Limited Bandwidth Research Articles

Artificial Photothermal Nociceptor Using Mott Oscillators.

Bioinspired sensory systems based on spike neural networks have received considerable attention in resolving high energy consumption and limited bandwidth in current sensory systems. To efficiently produce spike signals upon exposure to external stimuli, compact neuron devices are required for signal detection and their encoding into spikes in a single device. Herein, it is demonstrated that Mott oscillative spike neurons can integrate sensing and ceaseless spike generation in a compact form, which emulates the process of evoking photothermal sensing in the features of biological photothermal nociceptors. Interestingly, frequency-tunable and repetitive spikes are generated above the threshold value (Pth =84mWcm-2) as a characteristic of "threshold" in leaky-integrate-and-fire (LIF) neurons; the neuron devices successfully mimic a crucial feature of biological thermal nociceptors, including modulation of frequency coding and startup latency depending on the intensity of photothermal stimuli. Furthermore, Mott spike neurons are self-adapted after sensitization upon exposure to high-intensity electromagnetic radiation, which can replicate allodynia and hyperalgesia in a biological sensory system. Thus, this study presents a unique approach to capturing and encoding environmental source data into spikes, enabling efficient sensing of environmental sources for the application of adaptive sensory systems.

Analysis of development of fifth generation communication networks

The article is devoted to a comprehensive analysis of key aspects of the development of fifth-generation (5G) networks in Ukraine. Current problems and prospects for the implementation of 5G are studied, taking into account technological, economic and regulatory aspects. Mathematical models and algorithms are proposed for optimizing the allocation of radio frequency spectrum, placement of base stations, implementation of virtualization of network functions Network Function Virtualization (NFV) and software-configured networks Software-Defined Networking (SDN), as well as ensuring quality of service (QoS) for different classes of traffic. The developed solutions allow to increase the efficiency of deployment and operation of 5G networks in conditions of limited resources. A mathematical model of spectrum allocation optimization using linear programming has been developed, which takes into account the efficiency of spectrum use by different operators. To optimize the placement of base stations, an approach based on game theory is proposed, which takes into account bandwidth limitations and placement costs while ensuring the necessary coverage. A mathematical model is presented for optimizing the placement of virtualized network functions on servers with limited resources in order to minimize costs and ensure the required performance. An algorithm based on gradient descent for dynamic resource management and QoS is proposed. Based on a comparative analysis of optimization methods, an integrated approach to solving key problems of 5G implementation is developed. A mathematical model for optimizing the allocation of radio frequency spectrum based on linear programming is proposed, which provides an increase in spectral efficiency by 23–27 % compared to basic methods. A game-theoretic approach to optimizing the placement of base stations is presented, which allows reducing the number of overloaded sectors by 45 % and increasing energy efficiency by 13.3 %. A genetic algorithm for optimizing the placement of virtualized network functions (VNF) is developed, which provides a 21.4 % higher resource utilization. Experimental studies have confirmed that the proposed solutions allow achieving an overall increase in network efficiency by 20–25 % while reducing operating costs by 15–20 %. The results create a methodological basis for effective planning and deployment of 5G networks in Ukraine.

Ultra‐Large Bandwidth and Ultra‐High Sensitivity Germanium/Silicon Avalanche Photodiode

AbstractGermanium/silicon (Ge/Si) avalanche photodiode (APD) has emerged as a highly desirable component for optical communication, sensing, and computing, attributed to its inherent gain. Conventional schemes typically suffer from limited bandwidth and significant excess noise due to the high gain, restricting the high‐sensitivity detection in burgeoning high‐speed applications. Here, a Ge/Si APD is developed with an ultra‐large bandwidth at an optimal gain. This breakthrough is achieved by implementing an extremely narrow multiplication layer to enhance the space charge effect, overcoming the intrinsic bandwidth limitation in conventional APDs while elaborately harnessing the gain to a moderate value to ensure the optimal sensitivity. The device possesses a bandwidth of 67 GHz at an optimal gain of 6.6 and enables data reception of 240 Gb s−1 four‐level pulse amplitude modulation signal—the largest bandwidth and highest single‐channel bitrate among all reported APDs. The presented APD suggests promising applications for high‐speed and high‐sensitivity data communication owing to its competitive performance, cost‐effectiveness, and high‐yield production.

The identification of extensive samples of motor units in human muscles reveals diverse effects of neuromodulatory inputs on the rate coding.

Movements are performed by motoneurons transforming synaptic inputs into an activation signal that controls muscle force. The control signal emerges from interactions between ionotropic and neuromodulatory inputs to motoneurons. Critically, these interactions vary across motoneuron pools and differ between muscles. To provide the most comprehensive framework to date of motor unit activity during isometric contractions, we identified the firing activity of extensive samples of motor units in the tibialis anterior (129 ± 44 per participant; n=8) and the vastus lateralis (130 ± 63 per participant; n=8) muscles during isometric contractions of up to 80% of maximal force. From this unique dataset, the rate coding of each motor unit was characterised as the relation between its instantaneous firing rate and the applied force, with the assumption that the linear increase in isometric force reflects a proportional increase in the net synaptic excitatory inputs received by the motoneuron. This relation was characterised with a natural logarithm function that comprised two stages. The initial stage was marked by a steep acceleration of firing rate, which was greater for low- than medium- and high-threshold motor units. The second stage comprised a linear increase in firing rate, which was greater for high- than medium- and low-threshold motor units. Changes in firing rate were largely non-linear during the ramp-up and ramp-down phases of the task, but with significant prolonged firing activity only evident for medium-threshold motor units. Contrary to what is usually assumed, our results demonstrate that the firing rate of each motor unit can follow a large variety of trends with force across the pool. From a neural control perspective, these findings indicate how motor unit pools use gain control to transform inputs with limited bandwidths into an intended muscle force.

Acoustic Sensors data transmission integrity and endurance with IoT-enabled location-aware framework

Environmental monitoring and disaster mitigation are critical applications of underwater acoustic sensor networks (UASNs). However, UASNs face significant challenges, including high latency, limited bandwidth, and energy constraints. This study introduces an Internet of Things (IoT)-driven location-aware framework (ILAF) designed to enhance UASN performance by utilizing non-GPS geographic coordinates for determining the location of sensor and sink nodes, identifying their neighbors based on coordinates and transmission range, and optimizing node placement and routing without the need for GPS modems. The framework is compared with several state-of-the-art protocols, including Bald Eagle Search inspired optimized energy efficient routing protocol (BES-OEERP) and IoT-enabled depth-based routing technique (IDBR), demonstrating superior performance. Specifically, ILAF achieved a packet delivery ratio (PDR) of 99%, which outperforms energy-efficient region-based source distributed routing algorithm (EERSDRA) (98%) and energy-efficient geo-opportunistic routing protocols (EEGORP) (96%). Additionally, ILAF reduced energy consumption by 20% compared to these existing protocols. These improvements result in a more energy-efficient network with fewer dead nodes (12 after 1,000 rounds) and higher throughput (5.7 kbps at 1,000 rounds), making ILAF suitable for real-time underwater applications. Future research will explore integrating lightweight IoT protocols like Message Queue Telemetry Transport (MQTT) and Constrained Application Protocol (CoAP) to enhance the framework’s performance and reliability further.

The identification of extensive samples of motor units in human muscles reveals diverse effects of neuromodulatory inputs on the rate coding

Movements are performed by motoneurons transforming synaptic inputs into an activation signal that controls muscle force. The control signal emerges from interactions between ionotropic and neuromodulatory inputs to motoneurons. Critically, these interactions vary across motoneuron pools and differ between muscles. To provide the most comprehensive framework to date of motor unit activity during isometric contractions, we identified the firing activity of extensive samples of motor units in the tibialis anterior (129 ± 44 per participant; n=8) and the vastus lateralis (130 ± 63 per participant; n=8) muscles during isometric contractions of up to 80% of maximal force. From this unique dataset, the rate coding of each motor unit was characterised as the relation between its instantaneous firing rate and the applied force, with the assumption that the linear increase in isometric force reflects a proportional increase in the net synaptic excitatory inputs received by the motoneuron. This relation was characterised with a natural logarithm function that comprised two stages. The initial stage was marked by a steep acceleration of firing rate, which was greater for low- than medium- and high-threshold motor units. The second stage comprised a linear increase in firing rate, which was greater for high- than medium- and low-threshold motor units. Changes in firing rate were largely non-linear during the ramp-up and ramp-down phases of the task, but with significant prolonged firing activity only evident for medium-threshold motor units. Contrary to what is usually assumed, our results demonstrate that the firing rate of each motor unit can follow a large variety of trends with force across the pool. From a neural control perspective, these findings indicate how motor unit pools use gain control to transform inputs with limited bandwidths into an intended muscle force.

Event‐Triggered Fault‐Tolerant Control for Nonlinear Multilateral Teleoperation System With Unknown Environmental Forces

ABSTRACTIn this paper, an event‐triggered fuzzy adaptive fault‐tolerant control scheme is investigated to achieve displacement synchronization and force tracking for nonlinear multilateral teleoperation systems subject to actuator faults and communication network constraints. The time‐varying delays and network communication bandwidth limitations are incorporated into the communication network constraints, and the considered nonlinear systems are modeled by using T‐S fuzzy system theory. Then, a novel event‐triggered fuzzy adaptive fault‐tolerant control algorithm is designed to simultaneously estimate and compensate for possible actuator faults during system operation. Next, unlike many existing works, the unknown environmental forces are estimated by introducing radial basis function neural networks, and the estimated results are taken into account in the design of the event‐triggered mechanisms. Finally, a numerical simulation example is presented to illustrate the effectiveness of the designed algorithm.

Secure Drone Communications using MQTT protocol

With the revolutionary change in emerging technologies, the usage of drones or unmanned aerial vehicles (UAV) has exponentially increased in different sectors like Industry, healthcare, military, agriculture, real estate, manufacturing, logistics, energy and many more utilities. This rapid growth creates a concern for the secure communication between the internal communication modules and the ground based computer system used for controlling the UAV. Intruder can hack into the device and attack the internal communication device with the injection of the malicious code which can lead to the malfunction of the aircraft. Security issues related to the communication between the internal modules of the drone and the ground based computer system is of major concern and is crucial. UAVs have to operate in constrained networks with limited bandwidth. In such a constrained environment MQTT protocol can be an excellent protocol. No cryptographic techniques are used to retain the simplicity and the light weight of the MQTT protocol. This contributes for the large scope for emerging with new solutions in the protection issues of MQTT communications. This paper mainly focuses on Armstrong number encryption standard algorithm for providing a computationally simple yet a secure and strong algorithm for UAVs encryption and decryption process on the communication links using MQTT protocol.

Integrating Blockchains with the IoT: A Review of Architectures and Marine Use Cases

This review examines the integration of blockchain technology with the IoT in the Marine Internet of Things (MIoT) and Internet of Underwater Things (IoUT), with applications in areas such as oceanographic monitoring and naval defense. These environments present distinct challenges, including a limited communication bandwidth, energy constraints, and secure data handling needs. Enhancing BIoT systems requires a strategic selection of computing paradigms, such as edge and fog computing, and lightweight nodes to reduce latency and improve data processing in resource-limited settings. While a blockchain can improve data integrity and security, it can also introduce complexities, including interoperability issues, high energy consumption, standardization challenges, and costly transitions from legacy systems. The solutions reviewed here include lightweight consensus mechanisms to reduce computational demands. They also utilize established platforms, such as Ethereum and Hyperledger, or custom blockchains designed to meet marine-specific requirements. Additional approaches incorporate technologies such as fog and edge layers, software-defined networking (SDN), the InterPlanetary File System (IPFS) for decentralized storage, and AI-enhanced security measures, all adapted to each application’s needs. Future research will need to prioritize scalability, energy efficiency, and interoperability for effective BIoT deployment.

Performance Improvement by FRFT-OFDM for Visible Light Communication and Positioning Systems

In indoor visible light communication (VLC) and visible light positioning (VLP) systems, the performance of conventional orthogonal frequency-division multiplexing (OFDM) schemes is often compromised due to the nonlinear characteristics and limited modulation bandwidth of light-emitting diodes, the multipath effect in enclosed indoor environments, and the relative positions of transmitters and receivers. This paper proposes an OFDM scheme based on the fractional Fourier transform (FRFT) to address these issues, demonstrating promising results when applied to indoor VLC and VLP systems. The FRFT, a generalization of the conventional Fourier transform (FT) in the fractional domain, captures information in both the time and frequency domains, offering greater flexibility than the FT. In this paper, we first introduce the computation method of the reality-preserving FRFT for an intensity modulation/direct detection VLC system and integrate it with OFDM to optimize system performance. By adopting FRFT-OFDM under the optimal fractional order, we enhance both the bit error ratio (BER) performance and positioning accuracy. Simulation results reveal that the FRFT-OFDM scheme with an optimized fractional order significantly improves the BER and positioning accuracy compared to the FT-OFDM scheme across most receiver positions within the indoor observation plane. For communication, the FRFT-OFDM scheme achieves over 6 dB Eb/N0 gain compared to the FT-OFDM scheme at a BER of 3×10−4 when the receiver is positioned at most locations in the room. For positioning, the FRFT-OFDM scheme enhances positioning accuracy by more than 1 cm relative to the FT-OFDM scheme at most locations in the room. Notably, both systems maintain the same computational complexity and spectral efficiency.

PIMCoSim: Hardware/Software Co-Simulator for Exploring Processing-in-Memory Architectures

As the scope of artificial intelligence (AI) expands and the structure becomes more complex, the amount of data for inference and training has increased. In traditional computer architectures, the memory bandwidth limitations have intensified bottlenecks in AI systems, and processing-in-memory (PIM) architectures have been proposed to overcome this issue. PIM is an architecture that performs computations within memory, thereby reducing data movement between the CPU and memory. However, since PIM is difficult to optimize as a general-purpose architecture, it is essential to adopt an architecture suitable for the target application. While various simulators and emulators have been introduced for the design space exploration (DSE) of different PIM architectures, simulators are limited in debugging hardware operations, and emulators face challenges in flexibly modifying the system configuration, as emulators implement the entire architecture in hardware. Therefore, this paper introduces PIMCoSim, a comprehensive hardware–software co-simulator for the DSE of DRAM-PIM systems. This co-simulator partially emulates simplified hardware-implemented processing elements (PEs) and integrates software models for memory operations, facilitating the DSE of PIM systems. To validate PIMCoSim, we analyzed results for different computational workloads by varying PIM structures and operational policies, demonstrating the efficiency of DRAM-PIM systems. The co-simulation approach in PIMCoSim aims to contribute to analyzing DRAM-PIM configurations and adopting optimized structures.

An improving secure communication using multipath malicious avoidance routing protocol for underwater sensor network

The Underwater Sensor Network (UWSN) comprises sensor nodes with sensing, data processing, and communication capabilities. Due to the limitation of underwater radio wave propagation, nodes rely on acoustic signals to communicate. The data gathered by these nodes is transmitted to coordinating nodes or ground stations for additional processing and analysis. The characteristics of UWSN with underwater channels make them vulnerable to malicious attacks. UWSN communication networks are particularly susceptible to malicious attacks owing to high bit error rates, significant propagation delay variations, and low bandwidth. Moreover, because of the challenging and erratic underwater conditions, limited bandwidth, slow data transmission speed, and power constraints of underwater sensor nodes establishing secure communication in UWSN presents a significant challenge. To address the issues mentioned above, we have introduced the Multipath Malicious Avoidance Routing Protocol (M2ARP) and Foldable Matrix based Padding Rail Fence Encryption Scheme (FM-PRFES) methods to enhance secure communication in UWSNs. The proposed FM-PRFES method encrypts the input data to prevent unauthorized access during transmission within the network. Subsequently, the proposed Energy Efficiency Node Selection (EENS) method is used to identify the significant nodes in the network. Additionally, the Cuckoo Search Optimization (CSO) method is utilized to select the Cluster Head (CH) for data transmission. Subsequently, M2ARP is employed to analyze various routes and avoid adversarial nodes in the network. As a result, the proposed experimental analysis yields more efficient results regarding security, Packet Delivery Ratio (PDR), and throughput performance than traditional approaches.

Generation of broadband chaotic laser based on a four-segment InP-based monolithically integrated chaotic semiconductor laser

Aiming at the problems of limited bandwidth and obvious time-delay signature (TDS) of monolithically integrated chaotic semiconductor lasers, this paper proposes a four-segment InP-based monolithically integrated chaotic semiconductor laser. The laser structure is composed of a distributed feedback (DFB1) laser region, a semiconductor optical amplifier (SOA) region, a distributed Bragg reflector (DBR) grating region and a distributed feedback (DFB2) laser region. Mutual injection between the two DFB laser regions effectively enhances the bandwidth of power spectrum. The DBR grating region is used to form a complex multi-feedback cavity to suppress the TDS caused by the fixed external cavity structure. The simulation results show that the chaotic signal with the standard bandwidth of 29.2 GHz and the TDS value of 0.094 is generated. The research in this paper can further improve the performance of monolithically integrated chaotic laser, and provide a high-quality chaotic laser source for secure optical communication, chaotic lidar and distributed optical fiber sensing.

Internal Crisis Communication in Hospitals the Choice of Communication Channels and Its Impact on Effectiveness

ABSTRACTThe COVID‐19 pandemic has highlighted the need for effective internal crisis communication (ICC) in hospitals. However, only little is known about how the choice of communication channels influences the effectiveness of ICC. Our case study offers novel insights into this relationship. We performed an in‐depth analysis of ICC during the COVID‐19 pandemic at a Norwegian tertiary public hospital. We conducted 22 in‐depth interviews with stakeholders from various hierarchical levels who actively participated in ICC. We mapped the relationships of the actors involved in ICC and performed a social network analysis. The emergency reorganization of the hospital made ICC processes more complex compared to the ordinary line structure of communication, and on lower hierarchical levels several redundant (and not necessarily officially approved) communication channels were used. Moreover, we found that the effectiveness of ICC was reduced by communication channels with speed and bandwidth limits. In contrast, communication channels with a high capability to transmit contextualized information improved the effectiveness of ICC. Since our case hospital shares common characteristics with many other tertiary public hospitals, including fragmentation of responsibilities during crisis response, we use our results as a basis for recommending appropriate communication channels and avoiding a decoupling of ICC between hierarchical levels and professions.

Ultra-wide band and high efficient Polarization converting metasurface employing Bell-shaped unit cell for RCS reduction

Polarization is a dominant parameter regarding communication systems in recent times. The standard polarization techniques can be used only to a certain extent because of their huge size and limited bandwidth constraints. A design of bell-shaped polarization converting metasurface (PCMS) is presented in this paper which is highly efficient for Radar cross section (RCS reduction) and also operates in ultra-wideband. The designed PCMS attains a polarization conversion ratio of more than 90% by demonstrating the transformation of the linear polarization wave to its orthogonal counterpart. The PCMS is arranged in a triangular chessboard configuration to reduce the RCS. RCS reduction is obtained by achieving destructive interference, accomplished by two unit cells. The two unit cells, PCMS and its mirror will have a phase difference of 180 ± 37°. The phase cancellation is obtained by rotating and arranging the proposed PCMS at 90°, 180° and 270°. RCS reduction is obtained in a frequency range from 4 GHz to 24.8 GHz with 144% FBW. This PCMS is verified experimentally. A good agreement is found between the simulation and the experimental results.

Communication‐Efficient Distributed Gradient Descent via Random Projection

ABSTRACTThe gradient descent algorithm is one type of communication‐efficient algorithm in distributed computing as it only requires transmitting the gradient vectors to update parameters. However, as the dimensionality of model parameters increases, even transmitting the gradients alone can result in a significant amount of communication costs. On the other hand, many local computers in the distributed system may suffer from communication bandwidth limitations, so the transmission of the full gradients are practically prohibited. Therefore, reducing the communication cost of gradient descent algorithms, particularly the communication bandwidth, becomes an important issue. To address this problem, we propose a randomly projected gradient descent (RPGD) algorithm. The proposed algorithm consists of three main steps. First, the gradient computed by the local computers is compressed into a low‐dimensional vector using a random matrix. Then, these projected gradients are transmitted to the central computer, aggregated and broadcasted back to the local ones. Finally, the local computers recover the gradients to their original dimensions and update the parameters. By employing random projection, we can reduce the communication bandwidth requirements in distributed computing while we can also provide better privacy protection for local computers. We have provided a theoretical convergence analysis of the RPGD algorithm. Extensive numerical studies have been conducted to demonstrate the finite sample performance of the proposed method.

An improved digital predistortion scheme for nonlinear transmitters with limited bandwidth

In modern wireless communication systems, wide signal bandwidth is the most straightforward approach to accommodate high data rates. Wide signal bandwidth, on the other hand, introduces severe challenges to the power amplifier (PA) and digital predistortion (DPD) design in both performance and cost. Conventional DPD systems usually ignore the impact of the transmit low-pass filter (Tx LPF) bandwidth and assume the transmit bandwidth is sufficiently large. In wideband signal transmissions, the bandwidth of Tx LPF can become the system bottleneck, limiting DPDs compensation effects. Existing DPD studies mostly investigate the DPD with reduced feedback bandwidth. In this paper, we study the impact of Tx LPF bandwidth on the DPD performance. A full-band error minimization DPD based on direct learning structure is proposed. The DPD coefficients are estimated by minimizing the full-band error between the input signal and PA output signal in the frequency domain. Furthermore, we propose a weighted DPD with improved performance by introducing a weighting diagonal matrix to the error function. Compared to existing solutions, the weighted DPD achieves a good trade-off between the in-band distortion compensation and out-of-band spectral regrowth suppression. Simulations and experiments validate the effectiveness of the proposed DPD schemes.

Rotation matrix-based finite-time trajectory tracking control of benthic AUV with communication bandwidth limitation

Rotation matrix-based finite-time trajectory tracking control of benthic AUV with communication bandwidth limitation

Beyond two-octave coherent OAM supercontinuum generation in air-core Ge-doped ring fiber

Orbital angular momentum (OAM) has emerged as a revolutionary technology for communication networks due to its ability to significantly increase the channel capacity. However, traditional optical fibers present significant hurdles to harnessing OAM’s full potential, including dispersion and limited bandwidth, which facilitates investigations on supercontinuum (SC) generation for OAM beams. In this paper, an air-core Ge-doped ring fiber is proposed and designed to support high-order OAM mode up to |l| = 24. To achieve this, the fiber has a high refractive index difference between the ring core and the cladding, enabling stable transmission of high-order OAM modes. A key feature of this design is the OAM24,1 mode, which exhibits near-zero and flat dispersion. This characteristic translates into high coherence and a remarkably broad SC generation. The generated SC spans over two octaves (2336 nm) within the infrared wavelength range (764 nm to 3100 nm) at a power level of −40 dB. Furthermore, by optimizing the structural parameters, we ensure near-zero and flat dispersion characteristics for the other OAM modes (|l| < 24), along with broad SC generation exceeding two octaves. This fiber design holds significant promise for future advancements in OAM beam transmission within the infrared spectrum.

Research and Flight Test on the Terminal Guidance Control Technology for Cruising Unmanned Aerial Vehicles

The Cruising Unmanned Aerial Vehicle (CUAV) exemplifies an advanced system integrating UAV and munitions technology. The primary challenge lies in devising strategies to achieve precision strikes. Achieving precision strikes is a critical combat mission for CUAV and serves as the primary focus of this research. This paper introduces a three-loop pseudo-angle-of-attack acceleration autopilot design with proportional–integral (PI) correction, overcoming the limitations of existing two-loop and three-loop systems. The existing two-loop acceleration autopilot with PI correction suffers from low robustness, whereas the three-loop autopilot exhibits slow response to acceleration deviations. The proposed design overcomes these shortcomings by optimizing the autopilot for high-dynamic and fast-response scenarios. The design methodology leverages pole assignment, referencing the pole co-circle method and accommodating servo bandwidth limitations. A comparison of the designed three-loop acceleration autopilot with PI correction with other acceleration autopilots reveals superior accuracy advantages. The reliability and robustness of the proposed autopilot were validated through flight tests, achieving a drop point accuracy of less than 0.5 m. This study demonstrates the engineering application of a pseudo-angle-of-attack three-loop acceleration autopilot with PI correction, designed using the pole assignment method, on a short-range CUAV. Future efforts will focus on optimizing the autopilot to further enhance its adaptability and robustness.