This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio network.The threshold identification method is implemented in the received signal at the second...This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio network.The threshold identification method is implemented in the received signal at the secondary user based on the square law.The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing.Additionally,the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems.In the dynamic threshold,the signal ratio-based threshold is fixed.The threshold is computed by considering the Modified Black Widow Optimization Algorithm(MBWO).So,the proposed methodology is a combination of dynamic threshold detection and MBWO.The general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user signal.These limitations undermine the sensing accuracy of the energy identification technique.Hence,the ETBED technique is developed to enhance the energy efficiency of cognitive radio networks.The projected approach is executed and analyzed with performance and comparison analysis.The proposed method is contrasted with the conventional techniques of theWhale Optimization Algorithm(WOA)and GreyWolf Optimization(GWO).It indicated superior results,achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8,outperforming conventional techniques.展开更多
Cognitive Radio Networks(CRNs)have become a successful platform in recent years for a diverse range of future systems,in particularly,industrial internet of things(IIoT)applications.In order to provide an efficient co...Cognitive Radio Networks(CRNs)have become a successful platform in recent years for a diverse range of future systems,in particularly,industrial internet of things(IIoT)applications.In order to provide an efficient connection among IIoT devices,CRNs enhance spectrum utilization by using licensed spectrum.However,the routing protocol in these networks is considered one of the main problems due to node mobility and time-variant channel selection.Specifically,the channel selection for routing protocol is indispensable in CRNs to provide an adequate adaptation to the Primary User(PU)activity and create a robust routing path.This study aims to construct a robust routing path by minimizing PU interference and routing delay to maximize throughput within the IIoT domain.Thus,a generic routing framework from a cross-layer perspective is investigated that intends to share the information resources by exploiting a recently proposed method,namely,Channel Availability Probability.Moreover,a novel cross-layer-oriented routing protocol is proposed by using a time-variant channel estimation technique.This protocol combines lower layer(Physical layer and Data Link layer)sensing that is derived from the channel estimation model.Also,it periodically updates and stores the routing table for optimal route decision-making.Moreover,in order to achieve higher throughput and lower delay,a new routing metric is presented.To evaluate the performance of the proposed protocol,network simulations have been conducted and also compared to the widely used routing protocols,as a benchmark.The simulation results of different routing scenarios demonstrate that our proposed solution outperforms the existing protocols in terms of the standard network performance metrics involving packet delivery ratio(with an improved margin of around 5–20%approximately)under varying numbers of PUs and cognitive users in Mobile Cognitive Radio Networks(MCRNs).Moreover,the cross-layer routing protocol successfully achieves high routing performance in finding a robust route,selecting the high channel stability,and reducing the probability of PU interference for continued communication.展开更多
Intelligent reflecting surface(IRS)is widely recognized as a promising technique to enhance the system perfor-mance,and thus is a hot research topic in future wireless communications.In this context,this paper propose...Intelligent reflecting surface(IRS)is widely recognized as a promising technique to enhance the system perfor-mance,and thus is a hot research topic in future wireless communications.In this context,this paper proposes a robust BF scheme to improve the spectrum and energy harvesting efficiencies for the IRS-aided simultaneous wireless information and power transfer(SWIPT)in a cognitive radio network(CRN).Here,the base station(BS)utilizes spectrum assigned to the primary users(PUs)to simultaneously serve multiple energy receivers(ERs)and information receivers(IRs)through IRS-aided multicast technology.In particular,by assuming that only the imperfect channel state information(CSI)is available,we first formulate a constrained problem to maximize the minimal achievable rate of IRs,while satisfying the harvesting energy threshold of ERs,the quality-of-service requirement of IRs,the interference threshold of PUs and transmit power budget of BS.To address the non-convex problem,we then adopt triangle inequality to deal with the channel uncertainty,and propose a low-complexity algorithm combining alternating direction method of multipliers(ADMM)with alternating optimi-zation(AO)to jointly optimize the active and passive beamformers for the BS and IRS,respectively.Finally,our simulation results confirm the effectiveness of the proposed BF scheme and also provide useful insights into the importance of introducing IRS into the CRN with SWIPT.展开更多
This paper investigates the effects of the outdated channel state information(CSI)on the secrecy performance of an underlay spectrum sharing cognitive radio networks(CRNs),where the secondary user(SU)source node(Alice...This paper investigates the effects of the outdated channel state information(CSI)on the secrecy performance of an underlay spectrum sharing cognitive radio networks(CRNs),where the secondary user(SU)source node(Alice)aims to transmit the trusted messages to the full-duplex(FD)aided SU receiver(Bob)with the assistance of cooperative relay(Relay).Considering the impact of feedback delay,outdated CSI will aggravate the system performance.To tackle such challenge,the collaborative zero-forcing beamforming(ZFB)scheme of FD technique is further introduced to implement jamming so as to confuse the eavesdropping and improve the security performance of the system.Under such setup,the exact and asymptotic expressions of the secrecy outage probability(SOP)under the outdated CSI case are derived,respectively.The results reveal that i)the outdated CSI of the SU transmission channel will decrease the diversity gain from min(NANR,NRNB)to NRwith NA,NRand NBbeing the number of antennas of Alice,Relay and Bob,respectively,ii)the introduction of FD technique can improve coding gain and enhance system performance.展开更多
In cognitive radio networks(CoR),the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability.Several optimization methods are usually used to ...In cognitive radio networks(CoR),the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability.Several optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold selection.However,these methods do not take into account the effect of sample size and its effect on improving CoR performance.In general,a large sample size results in more reliable detection,but takes longer sensing time and increases complexity.Thus,the locally sensed sample size is an optimization problem.Therefore,optimizing the local sample size for each cognitive user helps to improve CoR performance.In this study,two new methods are proposed to find the optimum sample size to achieve objective-based improved(single/double)threshold energy detection,these methods are the optimum sample size N^(*)and neural networks(NN)optimization.Through the evaluation,it was found that the proposed methods outperform the traditional sample size selection in terms of the total error rate,detection probability,and throughput.展开更多
In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promisingapproach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio(SNR), ther...In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promisingapproach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio(SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambientRadio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum forthe transmission of data without loss or without collision at a specific time. In this paper, the authors proposed anovel Spectrum Sensing (SS) detection technique in the Cognitive Radio (CR) spectrum, by developing the AmBC.Novel Matched Filter Detection with Inverse covariance (MFDI), Cyclostationary Feature Detection with Inversecovariance (CFDI) and Hybrid Filter Detection with Inverse covariance (HFDI) approaches are used with AmBCto detect the presence of users at low power levels. The performance of the three detection techniques is measuredusing the parameters of Probability of Detection (PD), Probability of False Alarms (Pfa), Probability of MissedDetection (Pmd), sensing time and throughput at low power or low SNR. The results show that there is a significantimprovement via the HFDI technique for all the parameters.展开更多
The computational complexity of resource allocation processes,in cognitive radio networks(CRNs),is a major issue to be managed.Furthermore,the complicated solution of the optimal algorithm for handling resource alloca...The computational complexity of resource allocation processes,in cognitive radio networks(CRNs),is a major issue to be managed.Furthermore,the complicated solution of the optimal algorithm for handling resource allocation in CRNs makes it unsuitable to adopt in real-world applications where both cognitive users,CRs,and primary users,PUs,exist in the identical geographical area.Hence,this work offers a primarily price-based power algorithm to reduce computational complexity in uplink scenarioswhile limiting interference to PUs to allowable threshold.Hence,this paper,compared to other frameworks proposed in the literature,proposes a two-step approach to reduce the complexity of the proposed mathematical model.In the first step,the subcarriers are assigned to the users of the CRN,while the cost function includes a pricing scheme to provide better power control algorithm with improved reliability proposed in the second stage.The main contribution of this paper is to lessen the complexity of the proposed algorithm and to offer flexibility in controlling the interference produced to the users of the primary networks,which has been achieved by including a pricing function in the proposed cost function.Finally,the performance of the proposed power and subcarrier algorithm is confirmed for orthogonal frequency-division multiplexing(OFDM).Simulation results prove that the performance of the proposed algorithm is better than other algorithms,albeit with a lesser complexity of O(NM)+O(Nlog(N)).展开更多
This paper outlined a Non-Orthogonal Multiple Access (NOMA) grouping transmission scheme for cognitive radio networks. To address the problems of small channel gain difference of the middle part users caused by the tr...This paper outlined a Non-Orthogonal Multiple Access (NOMA) grouping transmission scheme for cognitive radio networks. To address the problems of small channel gain difference of the middle part users caused by the traditional far-near pairing algorithm, and the low transmission rate of the traditional Orthogonal Multiple Access (OMA) transmission, a joint pairing algorithm was proposed, which provided multiple pairing schemes according to the actual scene. Firstly, the secondary users were sorted according to their channel gain, and then different secondary user groups were divided, and the far-near pairing combined with (Uniform Channel Gain Difference (UCGD) algorithm was used to group the secondary users. After completing the user pairing, the power allocation problem was solved. Finally, the simulation data results showed that the proposed algorithm can effectively improve the system transmission rate.展开更多
This paper investigates the power control and routing problem in the communication process of an energy harvesting(EH)multi-hop cognitive radio network(CRN).The secondary user(SU)nodes(i.e.,source node and relay nodes...This paper investigates the power control and routing problem in the communication process of an energy harvesting(EH)multi-hop cognitive radio network(CRN).The secondary user(SU)nodes(i.e.,source node and relay nodes)harvest energy from the environment and use the energy exclusively for transmitting data.The SU nodes(i.e.,relay nodes)on the path,store and forward the received data to the destination node.We consider a real world scenario where the EH-SU node has only local causal knowledge,i.e.,at any time,each EH-SU node only has knowledge of its own EH process,channel state and currently received data.In order to study the power and routing issues,an optimization problem that maximizes path throughput considering quality of service(QoS)and available energy constraints is proposed.To solve this optimization problem,we propose a hybrid game theory routing and power control algorithm(HGRPC).The EH-SU nodes on the same path cooperate with each other,but EH-SU nodes on the different paths compete with each other.By selecting the best next hop node,we find the best strategy that can maximize throughput.In addition,we have established four steps to achieve routing,i.e.,route discovery,route selection,route reply,and route maintenance.Compared with the direct transmission,HGRPC has advantages in longer distances and higher hop counts.The algorithm generates more energy,reduces energy consumption and increases predictable residual energy.In particular,the time complexity of HGRPC is analyzed and its convergence is proved.In simulation experiments,the performance(i.e.,throughput and bit error rate(BER))of HGRPC is evaluated.Finally,experimental results show that HGRPC has higher throughput,longer network life,less latency,and lower energy consumption.展开更多
In traditional cognitive radio(CR) network,secondary users(SUs) are always assumed to obey the rule of"introducing no interference to the primary users(PUs) ".However,this assumption may be not realistic as ...In traditional cognitive radio(CR) network,secondary users(SUs) are always assumed to obey the rule of"introducing no interference to the primary users(PUs) ".However,this assumption may be not realistic as the CR devices becoming more and more intelligent nowadays.In this paper,with the concept of lighthanded CR,which is proposed to deal with the above mentioned problem by enforcing"punishment"to illegal CR transmissions,the action decisions of primary users(PUs) are modeled as a partially observable Markov decision process(POMDP),and the optimal spectrum allocation scheme with the objective of maximizing their reward is proposed,which is defined by the utility function.Furthermore,a reduced scheme with much smaller state space has been proposed in this paper for lower computational complexity.Extensive simulation results show that the proposed schemes improve the reward significantly compared to the existing scheme.展开更多
The vast revolution in networking is increasing rapidly along with tech-nology advancements,which requires more effort from all cyberspace profes-sionals to cope with the challenges that come with advanced technology ...The vast revolution in networking is increasing rapidly along with tech-nology advancements,which requires more effort from all cyberspace profes-sionals to cope with the challenges that come with advanced technology privileges and services.Hence,Cognitive Radio Network is one of the promising approaches that permit a dynamic type of smart network for improving the utili-zation of idle spectrum portions of wireless communications.However,it is vul-nerable to security threats and attacks and demands security mechanisms to preserve and protect the cognitive radio networks for ensuring a secure commu-nication environment.This paper presents an effective secure MAC protocol for cognitive radio networks,significantly enhancing the security level of the existing DSMCRN and SSMCRN protocols by eliminating the authentication server’s necessity,which can be a single point of failure to compromise the entire network communication.The proposed protocol has proven to be effective and reliable since it does not rely on a centralized entity for providing the required security for a single pair of cognitive users.The protocol also improves the performance in the context of fast switching to data channels leading to higher throughput is achieved compared to the benchmark protocols.展开更多
Cognitive Radio Networks(CRN)are the possible and ideal solution for meeting the spectrum needs of next-generation communication systems.CRN is a promising alternative approach that allows spectrum sharing in many app...Cognitive Radio Networks(CRN)are the possible and ideal solution for meeting the spectrum needs of next-generation communication systems.CRN is a promising alternative approach that allows spectrum sharing in many applications.The licensed users considered Primary Users(PU)and unlicensed users as Secondary Users(SU).Time and power consumption on security issues are considered degrading factors in performance for improving the Quality of Service(QoS).Irrespective of using different optimization techniques,the same methodology is to be updated for the task.So that,learning and optimization go hand in hand.It ensures the security in CRN,risk factors in spectrum sharing to SU for secure communication.The objective of the proposed work is to preserve the location of the SU from attackers and attain the clustering of SU to utilize the resource.Ant Colony Optimization(ACO)is implemented to increase the overall efficiency and utilization of the CRN.ACO is used to form clusters of SUs in the co-operative spectrum sensing technique.This paper deals with threat detection and classifying threats using parameters such as unlikability,context privacy,anonymity,conditional traceability,and trade-off.In this privacy-preserving model,overall accuracy is 97.4%,and it is 9%higher than the conventional models without Privacy-Preserving Architecture(PPA).展开更多
In this article,we optimize harvesting and sensing duration for Cognitive Radio Networks(CRN)using Intelligent Reflecting Surfaces(IRS).The secondary source harvests energy using the received signal from node A.Then,i...In this article,we optimize harvesting and sensing duration for Cognitive Radio Networks(CRN)using Intelligent Reflecting Surfaces(IRS).The secondary source harvests energy using the received signal from node A.Then,it performs spectrum sensing to detect Primary Source PS activity.When PS activity is not detected,The Secondary Source SS transmits data to Secondary Destination SD where all reflected signals on IRS are in phase at SD.We show that IRS offers 14,20,26,32,38,44,50 dB enhancement in throughput using M=8,16,32,64,128,256,512 reflectors with respect to CRN without IRS.We also suggested to add a second IRS between A and SS to increase the harvested energy.The use of 2 IRS with M1=8 reflectors in the first IRS and M2=8 reflectors in the second IRS offers 18 dB gain(respectively 32 dB)gain with respect to a single IRS with M2=8 reflectors(respectively without IRS).The use of 2 IRS with M1=16 reflectors in the first IRS and M2=8 reflectors in the second IRS offers 28 dB gain(respectively 42 dB)gain with respect to a single IRS with M2=8 reflectors(respectively without IRS).Our results are valid for Nakagami channels of fading figure m.We also provide the throughput of IRS with energy harvesting.We have studied packet waiting time and total delay in the presence and absence or IRS.At Signal to Noise Ratio(SNR)per bit equal to 0 dB,packet waiting time is 0.9 ms when there is no IRS and 0.5 ms when there is an IRS with M=8 reflector.At SNR per bit equal to 0 dB,total transmission delay is 54 ms when there is no IRS and 1.5 ms when there is an IRS with M=8 reflectors.We show that the energy efficiency is larger when both harvesting and sensing durations are optimized.The maximum of energy efficiency is 260 Mbit/s/Hz/J when harvesting and sensing durations are optimized while the maximum is 80 Mbit/s/Hz/J when harvesting and sensing durations are not optimized.展开更多
A novel joint optimization strategy for the secondary user( SU) was proposed to consider the short-term and long-term video transmissions over distributed cognitive radio networks( DCRNs).Since the long-term video tra...A novel joint optimization strategy for the secondary user( SU) was proposed to consider the short-term and long-term video transmissions over distributed cognitive radio networks( DCRNs).Since the long-term video transmission consisted of a series of shortterm transmissions, the optimization problem in the video transmission was a composite optimization process. Firstly,considering some factors like primary user's( PU's) collision limitations,non-synchronization between SU and PU,and SU's limited buffer size, the short-term optimization problem was formulated as a mixed integer non-linear program( MINLP) to minimize the block probability of video packets. Secondly,combining the minimum packet block probability obtained in shortterm optimization and SU's constraint on hardware complexity,the partially observable Markov decision process( POMDP) framework was proposed to learn PU's statistic information over DCRNs.Moreover,based on the proposed framework,joint optimization strategy was designed to obtain the minimum packet loss rate in long-term video transmission. Numerical simulation results were provided to demonstrate validity of our strategies.展开更多
In cognitive radio networks, Secondary Users (SUs) have opportunities to access the spectrum channel when primary user would not use it, which will enhance the resource utilization. In order to avoid interference to p...In cognitive radio networks, Secondary Users (SUs) have opportunities to access the spectrum channel when primary user would not use it, which will enhance the resource utilization. In order to avoid interference to primary users, it is very important and essential for SUs to sense the idle spectrum channels, but also it is very hard to detect all the channels in a short time due to the hardware restriction. This paper proposes a novel spectrum prediction scheme based on Support Vector Machines (SVM), to save the time and energy consumed by spectrum sensing via predicting the channels' state before detecting. Besides, spectrum utilization is further improved by using the cooperative mechanism, in which SUs could share spectrum channels' history state information and prediction results with neighbor nodes. The simulation results show that the algorithm has high prediction accuracy under the condition of small training sample case, and can obviously reduce the detecting energy, which also leads to the improvement of spectrum utilization.展开更多
Channel estimation techniques applied to cognitive radio networks (CRN) are analyzed for simultaneously primary and secondary channel estimations operating in underlay cognitive radio networks (uCRN). A complete base-...Channel estimation techniques applied to cognitive radio networks (CRN) are analyzed for simultaneously primary and secondary channel estimations operating in underlay cognitive radio networks (uCRN). A complete base-band transmission including pilot sequence transmission, channel matrix estimation and optimal precoder matrix generation based on imperfect channel estimation are described. Also, the effect of imperfect channel estimation has been studied to provide means of developing techniques to overcome problems while enhancing the MIMO communication performance.展开更多
Dynamic spectrum access(DSA) based on cognitive radios(CR) technique is an effective approach to address the "spectrum scarcity" issue. However, traditional CR-enabled DSA system employs only single DSA stra...Dynamic spectrum access(DSA) based on cognitive radios(CR) technique is an effective approach to address the "spectrum scarcity" issue. However, traditional CR-enabled DSA system employs only single DSA strategy, which might not be suited to the dynamic network environment. In this paper, we propose a multi-strategy DSA(MS-DSA) system, where the primary and the secondary system share spectrum resources with multiple DSA strategies simultaneously. To analyze the performance of the proposed MS-DSA system, we model it as a continuous-time Markov chain(CTMC) and derive the expressions to compute the corresponding performance metrics. Based on this, we define a utility function involving the concerns of effective throughput, interference quantity on primary users, and spectrum leasing cost. Two optimization schemes, named as spectrum allocation and false alarm probability selection, are proposed to maximize the utility function. Finally, numerical simulations are provided to validate our analysis and demonstrate that the performance can be significantly improved caused by virtues of the proposed MS-DSA system.展开更多
In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user syste...In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing,meanwhile considering the maximum transmit power,user quality of service(QoS)requirements,interference limitations,and primary user protection.The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem.The Dinkelbach’s method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction.Then,an iterative power allocation algorithm is proposed to solve the optimization problem.The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.展开更多
Cognitive Radio Network provides an opportunity to reduce the spectrum resource crisis by allowing secondary users to access the idle spectrum allocated to primary users. The precondition of spectrum sharing is to obt...Cognitive Radio Network provides an opportunity to reduce the spectrum resource crisis by allowing secondary users to access the idle spectrum allocated to primary users. The precondition of spectrum sharing is to obtain the Spectrum Availability Information(SAI). Energy detection is a typical technology to get SAI. With the mobility of primary users, the energy received by secondary users varies greatly with the distance from the target primary users. Most of the existing energy detection algorithms that use fixed thresholds are not suitable. We propose a Dynamic Matching-Based Spectrum Detection(DMBSD) scheme which can detect sensing data, reduce the impact of malicious data and make final sensing results more accurate with dynamic threshold setting and data matching. Simulation results show that the proposed scheme can detect tempered data, and increase detection probability by decreasing false alarm probability and missed detection probability.展开更多
In a cognitive radio network wherein primary and secondary users coexist, an efficient power allocation method represents one of the most important key aspects. This paper provides a novel approach based on a game the...In a cognitive radio network wherein primary and secondary users coexist, an efficient power allocation method represents one of the most important key aspects. This paper provides a novel approach based on a game theory framework to solve this problem in a distributed and fair way. Formulated as an optimization problem, the resource allocation problem between secondary users and primary users can be modeled and investigated with the Game Theory, and in particular S-Modular Games, since they provide useful tools for the definition of multi objective distributed algorithms in the context of radio communications. This paper provides also a performance comparison among the proposed game and two other algorithms, frequently used in this context: Simulated Annealing and Water Filling.展开更多
文摘This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio network.The threshold identification method is implemented in the received signal at the secondary user based on the square law.The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing.Additionally,the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems.In the dynamic threshold,the signal ratio-based threshold is fixed.The threshold is computed by considering the Modified Black Widow Optimization Algorithm(MBWO).So,the proposed methodology is a combination of dynamic threshold detection and MBWO.The general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user signal.These limitations undermine the sensing accuracy of the energy identification technique.Hence,the ETBED technique is developed to enhance the energy efficiency of cognitive radio networks.The projected approach is executed and analyzed with performance and comparison analysis.The proposed method is contrasted with the conventional techniques of theWhale Optimization Algorithm(WOA)and GreyWolf Optimization(GWO).It indicated superior results,achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8,outperforming conventional techniques.
文摘Cognitive Radio Networks(CRNs)have become a successful platform in recent years for a diverse range of future systems,in particularly,industrial internet of things(IIoT)applications.In order to provide an efficient connection among IIoT devices,CRNs enhance spectrum utilization by using licensed spectrum.However,the routing protocol in these networks is considered one of the main problems due to node mobility and time-variant channel selection.Specifically,the channel selection for routing protocol is indispensable in CRNs to provide an adequate adaptation to the Primary User(PU)activity and create a robust routing path.This study aims to construct a robust routing path by minimizing PU interference and routing delay to maximize throughput within the IIoT domain.Thus,a generic routing framework from a cross-layer perspective is investigated that intends to share the information resources by exploiting a recently proposed method,namely,Channel Availability Probability.Moreover,a novel cross-layer-oriented routing protocol is proposed by using a time-variant channel estimation technique.This protocol combines lower layer(Physical layer and Data Link layer)sensing that is derived from the channel estimation model.Also,it periodically updates and stores the routing table for optimal route decision-making.Moreover,in order to achieve higher throughput and lower delay,a new routing metric is presented.To evaluate the performance of the proposed protocol,network simulations have been conducted and also compared to the widely used routing protocols,as a benchmark.The simulation results of different routing scenarios demonstrate that our proposed solution outperforms the existing protocols in terms of the standard network performance metrics involving packet delivery ratio(with an improved margin of around 5–20%approximately)under varying numbers of PUs and cognitive users in Mobile Cognitive Radio Networks(MCRNs).Moreover,the cross-layer routing protocol successfully achieves high routing performance in finding a robust route,selecting the high channel stability,and reducing the probability of PU interference for continued communication.
基金supported in part by the Key International Cooper-ation Research Project under Grant 61720106003in part by NUPTSF under Grant NY220111+1 种基金in part by NUPTSF under Grant NY221009in part by the Postgraduate Research and Practice Innovation Program of Jiangsu Province under Grant KYCX22_0959.
文摘Intelligent reflecting surface(IRS)is widely recognized as a promising technique to enhance the system perfor-mance,and thus is a hot research topic in future wireless communications.In this context,this paper proposes a robust BF scheme to improve the spectrum and energy harvesting efficiencies for the IRS-aided simultaneous wireless information and power transfer(SWIPT)in a cognitive radio network(CRN).Here,the base station(BS)utilizes spectrum assigned to the primary users(PUs)to simultaneously serve multiple energy receivers(ERs)and information receivers(IRs)through IRS-aided multicast technology.In particular,by assuming that only the imperfect channel state information(CSI)is available,we first formulate a constrained problem to maximize the minimal achievable rate of IRs,while satisfying the harvesting energy threshold of ERs,the quality-of-service requirement of IRs,the interference threshold of PUs and transmit power budget of BS.To address the non-convex problem,we then adopt triangle inequality to deal with the channel uncertainty,and propose a low-complexity algorithm combining alternating direction method of multipliers(ADMM)with alternating optimi-zation(AO)to jointly optimize the active and passive beamformers for the BS and IRS,respectively.Finally,our simulation results confirm the effectiveness of the proposed BF scheme and also provide useful insights into the importance of introducing IRS into the CRN with SWIPT.
基金supported by the National Natural Science Foundation of China(No.62201606 and No.62071486)the Project of Science and Technology Planning of Guizhou Province(No.[2020]-030)+3 种基金the Project of Science and Technology Fund of Guizhou Provincial Health Commission(gzwkj2022524)the Project of Youth Science and Technology Talent Growth Guizhou Provincial Department of Education(No.KY[2021]230)the Key Research Base Project of Humanities and Social Sciences of Education Department of Guizhou Provincethe Project of Science and Technology Planning of Zunyi City(No.2022-381 and No.2022-384)。
文摘This paper investigates the effects of the outdated channel state information(CSI)on the secrecy performance of an underlay spectrum sharing cognitive radio networks(CRNs),where the secondary user(SU)source node(Alice)aims to transmit the trusted messages to the full-duplex(FD)aided SU receiver(Bob)with the assistance of cooperative relay(Relay).Considering the impact of feedback delay,outdated CSI will aggravate the system performance.To tackle such challenge,the collaborative zero-forcing beamforming(ZFB)scheme of FD technique is further introduced to implement jamming so as to confuse the eavesdropping and improve the security performance of the system.Under such setup,the exact and asymptotic expressions of the secrecy outage probability(SOP)under the outdated CSI case are derived,respectively.The results reveal that i)the outdated CSI of the SU transmission channel will decrease the diversity gain from min(NANR,NRNB)to NRwith NA,NRand NBbeing the number of antennas of Alice,Relay and Bob,respectively,ii)the introduction of FD technique can improve coding gain and enhance system performance.
基金This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R97),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘In cognitive radio networks(CoR),the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability.Several optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold selection.However,these methods do not take into account the effect of sample size and its effect on improving CoR performance.In general,a large sample size results in more reliable detection,but takes longer sensing time and increases complexity.Thus,the locally sensed sample size is an optimization problem.Therefore,optimizing the local sample size for each cognitive user helps to improve CoR performance.In this study,two new methods are proposed to find the optimum sample size to achieve objective-based improved(single/double)threshold energy detection,these methods are the optimum sample size N^(*)and neural networks(NN)optimization.Through the evaluation,it was found that the proposed methods outperform the traditional sample size selection in terms of the total error rate,detection probability,and throughput.
基金the Ministry of Higher Education Malaysia for funding this research project through Fundamental Research Grant Scheme(FRGS)with Project Code:FRGS/1/2022/TK02/UCSI/02/1 and also to UCSI University.
文摘In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promisingapproach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio(SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambientRadio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum forthe transmission of data without loss or without collision at a specific time. In this paper, the authors proposed anovel Spectrum Sensing (SS) detection technique in the Cognitive Radio (CR) spectrum, by developing the AmBC.Novel Matched Filter Detection with Inverse covariance (MFDI), Cyclostationary Feature Detection with Inversecovariance (CFDI) and Hybrid Filter Detection with Inverse covariance (HFDI) approaches are used with AmBCto detect the presence of users at low power levels. The performance of the three detection techniques is measuredusing the parameters of Probability of Detection (PD), Probability of False Alarms (Pfa), Probability of MissedDetection (Pmd), sensing time and throughput at low power or low SNR. The results show that there is a significantimprovement via the HFDI technique for all the parameters.
基金Authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups Project under Grant Number RGP.2/111/43supported in part by the Agencia Estatal de Investigación,Ministerio de Ciencia e Innovación(MCIN/AEI/10.13039/501100011033)+1 种基金the R+D+i Project under Grant PID2020-115323RB-C31in part by the Grant from the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union-NextGenerationEU under Grant UNICO-5G I+D/AROMA3D-Hybrid TSI-063000-2021-71.
文摘The computational complexity of resource allocation processes,in cognitive radio networks(CRNs),is a major issue to be managed.Furthermore,the complicated solution of the optimal algorithm for handling resource allocation in CRNs makes it unsuitable to adopt in real-world applications where both cognitive users,CRs,and primary users,PUs,exist in the identical geographical area.Hence,this work offers a primarily price-based power algorithm to reduce computational complexity in uplink scenarioswhile limiting interference to PUs to allowable threshold.Hence,this paper,compared to other frameworks proposed in the literature,proposes a two-step approach to reduce the complexity of the proposed mathematical model.In the first step,the subcarriers are assigned to the users of the CRN,while the cost function includes a pricing scheme to provide better power control algorithm with improved reliability proposed in the second stage.The main contribution of this paper is to lessen the complexity of the proposed algorithm and to offer flexibility in controlling the interference produced to the users of the primary networks,which has been achieved by including a pricing function in the proposed cost function.Finally,the performance of the proposed power and subcarrier algorithm is confirmed for orthogonal frequency-division multiplexing(OFDM).Simulation results prove that the performance of the proposed algorithm is better than other algorithms,albeit with a lesser complexity of O(NM)+O(Nlog(N)).
文摘This paper outlined a Non-Orthogonal Multiple Access (NOMA) grouping transmission scheme for cognitive radio networks. To address the problems of small channel gain difference of the middle part users caused by the traditional far-near pairing algorithm, and the low transmission rate of the traditional Orthogonal Multiple Access (OMA) transmission, a joint pairing algorithm was proposed, which provided multiple pairing schemes according to the actual scene. Firstly, the secondary users were sorted according to their channel gain, and then different secondary user groups were divided, and the far-near pairing combined with (Uniform Channel Gain Difference (UCGD) algorithm was used to group the secondary users. After completing the user pairing, the power allocation problem was solved. Finally, the simulation data results showed that the proposed algorithm can effectively improve the system transmission rate.
基金This work was partially supported by the National Natural Science Foundation of China(No.61771410,No.61876089)by the Postgraduate Innovation Fund Project by Southwest University of Science and Technology(No.19ycx0106)+2 种基金by the Artificial Intelligence Key Laboratory of Sichuan Province(No.2017RYY05,No.2018RYJ03)by the Zigong City Key Science and Technology Plan Project(2019YYJC16)by and by the Horizontal Project(No.HX2017134,No.HX2018264,Nos.E10203788,HX2019250).
文摘This paper investigates the power control and routing problem in the communication process of an energy harvesting(EH)multi-hop cognitive radio network(CRN).The secondary user(SU)nodes(i.e.,source node and relay nodes)harvest energy from the environment and use the energy exclusively for transmitting data.The SU nodes(i.e.,relay nodes)on the path,store and forward the received data to the destination node.We consider a real world scenario where the EH-SU node has only local causal knowledge,i.e.,at any time,each EH-SU node only has knowledge of its own EH process,channel state and currently received data.In order to study the power and routing issues,an optimization problem that maximizes path throughput considering quality of service(QoS)and available energy constraints is proposed.To solve this optimization problem,we propose a hybrid game theory routing and power control algorithm(HGRPC).The EH-SU nodes on the same path cooperate with each other,but EH-SU nodes on the different paths compete with each other.By selecting the best next hop node,we find the best strategy that can maximize throughput.In addition,we have established four steps to achieve routing,i.e.,route discovery,route selection,route reply,and route maintenance.Compared with the direct transmission,HGRPC has advantages in longer distances and higher hop counts.The algorithm generates more energy,reduces energy consumption and increases predictable residual energy.In particular,the time complexity of HGRPC is analyzed and its convergence is proved.In simulation experiments,the performance(i.e.,throughput and bit error rate(BER))of HGRPC is evaluated.Finally,experimental results show that HGRPC has higher throughput,longer network life,less latency,and lower energy consumption.
基金Sponsored by the National Natural Science Foundation of China(Grant No. 61101113,61072088)the Doctoral Research Initiation Foundation Project of Beijing University of Technology(Grant No. X0002012201104)
文摘In traditional cognitive radio(CR) network,secondary users(SUs) are always assumed to obey the rule of"introducing no interference to the primary users(PUs) ".However,this assumption may be not realistic as the CR devices becoming more and more intelligent nowadays.In this paper,with the concept of lighthanded CR,which is proposed to deal with the above mentioned problem by enforcing"punishment"to illegal CR transmissions,the action decisions of primary users(PUs) are modeled as a partially observable Markov decision process(POMDP),and the optimal spectrum allocation scheme with the objective of maximizing their reward is proposed,which is defined by the utility function.Furthermore,a reduced scheme with much smaller state space has been proposed in this paper for lower computational complexity.Extensive simulation results show that the proposed schemes improve the reward significantly compared to the existing scheme.
基金Supporting Project(TURSP),Taif University,Kingdom of Saudi Arabia under the Grant Number:TURSP-2020/107.
文摘The vast revolution in networking is increasing rapidly along with tech-nology advancements,which requires more effort from all cyberspace profes-sionals to cope with the challenges that come with advanced technology privileges and services.Hence,Cognitive Radio Network is one of the promising approaches that permit a dynamic type of smart network for improving the utili-zation of idle spectrum portions of wireless communications.However,it is vul-nerable to security threats and attacks and demands security mechanisms to preserve and protect the cognitive radio networks for ensuring a secure commu-nication environment.This paper presents an effective secure MAC protocol for cognitive radio networks,significantly enhancing the security level of the existing DSMCRN and SSMCRN protocols by eliminating the authentication server’s necessity,which can be a single point of failure to compromise the entire network communication.The proposed protocol has proven to be effective and reliable since it does not rely on a centralized entity for providing the required security for a single pair of cognitive users.The protocol also improves the performance in the context of fast switching to data channels leading to higher throughput is achieved compared to the benchmark protocols.
文摘Cognitive Radio Networks(CRN)are the possible and ideal solution for meeting the spectrum needs of next-generation communication systems.CRN is a promising alternative approach that allows spectrum sharing in many applications.The licensed users considered Primary Users(PU)and unlicensed users as Secondary Users(SU).Time and power consumption on security issues are considered degrading factors in performance for improving the Quality of Service(QoS).Irrespective of using different optimization techniques,the same methodology is to be updated for the task.So that,learning and optimization go hand in hand.It ensures the security in CRN,risk factors in spectrum sharing to SU for secure communication.The objective of the proposed work is to preserve the location of the SU from attackers and attain the clustering of SU to utilize the resource.Ant Colony Optimization(ACO)is implemented to increase the overall efficiency and utilization of the CRN.ACO is used to form clusters of SUs in the co-operative spectrum sensing technique.This paper deals with threat detection and classifying threats using parameters such as unlikability,context privacy,anonymity,conditional traceability,and trade-off.In this privacy-preserving model,overall accuracy is 97.4%,and it is 9%higher than the conventional models without Privacy-Preserving Architecture(PPA).
文摘In this article,we optimize harvesting and sensing duration for Cognitive Radio Networks(CRN)using Intelligent Reflecting Surfaces(IRS).The secondary source harvests energy using the received signal from node A.Then,it performs spectrum sensing to detect Primary Source PS activity.When PS activity is not detected,The Secondary Source SS transmits data to Secondary Destination SD where all reflected signals on IRS are in phase at SD.We show that IRS offers 14,20,26,32,38,44,50 dB enhancement in throughput using M=8,16,32,64,128,256,512 reflectors with respect to CRN without IRS.We also suggested to add a second IRS between A and SS to increase the harvested energy.The use of 2 IRS with M1=8 reflectors in the first IRS and M2=8 reflectors in the second IRS offers 18 dB gain(respectively 32 dB)gain with respect to a single IRS with M2=8 reflectors(respectively without IRS).The use of 2 IRS with M1=16 reflectors in the first IRS and M2=8 reflectors in the second IRS offers 28 dB gain(respectively 42 dB)gain with respect to a single IRS with M2=8 reflectors(respectively without IRS).Our results are valid for Nakagami channels of fading figure m.We also provide the throughput of IRS with energy harvesting.We have studied packet waiting time and total delay in the presence and absence or IRS.At Signal to Noise Ratio(SNR)per bit equal to 0 dB,packet waiting time is 0.9 ms when there is no IRS and 0.5 ms when there is an IRS with M=8 reflector.At SNR per bit equal to 0 dB,total transmission delay is 54 ms when there is no IRS and 1.5 ms when there is an IRS with M=8 reflectors.We show that the energy efficiency is larger when both harvesting and sensing durations are optimized.The maximum of energy efficiency is 260 Mbit/s/Hz/J when harvesting and sensing durations are optimized while the maximum is 80 Mbit/s/Hz/J when harvesting and sensing durations are not optimized.
基金National Natural Science Foundation of China(No.61301101)
文摘A novel joint optimization strategy for the secondary user( SU) was proposed to consider the short-term and long-term video transmissions over distributed cognitive radio networks( DCRNs).Since the long-term video transmission consisted of a series of shortterm transmissions, the optimization problem in the video transmission was a composite optimization process. Firstly,considering some factors like primary user's( PU's) collision limitations,non-synchronization between SU and PU,and SU's limited buffer size, the short-term optimization problem was formulated as a mixed integer non-linear program( MINLP) to minimize the block probability of video packets. Secondly,combining the minimum packet block probability obtained in shortterm optimization and SU's constraint on hardware complexity,the partially observable Markov decision process( POMDP) framework was proposed to learn PU's statistic information over DCRNs.Moreover,based on the proposed framework,joint optimization strategy was designed to obtain the minimum packet loss rate in long-term video transmission. Numerical simulation results were provided to demonstrate validity of our strategies.
基金Sponsored by the Youth Foundation of Beijing Univesity of Postsand Telecommunications(Grant No.2011RC0110)Director Foundation of Key Lab of Universal Wirelsess Communication of Ministry of Education(Grant No.ZRJJ-2010-3)Ministry of Industry and Information Technology of China(Grant No.2011ZX03001-007-03)
文摘In cognitive radio networks, Secondary Users (SUs) have opportunities to access the spectrum channel when primary user would not use it, which will enhance the resource utilization. In order to avoid interference to primary users, it is very important and essential for SUs to sense the idle spectrum channels, but also it is very hard to detect all the channels in a short time due to the hardware restriction. This paper proposes a novel spectrum prediction scheme based on Support Vector Machines (SVM), to save the time and energy consumed by spectrum sensing via predicting the channels' state before detecting. Besides, spectrum utilization is further improved by using the cooperative mechanism, in which SUs could share spectrum channels' history state information and prediction results with neighbor nodes. The simulation results show that the algorithm has high prediction accuracy under the condition of small training sample case, and can obviously reduce the detecting energy, which also leads to the improvement of spectrum utilization.
文摘Channel estimation techniques applied to cognitive radio networks (CRN) are analyzed for simultaneously primary and secondary channel estimations operating in underlay cognitive radio networks (uCRN). A complete base-band transmission including pilot sequence transmission, channel matrix estimation and optimal precoder matrix generation based on imperfect channel estimation are described. Also, the effect of imperfect channel estimation has been studied to provide means of developing techniques to overcome problems while enhancing the MIMO communication performance.
基金supported in part by the National Natural Sciences Foundation of China (NSFC) under Grant 61525103the National Natural Sciences Foundation of China under Grant 61501140the Shenzhen Fundamental Research Project under Grant JCYJ20150930150304185
文摘Dynamic spectrum access(DSA) based on cognitive radios(CR) technique is an effective approach to address the "spectrum scarcity" issue. However, traditional CR-enabled DSA system employs only single DSA strategy, which might not be suited to the dynamic network environment. In this paper, we propose a multi-strategy DSA(MS-DSA) system, where the primary and the secondary system share spectrum resources with multiple DSA strategies simultaneously. To analyze the performance of the proposed MS-DSA system, we model it as a continuous-time Markov chain(CTMC) and derive the expressions to compute the corresponding performance metrics. Based on this, we define a utility function involving the concerns of effective throughput, interference quantity on primary users, and spectrum leasing cost. Two optimization schemes, named as spectrum allocation and false alarm probability selection, are proposed to maximize the utility function. Finally, numerical simulations are provided to validate our analysis and demonstrate that the performance can be significantly improved caused by virtues of the proposed MS-DSA system.
基金supported in part by the National Natural Science Foundation of China for Young Scholars under Grant No.61701167Young Elite Backbone Teachers in Blue and Blue Project of Jiangsu Province, China
文摘In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing,meanwhile considering the maximum transmit power,user quality of service(QoS)requirements,interference limitations,and primary user protection.The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem.The Dinkelbach’s method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction.Then,an iterative power allocation algorithm is proposed to solve the optimization problem.The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.
基金supported by the National Natural Science Foundation of China (No.61602358)the Key Program of NSFC-Tongyong Union Foundation under Grant U1636209the Fundamental Research Funds for the Central Universities (No.XJS17078)
文摘Cognitive Radio Network provides an opportunity to reduce the spectrum resource crisis by allowing secondary users to access the idle spectrum allocated to primary users. The precondition of spectrum sharing is to obtain the Spectrum Availability Information(SAI). Energy detection is a typical technology to get SAI. With the mobility of primary users, the energy received by secondary users varies greatly with the distance from the target primary users. Most of the existing energy detection algorithms that use fixed thresholds are not suitable. We propose a Dynamic Matching-Based Spectrum Detection(DMBSD) scheme which can detect sensing data, reduce the impact of malicious data and make final sensing results more accurate with dynamic threshold setting and data matching. Simulation results show that the proposed scheme can detect tempered data, and increase detection probability by decreasing false alarm probability and missed detection probability.
文摘In a cognitive radio network wherein primary and secondary users coexist, an efficient power allocation method represents one of the most important key aspects. This paper provides a novel approach based on a game theory framework to solve this problem in a distributed and fair way. Formulated as an optimization problem, the resource allocation problem between secondary users and primary users can be modeled and investigated with the Game Theory, and in particular S-Modular Games, since they provide useful tools for the definition of multi objective distributed algorithms in the context of radio communications. This paper provides also a performance comparison among the proposed game and two other algorithms, frequently used in this context: Simulated Annealing and Water Filling.
