Design of Communication Systems for Wireless-Powered Communications with Multiple Frequency Bands

Neural oscillations are fundamental for brain function and govern various cognitive processes. Recent functional magnetic resonance imaging advances offer the opportunity to study frequency-specific properties of blood-oxygen-level-dependent oscillations at multiple frequency bands. However, most have focused on spontaneous brain activity in the resting state, leaving a gap in direct evidence regarding the specific activations of cognitive tasks across different frequency bands. We aim to address this gap by exploring the role of blood-oxygen-level-dependent oscillations across multiple frequency bands in cognitive processes. We used task-functional magnetic resonance imaging data of 339 healthy young adults from the Human Connectome Project to map the activation patterns of performing seven cognitive tasks at multiple frequency bands (ie slow-1 to slow-6). Our findings revealed that different frequency bands are associated with distinct task-activation patterns. Specifically, slow-1/2/3 oscillations primarily contribute to local sensory information processing, while slow-4 is crucial for various fundamental cognitive functions. Slow-5 is involved in cognitive processes that require greater memory load, integrated cognitive processing, and attention maintenance. This underscores the importance of analyzing a broad frequency range to capture the full spectrum of cognitive function, highlighting the diverse roles of different frequency bands in brain activity, shedding light on the underlying mechanism of brain–behavior associations.

Wi-Fi Backscatter communication is method for zero-energy wireless connectivity using the ambient RF signals without needing an additional wireless communication infrastructure. Because this communication method uses Wi-Fi signal, there is a limit that cannot transmit a backscatter data faster than Wi-Fi packet transmission rate in the time-domain. This paper presents multi-level modulated-backscatter communication system using ambient Wi-Fi signal. We propose a method to improve data rate of backscatter communication using Wi-Fi signal. We implement and test Wi-Fi backscatter communication system applying transmitting multi-level load modulate data. The backscatter data transmission is achieved at a data rate of 60 kbps by the proposed multi-level backscatter modulator using Wi-Fi signal.

A structure for an underwater sound absorber with subwavelength thickness and a quasi-perfect absorption property at multiple frequency bands is reported. This absorber consists of a viscoelastic coating layer embedded with periodically distributed plate scatterers (PSs). The embedded PSs cannot only slow sound waves in the coating, leading to a down-shifted resonance frequency where the absorption is maximized, but also introduce multiple local bending modes and local longitudinal modes in the coating. Via proper selection of the parameters of the PSs and the PS array, multiple local resonance modes of different types in a coating unit can be excited, resulting in quasi-perfect absorption of incident sound at multiple frequencies whose wavelengths are much longer than the thickness of the coating layer. For example, absorption (89%) of underwater sound at 462.9 Hz is achieved by such a layer with a thickness of 6 cm, which is 1.9% of the wavelength of the incident sound. Broadband quasi-perfect absorption can also be realized by coupling of those multiple local resonant modes. This quasi-perfect absorption property can also be observed for sound waves with different incident angles, because a large number of local intrinsic modes could still be excited.

Although cognitive functions are hypothesized to be mediated by synchronous neuronal interactions in multiple frequency bands among widely distributed cortical areas, we still lack a basic understanding of the distribution and task dependence of oscillatory activity across the cortical map. Here, we ask how the spectral and temporal properties of the local field potential (LFP) vary across the primate cerebral cortex, and how they are modulated during visual short-term memory. We measured the LFP from 55 cortical areas in two macaque monkeys while they performed a visual delayed match to sample task. Analysis of peak frequencies in the LFP power spectra reveals multiple discrete frequency bands between 3–80 Hz that differ between the two monkeys. The LFP power in each band, as well as the Sample Entropy, a measure of signal complexity, display distinct spatial gradients across the cortex, some of which correlate with reported spine counts in layer 3 pyramidal neurons. Cortical areas can be robustly decoded using a small number of spectral and temporal parameters, and significant task dependent increases and decreases in spectral power occur in all cortical areas. These findings reveal pronounced, widespread and spatially organized gradients in the spectral and temporal activity of cortical areas. Task-dependent changes in cortical activity are globally distributed, even for a simple cognitive task.

Understanding user-induced effects on signal reception across multiple frequency bands is of great scientific and military importance to the wireless industry. Various onbody locations and directional heading of the user are believed to impact the performance of mobile devices, but there has been little work across multiple frequency bands to quantify these user-induced effects. In this work, we perform a measurement study to explore user effects on radio wave propagation with varying line-of-sight conditions and environments across multiple frequency bands, including white space (500 and 800 MHz), cellular (1800 MHz), and WiFi (2400 MHz) frequency bands. To do so, we first conduct a baseline experiment that characterizes the propagation channel in this environment. We show that the propagation differences for ground-to-ground communication (common in Ad Hoc and WiFi scenarios) and tower-to-ground communication (common in cellular scenarios) are frequency dependent. Then, we measure signal quality as a function of the on-body location of the receiver, directional heading of the user with respect to the transmitter, vegetation type, frequency band, and propagation distance. Our assessment reveals that the user directionality with respect to the transmitter can reduce received signal strength up to 20 dB and reduce throughput by 20.9% at most. We also find that the body can act like an antenna, increasing reception by 4.4 dB and throughput by 14.4% over a reference node at the same distance. Since our study spans many critical (UHF) frequency bands, we believe these results will have far-reaching impact on a broad range of network types.

We present the design of a communication system that enables two devices to communicate using ambient RF as the only source of power. Our approach leverages existing TV and cellular transmissions to eliminate the need for wires and batteries, thus enabling ubiquitous communication where devices can communicate among themselves at unprecedented scales and in locations that were previously inaccessible. To achieve this, we introduce ambient backscatter, a new communication primitive where devices communicate by backscattering ambient RF signals. Our design avoids the expensive process of generating radio waves; backscatter communication is orders of magnitude more power-efficient than traditional radio communication. Further, since it leverages the ambient RF signals that are already around us, it does not require a dedicated power infrastructure as in traditional backscatter communication. To show the feasibility of our design, we prototype ambient backscatter devices in hardware and achieve information rates of 1 kbps over distances of 2.5 feet and 1.5 feet, while operating outdoors and indoors respectively. We use our hardware prototype to implement proof-of-concepts for two previously infeasible ubiquitous communication applications.

ObjectiveThis study aimed to elucidate the distributions of abnormal activities, as well as the functional connectivity and topological properties of brain networks, in patients diagnosed with anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis.MethodFrom February 2016 to February 2025, acute-phase magnetoencephalography (MEG) data were successfully acquired from 16 patients diagnosed with anti-NMDAR encephalitis at the Affiliated Brain Hospital of Nanjing Medical University. MEG was employed to evaluate the power spectral density (PSD) across multiple frequency bands. Further analysis concentrated on functional connectivity and the topological characteristics of brain networks in order to identify distinctive neurophysiological features associated with the condition.ResultsDuring the acute phase, the PSD in the delta band (1–3 Hz) showed greater power in posterior regions and lower power in anterior regions, with the highest energy concentrated bilaterally in the occipitoparietal and temporal areas. In the theta band (5–7 Hz), the PSD was predominantly localized to the bilateral occipitoparietal regions. The beta1 band (13–20 Hz) was primarily distributed in the right temporo-occipitoparietal regions, while the beta2 band (20–30 Hz) was predominantly distributed in the left temporal, occipitoparietal, and certain frontal regions. Functional connectivity analysis revealed enhanced connections between the left caudal anterior cingulate (CAC_L) and the left superior parietal lobe in the delta and theta bands. Increased connectivity was also observed between the left frontal pole and Precuneus_L, CAC_L, and the left superior temporal gyrus (STG_L)in the theta and beta2 bands. Furthermore, enhanced connectivity between STG_L and Pericalcarine_R was observed in the theta, beta2, and gamma bands. Patients with anti-NMDAR encephalitis demonstrated significantly reduced global efficiency and notable increases in average path length, local efficiency, and clustering coefficient in multiple bands, suggesting local clustering of brain networks during the acute phase.ConclusionAlterations in PSD distribution and brain networks across different frequency bands may provide valuable insights into the electrophysiological changes observed in the brains of anti-NMDAR encephalitis patients. Furthermore, these findings may offer valuable mechanistic insights that could contribute to the development of future diagnostic strategies.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00415-025-13302-x.

Recent findings in monkeys suggest that intrinsic periodic spiking activity in selective cortical areas occurs at timescales that follow a sensory or lower order-to-higher order processing hierarchy (Murray JD, Bernacchia A, Freedman DJ, Romo R, Wallis JD, Cai X, Padoa-Schioppa C, Pasternak T, Seo H, Lee D, Wang XJ. Nat Neurosci 17: 1661-1663, 2014). It has not yet been fully explored if a similar timescale hierarchy is present in humans. Additionally, these measures in the monkey studies have not addressed findings that rhythmic activity within a brain area can occur at multiple frequencies. In this study we investigate in humans if regions may be biased toward particular frequencies of intrinsic activity and if a full cortical mapping still reveals an organization that follows this hierarchy. We examined the spectral power in multiple frequency bands (0.5-150 Hz) from task-independent data using magnetoencephalography (MEG). We compared standardized power across bands to find regional frequency biases. Our results demonstrate a mix of lower and higher frequency biases across sensory and higher order regions. Thus they suggest a more complex cortical organization that does not simply follow this hierarchy. Additionally, some regions do not display a bias for a single band, and a data-driven clustering analysis reveals a regional organization with high standardized power in multiple bands. Specifically, theta and beta are both high in dorsal frontal cortex, whereas delta and gamma are high in ventral frontal cortex and temporal cortex. Occipital and parietal regions are biased more narrowly toward alpha power, and ventral temporal lobe displays specific biases toward gamma. Thus intrinsic rhythmic neural activity displays a regional organization but one that is not necessarily hierarchical.NEW & NOTEWORTHY The organization of rhythmic neural activity is not well understood. Whereas it has been postulated that rhythms are organized in a hierarchical manner across brain regions, our novel analysis allows comparison of full cortical maps across different frequency bands, which demonstrate that the rhythmic organization is more complex. Additionally, data-driven methods show that rhythms of multiple frequencies or timescales occur within a particular region and that this nonhierarchical organization is widespread.

Wireless devices such as smart meters, trackers, and sensors need connections at multiple frequency bands with low power consumption, thus requiring multiband and efficient antenna systems. At the same time, antennas should be small to easily fit in the scarce space existing in wireless devices. Small, multiband, and efficient operation is addressed here with non-resonant antenna elements, featuring volumes less than 90 mm3 for operating at 698–960 MHz as well as some bands in a higher frequency range of 1710–2690 MHz. These antenna elements are called antenna boosters, since they excite currents on the ground plane of the wireless device and do not rely on shaping complex geometric shapes to obtain multiband behavior, but rather the design of a multiband matching network. This design approach results in a simpler, easier, and faster method than creating a new antenna for every device. Since multiband operation is achieved through a matching network, frequency bands can be configured and optimized with a reconfigurable matching network. Two kinds of reconfigurable multiband architectures with antenna boosters are presented. The first one includes a digitally tunable capacitor, and the second one includes radiofrequency switches. The results show that antenna boosters with reconfigurable architectures feature multiband behavior with very small sizes, compared with other prior-art techniques.

Deep reinforcement learning has achieved significant success in solving sequential decision-making tasks. Excellent models usually require the input of valid state signals during training, which is challenging to encode temporal state features for the deep reinforcement learning model. To address this issue, recent methods attempt to encode multi-step sequential state signals so as to obtain more comprehensive observational information. However, these methods usually have a lower performance on complex continuous control tasks because mapping the state sequence into a low-dimensional embedding causes blurring of the immediate state features. In this paper, we propose a multiple frequency bands temporal state representation learning framework. The temporal state signals are decomposed into discrete state signals of various frequency bands by Discrete Fourier Transform (DFT). Then, feature signals filtered out different high-frequency bands are generated. Meanwhile, the mask generator evaluates the weights of signals of various frequency bands and encodes high-quality representations for agent training. Our intuition is that temporal state representations considering multiple frequency bands have high fidelity and stability. We conduct experiments tasks and verify that our method has obvious advantages over the baseline in complex continuous control tasks such as Walker and Crawler.

This article investigates physical-layer security (PLS) of a typical wireless-powered communication (WPC) system with the aid of intelligent reflecting surface (IRS) in the presence of a passive eavesdropper for Internet of Things (IoT), and proposes three IRS-aided secure WPC modes. Specifically, in mode-I, the IRS is deployed between hybrid access point (HAP) and wireless user (U) for co-located power station (PS) and access point (AP). In mode-II, the IRS is deployed between AP and U for separate PS and AP, while in mode-III, the IRS is deployed between PS and U for separate PS and AP. For each mode, the optimal phase shift is designed to maximize the reception of energy and information at the legitimate receiver. We comprehensively analyze the performance of each mode, and derive the closed-form expressions of connection outage probability (COP), secrecy outage probability (SOP), and effective secrecy throughput (EST) for each mode, respectively. The theoretical analysis and simulation results reveal that from the perspective of reliability, mode-I can achieve the best COP with the increased number of IRS elements, while mode-II and mode-III have a similar COP. From the perspective of security, mode-II can achieve the best SOP with the increased number of IRS elements, while mode-I and mode-III have a similar SOP. Moreover, under the condition of small transmission power at HAP/PS or small number of IRS elements, mode-I has the best EST, while as the power or the number increases, the EST of mode-II becomes the best one.

A large number of traffic accidents due to driver drowsiness have been under more attention of many countries. The organization of the functional brain network is associated with drowsiness, but little is known about the brain network topology that is modulated by drowsiness. To clarify this problem, in this study, we introduce a novel approach to detect driver drowsiness. Electroencephalogram (EEG) signals have been measured during a simulated driving task, in which participants are recruited to undergo both alert and drowsy states. The filtered EEG signals are then decomposed into multiple frequency bands by wavelet packet transform. Functional connectivity between all pairs of channels for multiple frequency bands is assessed using the phase lag index (PLI). Based on this, PLI-weighted networks are subsequently calculated, from which minimum spanning trees are constructed-a graph method that corrects for comparison bias. Statistical analyses are performed on graph-derived metrics as well as on the PLI connectivity values. The major finding is that significant differences in the delta frequency band for three graph metrics and in the theta frequency band for five graph metrics suggesting network integration and communication between network nodes are increased from alertness to drowsiness. Together, our findings also suggest a more line-like configuration in alert states and a more star-like topology in drowsy states. Collectively, our findings point to a more proficient configuration in drowsy state for lower frequency bands. Graph metrics relate to the intrinsic organization of functional brain networks, and these graph metrics may provide additional insights on driver drowsiness detection for reducing and preventing traffic accidents and further understanding the neural mechanisms of driver drowsiness.

For clinical applications in epilepsy, magnetoencephalography (MEG) has been mostly used to localize sources of interictal spike activity using the single equivalent current dipole (ECD) method. Thanks to the advancement of analytical methodology for MEG signals, multiple frequency band signals, especially fast oscillations (>30 Hz), are now being used for localization of ictal and interictal epileptic activity in addition to the ECD method. Moreover, connectivity and network analysis utilizing multiple frequency band MEG signals have recently been adopted in the field of epilepsy. This chapter provides an overview of the clinical applications of multiple frequency band signal analysis in epilepsy for the purpose of localization of epileptiform activity sources and assessment of functional connectivity.

This study presents design and simulation of a new planar microstrip elliptical split-ring resonator (ESRR) exhibiting negative index of refraction at multiple bands while no metallic strip or rod used for electrical resonance. These kinds of planar microstrip structures are excellent for use in applications where equipment space is limited. Despite being based on a Split-Ring Resonator (SRR), the structure does not include an additional metallic rod for electrical resonance, as is the case with traditional SRRs. Coaxial dual feeding that is offset in phase has been used, and the rings are elliptical in shape. Simulations of the elliptical split ring resonator (ESRR) have been carried out in microwave regime. S-parameter simulation results of the resonator show metamaterial property at multiple frequency bands.

Due to the rapid development of wireless communication systems, good numbers of services and devices use different frequency bands and protocols. To concurrently cover all these services, the antenna in communication devices should operate over multiple frequency bands. The use of wide and multi-band antennas not only reduces the number of antennas necessary to cover multiple frequency bands but also lessens the system complexity, size, and costs. To operate over eight frequency bands to cover sixteen well-established narrow service bands, a planar monopole antenna is proposed for portable communication devices. The proposed antenna is comprised of an inverted F-shaped monopole patch with a rotated L-shaped strip and an F-shaped ground strip with a rotated L-shaped branch. The studied antenna can excite at multiple resonant modes which helps it to achieve eight measured operating bands of 789–921 MHz, 1367–1651 MHz, 1995–2360 MHz, 2968–3374 MHz, 3546–3707, 4091–4405 MHz, 4519–5062 MHz and 5355–6000 MHz. The achieved measured operating bands can cover sixteen popular narrow service bands for 4G/3G/2G, MWT, WiFi, WiMAX, WLAN, and sub-6 GHz 5G wireless communication system. The studied antenna achieved good gain, efficiency and exhibits stable radiation characteristics. Moreover, the antenna does not use any lumped element and left ample space for other circuitries which makes it easier to use in portable devices such as tablets, laptops, etc. with low manufacturing cost.