Showing papers on "Bandwidth (signal processing) published in 2019"
TL;DR: Increased amounts of bandwidth are required to guarantee both high-quality/high-rate wireless services (4G and 5G) and reliable sensing capabilities, such as for automotive radar, air traffic control, earth geophysical monitoring, and security applications.
Abstract: Increased amounts of bandwidth are required to guarantee both high-quality/high-rate wireless services (4G and 5G) and reliable sensing capabilities, such as for automotive radar, air traffic control, earth geophysical monitoring, and security applications. Therefore, coexistence between radar and communication systems using overlapping bandwidths has come to be a primary investigation field in recent years. Various signal processing techniques, such as interference mitigation, precoding or spatial separation, and waveform design, allow both radar and communications to share the spectrum.
344 citations
TL;DR: A novel distributed dynamic spectrum access algorithm based on deep multi-user reinforcement leaning is developed for accessing the spectrum that maximizes a certain network utility in a distributed manner without online coordination or message exchanges between users.
Abstract: We consider the problem of dynamic spectrum access for network utility maximization in multichannel wireless networks. The shared bandwidth is divided into $K$ orthogonal channels. In the beginning of each time slot, each user selects a channel and transmits a packet with a certain transmission probability. After each time slot, each user that has transmitted a packet receives a local observation indicating whether its packet was successfully delivered or not (i.e., ACK signal). The objective is a multi-user strategy for accessing the spectrum that maximizes a certain network utility in a distributed manner without online coordination or message exchanges between users. Obtaining an optimal solution for the spectrum access problem is computationally expensive, in general, due to the large-state space and partial observability of the states. To tackle this problem, we develop a novel distributed dynamic spectrum access algorithm based on deep multi-user reinforcement leaning. Specifically, at each time slot, each user maps its current state to the spectrum access actions based on a trained deep-Q network used to maximize the objective function. Game theoretic analysis of the system dynamics is developed for establishing design principles for the implementation of the algorithm. The experimental results demonstrate the strong performance of the algorithm.
326 citations
TL;DR: A signal processing perspective of mm-wave JRC systems with an emphasis on waveform design is provided, to exploit opportunities to exploit recent advances in cognition, compressed sensing, and machine learning to reduce required resources and dynamically allocate them with low overheads.
Abstract: Synergistic design of communications and radar systems with common spectral and hardware resources is heralding a new era of efficiently utilizing a limited radio-frequency (RF) spectrum. Such a joint radar communications (JRC) model has advantages of low cost, compact size, less power consumption, spectrum sharing, improved performance, and safety due to enhanced information sharing. Today, millimeter-wave (mmwave) communications have emerged as the preferred technology for short distance wireless links because they provide transmission bandwidth that is several gigahertz wide. This band is also promising for short-range radar applications, which benefit from the high-range resolution arising from large transmit signal bandwidths. Signal processing techniques are critical to the implementation of mm-wave JRC systems. Major challenges are joint waveform design and performance criteria that would optimally trade off between communications and radar functionalities. Novel multiple-input, multiple-output (MIMO) signal processing techniques are required because mm-wave JRC systems employ large antenna arrays. There are opportunities to exploit recent advances in cognition, compressed sensing, and machine learning to reduce required resources and dynamically allocate them with low overheads. This article provides a signal processing perspective of mm-wave JRC systems with an emphasis on waveform design.
325 citations
TL;DR: Splicer, a software-based system that derives high-resolution power delay profiles by splicing the CSI measurements from multiple WiFi frequency bands is presented and a set of key techniques to separate the mixed hardware errors from the collected CSI measurements are proposed.
Abstract: Power delay profiles characterize multipath channel features, which are widely used in motion- or localization-based applications. The performance of power delay profile obtained using commodity Wi-Fi devices is limited by two dominating factors. The resolution of the derived power delay profile is determined by the channel bandwidth, which is however limited on commodity WiFi. The collected CSI reflects the signal distortions due to both the channel attenuation and the hardware imperfection. A direct derivation of power delay profiles using raw CSI measures, as has been done in the literature, results in significant inaccuracy. In this paper, we present Splicer, a software-based system that derives high-resolution power delay profiles by splicing the CSI measurements from multiple WiFi frequency bands. We propose a set of key techniques to separate the mixed hardware errors from the collected CSI measurements. Splicer adapts its computations within stringent channel coherence time and thus can perform well in the presence of mobility. Our experiments with commodity WiFi NICs show that Splicer substantially improves the accuracy in profiling multipath characteristics, reducing the errors of multipath distance estimation to be less than $2\;\mathrm{m}$2m. Splicer can immediately benefit upper-layer applications. Our case study with recent single-AP localization achieves a median localization error of $0.95\;\mathrm{m}$0.95m.
274 citations
TL;DR: The principles of DFRC systems are reviewed and the progress made to date in devising different forms of signal embedding are described, including downlink and uplink signaling schemes and their respective benefits and limitations.
Abstract: To get the most use out of scarce spectrum, technologies have emerged that permit single systems to accommodate both radar and communications functions. Dual-function radar communication (DFRC) systems, where the two systems use the same platform and share the same hardware and spectral resources, form a specific class of radio-frequency (RF) technology. These systems support applications where communication data, whether as target and waveform parameter information or as information independent of the radar operation, are efficiently transmitted using the same radar aperture and frequency bandwidth. This is achieved by embedding communication signals into radar pulses. In this article, we review the principles of DFRC systems and describe the progress made to date in devising different forms of signal embedding. Various approaches to DFRC system design, including downlink and uplink signaling schemes, are discussed along with their respective benefits and limitations. We present tangible applications of DFRC systems and delineate their design requirements and challenges. Future trends and open research problems are also highlighted.
270 citations
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TL;DR: Results show clear advantages for the proposed analog over-the-air DSGD scheme, which suggests that learning and communication algorithms should be designed jointly to achieve the best end-to-end performance in machine learning applications at the wireless edge.
Abstract: We study federated machine learning at the wireless network edge, where limited power wireless devices, each with its own dataset, build a joint model with the help of a remote parameter server (PS). We consider a bandwidth-limited fading multiple access channel (MAC) from the wireless devices to the PS, and propose various techniques to implement distributed stochastic gradient descent (DSGD). We first propose a digital DSGD (D-DSGD) scheme, in which one device is selected opportunistically for transmission at each iteration based on the channel conditions; the scheduled device quantizes its gradient estimate to a finite number of bits imposed by the channel condition, and transmits these bits to the PS in a reliable manner. Next, motivated by the additive nature of the wireless MAC, we propose a novel analog communication scheme, referred to as the compressed analog DSGD (CA-DSGD), where the devices first sparsify their gradient estimates while accumulating error, and project the resultant sparse vector into a low-dimensional vector for bandwidth reduction. Numerical results show that D-DSGD outperforms other digital approaches in the literature; however, in general the proposed CA-DSGD algorithm converges faster than the D-DSGD scheme and other schemes in the literature, and reaches a higher level of accuracy. We have observed that the gap between the analog and digital schemes increases when the datasets of devices are not independent and identically distributed (i.i.d.). Furthermore, the performance of the CA-DSGD scheme is shown to be robust against imperfect channel state information (CSI) at the devices. Overall these results show clear advantages for the proposed analog over-the-air DSGD scheme, which suggests that learning and communication algorithms should be designed jointly to achieve the best end-to-end performance in machine learning applications at the wireless edge.
221 citations
TL;DR: This paper proposes a new way to encode and decode the event-triggered control signals to further decrease the communication rate and proves that the boundedness of all the signals is ensured and the output signal can be regulated to a compact set around zero, which is adjustable.
Abstract: In this paper, we investigate the problem of output feedback control for a class of uncertain nonlinear systems with event-triggered input. The considered system contains not only unknown system parameters, but also general nonlinear functions that are not required to be globally Lipschitz, in contrast to most of the existing results in the area. Besides providing two different event-triggered strategies without input-to-state stable assumption with respect to the measurement errors, we propose a new way to encode and decode the event-triggered control signals to further decrease the communication rate. With our newly proposed encoding–decoding mechanism, each time when the triggering event is violated, only 1-bit signal, either 1 or 0, is rendered to transmit through the communication channel between the controller and actuator. Clearly, this signal transmission mechanism is more effective and consumes less channel bandwidth. Through Lyapunov analyses, it is proved that the boundedness of all the signals is ensured and the output signal can be regulated to a compact set around zero, which is adjustable.
220 citations
26 Jun 2019
TL;DR: In this article, the spatial embeddings of pixels belonging to the same instance are jointly learned to maximize the intersection-over-union of the resulting instance mask, which achieves state-of-the-art performance on the Cityscapes benchmark.
Abstract: Current state-of-the-art instance segmentation methods are not suited for real-time applications like autonomous driving, which require fast execution times at high accuracy. Although the currently dominant proposal-based methods have high accuracy, they are slow and generate masks at a fixed and low resolution. Proposal-free methods, by contrast, can generate masks at high resolution and are often faster, but fail to reach the same accuracy as the proposal-based methods. In this work we propose a new clustering loss function for proposal-free instance segmentation. The loss function pulls the spatial embeddings of pixels belonging to the same instance together and jointly learns an instance-specific clustering bandwidth, maximizing the intersection-over-union of the resulting instance mask. When combined with a fast architecture, the network can perform instance segmentation in real-time while maintaining a high accuracy. We evaluate our method on the challenging Cityscapes benchmark and achieve top results (5% improvement over Mask R-CNN) at more than 10 fps on 2MP images.
198 citations
20 Mar 2019
TL;DR: In this article, an ultra-low-loss integrated visible photonics platform based on thin-film lithium niobate on an insulator is proposed for frequency metrology and quantum information processing.
Abstract: Integrated photonics is a powerful platform that can improve the performance and stability of optical systems while providing low-cost, small-footprint, and scalable alternatives to implementations based on free-space optics. While great progress has been made on the development of low-loss integrated photonics platforms at telecom wavelengths, the visible wavelength range has received less attention. Yet, many applications utilize visible or near-visible light, including those in optical imaging, optogenetics, and quantum science and technology. Here we demonstrate an ultra-low-loss integrated visible photonics platform based on thin-film lithium niobate on an insulator. Our waveguides feature ultra-low propagation loss of 6 dB/m, while our microring resonators have an intrinsic quality factor of 11 million, both measured at 637 nm wavelength. Additionally, we demonstrate an on-chip visible intensity modulator with an electro-optic bandwidth of 10 GHz, limited by the detector used. The ultra-low-loss devices demonstrated in this work, together with the strong second- and third-order nonlinearities in lithium niobate, open up new opportunities for creating novel passive and active devices for frequency metrology and quantum information processing in the visible spectrum range.
175 citations
TL;DR: This work reports on the first demonstration of a THz link that is seamlessly integrated into a fiber-optic network using direct terahertz-to-optical (T/O) conversion at the wireless receiver.
Abstract: Future wireless communication networks will need to handle data rates of tens or even hundreds of Gbit s−1 per link, requiring carrier frequencies in the unallocated THz spectrum1,2. In this context, seamless integration of THz links into existing fibre-optic infrastructures3 is of great importance to complement the inherent portability and flexibility advantages of wireless networks and the reliable and virtually unlimited capacity of optical transmission systems. On the technological level, this requires novel device and signal processing concepts for direct conversion of data streams between the THz and optical domains. Here, we demonstrate a THz link that is seamlessly integrated into a fibre-optic network using direct THz-to-optical (T/O) conversion at the wireless receiver. We exploit an ultra-broadband silicon-plasmonic modulator having a 3 dB bandwidth in excess of 0.36 THz for T/O conversion of a 50 Gbit s−1 data stream that is transmitted on a 0.2885 THz carrier over a 16-m-long wireless link. Optical-to-THz (O/T) conversion at the wireless transmitter relies on photomixing in a uni-travelling-carrier photodiode. A high-speed wireless THz communication link is seamlessly integrated into a fibre-optic network. The demonstration relies on an ultra-broadband modulator exploiting two-dimensionally localized gap plasmons for direct conversion of the THz signals to the optical domain.
160 citations
TL;DR: The experimental results match well with theory, showing that the transversal filter is a competitive solution to implement advanced adaptive RF filters with broad operational bandwidth, high frequency selectivity, high reconfigurability, and potentially reduced cost and footprint.
Abstract: We demonstrate a photonic radio frequency (RF) transversal filter based on an integrated optical micro-comb source featuring a record low free spectral range of 49 GHz, yielding 80 micro-comb lines across the C -band. This record high number of taps, or wavelengths for the transversal filter results in significantly increased performance including a Q RF factor more than four times higher than previous results. Furthermore, by employing both positive and negative taps, an improved out-of-band rejection of up to 48.9 dB is demonstrated using a Gaussian apodization, together with a tunable center frequency covering the RF spectra range, with a widely tunable 3-dB bandwidth and versatile dynamically adjustable filter shapes. Our experimental results match well with theory, showing that our transversal filter is a competitive solution to implement advanced adaptive RF filters with broad operational bandwidth, high frequency selectivity, high reconfigurability, and potentially reduced cost and footprint. This approach is promising for applications in modern radar and communications systems.
08 Feb 2019
TL;DR: In this article, an active nonlinear micro-ring resonator (MRR) was used as a high-quality micro-comb source and a passive high-Q MRR was used to slice the RF spectra modulated on the shaped comb.
Abstract: We demonstrate high-resolution photonic RF filters using an RF bandwidth scaling approach based on integrated Kerr optical micro-combs. By employing both an active nonlinear micro-ring resonator (MRR) as a high-quality micro-comb source and a passive high-Q MRR to slice the RF spectra modulated on the shaped comb, a large RF instantaneous bandwidth of 4.64 GHz and a high resolution of 117 MHz are achieved, together with a broad RF operation band covering 3.28–19.4 GHz (L to Ku bands) using thermal tuning. We achieve programmable RF transfer functions including binary-coded notch filters and RF equalizing filters with reconfigurable slopes. Our approach is an attractive solution for RF spectral shaping with high performance and flexibility.
TL;DR: Extensive simulation results validate that the training speed of FFD net is faster than state-of-the-art channel estimators without sacrificing normalized mean square error performance, which makes FFDNet as an practical channel estimator for cell-free mmWave massive MIMO systems.
Abstract: The combination of cell-free massive multiple-input multiple-output (MIMO) systems along with millimeter-wave (mmWave) bands is indeed one of most promising technological enablers of the envisioned wireless Gbit/s experience. However, both massive antennas at access points and large bandwidth at mmWave induce high computational complexity to exploit an accurate estimation of channel state information. Considering the sparse mmWave channel matrix as a natural image, we propose a practical and accurate channel estimation framework based on the fast and flexible denoising convolutional neural network (FFDNet). In contrast to previous deep learning based channel estimation methods, FFDNet is suitable a wide range of signal-to-noise ratio levels with a flexible noise level map as the input. More specifically, we provide a comprehensive investigation to optimize the FFDNet based channel estimator. Extensive simulation results validate that the training speed of FFDNet is faster than state-of-the-art channel estimators without sacrificing normalized mean square error performance, which makes FFDNet as an practical channel estimator for cell-free mmWave massive MIMO systems.
TL;DR: In this paper, the potentials of harnessing the space as an additional degree of freedom for communication applications including free space optics, optical fiber installation, underwater wireless optical links, on-chip interconnects, data center indoor connections, radio frequency, and acoustic communications are reviewed.
Abstract: Time, polarization, and wavelength multiplexing schemes have been used to satisfy the growing need of transmission capacity. Using space as a new dimension for communication systems has been recently suggested as a versatile technique to address future bandwidth issues. We review the potentials of harnessing the space as an additional degree of freedom for communication applications including free space optics, optical fiber installation, underwater wireless optical links, on-chip interconnects, data center indoor connections, radio frequency, and acoustic communications. We focus on the orbital angular momentum (OAM) modes and equally identify the challenges related to each of the applications of spatial modes and the particular OAM modes in communication. We further discuss the perspectives of this emerging technology. Finally, we provide the open research directions and discuss the practical deployment of OAM communication links for different applications.
TL;DR: Finely tailored pulse-shaping operations, including splitting, compression, chirping, and higher-order distortion, are achieved using a Fourier-transform setup embedding metasurfaces able to manipulate, simultaneously and independently, the amplitude and phase of the constituent frequency components of the pulse.
Abstract: Advances in ultrafast lasers, chirped pulse amplifiers, and frequency comb technology require fundamentally new pulse-modulation strategies capable of supporting unprecedentedly large bandwidth and high peak power while maintaining high spectral resolution. We demonstrate how dielectric metasurfaces can be leveraged to shape the temporal profile of a near-infrared femtosecond pulse. Finely tailored pulse-shaping operations, including splitting, compression, chirping, and higher-order distortion, are achieved using a Fourier-transform setup embedding metasurfaces able to manipulate, simultaneously and independently, the amplitude and phase of the constituent frequency components of the pulse. Exploiting metasurfaces to manipulate the temporal characteristics of light expands their impact and opens new vistas in the field of ultrafast science and technology.
TL;DR: This study concludes that the actual implementation of fully operational Terahertz communication systems obliges to carry out a multi-disciplinary effort including statistical propagation and channel characterizations, adaptive transceiver designs, reconfigurable platforms, advanced signal processing algorithms and techniques along with upper layer protocols equipped with various security and privacy levels.
20 Feb 2019
TL;DR: In this paper, a low-noise high-channel-count 20 GHz passively mode-locked quantum dot laser is presented, which can fulfill the rapidly increasing bandwidth and lower energy per bit requirements.
Abstract: Low-cost, small-footprint, highly efficient, and mass-producible on-chip wavelength-division-multiplexing (WDM) light sources are key components in future silicon electronic and photonic integrated circuits (EPICs), which can fulfill the rapidly increasing bandwidth and lower energy per bit requirements. We present here, for the first time to our knowledge, a low-noise high-channel-count 20 GHz passively mode-locked quantum dot laser grown on a complementary metal-oxide-semiconductor compatible on-axis (001) silicon substrate. The laser demonstrates a wide mode-locking regime in the O band. A record low timing jitter value for passively mode-locked semiconductor lasers of 82.7 fs (4–80 MHz) and a narrow RF 3 dB linewidth of 1.8 kHz are measured. The 3 dB optical bandwidth of the comb is 6.1 nm (containing 58 lines, with 80 lines within the 10 dB bandwidth). The integrated average relative intensity noise values of the whole spectrum and a single wavelength channel are −152 dB/Hz and −133 dB/Hz in the frequency range from 10 MHz to 10 GHz, respectively. Utilizing 64 channels, an aggregate total transmission capacity of 4.1 terabits per second is realized by employing a 32 Gbaud Nyquist four-level pulse amplitude modulation format. The demonstrated performance makes the laser a compelling on-chip WDM source for multi-terabit/s optical interconnects in future large-scale silicon EPICs.
TL;DR: An organic-based multilayered phased-array antenna package for 28-GHz mm-wave radio access applications is implemented, which incorporates 64 dual-polarized antenna elements and features an air cavity common to all antennas.
Abstract: Silicon-based millimeter-wave (mm-wave) phased-array technologies are enabling directional wireless data communications at Gb/s speeds. In this paper, we review and discuss the challenges of implementing a multichip phased-array antenna module for mm-wave applications using organic buildup substrate technology. A prototype test vehicle has been fabricated and studied to evaluate the antenna and interconnect performance, dielectric properties, package substrate warpage conditions at different temperatures, chip- and board-level joint process reliability, and thermal management feasibility for cooling. Based on the learning from the test vehicle, an organic-based multilayered phased-array antenna package for 28-GHz mm-wave radio access applications is implemented. The package incorporates 64 dual-polarized antenna elements and features an air cavity common to all antennas. Direct probing measurements on a single-antenna element of the package show over 3 GHz of bandwidth and 3-dBi gain at 28 GHz. A phased-array transceiver module has been developed with the package; the module includes four SiGe BiCMOS ICs attached using flip-chip assembly. Module-level measurements in the TX mode show a 35-dB near-ideal output power increase for 64-element power combining; 64-element radiation pattern measurements are reported with a steering range of ± 50° without tapering in off-boresight directions, and 64-element radiation pattern measurements with tapering show achievement of a sidelobe level lower than −20 dB. The transceiver modules achieved 20.64-Gb/s throughput with 256 QAM and 800-MHz bandwidth in direct over-the-air link measurement results.
TL;DR: This paper presents a new decomposition approach called adaptive chirp mode pursuit (ACMP), similar to the matching pursuit method, the ACMP captures signal modes one by one in a recursive framework.
TL;DR: The extension of the feasibility of digital communication via this quantum-based antenna over a continuously tunable RF-carrier at off-resonance is studied and a choice of linear gain response to the RF-amplitude can suppress the signal distortion.
Abstract: Up to now, the measurement of radio-frequency (RF) electric field achieved using the electromagnetically-induced transparency (EIT) of Rydberg atoms has proved to be of high-sensitivity and shows a potential to produce a promising atomic RF receiver at resonance between two chosen Rydberg states. In this paper, we study the extension of the feasibility of digital communication via this quantum-based antenna over a continuously tunable RF-carrier at off-resonance. Our experiment shows that the digital communication at a rate of 500 kbps can be performed reliably within a tunable bandwidth of 200 MHz near a 10.22 GHz carrier. Outside of this range, the bit error rate (BER) increases, rising to, for example, 15% at an RF-detuning of ±150 MHz. In the measurement, the time-varying RF field is retrieved by detecting the optical power of the probe laser at the center frequency of RF-induced symmetric or asymmetric Autler-Townes splitting in EIT. Prior to the digital test, we studied the RF-reception quality as a function of various parameters including the RF detuning and found that a choice of linear gain response to the RF-amplitude can suppress the signal distortion. The modulating signal can be decoded at speeds up to 500 kHz in the tunable bandwidth. Our test consolidates the physical basis for reliable communication and spectral sensing over a wider broadband RF-carrier, which paves a way for the concurrent multi-channel communications founded on the same pair of Rydberg states.
TL;DR: This paper establishes the first practically viable solution for initial access and, hence, the first demonstration of stand-alone mmWave communication in the relevant regime of low (−10 dB to +5 dB) raw SNR.
Abstract: Millimeter wave (mmWave) communication with large antenna arrays is a promising technique to enable extremely high data rates due to large available bandwidth in mmWave frequency bands. In addition, given the knowledge of an optimal directional beamforming vector, large antenna arrays have been shown to overcome both the severe signal attenuation in mmWave as well as the interference problem. However, fundamental limits on achievable learning rate of an optimal beamforming vector remain. This paper considers the problem of adaptive and sequential optimization of the beamforming vectors during the initial access phase of communication. With a single-path channel model, the problem is reduced to actively learning the Angle-of-Arrival (AoA) of the signal sent from the user to the Base Station (BS). Drawing on the recent results in the design of a hierarchical beamforming codebook, sequential measurement dependent noisy search strategies, and active learning from an imperfect labeler, an adaptive and sequential alignment algorithm is proposed. For any given resolution and error probability of the estimated AoA, an upper bound on the expected search time of the proposed algorithm is derived via Extrinsic Jensen-Shannon Divergence. The upper bound demonstrates that the search time of the proposed algorithm asymptotically matches the performance of the noiseless bisection search up to a constant factor, in effect, characterizing the AoA acquisition rate. Furthermore, the upper bound shows that the acquired AoA error probability decays exponentially fast with the search time with an exponent that is a decreasing function of the acquisition rate. Numerically, the proposed algorithm is compared with prior work where a significant improvement of the system communication rate is observed. Most notably, in the relevant regime of low (−10 dB to +5 dB) raw SNR, this establishes the first practically viable solution for initial access and, hence, the first demonstration of stand-alone mmWave communication.
TL;DR: This work uses flexible epicortical and intracortical arrays of graphene solution-gated field-effect transistors (gSGFETs) to map cortical spreading depression in rats and demonstrates that gSGFETS are able to record, with high fidelity, infraslow signals together with signals in the typical local field potential bandwidth.
Abstract: Recording infraslow brain signals (<0.1 Hz) with microelectrodes is severely hampered by current microelectrode materials, primarily due to limitations resulting from voltage drift and high electrode impedance. Hence, most recording systems include high-pass filters that solve saturation issues but come hand in hand with loss of physiological and pathological information. In this work, we use flexible epicortical and intracortical arrays of graphene solution-gated field-effect transistors (gSGFETs) to map cortical spreading depression in rats and demonstrate that gSGFETs are able to record, with high fidelity, infraslow signals together with signals in the typical local field potential bandwidth. The wide recording bandwidth results from the direct field-effect coupling of the active transistor, in contrast to standard passive electrodes, as well as from the electrochemical inertness of graphene. Taking advantage of such functionality, we envision broad applications of gSGFET technology for monitoring infraslow brain activity both in research and in the clinic.
TL;DR: Results show that the proposed method outperforms the auto-regressive AR- MSSE, VKF-MSSE and EEMD-MS SE in identifying fault types of planetary gearboxes.
TL;DR: This paper first proves that each path component of the wideband beamspace channel exhibits a unique frequency-dependent sparse structure, and then proposes a successive support detection (SSD) based beam space channel estimation scheme, which successively estimates all the sparse path components following the classical idea of successive interference cancellation.
Abstract: Beamspace channel estimation is indispensable for millimeter-wave MIMO systems relying on lens antenna arrays for achieving substantially increased data rates, despite using a small number of radio-frequency chains. However, most of the existing beamspace channel estimation schemes have been designed for narrowband systems, while the rather scarce wideband solutions tend to assume that the sparse beamspace channel exhibits a common support in the frequency domain, which has a limited validity owing to the effect of beam squint caused by the wide bandwidth in practice. In this paper, we investigate the wideband beamspace channel estimation problem without the common support assumption. Specifically, by exploiting the effect of beam squint, we first prove that each path component of the wideband beamspace channel exhibits a unique frequency-dependent sparse structure. Inspired by this structure, we then propose a successive support detection (SSD) based beamspace channel estimation scheme, which successively estimates all the sparse path components following the classical idea of successive interference cancellation. For each path component, its support at different frequencies is jointly estimated to improve the accuracy by utilizing the proved sparse structure, and its influence is removed to estimate the remaining path components. The performance analysis shows that the proposed SSD-based scheme can accurately estimate the wideband beamspace channel at a low complexity. Simulation results verify that the proposed SSD-based scheme enjoys a reduced pilot overhead, and yet achieves an improved channel estimation accuracy.
TL;DR: In this article, a wideband filtering patch antenna is investigated, which consists of one upper and two lower horizontal arms, as well as a vertical arm that connects them, and two probe modes along with a patch mode are simultaneously excited within the passband, producing a wide bandwidth of 21.3%.
Abstract: A wideband filtering patch antenna is investigated in this paper. The patch antenna is fed by an F-shaped probe, which consists of one upper and two lower horizontal arms, as well as a vertical arm that connects them. Owing to the novel excitation scheme, two probe modes along with a patch mode are simultaneously excited within the passband, producing a wide bandwidth of 21.3% with stable antenna gains and radiation patterns. Meanwhile, cross-coupling is constructed in the antenna, generating two symmetrical radiation nulls right at the two sides of the passband. Consequently, a compact filtering antenna with bandpass response and high selectivity is obtained, without utilizing any extra filtering circuit. This design is also extended to realize a reconfigurable filtering antenna. Two varactor diodes are embedded in the F-shaped probe to continuously tune the frequency of the operating band from 2.05 to 2.52 GHz. The antenna bandwidth can be flexibly tuned from 2.2% to 21.3%, and simultaneously good filtering performance is kept during the tuning of different states.
TL;DR: An ultra-low loss lithium niobate piezoelectric electric dipole driven at acoustic resonance that radiates with greater than 300x higher efficiency compared to the previous state of the art at a comparable electrical size is demonstrated.
Abstract: Very low frequency communication systems (3 kHz–30 kHz) enable applications not feasible at higher frequencies. However, the highest radiation efficiency antennas require size at the scale of the wavelength (here, >1 km), making portable transmitters extremely challenging. Facilitating transmitters at the 10 cm scale, we demonstrate an ultra-low loss lithium niobate piezoelectric electric dipole driven at acoustic resonance that radiates with greater than 300x higher efficiency compared to the previous state of the art at a comparable electrical size. A piezoelectric radiating element eliminates the need for large impedance matching networks as it self-resonates at the acoustic wavelength. Temporal modulation of this resonance demonstrates a device bandwidth greater than 83x beyond the conventional Bode-Fano limit, thus increasing the transmitter bitrate while still minimizing losses. These results will open new applications for portable, electrically small antennas. Designing high radiation efficiency antennas for portable transmitters in low frequency communication systems remains a challenge. Here, the authors report on using piezoelectricity to more efficiently radiate while achieving a bandwidth eighty three times higher than the passive Bode-Fano limit.
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TL;DR: In this article, the authors proposed a Reconfigurable Intelligent Surface (RIS) based approach to control the physical propagation environment in which they are embedded by passively reflecting EM waves in preferred directions.
Abstract: 5G radio at millimeter wave (mmWave) and beyond 5G concepts at 0.1-1 THz can exploit angle and delay measurements for localization, by the virtue of increased bandwidth and large antenna arrays but are limited in terms of blockage caused by obstacles. Reconfigurable intelligent surfaces (RISs) are seen as a transformative technology that can control the physical propagation environment in which they are embedded by passively reflecting EM waves in preferred directions. Whereas such RISs have been mainly intended for communication purposes, RISs can have great benefits in terms of performance, energy consumption, and cost for localization and mapping. These benefits as well as associated challenges are the main topics of this paper.
TL;DR: A survey on the state-of-the-art spectrum allocation algorithms based on reinforcement learning techniques in cognitive radio networks and the advantages and disadvantages of each algorithm are analyzed in their specific practical application scenarios.
Abstract: Cognitive radio is an emerging technology that is considered to be an evolution for software device radio in which cognition and decision-making components are included. The main function of cognitive radio is to exploit "spectrum holes" or "white spaces" to address the challenge of the low utilization of radio resources. Dynamic spectrum allocation, whose significant functions are to ensure that cognitive users access the available frequency and bandwidth to communicate in an opportunistic manner and to minimize the interference between primary and secondary users, is a key mechanism in cognitive radio networks. Reinforcement learning, which rapidly analyzes the amount of data in a model-free manner, dramatically facilitates the performance of dynamic spectrum allocation in real application scenarios. This paper presents a survey on the state-of-the-art spectrum allocation algorithms based on reinforcement learning techniques in cognitive radio networks. The advantages and disadvantages of each algorithm are analyzed in their specific practical application scenarios. Finally, we discuss open issues in dynamic spectrum allocation that can be topics of future research.
TL;DR: An adaptive Kurtograms (AK) method is proposed, which improves the shortcomings of the center frequency and the bandwidth of the fast Kurtogram (FK) that cannot be explained theoretically.
TL;DR: In this article, a pole-zero temperature compensation proportional controller (PZTCPC) is proposed to expand the bandwidth of a dual-mass microelectromechanical system (MEMS) gyroscope under different temperatures.
Abstract: This paper presents a bandwidth expansion method for dual-mass microelectromechanical system (MEMS) gyroscopes based on the pole–zero temperature compensation method. When the sense loop operates under open conditions, the mechanical sensitivity of the gyroscope structure conflicts with the bandwidth and is governed by the frequency difference between the drive and the sense modes (min {Δ ω 1, Δ ω 2}), which is proven to change with temperature during the experiment. The pole–zero temperature compensation proportional controller (PZTCPC) is proposed to expand the bandwidth under different temperatures based on the pole–zero compensation method. The force rebalancing combs stimulation method (FRCSM) is used to achieve accurate gyroscope bandwidth characteristics. The mechanical bandwidth of the gyroscope is proven to be approximately 13 Hz when the sense-mode loop is open, and the simulation results show that the PZTCPC method expands the bandwidth to greater than 91.7 Hz after the sense-mode loop is closed. The FRCSM experiments indicate that gyroscope bandwidth is expanded to 95 Hz at –40 °C, 94 Hz at 20 °C and 92 Hz at 60 °C, while the bandwidths at –40, 20, and 60 °C are all 93 Hz with the turntable method. The experimental curves match the simulation curves well and verify the simulation results. The new limiting condition of the closed-loop bandwidth is the trough generated by conjugate zeros, formed by superposition of in-phase and anti-phase sense modes.