Cognitive Transmission Research Articles

Dynamic human error risk assessment of group decision-making in extreme cooperative scenario

For groups in extreme environments, their reliability requirements in complex operational systems are high due to isolation from society, physical constraints for extended periods of time, and exposure to significant hazards. This study attempts to solve the problem of dynamic quantitative risk analysis of decision-making process for extreme group during complex cooperative scenarios. Based on an extended IDA team cognitive model, typical failure modes and performance quantification mechanisms of team communication were analyzed. The performance curve was utilized to distinctively model the cognitive behaviors of operators within the team, driving the cognitive transmission paths of group decision-making in a hybrid event tree. Error calibration of human error due to time uncertainty was conducted. The steps and techniques for dynamic risk analysis of decision-making of extreme groups under complex, dynamic, and ambiguous scenarios were summarized. The proposed method was validated through simulation in a typical powered diving task of manned submarine.

Security and Reliability Tradeoff of UAV Relays Assisted Cognitive Transmissions With Hardware Impairments

Security and Reliability Tradeoff of UAV Relays Assisted Cognitive Transmissions With Hardware Impairments

Jointly Active/Passive Beamforming Optimization for Intelligent-Reflecting Surface-Assisted Cognitive-IoT Networks

To overcome challenges such as limited energy availability for terminal devices, constrained network coverage, and suboptimal spectrum resource utilization, with the overarching objective of establishing a sustainable and efficient interconnection infrastructure, we introduce an innovative Intelligent Reflective Surface (IRS) technology. This cutting-edge IRS technology is employed to architect a wireless and energy-efficient cognitive secure communication network assisted by IRS. To further optimize the overall energy harvesting of this network, we present a cognitive secure resource allocation scheme, aiming to maximize the system’s total collected energy. This scheme carefully considers various constraints, including transmission power constraints for cognitive base stations, power constraints for jammer devices, interference limitations for all primary users, minimum security rate constraints for all cognitive Internet of Things (IoT) devices, and phase shift constraints for IRS. We establish a comprehensive hybrid cognitive secure resource allocation model, encompassing joint cognitive transmission beam design, jammer device transmission beam design, and phase shift design. Given the non-convex nature of the formulated problem and the intricate coupling relationships among variables, we devise an effective block coordinate descent (BCD) iterative algorithm. The realization of joint cognitive/jammer base station transmission beam design and phase shift design employs sophisticated techniques such as continuous convex approximation methods and semi-definite programming. Simulation results underscore the superior performance of the proposed scheme compared to existing resource allocation approaches, particularly in terms of total harvested energy and other critical metrics.

Securing Multiuser Underlay Cognitive Transmissions With Hardware Impairments and Channel Estimation Errors

Securing Multiuser Underlay Cognitive Transmissions With Hardware Impairments and Channel Estimation Errors

Shannon meets Stackelberg on the cognitive interference channel part I: A deterministic view

AbstractIn this paper, we have combined a game‐theoretic and an information‐theoretic notions to describe the selfish behavior of each user in a two‐user linear deterministic cognitive interference channel (LD‐CIC). The two‐user LD‐CIC is the simple case of the cognitive radio technology in the high SNR regime. This model is a solution to improve the spectral efficiency in software defined network (SDN) concept in 5G. In the two‐user LD‐CIC, the information bits of the primary/licensed transmitter is a‐priori provided at the cognitive/secondary/unlicensed transmitter. So that, the cognitive transmitter can cooperate and utilize the frequency spectrum to send the information bits of the both transmitters. In information‐theoretic approaches, full cooperation is assumed between transmitters for codebook and rate selection in this channel. This may not be a realistic assumption if transmitters are selfish and are willing to maximize their own benefit. In particular, we have defined the Stackelberg equilibrium (SE) region on the capacity region of the two‐user LD‐CIC to capture the behavior of each transmitter when they compete even though one of them is informed of the other transmitter information bits. We have implemented a two‐phase Stackelberg game with the primary and cognitive transmitters acting as the leader in the first phase, and the follower in the second phase, respectively. In this implementation, both transmitters are assumed to be selfish and only interested in optimizing their own pay‐offs. The SE region is characterized as a subset of capacity region in which the transmitters cannot gain more transmission rate by individually deviating from the SE strategy. The achievability of the resultant region has been configured using a randomized Han‐Kobayashi scheme for all the channel gains. Also, we have compared the obtained SE region with the previous equilibrium regions such as Nash equilibrium (NE) region of the linear deterministic interference channel (LD‐IC). The results have shown that the SE points on the sum‐rate of the LD‐CIC capacity region are more than the NE points on the sum rate of the capacity region of LD‐IC, so the SE region of the LD‐CIC is Pareto superior to the NE region of LD‐IC.

Aberrant hippocampal transmission and behavior in mice with a stargazin mutation linked to intellectual disability

Mutations linked to neurodevelopmental disorders, such as intellectual disability (ID), are frequently found in genes that encode for proteins of the excitatory synapse. Transmembrane AMPA receptor regulatory proteins (TARPs) are AMPA receptor auxiliary proteins that regulate crucial aspects of receptor function. Here, we investigate a mutant form of the TARP family member stargazin, described in an ID patient. Molecular dynamics analyses predicted that the ID-associated stargazin variant, V143L, weakens the overall interface of the AMPAR:stargazin complex and impairs the stability of the complex. Knock-in mice harboring the V143L stargazin mutation manifest cognitive and social deficits and hippocampal synaptic transmission defects, resembling phenotypes displayed by ID patients. In the hippocampus of stargazin V143L mice, CA1 neurons show impaired spine maturation, abnormal synaptic transmission and long-term potentiation specifically in basal dendrites, and synaptic ultrastructural alterations. These data suggest a causal role for mutated stargazin in the pathogenesis of ID and unveil a new role for stargazin in the development and function of hippocampal synapses.

Comparing Adversary Defense Mechanisms in Cognitive Radio Networks

BACKGROUND: In a cognitive radio network, the cognitive transmitter senses the medium to detect spectrum opportunities and transmits its own data if the channel is sensed to be idle. A jammer can also sense the medium and identify the slots of successful transmission. The jammer’s main objective is to reduce the throughput of the cognitive transmitter. METHODS: Towards this objective, the jammer builds a deep learning classifier in which the most recent sensing results of acknowledgments (ACKs) sent by the receiver are used to predict the slots of successful transmissions of the cognitive transmitter. This allows the attacker to reliably predict the successful transmissions and can effectively jam these transmissions. The deep learning classification soft decision probabilities are used by the jammer for power control subject to a certain power budget. A receiver-based defense mechanism is developed against the jamming attacks. The receiver purposely takes some wrong actions, i.e., sends ACK when transmission is not successful and vice versa, to poison the training process of the attacker. Results: We show that our receiver’s defense mechanism effectively enhances the throughput of the cognitive transmitter when compared to the transmitter’s defense mechanism, where the transmitter takes some wrong decisions when it accesses the medium. CONCLUSION: A novel defense mechanism against jamming attacks in cognitive radio networks is introduced.

Security-aware spectrum sharing for NOMA in cognitive radio networks with discrete-time energy harvesting

In this paper, we propose a security-aware spectrum sharing scheme for wireless-powered cognitive radio networks (CRNs) with non-orthogonal multiple access (NOMA). In this system, a primary transmitter (PT) intends to send confidential signal to a primary receiver (PR) by assisting of a secondary transmitter (ST), while there is a potential eavesdropper (PE) within the scope of PR. It is assume that ST has no fixed energy supply but the NOMA cognitive transmission can be performed after harvesting sufficient radio frequency (RF) energy. To ensure that PT’s confidential signal is safety, PR will be equipped with two antennas and operating in full-duplex mode, so that while ST is performing cognitive transmission, one of the antennas sends artificial noise (AN) from PR to interfere the signal receiving of PE. According to whether the accumulated energy of ST is sufficient and whether ST can correctly decode the PT’s signal, the system can operate in three modes. Since ST needs to accumulate enough energy through several continuous transmission slots, the charging and discharging processes of the battery in the ST can be simulated as a discrete-time Markov chain. Based on these, we derive exact expressions of outage probabilities of the primary and secondary systems, then an approximate formula of secrecy outage probability (SOP) of primary system is also derived. In addition, in order to further improve the transmission performance of the system, optimal power allocation factor and power level of AN are obtained by maximizing the secrecy rate of the primary system, while guaranteeing the system energy efficiency. Compared with zero-forcing (ZF) technique, the proposed secure spectrum sharing scheme has a slight disadvantage in secrecy energy efficiency, but it is simple to deploy, low cost, and achieves a better secrecy rate, which can be applied for a variety of application scenarios.

Analysis of Dynamic Interference Constraints in Cognitive Radio Cloud Networks

To analyze the security performance of a cloud network integrated with a cognitive radio. Cognitive Radio Cloud Network (CRCN) have a resilient potential for dynamic operation for energy saving. Integrating this Cognitive Radio Network (CRN) along with that of a cloud network produces great network exposure, spectrum usage and reduced power consumption. The problem arises for secure transmission and safe storage of huge amount of data in the cloud-based Cognitive Radio (CR) network. This paper, shows a study on preventing the CRCN from some advanced jamming techniques. An adversarial machine learning approach is introduced to launch jamming attacks on wireless communications and a defense strategy is presented. A cognitive transmitter uses a pre-trained classifier to predict the current channel status based on recent sensing results and decides whether to transmit or not, and then uses a Generative Adversarial Network (GAN), for generating synthetic data or false data, thus misleading the jammer to sense false data. The transmitter systematically selects when to take wrong actions and adapts the level of defense to mislead the jammer into making prediction errors and consequently increase its throughput. And to use the conventional cryptographic protocols for protecting the stored database in the cloud network from unauthorized users.

Bayesian Optimization for Nonlinear System Identification and Pre-Distortion in Cognitive Transmitters

We present a digital signal processing (DSP) scheme that performs hyperparameter tuning (HT) via Bayesian optimization (BO) to autonomously optimize memory tap distribution of Volterra series and adapt parameters used in the synthetization of a digital pre-distortion (DPD) filter for optical transmitters. Besides providing a time-efficient technique, this work demonstrates that the self-adaptation of DPD hyperparameters to correct the component-induced nonlinear distortions as different driver amplifier (DA) gains, symbol rates and modulation formats are used, leads to an improvement in transmitter performance. The scheme has been validated in back-to-back (b2b) experiments using dual-polarization (DP) 64 and 256 quadrature amplitude modulation (QAM) formats, and symbol rates of 64 and 80 GBd. For DP-64QAM at 64 GBd, it is shown that the DPD scheme reduces the required optical signal-to-noise ratio (OSNR) at a bit error ratio of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> by 0.9 dB and 0.6 dB with respect to linear DPD and a heuristic nonlinear DPD approach, respectively. Moreover, we show that the proposed approach also reduces filter complexity by 75% in conjunction with the use of memory polynomials (MP), while achieving a similar performance to Volterra pre-distortion filters.

Exploring latent states of problem‐solving competence using hidden Markov model on process data

AbstractThe response process of problem‐solving items contains rich information about respondents' behaviours and cognitive process in the digital tasks, while the information extraction is a big challenge. The aim of the study is to use a data‐driven approach to explore the latent states and state transitions underlying problem‐solving process to reflect test‐takers' behavioural patterns, and to investigate how these states and state transitions could be associated with test‐takers' performance. We employed the Hidden Markov Modelling approach to identify test takers' hidden states during the problem‐solving process and compared the frequency of states and/or state transitions between different performance groups. We conducted comparable studies in two problem‐solving items with a focus on the US sample that was collected in PIAAC 2012, and examined the correlation between those frequencies from two items. Latent states and transitions between them underlying the problem‐solving process were identified and found significantly different by performance groups. The groups with correct responses in both items were found more engaged in tasks and more often to use efficient tools to solve problems, while the group with incorrect responses was found more likely to use shorter action sequences and exhibit hesitative behaviours. Consistent behavioural patterns were identified across items. This study demonstrates the value of data‐driven based HMM approach to better understand respondents' behavioural patterns and cognitive transmissions underneath the observable action sequences in complex problem‐solving tasks.

Research on cognitive signal waveform technology based on artificial intelligence algorithm

With the continuous development of communication measurement and control technology, the communication environment is increasingly complex and changeable, and the traditional communication technology has been unable to meet people’s communication needs. The proposal of cognitive dynamic system (CDS) provides a new direction for the development of wireless communication technology. At present, the two main application directions of cognitive system are cognitive radio (CR) and cognitive radar (CR)[1][2]. Considering the innovative combination of cognitive system and TT& C communication scene, this paper studies the cognitive transmission performance under various environmental noises based on chirp signal, and uses BP neural network to optimize the system performance. The simulation results show that the adaptive waveform technology can improve the anti-jamming ability, and the BP algorithm has good prediction effect and reduces the computational complexity of the system.

Метафора в структуре познания сложности

The paper presents a review of modern philosophical and methodological literature on exploring complexity. The research featured the effect of metaphor in the cognitive processes, research communication, and transmission of complex ideas. The author developed a classification of metaphors in the context of exploring complexity. The approach is based on the identification of a certain ontological and epistemic content of the metaphor. The contextual role of the metaphor in cognition processes depends on these aspects of its content. The author analyzed the groups of metaphors associated with such topics of exploring complexity as self-organization, ecology, and dialogue. The metaphors proved important in developing a complex vision of the relationship between the cognizer and the world. The study also examined the axiological aspects of the metaphors, as well as the connection between the metaphor and the new vision of rationality, typical of the philosophical reflection of complexity. The metaphor proved to have a heuristic, communicative, and organizational potential in conditions of methodological uncertainty. The context of philosophical and theoretical-methodological reflection of complexity makes it possible to study the metaphor in order to identify the existing models of exploring complexity and their cognitive stylistics.

Impact of Artificial Noise on Security Capability of Energy Harvesting Overlay Networks

Artificial noise, energy harvesting, and overlay communications can assure design metrics of modern wireless networks such as data security, energy efficiency, and spectrum utilization efficiency. This paper studies impact of artificial noise on security capability of energy harvesting overlay networks in which the cognitive transmitter capable of self‐powering its operation by harvesting radio frequency energy and self‐securing its communications against eavesdroppers by generating artificial noise amplifies and forwards the signal of the primary transmitter as well as transmits its individual signal concurrently. To quantify this impact, the current paper firstly suggests accurate expressions of crucial security performance indicators. Then, computer simulations are supplied to corroborate these expressions. Finally, numerous results are demonstrated to expose insights into this impact from which optimum specifications are determined. Notably, primary/cognitive communications can be secured at distinct degrees by flexibly controlling multiple specifications of the suggested system model.

Full-Duplex Non-Orthogonal Multiple Access Cooperative Spectrum-Sharing Networks With Non-Linear Energy Harvesting

In this paper, we analyze the performance of a non-orthogonal multiple access (NOMA) cognitive relay system, where a multi-antenna full-duplex cognitive transmitter employs NOMA concept to assist the transmission from a wireless-powered primary transmitter to its corresponding receiver, while simultaneously communicating with a cognitive receiver. A practical non-linear energy harvesting (EH) model, which taking into account harvester's sensitivity and saturation effects is considered. We propose an optimum beamforming design at the cognitive transmitter such that the rate of cognitive network is maximized, under a constraint that the rate of the primary network is above a certain threshold. Results show that proposed optimization framework can substantially enlarge the rate region toward both primary and secondary networks. Furthermore, in order to characterize the network delay-constrained throughput, tractable outage probability expressions for primary and secondary networks assuming sub-optimum zero-forcing based beamforming scheme are derived. Our results reveal that due to required minimum power for harvesting operation as well as saturation of the harvested power at high transmit power levels, conventional linear EH model may lead to performance mismatches for practical non-linear EH circuits in both low and high transmit power regimes.

Achievable rates of Gaussian cognitive interference channel with common interference

This study considers the Gaussian cognitive interference channel (IC), in which one of the two users operates in cognitive mode. In addition, to transmit its signal, the cognitive sender can cooperatively forward the primary signal to its destination, the primary receiver. Moreover, the transmission over this IC also experiences interference from a third source, which is commonly known as the common interferer source. To reduce the effect of both the primary signal and the common interference signal at the secondary destination, both the cognitive transmitter and its destination may have noisy complete (non-causal) or partial (causal) knowledge of these signals. For this channel model, the achievable rate region is computed in which the availability of both the primary signal and the common interference signal at the cognitive transmitter and its destination can be (i) noisy non-causal and (ii) causally estimated. The authors numerical results confirm that knowing both the primary signal and the common interference signal can significantly increase the achievable rate region. Indeed, the obtained achievable rate region is larger than the available bounds in the literature. Furthermore, representative numerical examples are also shown to demonstrate the value of the power allocation at the cognitive source.

Secrecy analysis of multiple‐input multiple‐output underlay cognitive radio networks with energy harvesting

AbstractThe cognitive radio (CR) technique is an encouraging approach to deal with spectrum scarcity in wireless networks. However, this technique raises the issues of secrecy and privacy in the CR network. In this work, a multiple‐input multiple‐output underlay CR network is considered, which consists of a primary network, a secondary network, and an eavesdropper. All the primary, secondary as well aseavesdropper's nodes are assumed to have multiple antennas with radio frequency energy harvesters to enhance their spectral and energy efficiency properties. The eavesdropper node manipulates it's simultaneous wireless information and power transfer architecture in a pursuit to intercept the secure communication between the cognitive transmitter and the cognitive receiver. This technique and considered network are combined with the traditional selection combining (SC) and maximal ratio combining (MRC) scheme and the results are compared. The Monte Carlo simulation is done for the validation of results. The main aim is to drive the closed‐form analytical expression for exact and asymptotic secrecy outage probability. The present results show that the SC scheme at eavesdropper provides better secrecy in comparison to the MRC technique and also the number of antennas affects the secrecy of the system. Moreover, the impact of power splitter is considered and also the optimal value of power splitter is derived to maximize information decoding.

Censoring-Based Relay Transmission for Achieving Energy Efficiency in Cognitive Radio Networks

Energy efficiency (EE) is critical to achieve cooperative sensing and transmission in relay-assisted cognitive radio networks (CRNs) with limited battery capacity. This paper proposes an energy-efficient cooperative transmission strategy with combined censoring report and spatial diversity in cooperative process, namely, censoring-based relay transmission (CRT). Specifically, secondary relays (SRs) take part in cooperative sensing with differential censoring to reduce energy consumption, and the best SR assists secondary transmission to enhance communication quality in transmission stage and thus to improve secondary transmission EE. First, we derived generalized-form expressions for detection probability, reporting probability, sensing energy, and expected throughput for CRT. Second, we investigate a mean EE-oriented maximization nonconvex problem by joint optimizing sensing duration and power allocation for secondary users under secondary outage probability and sensing performance constraints. With the aid of Jensen’s inequality, an efficient cross-iteration algorithm with low complexity is proposed to obtain the suboptimal solutions, which is developed by golden segmentation search method. Finally, extensive simulations are conducted to evaluate the performance of CRT. The results show significant improvements of SUs’ EE compared with traditional noncooperation single cognitive transmission schemes, which demonstrate the benefits of our proposed cooperative strategy in conserving energy for secondary transmission.

A Novel Idea of Implementing Birth-Death Process to Model SU Transmission in CRN Over MPC

This article proposes a solution to address spectrum scarcity matter by providing birth-death process dealing with a secondary user (SU) transmission over multiple primary channels (MPC) in a cognitive radio network (CRN). By taking advantage of the under-use of spectrum resources of licensed users, CR systems can develop the use of radio spectrum efficiently. The SU must remain in the interweaving performance process and find spectrum gaps before transmission. Furthermore, both expected slots and transmission slots comprise the extended delivery time (EDT) for the secondary user. In order to model the cognitive transmission of the SU on MPC, especially the author has made a birth-death model. This strategy is referred to as an accurate probability density function (PDF) and probability mass function (PMF) of EDT of the secondary transmission for both continuous and periodic sensing cases. In this research, the author also represents numerical and simulation results to demonstrate analysis and mathematical expression.

Optimal Sensing and Transmission of Energy Efficient Cognitive Radio Networks

The issue of spectrum scarcity can be alleviated by the cognitive radio technology with efficient spectrum sensing and allocation of free spectrum bands. In Cognitive Radio Networks energy efficiency improvement is the state of art now days. This paper considers the case of primary user protection from cognitive user transmission to optimize the energy efficiency. The parameters of optimal design problem are sensing, transmission time and transmission power. A Sub Optimal Iterative Search Algorithm is proposed to maximize efficiency by optimizing sensing time and transmitting time. Simulation results exhibits substantial improvement in energy efficiency compared to the recent algorithms.