Cooperative Cognitive Radio Research Articles

Empirical Mode Decomposition Based Amplify and Forward Technique for Cooperative Cognitive Radio System

The rapid growth in the mobile industry due to increase in number of users accessing diverse services causes a high demand for radio spectrum. Nonetheless, the radio spectrum allocated for different wireless communication services is restricted. Cooperative Cognitive Radio (CCR) technique with Amplify and Forward (AF) relaying protocol used to address the problem suffers from noise amplification resulting in poor reception at the destination. Hence, in this paper, Empirical Mode Decomposition (EMD) based AF technique for CCR system was carried out to improve the performance of the existing CCR with AF relaying protocol. The transmitted signal from Primary User (PU) was received at the Secondary User (SU) where SU superimposed its own signal using Exclusive OR (XOR) rule. The combined signal from XOR was made to pass through EMD and amplified using AF by multiplying with the relay gain. The amplified signal was radiated to PU and SU receivers during the second hop transmission. The multiple copies of the receive signal at the SU receiver at different number of path (L = 2, 4) were combined at destination using Maximal Ratio Combiner (MRC). Mathematical expression for Bit Error Rate (BER) and Throughput (TP) were derived using the Probability Density Function (PDF) of the Nakagami-m fading distribution. Extensive simulations using MATLAB R2021a were employed to assess the effectiveness of the proposed technique and evaluated using BER and TP by comparing with the existing AF CCR. The EMD based AF technique proposed gave better performance with 75.2% reduction in BER and 21.86% increase in TP over the existing AF technique for CCR. The proposed technique can be deployed to improve the performance of cooperative cognitive radio system.

BER Analysis of Underlay Cooperative Cognitive Radio-based NOMA System

Background: The integration of Cooperative Communications (CC), Cognitive Radio (CR) technology, and Non-Orthogonal Multiple Access (NOMA) techniques, termed Cooperative Cognitive Radio used NOMA (CCR-NOMA) systems, has emerged as a promising solution to address spectrum scarcity and connectivity challenges anticipated in sixth generation (6G) networks. Aim: This studyaims to investigate the Bit Error Rate (BER) performance of underlay CCRNOMA systems. Methods: We derive precise closed-form expressions for BER at distant users under perfect and imperfect Channel State Information (CSI) conditions. These mathematical formulations are validated through Monte Carlo simulations. Results: Our results indicate that the near user CU! exhibits superior performance compared to the far user CU!. Additionally, distant users utilizing the CCR-OMA protocol demonstrate better BER performance than those employing the CCR-NOMA protocol. Conclusion: The presence of imperfect CSI adversely affects BER performance. Moreover, the derived closed-form expressions for BER in the investigated system align well with Monte Carlo simulations. These findings provide valuable insights for optimizing the performance of CCR-NOMA systems in real-world scenarios.

Correction to: Radio Resource Allocation Fairness in Cooperative Cognitive Radio Relay Networks

Correction to: Radio Resource Allocation Fairness in Cooperative Cognitive Radio Relay Networks

Radio Resource Allocation Fairness in Cooperative Cognitive Radio Relay Networks

Radio Resource Allocation Fairness in Cooperative Cognitive Radio Relay Networks

Performance Analysis of Spatial Modulation in Cooperative Cognitive Radio Networks with Energy Harvesting

Performance Analysis of Spatial Modulation in Cooperative Cognitive Radio Networks with Energy Harvesting

Enhance the Probability of Detection of Cooperative Spectrum Sensing in Cognitive Radio Networks Using Blockchain Technology

Cognitive radio (CR) is the best way to improve the efficiency of spectrum consumption for wireless multimedia communications. Spectrum sensing, which allows legitimate secondary users (SU) to find vacant bands in the spectrum, plays a vital role in CR networks. When cooperative sensing is used in CR networks, spectrum availability must be taken into account. In many ways, the shared cooperative spectrum sensing (CSS) data among SU. The presence of a malicious user (MU) in the system and sending false sensing data can degrade the performance of cooperative CR. The sharp rise in mobile data traffic causes congestion in the licensed band for the transmission of signals. Handling this security issue in real time, on top of spectrum sharing, is a challenge in such networks. In order to manage the spectrum and identify MU, blockchain-based CSS is developed in this article. To gauge the efficiency of the proposed topology, performance metrics like sensitivity, node selection, throughput measurement, and energy efficiency are used. This work suggests a unique, easier-to-use CSS method with MU suppression that outperforms the current one. According to simulation studies, the suggested topology can increase the likelihood of MU detection by roughly 15% when 40% of system users are malicious.

Covert Communication in Two-Hop Cooperative Cognitive Radio System

Covert Communication in Two-Hop Cooperative Cognitive Radio System

A Game-Theoretic Approach to Achieve Covert Communication in Cognitive Radio Systems

In this paper, we investigate a covert cooperative cognitive radio (CCCR) system, where multiple primary transmitters (PTs) transmit information with the aid of multiple secondary transmitters (STs) in order to conserve power consumption. In return, by opportunistically accessing PT's spectrum, STs send confidential information to a secondary receiver (SR) in the presence of external eavesdropper (Eve). Aiming to maximize covert rate, we model our CCCR framework as an evolutionary game in which each PT and ST make decisions based on their utility histories. By introducing the evolutionary game, we propose a game-oriented secondary user scheduling (G-SUS) scheme to find when multiple STs determine to access PTs' spectrum. Moreover, we analyze covert performance of the proposed scheme and obtain a closed-form expression for Eve's detection error probability. Numerical results show that, the minimal detection error probability at Eve can be effectively impacted by creating channel uncertainty and noise uncertainty. Furthermore, the results also demonstrate the proposed scheme can converge quickly, which stimulates its practical implementation.

협력 인지 무선 네트워크 양자화 비트 수 할당기법의 감지성능분석

협력 인지 무선 네트워크 양자화 비트 수 할당기법의 감지성능분석

SWIPT Enabled Cooperative Cognitive Radio Sensor Network With Non-Linear Power Amplifier

In this work, performance of a simultaneous wireless information and power transfer (SWIPT) enabled cooperative cognitive radio sensor network (CRSN) is explored over generalized Nakagami-m faded channels. A time switching (TS) protocol for SWIPT is used and the impact of TS factor on energy harvesting and information transmission phases, and information processing and broadcasting phases are considered. The cooperative CRSN consists of a pair of primary nodes (PNs) and sensor nodes (SNs), where one of the SWIPT enabled SN provides cooperative relaying for PNs communication by utilizing amplify-and-forward protocol. The overlay spectrum sharing protocol is used at the SN, which supports PNs communication along with its own transmission and resolves the spectrum scarcity issue. The impact of a non-linear power amplifier (NLPA) is also considered on the network performance. The analytical expressions of outage probability (OP), asymptotic OP, system throughput, and energy efficiency are obtained over Nakagami-m faded channels for arbitrary m. Further, the analytical expressions of ergodic capacity (EC) and asymptotic EC are obtained. The impact of NLPA and other system parameters on the performance of the considered network are highlighted. Finally, the obtained analytical expressions are validated through Monte-Carlo simulations.

Secure Resource Allocations for Polarization-Enabled Multiple-Access Cooperative Cognitive Radio Networks With Energy Harvesting Capability

We address secure communications over energy-harvesting based orthogonal frequency-division multiple-access (OFDMA) cooperative cognitive radio networks, where one primary user (PU) cooperates with several size-limited secondary users (SUs) in terms of both information transmission and energy harvesting. To improve spectrum utilization and ensure that SU transmitters can harvest as much energy as possible, we let the size-limited SUs be equipped with orthogonally dual-polarized antennas (ODPAs). Based on these setting-ups, we propose the polarization-enabled two-phase cooperative framework, where SU transmitters first apply the power splitting technique to harvest energy from radio frequency (RF) signals radiated by the PU, and then use the harvested energy to concurrently transmit their own and the PU’s data over the same subcarriers. Under our proposed framework, we develop three secure resource allocation schemes for scenarios when SUs are untrusted users, which implies that each SU may overhear the PU’s and the other SUs’ confidential information. For these scenarios, which has hardly been studied, we jointly optimize the allocation of relays, subcarriers, power splitting ratios, and powers when SUs adopt the decode-and-forward (DF) strategy or the amplify-and-forward (AF) strategy to relay the PU’s information, with the objective to maximize the total secrecy rate of all SUs while guaranteeing the PU’s minimum secrecy rate. Finally, we validate and evaluate our proposed cooperative framework and secure resource allocation schemes through numerical analyses.

Precise cooperative sulfur placement leads to semi-crystallinity and selective depolymerisability in CS2/oxetane copolymers

CS2 promises easy access to degradable sulfur-rich polymers and insights into how main-group derivatisation affects polymer formation and properties, though its ring-opening copolymerisation is plagued by low linkage selectivity and small-molecule by-products. We demonstrate that a cooperative Cr(III)/K catalyst selectively delivers poly(dithiocarbonates) from CS2 and oxetanes while state-of-the-art strategies produce linkage scrambled polymers and heterocyclic by-products. The formal introduction of sulfur centres into the parent polycarbonates results in a net shift of the polymerisation equilibrium towards, and therefore facilitating, depolymerisation. During copolymerisation however, the catalyst enables near quantitative generation of the metastable polymers in high sequence selectivity by limiting the lifetime of alkoxide intermediates. Furthermore, linkage selectivity is key to obtain semi-crystalline materials that can be moulded into self-standing objects as well as to enable chemoselective depolymerisation into cyclic dithiocarbonates which can themselves serve as monomers in ring-opening polymerisation. Our report demonstrates the potential of cooperative catalysis to produce previously inaccessible main-group rich materials with beneficial chemical and physical properties.

Security Energy Efficiency Analysis of CR-NOMA Enabled IoT Systems for Edge-cloud Environment

With the development of the Internet of Things (IoT), more and more devices are connected in edge-cloud environment, and spectrum scarcity has become a major bottleneck for the employment of IoT devices in the end side of cloud computing. In addition, due to the broadcast nature of RF link, the potential eavesdropper may be presented in the wireless environment. To improve spectrum efficiency (SE) and ensure safe transmission of the users, in this paper, the two-way relay cooperative Cognitive Radio Non-Orthogonal Multiple Access (CR-NOMA) with massive multiple-in multiple-out (MIMO) is proposed. Our objective is to maximize the security energy efficiency (SEE) of the cognitive system subject to the quality of service (QoS) of users. Specifically, the multi-objective optimization problem is decomposed into three subproblems, i.e., the optimization of transmit power, power allocation, and antenna selection, respectively. The Lagrange dual algorithm based on the first-order Taylor series expansion function is proposed to solve the non-convex problem. Moreover, a novel orthogonal antenna selection algorithm is proposed to decrease the cost of radio frequency chains and limit the interference to the primary user. The simulation results show that the proposed scheme has significant performance gain on SEE. It can effectively increase the number of access for cloud computing edge IoT users. In addition, due to the impact of correlation between the antennas, as the number of relay antennas increases, the SEE converges to a specific value, which exists the optimal number of antenna.

Security design for integrated communication and computation networks through cooperative cognitive radios

AbstractIn this letter, a novel integrated communication and computation framework is proposed through cooperative cognitive radios, which includes a communication primary network (PN) and a computing secondary network. Specifically, two primary communication users intend to exchange their confidential information with the relay assistance of cognitive access point (CAP), meanwhile, multiple sensors share the spectrum of PN to transmit their concurrent sensing data to CAP. The CAP is assumed to be a potential eavesdropper and to ensure the secure communication of primary users (PUs) and computational performance of the CAP, it is proposed to maximize the sum achievable secrecy rate of PUs by jointly designing the transmit precoding, relay beamforming matrix, transmit scaling factors and aggregation beamforming vector, while satisfying the constraint of the computational mean square error of the CAP. A weighted minimum mean square error (WMMSE)‐based block coordinate descent (BCD) algorithm is developed to solve the formulated problem, and simulation results are provided to validate the effectiveness of our proposed schemes.

Ensemble Learning Aided QPSO-Based Framework for Secrecy Energy Efficiency in FD CR-NOMA Systems

Cognitive radio (CR), non-orthogonal multiple access (NOMA), and full-duplex (FD) communications have been considered key technologies for providing spectrum utilization improvement and higher energy efficiency on the internet of things (IoT) networks and next-generation communication. However, security concerns are still an issue to be addressed because confidential information is exposed in wireless systems. To solve this problem, we design a novel artificial intelligence (AI)-based framework for maximizing the secrecy energy efficiency (SEE) in FD cooperative relay underlay CR-NOMA systems that are exposed to multiple eavesdroppers. First, we formulate the non-convex SEE optimization problem as bi-level optimization, subject to constraints that satisfy the quality-of-service requirements of secondary users. In particular, the outer problem is solved with ensemble learning (EL) to select the optimal relay. Regarding the inner problem, we propose a quantum particle swarm optimization (QPSO)-based technique to optimize power allocation. In addition, for comparison purposes, we describe a cooperative relay CR network with orthogonal multiple access (OMA), rate-splitting multiple access (RSMA), and half-duplex technologies. Moreover, we evaluate comparative schemes based on machine learning algorithms and swarm intelligence baseline schemes. Furthermore, the proposed EL-aided QPSO-based framework achieves performance close to the optimal solutions, with a meaningful reduction in computation complexity.

Total Throughput Capacity Maximization in Cooperative Cognitive Radio Relay Networks

Total Throughput Capacity Maximization in Cooperative Cognitive Radio Relay Networks

User Scheduling Design for Covert Communication in Cooperative Cognitive Radio System

In this article, we investigate the covert communication for a cooperative cognitive radio (CCR) system, where the secondary transmitters (STs) help the primary transmitter (PT) to transmit information while covertly transmitting their own information to the secondary receiver (SR) against the warden of PT. In particular, the different ST scheduling schemes are proposed for covert communications, namely, covert rate maximization (CRM), best channel gain (BCG), and fairness oriented (FO). The closed-form expression is derived for the expected detection error probability at the warden PT. Based on that, we, respectively, analyze the covert rate and covert outage probability (COP) of the proposed ST scheduling schemes. The simulation results show that, under the both effects of channel uncertainty and noise uncertainty, the CRM scheme achieves the best covert rate performance, and the BCG and FO schemes ensure the quality of service (QoS) and the STs’ fairness as the cost of covert performance degraded.

Performance Optimization for Decode and Forward Cooperative Cognitive Radio Networks

This paper considers the problem of optimizing the data rate of the cooperative cognitive system subject to the dual constraints of the interference threshold of primary users and power budget of secondary users. In particular, under a single constraint, the rate can reach its peak easily. But under the double restrictions, the peak rate problem becomes complicated and changeable. According to different interference conditions and power supplies, four scenarios are formulated: total interference threshold and total power budget, total interference threshold and separate power budget, separate interference threshold and total power budget, and separate interference threshold and separate power budget. Each scenario needs to be further divided into many situations for discussion due to the sheer particularity. Through careful comparison and classification, we summarize and formulate each situation one by one to achieve the optimal value of the rate. Extensive simulation results demonstrate that the proposed resource allocation policy represents the best compromise between enhancing the rate of the secondary users and satisfying the interference threshold requirements of the primary users.

Secrecy Rate Maximization for Multicarrier-Based Cognitive Radio Networks With an Energy Harvesting Jammer

Cognitive radio (CR) is becoming an increasingly significant component of Internet-of-Things technologies because it overcomes the challenge of spectrum resource scarcity for wireless communications. For the cooperative CR network (CRN) based on the multicarrier system, this article investigates the physical layer security (PLS) to guarantee information privacy for the secondary network while guaranteeing the quality of service (QoS) of the primary network. First, we propose one communication scheme for this type of CRN. The secondary transmitter (ST) and secondary jammer (SJ) first harvest RF energy from the primary signal transmitted by the primary transmitter (PT). Then, ST transmits confidential information with the spectrum vacated by the primary network to the secondary receiver (SR), and SJ simultaneously generates the jamming signal to interfere with the eavesdropper (ED). Second, for the scenarios with the instantaneous channel state information (CSI) and the statistical CSI of the ED, respectively, we aim to maximize the secrecy rate of the secondary network while guaranteeing the QoS requirement of the primary network by jointly optimizing the time allocation between the two phases and the transmit power allocation for ST and SJ over subcarriers. For each scenario, the secrecy rate maximization is formulated as the nonconvex optimization problem. Finally, we design efficient algorithms for both two nonconvex problems. The optimal time allocation is obtained by the 1-D search method at the outer layer, and the optimal transmit power allocation is obtained by the difference of concave (DC) programming at the inner layer, where the Lagrange duality method is used to solve the convex approximation problem. Simulation results verify that the proposed scheme essentially improves the secrecy rate of the secondary network compared to benchmark schemes.

Throughput analysis in censoring‐based cooperative cognitive radio network with energy harvesting

SummaryAn energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.