Theta and alpha oscillations in human hippocampus and medial parietal cortex support the formation of location-based representations.

Our ability to navigate in a new environment depends on learning new locations. Mental representations of locations are quickly accessible during navigation and allow us to know where we are regardless of our current viewpoint. Recent functional magnetic resonance imaging (fMRI) research using pattern classification has shown that these location-based representations emerge in the retrosplenial cortex and parahippocampal gyrus, regions theorized to be critically involved in spatial navigation. However, little is currently known about the oscillatory dynamics that support the formation of location-based representations. We used magnetoencephalogram (MEG) recordings to investigate region-specific oscillatory activity in a task where participants could form location-based representations. Participants viewed videos showing that two perceptually distinct scenes (180° apart) belonged to the same location. This "overlap" video allowed participants to bind the two distinct scenes together into a more coherent location-based representation. Participants also viewed control "non-overlap" videos where two distinct scenes from two different locations were shown, where no location-based representation could be formed. In a post-video behavioral task, participants successfully matched the two viewpoints shown in the overlap videos, but not the non-overlap videos, indicating they successfully learned the locations in the overlap condition. Comparing oscillatory activity between the overlap and non-overlap videos, we found greater theta and alpha/beta power during the overlap relative to non-overlap videos, specifically at time-points when we expected scene integration to occur. These oscillations localized to regions in the medial parietal cortex (precuneus and retrosplenial cortex) and the medial temporal lobe, including the hippocampus. Therefore, we find that theta and alpha/beta oscillations in the hippocampus and medial parietal cortex are likely involved in the formation of location-based representations.

Effects of Catecholaminergic and Transcranial Direct Current Stimulation on Response Inhibition.

BACKGROUND: The principle of gain control determines the efficiency of neuronal processing and can be enhanced with pharmacological or brain stimulation methods. It is a key factor for cognitive control, but the degree of how much gain control may be enhanced underlies a physical limit. METHODS: To investigate whether methylphenidate (MPH) and transcranial direct current stimulation (tDCS) share common underlying mechanisms and cognitive effects, we administered MPH and anodal tDCS (atDCS) over the right inferior frontal gyrus both separately and combined, while healthy adult participants (n = 104) performed a response selection and inhibition task. The recorded EEG data were analyzed with a focus on theta band activity, and source estimation analyses were conducted. RESULTS: The behavioral data show that MPH and atDCS revealed interactive effects on the ability to inhibit responses. Both MPH and atDCS modulated task-related theta oscillations in the supplementary motor area when applied separately, making a common underlying mechanism likely. When both stimulation methods were combined, there was no doubling of effects in the supplementary motor area but a shift to inferior frontal areas in the cortical network responsible for theta-driven processing. CONCLUSIONS: The results indicate that both MPH and atDCS likely share a common underlying neuronal mechanism, and interestingly, they demonstrate interactive effects when combined, which are most likely due to the physical limitations of gain control increases. The current study provides critical groundwork for future combined applications of MPH and non-invasive brain stimulation.

Adapted Beamforming: A Robust and Flexible Approach for Removing Various Types of Artifacts from TMS-EEG Data.

Electroencephalogram (EEG) recorded as response to transcranial magnetic stimulation (TMS) can be highly informative of cortical reactivity and connectivity. Reliable EEG interpretation requires artifact removal as the TMS-evoked EEG can contain high-amplitude artifacts. Several methods have been proposed to uncover clean neuronal EEG responses. In practice, determining which method to select for different types of artifacts is often difficult. Here, we used a unified data cleaning framework based on beamforming to improve the algorithm selection and adaptation to the recorded signals. Beamforming properties are well understood, so they can be used to yield customized methods for EEG cleaning based on prior knowledge of the artifacts and the data. The beamforming implementations also cover, but are not limited to, the popular TMS-EEG cleaning methods: independent component analysis (ICA), signal-space projection (SSP), signal-space-projection-source-informed-reconstruction method (SSP-SIR), the source-estimate-utilizing noise-discarding algorithm (SOUND), data-driven Wiener filter (DDWiener), and the multiple-source approach. In addition to these established methods, beamforming provides a flexible way to derive novel artifact suppression algorithms by considering the properties of the recorded data. With simulated and measured TMS-EEG data, we show how to adapt the beamforming-based cleaning to different data and artifact types, namely TMS-evoked muscle artifacts, ocular artifacts, TMS-related peripheral responses, and channel noise. Importantly, beamforming implementations are fast to execute: We demonstrate how the SOUND algorithm becomes orders of magnitudes faster via beamforming. Overall, the beamforming-based spatial filtering framework can greatly enhance the selection, adaptability, and speed of EEG artifact removal.

The Benefit of Bimodal Hearing and Beamforming for Cochlear Implant Users.

INTRODUCTION: Cochlear implantation is the standard treatment for severe to profound hearing loss. While cochlear implant (CI) users can communicate effectively in quiet environments, speech understanding in noise remains challenging. Bimodal hearing, combining a CI in one ear and a hearing aid (HA) in the other, has shown advantages over unilateral electrical hearing, especially for speech understanding in noisy conditions. Beamforming is a technique used to improve speech understanding in noise by detecting sound direction and enhancing frontal (speech) sounds while attenuating background noise. One specific beamformer, Stereozoom, combines signals from microphones in both ears to create a focused beam toward the front resulting in a binaural beamformer (BB), in order to improve speech intelligibility in noise for bilateral and bimodal CI users. METHODS: A prospective crossover study involving 17 bimodal CI users was conducted, and participants were tested with various device configurations (CI, HA, CI + HA) with and without BB. Speech recognition testing with the Dutch/Flemish matrix test was performed in a sound-attenuated booth with diffuse noise to simulate realistic listening conditions. RESULTS: The results showed a statistically significant benefit of bimodal hearing over the CI configuration and showed a statistical significant benefit of BB for the CI and CI + HA configuration. The benefit of BB in the HA configuration was not statistically significant probably due to the higher variance. The benefit of BB in the three configurations did not differ statistically significant. CONCLUSION: In conclusion, bimodal hearing offers advantages for speech understanding in noise for CI users. BB provides a benefit in various device configurations, leading to improved speech intelligibility when speech comes from the front in challenging listening environments.

Low-Cost Scalable PCB-Based 2-D Transducer Arrays for Volumetric Photoacoustic Imaging.

Photoacoustic (PA) imaging provides deep tissue molecular imaging of chromophores with optical absorption contrast and ultrasonic resolution. Present PA imaging techniques are predominantly limited to one 2D plane per acquisition. 2D ultrasound transducers, required for real-time 3D PA imaging, are high-cost, complex to fabricate and have limited scalability in design. We present novel PCB-based 2D matrix ultrasound transducer arrays that are capable of being bulk manufactured at low-cost without using laborious ultrasound fabrication tools. The 2D ultrasound array specifications are easily scalable with respect to widely available PCB design and fabrication tools at low cost. To demonstrate scalability, we fabricated low (11 MHz) frequency 8x8 matrix array and high (40 MHz) frequency 4x4 matrix array by directly bonding an undiced polyvinylidene fluoride (PVDF) piezoelectric material of desired thickness to the custom designed PCB substrate. Characterization results demonstrate wideband PA receive sensitivity for both low (87%) and high (188%) frequency arrays. Volumetric PA imaging results of light absorbing targets inside optical scattering medium demonstrate improved spatial resolution and field of view with increase in aperture size.

A Volumetric Waveguide-Type Rotman Lens Antenna for Three-Dimensional Millimeter-Wave Beamforming.

In this paper, a volumetric Rotman lens antenna operating at 28 GHz is proposed. The design formula and procedure were derived for the 3-D Rotman lens antenna. The number of tilted beams is 3 × 3. The six rectangular blocks are assembled using a metallic bolt. The input port consists of a waveguide, and the output port is made of an open-ended waveguide. The input and output waveguides are drilled in a flat conducting plate. The input and output port positions are optimized. Simulated and measured results show that the radiating beam is controlled almost exactly as calculated. Compared with the previous two-stage stacked Rotman lens antenna, the proposed Rotman lens antenna can dramatically decrease the antenna volume by approximately 75%.

Feedback Beamforming in the Time Domain.

Real-time source localization is crucial for high-end automation and artificial intelligence (AI) products. However, a low signal-to-noise ratio (SNR) and limited processing time can reduce localization accuracy. This work proposes a new architecture for a time-domain feedback-based beamformer that meets real-time processing demands. The main objective of this design is to locate reflective sources by estimating their direction of arrival (DOA) and signal range. Incorporating a feedback mechanism in this architecture refines localization precision, a unique aspect of this approach. We conducted an in-depth analysis to compare the effectiveness of time-domain feedback beamforming against conventional time-domain methods, highlighting their benefits and limitations. Our evaluation of the proposed architecture, based on critical performance indicators such as peak-to-sidelobe ratio, mainlobe width, and directivity factor, demonstrates its ability to improve beamformer effectiveness significantly.

FireSonic: Design and Implementation of an Ultrasound Sensing-Based Fire Type Identification System.

Accurate and prompt determination of fire types is essential for effective firefighting and reducing damage. However, traditional methods such as smoke detection, visual analysis, and wireless signals are not able to identify fire types. This paper introduces FireSonic, an acoustic sensing system that leverages commercial speakers and microphones to actively probe the fire using acoustic signals, effectively identifying fire types. By incorporating beamforming technology, FireSonic first enhances signal clarity and reliability, thus mitigating signal attenuation and distortion. To establish a reliable correlation between fire type and sound propagation, FireSonic quantifies the heat release rate (HRR) of flames by analyzing the relationship between fire-heated areas and sound wave propagation delays. Furthermore, the system extracts spatiotemporal features related to fire from channel measurements. The experimental results demonstrate that FireSonic attains an average fire type classification accuracy of 95.5% and a detection latency of less than 400 ms, satisfying the requirements for real-time monitoring. This system significantly enhances the formulation of targeted firefighting strategies, boosting fire response effectiveness and public safety.

A General Scheme of a Branch-and-Bound Approach for the Sensor Selection Problem in Near-Field Broadband Beamforming.

This paper is devoted to the sensor selection problem. A broadband receiver beamforming working in a near-field is considered. The system response should be as close as possible to the desired one, which is optimized in the sense of L2 norm. The problem considered is at least NP-hard. Therefore, the branch-and-bound algorithm is developed to solve the problem. The proposed approach is universal and can be applied not only to microphone arrays but also to antenna arrays; that is, the methodology for the generation of consecutive solutions can be applied to different types of sensor selection problems. Next, for a larger microphone array, an efficient metaheuristic algorithm is constructed. The algorithm implemented is a hybrid genetic algorithm based on the ITÖ process. Numerical experiments show that the proposed approach can be successfully applied to the sensor selection problem.

Acoustic Imaging Method for Gas Leak Detection and Localization Using Virtual Ultrasonic Sensor Array.

An acoustic imaging method for detecting and locating gas leaks based on a virtual ultrasonic sensor array is proposed and experimentally demonstrated. A scanning sensor array of only two sensors is used to collect the acoustic signals generated by the leakage hole. The matrix of the leakage signal is processed by the cross-power spectrum method to achieve time consistency, afterward, the location of the leakage source can be calculated by the virtual beamforming method. The influence of the number of sensors and the distance between adjacent sensors on the effect of the proposed method are compared and discussed. To verify the effectiveness and operability of the detection and localization method, several experiments were carried out. Furthermore, a series of experiments were conducted to assess the accuracy and stability of this method. The experimental results demonstrate that the proposed method based on a virtual sensor array can achieve highly accurate localization of gas leaks and performs well regarding stability.

A 5G NR FR2 Beamforming System with Integrated Transceiver Module.

This paper presents a 5G new radio (NR) FR2 beamforming system with an integrated transceiver module. A real-time operating module providing enhanced flexibility and capability has been proposed. The integrated RF beamforming system with an integrated transceiver module can be operated in 8Tx-8Rx mode configuration simultaneously. A series-fed structure 8 × 7 microstrip antenna array for compact size and improved directivity is employed in the RF beamforming module. The RF beamforming module incorporates a custom 28 GHz, eight-channel fully differential beamforming IC (BFIC). An eight-channel BFIC in a phased-array beamforming system offers advantages in terms of increased antenna density and improved beam steering precision. The RF beamforming module is integrated with an RF transceiver module that enables the simultaneous up-conversion and down-conversion of the baseband signal. The RF transmitter module consists of a transmitter, a receiver, a signal generator, a power supply, and a control unit. The RF beamforming system can scan horizontally from -50° to +50° with a step of 10°. To achieve an optimized beam pattern, a calibration was conducted. The transmit and receive conversion gain of around 20 dB is achieved with the transceiver module. To verify the communication performance of the manufactured integrated RF beamforming system, a real-time wireless video transmission/reception test was performed at a frequency of 28 GHz, and the video file was transmitted smoothly in real time without interruption within a range of ±50°.

Respiration and Heart Rate Monitoring in Smart Homes: An Angular-Free Approach with an FMCW Radar.

This paper proposes a new approach for wide angle monitoring of vital signs in smart home applications. The person is tracked using an indoor radar. Upon detecting the person to be static, the radar automatically focuses its beam on that location, and subsequently breathing and heart rates are extracted from the reflected signals using continuous wavelet transform (CWT) analysis. In this way, leveraging the radar's on-chip processor enables real-time monitoring of vital signs across varying angles. In our experiment, we employ a commercial multi-input multi-output (MIMO) millimeter-wave FMCW radar to monitor vital signs within a range of 1.15 to 2.3 m and an angular span of -44.8 to +44.8 deg. In the Bland-Altman plot, the measured results indicate the average difference of -1.5 and 0.06 beats per minute (BPM) relative to the reference for heart rate and breathing rate, respectively.

Discussion and Demonstration of RF-MEMS Attenuators Design Concepts and Modules for Advanced Beamforming in the Beyond-5G and 6G Scenario-Part 1.

This paper describes different variants of broadband and simple attenuator modules for beamforming applications, based on radio frequency micro electro-mechanical systems (RF-MEMS), framed within coplanar waveguide (CPW) structures. The modules proposed in the first part of this work differ in their actuation voltage, topology, and desired attenuation level. Fabricated samples of basic 1-bit attenuation modules, characterized by a moderate footprint of 690 × 1350 µm2 and aiming at attenuation levels of -2, -3, and -5 dB in the 24.25-27.5 GHz range, are presented in their variants featuring both low actuation voltages (5-9 V) as well as higher values (~45 V), the latter ones ensuring larger mechanical restoring force (and robustness against stiction). Beyond the fabrication non-idealities that affected the described samples, the substantial agreement between simulations and measurement outcomes proved that the proposed designs could provide precise attenuation levels up to 40 GHz, ranging up to nearly -3 dB and -5 dB for the series and shunt variants, respectively. Moreover, they could be effective building blocks for future wideband and reconfigurable RF-MEMS attenuators. In fact, in the second part of this work, combinations of the discussed cells and other configurations meant for larger attenuation levels are investigated.

A Compact Linear Microstrip Patch Beamformer Antenna Array for Millimeter-Wave Future Communication.

5/6G is anticipated to address challenges such as low data speed and high latency in current cellular networks, particularly as the number of users overwhelms 4G and LTE capabilities. This paper proposes a microstrip patch antenna array comprising six radiating patches and utilizing a microstrip line feeding technique to facilitate the compact design crucial for 5G implementation. ROGER 3003, chosen for its advanced and environmentally friendly features, serves as the dielectric material, ensuring suitability for 5G and B5G applications. The designed antenna, evaluated at a resonating frequency of 28.8 GHz with a -10 dB impedance bandwidth of 1 GHz, offers a high gain of 9.19 dBi. Its compact array, cost-effectiveness, and broad impedance and radiation coverage position it as a viable candidate for 5G and future communication applications.

Adaptable Hybrid Beamforming with Subset Optimization Algorithm for Multi-User Massive MIMO Systems.

The exploiting of hybrid beamforming (HBF) in massive multiple-input multiple-output (MIMO) systems can enhance the system's sum rate while reducing power consumption and hardware costs. However, designing an effective hybrid beamformer is challenging, and interference between multiple users can negatively impact system performance. In this paper, we develop a scheme called Subset Optimization Algorithm-Hybrid Beamforming (SOA-HBF) that is based on the subset optimization algorithm (SOA), which effectively reduces inter-user interference by dividing the users set into subsets while optimizing the hybrid beamformer to maximize system capacity. To validate the proposed scheme, we constructed a system model that incorporates an intelligent reflecting surface (IRS) to address obstacles between the base station (BS) and the users set, enabling efficient wireless communication. Simulation results indicate that the proposed scheme outperforms the baseline by approximately 8.1% to 59.1% under identical system settings. Furthermore, the proposed scheme was applied to a classical BS-users set link without obstacles; the results show its effectiveness in both mmWave massive MIMO and IRS-assisted fully connected hybrid beamforming systems.

Bilayer Intelligent Omni-Surface-Assisted Full-Duplex Systems: Simultaneous Self-Interference Cancellation and Sum Rate Maximization.

Recently, reconfigurable intelligent surfaces (RISs) have attracted increasing attentions in the design of full-duplex (FD) systems due to their novel capability of propagation environment reconfiguration. However, in conventional RIS-assisted FD systems, the beamforming for self-interference cancellation (SIC) and sum rate maximization (SRM) are highly coupled during RIS optimization, which significantly degrades the system performance. To tackle this issue, we exploit a novel bilayer intelligent omni-surface (BIOS) structure in FD systems. Compared with the conventional RIS designs, the BIOS provides independent beams on both sides, thus enabling more flexible achievement of SRM and SIC. For the BIOS-assisted FD system, we first formulate an optimization problem to achieve SRM and efficient SIC simultaneously. Then, we exploit the relationship between the SRM and mean square error (MSE), and propose a weighted MSE minimization with SIC algorithm to solve the problem. Specifically, we jointly design the beamforming at the base station and the BIOS with manifold optimization while guaranteeing an SIC constraint. Furthermore, we theoretically derive a lower band for the BIOS size required for efficient SIC in FD systems. Simulation results indicate that the BIOS outperforms the conventional RIS designs in FD systems, and verify the accuracy of the derived lower bound for the BIOS size.

Transmit Beamforming Design Based on Multi-Receiver Power Suppression for STAR Digital Array.

The simultaneous transmit and receive (STAR) array system provides higher radiation gain and data rate compared to traditional radio system. Because of the various mutual couplings between each pair of transmit and receive elements, it is a great challenge to suppress the incident self-interference power at multiple receive elements, which is usually much higher than the desired signal of interest (SoI) power and causes the saturation of receive links and the distortion of the digital SoI. In this paper, we propose an optimized method for transmit beamforming based on radiation power constraints and transmit power control. Through adaptive transmit beamforming, high isolation between the transmit array and each receive link is achieved, minimizing the self-interference power at each receiving element. This method effectively reduces the self-interference power, avoiding distortion of the SoI digital signal caused by limited-bit analog-to-digital converters (ADCs). Simulation results demonstrate that this optimized transmit beamforming method can achieve more than 100 dB effective isotropic isolation (EII) on a 32-element two-dimensional phased array designed in HFSS, reducing the maximum incident self-interference power at the receive channels by approximately 35 dB, while effectively controlling the attenuation of the transmit gain. We also present the advantages in receive subarray isolation and lower ADCs digits under the transmit ABF method.

Dispersion Influence of Electroacoustic Transducer Parameters in the Design Process of Miniature Loudspeaker Arrays and Omnidirectional Sound Sources.

Electroacoustic transducers represent one of the crucial materials used in the construction of loudspeaker arrays. The dispersion in their parameters may influence the performance of a speaker set. Parametric loudspeaker arrays and omnidirectional sound sources have been used for years. However, the possible influence of transducer manufacturing tolerances on the arrays' performance has not been investigated. In previous research, the sources of possible dispersion in acoustic measurements carried out with omnidirectional sources were studied, pointing out that the problems with sound sources may be a significant reason behind the small measurement repeatability in standards. This paper investigated the measurement of several common types of miniature speakers, using 10 pieces of each type and investigating the influence of their parameter dispersion in electric and acoustic ways. Numerical simulations of omnidirectional sound sources were performed to investigate the drivers' dispersion influence sensitivity. The results provided proof of the small-signal parameter dispersion reaching 20% of the variation. The acoustic measurements show that the loudspeakers may differ in sensitivity parameters by up to 4 dB in 10 transducer tests. The analysis of an example multitransducer array indicated that a dispersion of a sensitivity higher than 1 dB might lead to significant misperformance in constructed arrays and measurement deviations with this type of array.

Novel Technologies towards the Implementation and Exploitation of "Green" Wireless Agriculture Sensors.

This manuscript presents the use of three novel technologies for the implementation of wireless green battery-less sensors that can be used in agriculture. The three technologies, namely, additive manufacturing, energy harvesting, and wireless power transfer from airborne transmitters carried from UAVs, are considered for smart agriculture applications, and their combined use is demonstrated in a case study experiment. Additive manufacturing is exploited for the implementation of both RFID-based sensors and passive sensors based on humidity-sensitive materials. A number of energy-harvesting systems at UHF and ISM frequencies are presented, which are in the position to power platforms of wireless sensors, including humidity and temperature IC sensors used as agriculture sensors. Finally, in order to provide wireless energy to the soil-based sensors with energy harvesting features, wireless power transfer (WPT) from UAV carried transmitters is utilized. The use of these technologies can facilitate the extensive use and exploitation of battery-less wireless sensors, which are environmentally friendly and, thus, "green". Additionally, it can potentially drive precision agriculture in the next era through the implementation of a vast network of wireless green sensors which can collect and communicate data to airborne readers so as to support, the Artificial Intelligence and Machine Learning-based decision-making with data.

Localization Performance Analysis and Algorithm Design of Reconfigurable Intelligent Surface-Assisted D2D Systems.

The research on high-precision and all-scenario localization using the millimeter-wave (mmWave) band is of great urgency. Due to the characteristics of mmWave, blockages make the localization task more complex. This paper proposes a cooperative localization system among user equipment (UEs) assisted by reconfigurable intelligent surfaces (RISs), which considers device-to-device (D2D) communication. RISs are used as anchor points, and position estimation is achieved through signal exchanges between UEs. Firstly, we establish a localization model based on this system and derive the UEs' positioning error bound (PEB) as a performance metric. Then, a UE-RIS joint beamforming design is proposed to optimize channel state information (CSI) with the objective of achieving the minimum PEB. Finally, simulation analysis demonstrates the advantages of the proposed scheme over RIS-assisted base station positioning, achieving centimeter-level accuracy with a 10 dBm lower transmission power.