Channel Occupancy Research Articles

Analysis of delays in medium access control devices in cognitive radio systems with correlation of time intervals in request flows

This article is about the development of a method for analyzing the average waiting time of a request in a queue with correlated inter-arrival and service times. The ON-OFF process is often used to model the primary user channel occupancy in different questions related to cognitive radio, such as resource allocation, medium access control protocols, spectrum handoff and others. It is assumed that the time intervals of the ON- and OFF- periods are not correlated. More realistic models of primary user activity require the presence of correlation not only between consequent periods, but also the presence of correlation between channel occupancy and other quantities interpreted as service time in models based on queuing systems. As a result, here is proposed a variant of constructing the probability density function of a random variable which is the difference between the service time of the i-th request and the time interval between the moments of arriving of the i-th and (i-1)-th requests with correlated inter-arrival and service times. Solution based on the use of a two-dimensional characteristic function, so in this case it is possible to more purposefully specify the components of the statistical connection of previously described sequences. These components are the cumulants of the described distribution. For a queuing system with hyperexponential distribution of inter-arrival and service intervals, an analytical expression for the average waiting time of a request in a queue is found.

Identification and characterisation of two functional antibiotic MATE efflux pumps in the archaeon Halorubrum amylolyticum

Multidrug efflux pumps have been found to play a crucial role in drug resistance in bacteria and eukaryotes. In this study, we investigated the presence of functional multidrug and toxic compound extrusion (MATE) efflux pumps, inferred from whole genome sequencing, in the halophilic archaeon Halorubrum amylolyticum CSM52 using Hoechst 33342 dye accumulation and antimicrobial sensitivity tests in the presence and absence of efflux pump inhibitors (EPIs). The whole genome sequence of H. amylolyticum CSM52 contained two putative MATE-type efflux pump genes, which may contribute to the inherent resistance to conventional antimicrobial agents reported in archaea. Antimicrobial susceptibility of the wild-type H. amylolyticum CSM52 testing revealed a lack of sensitivity to a wide range of antimicrobials, including glycopeptides, aminoglycosides, macrolides, fluoroquinolones, tetracycline, and chloramphenicol. However, the presence of EPIs, such as thioridazine, fluoxetine, and chlorpromazine, significantly increased the susceptibility of H. amylolyticum CSM52 to a number of these antimicrobials, indicating the potential involvement of efflux pumps in the observed resistance. A molecular modelling study with EPIs and substrate antimicrobials provided important insights into the molecular interactions with the putative transporter. It suggests that the occupancy of the transporter channel by EPIs has the potential to impact the efflux of antimicrobials. Phylogenetic analysis of the amino acid sequences of both MATE pumps showed low similarity with bacterial representatives, suggesting the presence of novel and distinct MATE efflux pumps in archaea. Our findings provide the first experimental evidence of active antibiotic efflux mechanisms in archaea and their potential roles in antimicrobial resistance, broadening our understanding of mechanisms of archaeal antimicrobial resistance, an overlooked aspect of AMR research.

Atomic resolution transmission electron microscopy visualisation of channel occupancy in beryl in different crystallographic directions

The causes of colour in beryl have been a research topic for decades. For some varieties, such as emerald (green, coloured by Cr3+ and/or V3+), the main cause of colour is substitutions by metal atoms within the framework. However, the causes for the yellow and blue colours in heliodor, golden beryl and aquamarine are still debated. It is generally agreed that Fe ions are responsible for the colour, but there are differing conclusions about the valence states of these ions, the occupied positions and the colour-inducing processes involved. The colour of aquamarine is commonly attributed to intervalence charge transfer (IVCT) between Fe3+ and Fe2+. Various combinations of sites have been proposed to host the Fe ions engaging in this IVCT. Here we present a new approach to address the topic of colour generation: atomic resolution scanning transmission electron microscopy (STEM). For the first time, atomic resolution images of a beryl (natural aquamarine) are presented in the three crystallographic directions [0001], [1-210] and [1-100]. Ions are clearly resolved in the channels. From the ratio of channel occupation and the correlation of the atoms per formula unit (apfu) calculations we conclude that Fe resides in the framework, not in the channels. The projections in the [1-210] direction directly show that the cavity channel site 2a is occupied, most likely by Cs, in agreement with recent results in the literature.

An architecture to improve performance of software-defined optical networks

The software-defined optical network (SDON) is a revolutionary approach in the field of optical networks. The separation of the control plane and data plane in software-defined networking (SDN) provides enhanced security and simplified network administration. Nevertheless, performance and control plane scalability are significant issues in SDN. SDN performance can be evaluated using parameters such as burst loss, delay, channel occupancy, packet loss, throughput, and average response time. The number of messages exchanged between the data plane and the control plane is used as a metric to determine controller scalability. As the network load increases, the controller experiences a higher flow of messages. It causes delay and burst loss in transmitting the burst. Occasionally, bursts exceed the capacity of the fixed-sized burstifier and are discarded because it takes a long time to identify a suitable route for the burst. Hence, it is essential to minimize the volume of messages exchanged between the control plane and the data plane to improve performance and controller scalability. In this paper, we propose a scalable SDN optical network architecture that minimizes the number of messages exchanged between the data plane and the control plane. We proposed mechanisms like channel reservation, transmission cycles, and guard time between cycles to enhance both the speed and the quality of burst transmission. Prior to transmission, resources or channels are allocated to bursts to minimize the possibility of burst collision and loss. The data plane comprises an optical burst switching (OBS) network, and the flow table entries are periodically updated to minimize inter-plane communication. We perform simulations to evaluate and compare the performance of the proposed architecture with the existing state-of-the-art architecture reported in the literature. The proposed architecture performs better than the existing state-of-the-art in terms of metrics including burst loss, delay, channel occupancy, packet loss, throughput, average response time, and reduction in the number of messages exchanged between the data plane and the control plane. Experimental results indicate a 41% reduction in mean burst loss probability and a 40.5% reduction in mean burst sending delay compared to existing architectures. Additionally, 42.1% fewer messages are exchanged between the control plane and the data plane compared to the number of exchanged messages in existing architectures.

Incorporation and substitution of ions and H2O in the structure of beryl

Abstract. Incorporation of ions into the crystal structure of beryl (Be3Al2[Si6O18]) can take place by direct ion-to-ion substitution of the framework components Al3+, Be2+ and Si4+ or by occupation of interstitial or structural channel sites. The most common impurities in beryl include transition metals, alkalis and H2O. It is accepted that the transition metals Mn, Cr and V directly substitute for Al at the octahedral site and induce colour. Similarly, the octahedral site can host Fe instead of Al. Nevertheless, it is shown that it remains disputed whether Fe can also be present at the tetrahedral, interstitial, or channel sites, and opposing hypotheses exist regarding these possibilities. However, in the case of Fe, not only the possible occupation of these sites remains under debate, but also their influence on the subsequent colour of beryl. Similarly, the residence of Li in the channels and at the Be tetrahedral or interstitial tetrahedral sites is still under debate. The presence of more than two types of H2O (type I and type II) in the structural channels of beryl is also unclear. This article aims to give an overview on the consensus and on the current debates found in the literature regarding these aspects. It mainly concentrates on the substitution by and the role of Fe ions and on channel occupancy by H2O.

Design, Synthesis, and Biological Evaluation of New Type of Gemini Analogues with a Cyclopropane Moiety in Their Side Chain.

We synthesized two new gemini analogues, UG-480 and UG-481, that incorporate a modified longer side chain containing a cyclopropane group. The evaluation of the bioactivities of the two gemini analogues indicated that the 17,20 threo (20S) compound, UG-480, is the most active one and is as active as 1,25(OH)2D3. Docking and molecular dynamics (MD) data showed that the compounds bind efficiently to vitamin D receptor (VDR) with UG-480 to form an energetically more favorable interaction with His397. Structural analysis indicated that whereas the UG-480 compound efficiently stabilizes the active VDR conformation, it induces conformational changes in the H6-H7 VDR region that are greater than those induced by the parental Gemini and that this is due to the occupancy of the secondary channel by its modified side chain.

Development of Enhanced Chimp Optimization Algorithm (OFCOA) in Cognitive Radio Networks for Energy Management and Resource Allocation

Transmit time and power optimisation increase secondary network energy efficiency (EE). The optimum resource allocation strategy in cognitive radio networks is the enhanced chimp optimisation algorithm (OFCOA) since the EE maximising problem is a nonlinear fractional programming problem. To control resources and energy, this research offers an energy-efficient CRN opposition function-based chimpanzee optimisation algorithm (OFCOA) solution. Combining the opposition function (OF) with the chimpanzee optimisation technique is recommended. OF in COAs improves decision-making. Spectrum measurements in energy management provide energy-efficient CRN operation. The suggested technique was evaluated using channel occupancy, CRN data, and four major and secondary user scenarios. CPU power, network life, transmission rate, latency, flush, power consumption, and overhead are utilized to evaluate the proposed approach in MATLAB. The proposed method is compared to existing approaches like Particle Swarm Optimisation (PSO), Chimpanzee Optimisation Algorithm (COA), and Whale Optimisation Algorithm.

Improved spectrum prediction model for cognitive radio networks using hybrid deep learning technique

Cognitive Radio (CR) technology has been highlighted as one of the most likely answers to the issue of spectrum shortage with the rise of fifth generation and beyond communication. Secondary users (SUs) in cognitive radio networks (CRN) must continuously monitor the spectrum to forecast channel occupancy by primary users (PUs) based on fundamental factors, such as location, time, and RF band. A hybrid deep learning model called LSTM-MLP (Long Short-Term Memory-Multilayer Perceptron) is proposed to improve idle channel prediction probability thus reducing the overall sensing time by cognitive users during spectrum sensing. Performance evaluation for the proposed model is done in terms of prediction error and efficiency, the GSM-900 spectrum dataset demonstrates that LSTM-MLP performs better in terms of improved prediction accuracy compared to existing state-of-art prediction techniques.

LoRadar: An Efficient LoRa Channel Occupancy Acquirer based on Cross-channel Scanning

LoRadar: An Efficient LoRa Channel Occupancy Acquirer based on Cross-channel Scanning

Exploring Deep Learning for Adaptive Energy Detection Threshold Determination: A Multistage Approach

The concept of spectrum sensing has emerged as a fundamental solution to address the growing demand for accessing the limited resources of wireless communications networks. This paper introduces a straightforward yet efficient approach that incorporates multiple stages that are based on deep learning (DL) techniques to mitigate Radio Frequency (RF) impairments and estimate the transmitted signal using the time domain representation of received signal samples. The proposed method involves calculating the energies of the estimated transmitted signal samples and received signal samples and estimating the energy of the noise using these estimates. Subsequently, the received signal energy and the estimated noise energy, adjusted by a correction factor (k), are employed in binary hypothesis testing to determine the occupancy of the wireless channel under investigation. The proposed system demonstrates encouraging outcomes by effectively mitigating RF impairments, such as carrier frequency offset (CFO), phase offset, and additive white Gaussian noise (AWGN), to a considerable degree. As a result, it enables accurate estimation of the transmitted signal from the received signal, with 3.85% false alarm and 3.06% missed detection rates, underscoring the system’s capability to adaptively determine a decision threshold for energy detection.

Implementation of Enhanced Chimp Optimization Algorithm in Cognitive Radio Networks for Vehicular Mobile Communication

In recent years, 6G technology has been extended to many different applications, especially mobile communications. As a result, the volume of mobile data increases, which poses a problem with the load on the plane of control (IoE, IoT). This problem is solved by efficient use of resources and reduced power consumption in cognitive radio networks (CRNs). In the literature, many methods have been developed by researchers to control spectrum sensing as well as energy -efficient operation, but they still need to be improved to improve system efficiency and processing power. Therefore, in this paper, an energy efficient method for Opposition Function -based Chimpanzee Optimization Algorithm (OFCOA) is developed in CRN for energy management as well as resource allocation. The proposed method is a combination of Opposition Function (OF) and Chimpanzee Optimization Algorithm (COA). In COAs, the optimal decision process is enhanced by the use of OF. The proposed method provides energy efficient operation in CRN through energy management taking into account spectrum measurements. The proposed method was tested under four Primary User (PU) and Secondary User (SU) conditions with channel occupation and CRN findings. The proposed methodology is implemented in MATLAB and performance is measured based on performance metrics such as processing power, network life, transmission rate, delay, flush, power consumption and overhead. The performance of the proposed methodology is compared with traditional methods such as Chimpanzee Optimization Algorithm (COA), Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO).

The Event-Triggered Impulsive Controls for Quasisynchronization of the Leader-Following Heterogeneous Dynamical Networks.

The time-triggered impulsive controls were widely used to study the collective behavior of homogeneous dynamical networks due to their low control cost, which was a bit conservative in the occupation of communication channels. This article addresses designing the event-triggered impulsive controls for the quasisynchronization, namely, a weak cooperative behavior with the synchronization error no more than a positive constant in the leader-following heterogeneous dynamical network, which thus can reduce the occupation of resources significantly. The centralized and distributed impulsive controls are designed to lead the followers to synchronize approximately to the leader within a nonzero bound, where the impulsive instants are triggered, respectively, by the global or local state-dependent conditions. Numerical results are put forward to verify the effectiveness of the proposed methods.

Spectrum-Weighted Fusion Cooperative Detection Algorithm Based on Double Thresholds for Underwater Acoustic Networks.

Spectrum-sensing technology is crucial for the development of underwater acoustic communication networks and plays a key role in detecting spectrum holes and channel occupancy. Energy detection technology, as the fundamental spectrum sensing technology in cognitive radio, has reached a mature level of development. Its application in hydroacoustic communications can significantly enhance the utilization of the hydroacoustic spectrum. However, due to the complexity of the hydroacoustic channel compared with that of the radio channel, the traditional double-threshold energy detection technique faces challenges such as fixed threshold values and limited flexibility. To address this, we propose a model for the hydroacoustic channel that incorporates a weight factor based on the signal-to-noise ratio in the algorithm. This allows for adaptive threshold values based on the user's signal-to-noise environment, reducing false detection rates and improving overall detection performance. Through simulation experiments and comparisons, our proposed signal-to-noise weighted collaborative spectrum-sensing technique demonstrates superior detection performance compared with other spectrum-sensing techniques.

Double-mode robust model predictive control of ship dynamic positioning system based on event-triggered mechanism

For the ship dynamic positioning (DP) system with limited communication resources under bounded disturbance, a double-mode robust event-triggered model predictive control (ET-MPC) method is proposed. Initially, the event-triggered mechanism is formulated by surveying the error between the system state and its optimal forecast. The controller only executes optimization when the error attains a certain triggering level. Next, the double-mode MPC control rule is devised according to the constraint conditions of the state equation. The control input is calculated by judging whether the current state information of the system is in the terminal domain. It can not only control the current state of the DP system, but also predict the future state of the system. The proposed ET-MPC method can ensure the robust constancy of the system, the channel occupation between the controller and the actuator is diminished, and the communication load is reduced. Finally, the effectiveness of the proposed control policy is verified by a comparative simulation of the model ship.

Joint congestion and contention avoidance in a scalable QoS-aware opportunistic routing in wireless ad-hoc networks.

Opportunistic routing (OR) can greatly increase transmission reliability and network throughput in wireless ad-hoc networks by taking advantage of the broadcast nature of the wireless medium. However, network congestion is a barrier in the way of OR's performance improvement, and network congestion control is a challenge in OR algorithms, because only the pure physical channel conditions of the links are considered in forwarding decisions. This paper proposes a new method to control network congestion in OR, considering three types of parameters, namely, the backlogged traffic, the traffic flows' Quality of Service (QoS) level, and the channel occupancy rate. Simulation results show that the proposed algorithm outperforms the state-of-the-art algorithms in the context of OR congestion control in terms of average throughput, end-to-end delay, and Packet Delivery Ratio (PDR). Due to the higher PDR at different traffic loads and different node densities, it can be concluded that the proposed algorithm also improves network scalability, which is very desirable given the recent changes in wireless networks.

As predicted and more: modulated channel occupation in YZn5+x.

Like many complex intermetallic phases, the crystal structures of REZn5+x compounds (RE = lanthanide or Group 3 element) based on the EuMg5 type have gradually unfolded. The original reports described a complex hexagonal structure with an unusual combination of tetrahedrally close-packed regions and open spaces, as well as observations of superstructure reflections. More recently, we reinvestigated the structure of YZn5, reclassifying it as the EuMg5+x-type compound YZn5+x (x ≃ 0.2), in which disordered channels run along c through the spaces formerly considered open. In addition, DFT-chemical pressure (DFT-CP) analysis of ordered models of YZn5+x highlighted paths for communication between neighboring channels setting the stage for superstructure formation. Herein, the experimental elucidation of this effect is presented with the synthesis and structure determination of a modulated form of YZn5+x. By slow-cooling samples of YZn5+x from the annealing temperature, crystals were obtained that exhibit satellite reflections with the modulation wavevector q = {1\over 3}a* + {1\over 3}b* + 0.3041c*. Structure solution and refinement using a (3+1)D model in superspace group P31c({1\over 3}\,\!{1\over 3}σ3)00s reveals incommensurate order in the structure's channels. Here, two Zn sites associated with the channels are present, each with discontinuous atomic domains that are slanted in the x3x4 plane. Their slanting corresponds to adjustments along the c axis for the presence or absence of close neighbors along that axis, while the occupation patterns of neighboring channels are shifted by {1\over 3} of the modulation period. These features follow earlier predictions from CP analysis, highlighting how this approach can be used predictively in search of new phenomena.

Edge Computing on IoT for Machine Signal Processing and Fault Diagnosis: A Review

Edge computing is an emerging paradigm that offloads the computations and analytics workloads onto the internet of things (IoT) edge devices to accelerate the computation efficiency, reduce the channel occupation of signal transmission, and reduce the storage and computation workloads on the cloud servers. These distinct merits make it a promising tool for IoT-based machine signal processing and fault diagnosis. This article reviews the edge computing methods in signal processing-based machine fault diagnosis from the aspects of concepts, state-of-the-art methods, case studies, and research prospects. In particular, the light-weight designed algorithms and application-specific hardware platforms of edge computing in the typical fault diagnosis procedures including signal acquisition, signal preprocessing, feature extraction, and pattern recognition are reviewed and discussed in detail. The review provides an insight into the edge computing framework, methods, and applications, so as to meet the requirements of IoT-based machine real-time signal processing, low-latency fault diagnosis, and high-efficient predictive maintenances.

Modulation-Agnostic Spectrum Sensing based on Anomaly detection for Cognitive Radio

This work proposes a Spectrum Sensing (SS) scheme based on a Convolutional Autoencoder (CAE) for application in Cognitive Radio Networks. The channel occupancy is modeled as an anomaly detection problem. The CAE is trained only with noise-signal samples so that any random modulated signal observed in the wireless channel will be regarded as an outlier. The relationship between the detection threshold and the system performance is evaluated. Experiments demonstrate that the SS proposal can identify primary signal presence with better accuracy (high detection and low false alarm rate) than conventional Energy Detection.

Two‐layer modelling of IEEE 802.11x channel occupancy

AbstractLow power IoT communication signals (e.g., Bluetooth and ZigBee) may seriously suffer from the presence of high‐power co‐channel interference like wireless local area network (WLAN) signal. They may effectively avoid WLAN interference by exploiting dynamic characteristics of WLAN traffic. Representing the arrival/departure of WLAN users using an M/M/m/m queueing structure, the characterization of large‐scale dynamics of WLAN channel occupancy is considered. The characterization of small‐scale dynamics of WLAN channel occupancy is also considered by generating WLAN signal using a two‐state semi‐Markovian process. Simulation results show that the proposed model generates WLAN signal having similar statistical characteristics to those of real WLAN signal.

An Improved Proactive Handoff Scheme (IPHS) for Target Channel Selection in Cognitive Radio Network

In recent years, one of the challenges of spectrum allocation and utilization was fixed spectrum allocation which lead to spectrum scarcity and underutilization. In an attempt to address this challenge, Cognitive Radio Network (CRN) which uses Dynamic Spectrum Access (DSA) was proposed. It allows licensed users’ or Primary Users’ (PUs) spectrum to be shared with unlicensed users or Secondary Users (SUs). DSA could be achieved by developing an effective channel selection scheme for SUs spectrum handoff. Selecting an appropriate channel for the SUs to continue their interrupted transmission is a challenging task. Several researchers have used different techniques such as Novel Proactive Handoff Scheme (NPHS) to enhance accurate channel selection for spectrum handoff by considering only channel occupancy. These techniques still suffer some set back like high number of spectrum handoff and delay in channel selection. This paper presents an Improved Proactive Spectrum Handoff Scheme (IPHS) for accurate target channel selection in CRN. The improvement is achieved by considering channel signal quality in addition to channel occupancy as a criteria for the selection of a backup channel for spectrum handoff. Simulation results showed that the IPHS reduced the number of spectrum handoff by 15% and 26% as compared to NPHS and IEEE 802.11 scheme respectively. The average delay was also reduced by 13% and 35% as compared to NPHS and IEEE 802.11 scheme respectively.