at mmWave frequencies for the potential use in 6G. Firstly, we develop a novel design for the single-cell FR2-IBFD-IAB networks with subarray-based hybrid beamforming, which can enhance the SE and coverage while reducing the latency. The radio frequency (RF) beamformers are obtained via RF codebooks given by a modified matrix-wise Linde-Buzo-Gray (LBG) algorithm. The self-interference (SI) is cancelled in three stages, where the first stage of antenna isolation is assumed to be successfully deployed. The second stage consists of the optical domain-based RF cancellation, where cancellers are connected with the RF chain pairs. The third stage is comprised of the digital cancellation via successive interference cancellation followed by minimum mean-squared error (MSE) baseband receiver. Multiuser interference in the access link is cancelled by zero-forcing at the IAB-node transmitter. The proposed codebook algorithm avoids undesirable low-rank behaviour, while the proposed staged-SI cancellation (SIC) shows satisfactory cancellation performance in the wideband IBFD scenario. However, the system performance can be affected by the hardware impairments (HWI) and RF effective channel estimation errors. Secondly, we study an FR2-IBFD-ISAC-IAB network for vehicle-to-everything communications, where the IAB-node acts as a roadside unit performing sensing and communication simultaneously (i.e., at the same time and frequency band). The SI due to the IBFD operation will be cancelled in the propagation, analogue, and digital domains; only the residual SI (RSI) is reserved for performance analysis. Considering the subarray-based hybrid beamforming structure, including HWI and RF effective SI channel estimation error, the unscented Kalman filter is used for tracking multiple vehicles in the studied scenario. The proposed system shows an enhanced SE compared with the HD system, and the tracking MSEs averaged across all vehicles of each state parameter are close to their posterior Cramér-Rao lower bounds. Thirdly, we analyse the performance of the multi-cell wideband single-hop backhaul FR2-IBFD-IAB networks by using stochastic geometry analysis. We model the wired-connected next generation NodeBs (gNBs) as the Matérn hard-core point process (MHCPP) to meet the real-world deployment requirement and reduce the cost caused by wired connection in the network. We first derive association probabilities that reflect how likely the typical user-equipment is served by a gNB or an IAB-node based on the maximum long-term averaged biased-received-desired-signal power criteria. Further, by leveraging the composite Gamma-Lognormal distribution, we derive results for the signal to interference plus noise ratio coverage, capacity with outage, and ergodic capacity of the network. In order to assess the impact of noise, we consider the sidelobe gain on inter-cell interference links and the analogue to digital converter quantization noise. Compared with the HD transmission, the designated system shows an enhanced capacity when the SIC operates successfully. We also study how the power bias and density ratio of the IAB-node to gNB, and the hard-core distance can affect system performance. Overall, this thesis aims to contribute to the research efforts of shaping the 6G wireless networks by designing and analysing the FR2-IBFD-IAB inspired networks in the FR2 band at mmWave frequencies that will be potentially used in 6G for both communication only and ISAC scenarios

    Intelligent Sensing and Learning for Advanced MIMO Communication Systems

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    Multi-Spectrally Constrained Low-PAPR Waveform Optimization for MIMO Radar Space-Time Adaptive Processing

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    This paper focuses on the joint design of transmit waveforms and receive filters for airborne multiple-input-multiple-output (MIMO) radar systems in spectrally crowded environments. The purpose is to maximize the output signal-to-interference-plus-noise-ratio (SINR) in the presence of signal-dependent clutter. To improve the practicability of the radar waveforms, both a multi-spectral constraint and a peak-to-average-power ratio (PAPR) constraint are imposed. A cyclic method is derived to iteratively optimize the transmit waveforms and receive filters. In particular, to tackle the encountered non-convex constrained fractional programming in designing the waveforms (for fixed filters), we resort to the Dinkelbach's transform, minorization-maximization (MM), and leverage the alternating direction method of multipliers (ADMM). We highlight that the proposed algorithm can iterate from an infeasible initial point and the waveforms at convergence not only satisfy the stringent constraints, but also attain superior performance

    QoS-Aware Precoder Optimization for Radar Sensing and Multiuser Communications Under Per-Antenna Power Constraints

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    In this work, we concentrate on designing the precoder for the multiple-input multiple-output (MIMO) dual functional radar-communication (DFRC) system, where the dual-functional waveform is designed for performing multiuser downlink transmission and radar sensing simultaneously. Specifically, considering the signal-independent interference and signal-dependent clutter, we investigate the optimization of transmit precoding for maximizing the sensing signal-to-interference-plus-noise ratio (SINR) at the radar receiver under the constraint of the minimum SINR received at multiple communication users and per-antenna power budget. The formulated problem is challenging to solve due to the nonconovex objective function and nonconvex per-antenna power constraint. In particular, for the signal-independent interference case, we propose a distance-majorization induced algorithm to approximate the nonconvex problem as a sequence of convex problems whose optima can be obtained in closed form. Subsequently, our complexity analysis shows that our proposed algorithm has a much lower computational complexity than the widely-adopted semidefinite relaxation (SDR)-based algorithm. For the signal-dependent clutter case, we employ the fractional programming to transform the nonconvex problem into a sequence of subproblems, and then we propose a distance-majorization based algorithm to obtain the solution of each subproblem in closed form. Finally, simulation results confirm the performance superiority of our proposed algorithms when compared with the SDR-based approach. In conclusion, the novelty of this work is to propose an efficient algorithm for handling the typical problem in designing the DFRC precoder, which achieves better performance with a much lower complexity than the state-of-the-art algorithm

    Full-Duplex Communication for ISAC: Joint Beamforming and Power Optimization

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    Beamforming design has been widely investigated for integrated sensing and communication (ISAC) systems with full-duplex (FD) sensing and half-duplex (HD) communication. To achieve higher spectral efficiency, in this paper, we extend existing ISAC beamforming design by considering the FD capability for both radar and communication. Specifically, we consider an ISAC system, where the BS performs target detection and communicates with multiple downlink users and uplink users reusing the same time and frequency resources. We jointly optimize the downlink dual-functional transmit signal and the uplink receive beamformers at the BS and the transmit power at the uplink users. The problems are formulated under two criteria: power consumption minimization and sum rate maximization. The downlink and uplink transmissions are tightly coupled due to both the desired target echo and the undesired interference received at the BS, making the problems challenging. To handle these issues in both cases, we first determine the optimal receive beamformers, which are derived in closed forms with respect to the BS transmit beamforming and the user transmit power, for radar target detection and uplink communications, respectively. Subsequently, we invoke these results to obtain equivalent optimization problems and propose efficient iterative algorithms to solve them by using the techniques of rank relaxation and successive convex approximation (SCA), where the adopted relaxation is proven to be tight. In addition, we consider a special case under the power minimization criterion and propose an alternative low complexity design. Numerical results demonstrate that the optimized FD communication-based ISAC brings tremendous improvements in terms of both power efficiency and spectral efficiency compared to the conventional ISAC with HD communication.Comment: Accepted to an IEEE Journa

    1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

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    A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance
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