A novel distributed cognitive radio multichannel medium access protocol without common control channel was proposed.The protocol divided a transmission interval into two parts for exchanging control information and da...A novel distributed cognitive radio multichannel medium access protocol without common control channel was proposed.The protocol divided a transmission interval into two parts for exchanging control information and data,respectively.In addition to evaluating system saturation throughput of the proposed protocol,a three-dimensional multi channel Markov chain model to describe the sate of the cognitive users (CUs) in dynamic spectrum access was presented.The proposed analysis was applied to the packet transmission schemes employed by the basic,RTS/CTS access mechanism adopted in the normal IEEE 802.11.Analyzing the advantage of the two methods,a hybrid access mechanism was proposed to improve the system throughput.The simulation results show that the experiment results are close to the value computed by the model (less than 5%),and the proposed protocol significantly improves the performance of the system throughput by borrowing the licensed spectrum.By analyzing the dependence of throughput on system parameters,hybrid mechanism dynamically selecting access mechanism can maintain high throughput.展开更多
In order to avoid the system performance deterioration caused by the wireless fading channel and imperfect channel estimation in cognitive radio networks, the spectrum sharing problem with the consideration of feedbac...In order to avoid the system performance deterioration caused by the wireless fading channel and imperfect channel estimation in cognitive radio networks, the spectrum sharing problem with the consideration of feedback control information from the primary user is analyzed. An improved spectrum sharing algorithm based on the combination of the feedback control information and the optimization algorithm is proposed. The relaxation method is used to achieve the approximate spectrum sharing model, and the spectrum sharing strategy that satisfies the individual outage probability constraints can be obtained iteratively with the observed outage probability. Simulation results show that the proposed spectrum sharing algorithm can achieve the spectrum sharing strategy that satisfies the outage probability constraints and reduce the average outage probability without causing maximum transmission rate reduction of the secondary user.展开更多
In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed...In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.展开更多
In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorith...In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorithm is used to identify the occupied subband set(OSS)and the idle subband set(ISS),and then the location and number information of the occupied channels are obtained according to the elements in the OSS.Compared with the classical BMSS methods based on the information theoretic criteria(ITC),the new method shows more excellent performance especially in the low signal-to-noise ratio(SNR)and the small sampling number scenarios,and more robust detection performance in noise uncertainty or unequal noise variance applications.Meanwhile,the new method performs more stablely than the ITC-based methods when the occupied subband number increases or the primary signals suffer multi-path fading.Simulation result verifies the effectiveness of the proposed method.展开更多
Cognitive radio（CR） technology is considered to be an effective solution to allocate spectrum resources,whereas the primary users of a network do not fully utilize available frequency bands.Spectrum auction framewor...Cognitive radio（CR） technology is considered to be an effective solution to allocate spectrum resources,whereas the primary users of a network do not fully utilize available frequency bands.Spectrum auction framework has been recognized as an effective way to achieve dynamic spectrum access.From the perspective of spectrum auction,multi-band multi-user auction provides a new challenge for spectrum management.This paper proposes an auction framework based on location information for multi-band multi-user spectrum allocation.The performance of the proposed framework is compared with that of traditional auction framework based on a binary interference model as a benchmark.Simulation results show that primary users will obtain more total system revenue by selling their idle frequency bands to secondary users and the spectrum utilization of the proposed framework is more effective and fairer.展开更多
In cognitive radio network(CRN), a secondary user(SU) may utilize the spectrum resource of the primary user(PU) and avoid causing harmful interference to the primary network(PN) via spectrum sensing. In the traditiona...In cognitive radio network(CRN), a secondary user(SU) may utilize the spectrum resource of the primary user(PU) and avoid causing harmful interference to the primary network(PN) via spectrum sensing. In the traditional time spectrum sensing, the SU cannot detect the PU's presence during its transmission, thus increasing interference to the PN. In this work, a novel weighed cooperative bandwidth spectrum sensing method is proposed, which allows multiple SUs to use part of the bandwidth to perform cooperative spectrum sensing throughout the whole frame in order to detect the PU's reappearance in time. The SU's spectrum efficiency is maximized by jointly optimizing sensing bandwidth proportion, number of cooperative SUs and detection probability, subject to the constraints on the SU's interference and the false alarm probability. Simulation results show significant decrease on the interference and improvement on the spectrum efficiency using the proposed weighed cooperative bandwidth spectrum sensing method.展开更多
For acquiring high energy efficiency and the maximal throughput, a new time slot structure is designed for energy harvesting(EH) cognitive radio(CR). Considering the CR system with EH and cooperative relay, a best coo...For acquiring high energy efficiency and the maximal throughput, a new time slot structure is designed for energy harvesting(EH) cognitive radio(CR). Considering the CR system with EH and cooperative relay, a best cooperative mechanism(BCM)is proposed for CR with EH. To get the optimal estimation performance, a quantum fireworks algorithm(QFA) is designed to resolve the difficulties of maximal throughput and EH, and the proposed cooperative mechanism is called as QFA-BCM. The proposed QFA combines the advantages of quantum computation theory with the fireworks algorithm(FA). Thus the QFA is able to obtain the optimal solution and its convergence performance is proved. By using the new cooperation mechanism and computing algorithm, the proposed QFA-BCM method can achieve comparable maximal throughput in the new timeslot structure. Simulation results have proved that the QFA-BCM method is superior to previous non-cooperative and cooperative mechanisms.展开更多
The spectrum sharing problem between primary and cognitive users is mainly investigated. Since the interference for primary users and the total power for cognitive users are constrained, based on the well-known water-...The spectrum sharing problem between primary and cognitive users is mainly investigated. Since the interference for primary users and the total power for cognitive users are constrained, based on the well-known water-filling theorem, a novel one-user water-filling algorithm is proposed, and then the corresponding simulation results are given to analyze the feasibility and validity. After that this algorithm is used to solve the communication utility optimization problem subject to the power constraints in cognitive radio network. First, through the gain to noise ratio for cognitive users, a subcarrier and power allocation algorithm based on the optimal frequency partition is proposed for two cognitive users. Then the spectrum sharing algorithm is extended to multiuser conditions such that the greedy and parallel algorithms are proposed for spectrum sharing. Theory and simulation analysis show that the subcarrier and power allocation algorithms can not only protect the primary users but also effectively solve the spectrum and power allocation problem for cognitive users.展开更多
In order to improve the throughput of cognitive radio(CR), optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing was investigated in a CR network that includes multiple ...In order to improve the throughput of cognitive radio(CR), optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing was investigated in a CR network that includes multiple users and one fusion center. The frame structure of cooperative spectrum sensing was divided into multiple transmission time slots and one sensing time slot consisting of local energy detection and cooperative overhead. An optimization problem was formulated to maximize the throughput of CR network, subject to the constraints of both false alarm probability and detection probability. A joint optimization algorithm of sensing time and number of users was proposed to solve this optimization problem with low time complexity. An allocation algorithm of cooperative users was proposed to preferentially allocate the users to the channels with high utilization probability. The simulation results show that the significant improvement on the throughput can be achieved through the proposed joint optimization and allocation algorithms.展开更多
Based on the analysis of the feature of cognitive radio networks, a relevant interference model was built. Cognitive users should consider especially the problem of interference with licensed users and satisfy the sig...Based on the analysis of the feature of cognitive radio networks, a relevant interference model was built. Cognitive users should consider especially the problem of interference with licensed users and satisfy the signal-to-interference noise ratio （SINR） requirement at the same time. According to different power thresholds, an approach was given to solve the problem of coexistence between licensed user and cognitive user in cognitive system. Then, an uplink distributed power control algorithm based on traditional iterative model was proposed. Convergence analysis of the algorithm in case of feasible systems was provided. Simulations show that this method can provide substantial power savings as compared with the power balancing algorithm while reducing the achieved SINR only slightly, since 6% S1NR loss can bring 23% power gain. Through further simulations, it can be concluded that the proposed solution has better effect as the noise power or system load increases.展开更多
A most promising solution to the expansion of spectrum efficiency is cognitive radio(CR)and this expansion is achieved by permitting the licensed frequency bands to be accessed by unlicensed secondary users(SUs)with a...A most promising solution to the expansion of spectrum efficiency is cognitive radio(CR)and this expansion is achieved by permitting the licensed frequency bands to be accessed by unlicensed secondary users(SUs)with a lack of interference with licensed primary users(PUs).This utilization of CR networks in the spectrum sensing causes vulnerable attacks like primary user emulation(PUE)attack and here PUs play the role of malicious user and do not permit other users to utilize PUs channel even in their unavailability.On the basis of the traditional single-threshold energy detection algorithm,a novel modified double-threshold energy detector is formulated in the CR network and the detection probability,miss detection probability,probability of false alarm,and their inter-relationship are analyzed.This paper develops a modified double threshold energy detection cooperative spectrum sensing technique to alleviate the PUE attack.Finally,performance-based evaluation is carried out between the proposed and the existing energy detection spectrum sensing method that had no consideration on PUE attack.The resultant of the simulation in MATLAB has revealed that the proposed model has significantly mitigated PUE attack by means of providing outstanding performance.展开更多
Different schemes, which performed channel, power and time allocation to enhance the network performance of overall end-to-end throughput for cooperative cognitive radio network, were investigated. Interference temper...Different schemes, which performed channel, power and time allocation to enhance the network performance of overall end-to-end throughput for cooperative cognitive radio network, were investigated. Interference temperature limit of corresponding primary users was considered. Due to the constraints caused by multiple dual channels, the power allocation problem is non-convex and NP-hard. Based on geometric programming (GP), a novel and general algorithm, which turned the problem into a series of GP problems by logarithm approximation (LASGP), was proposed to efficiently solve it. Numerical results verify the efficiency and availability of the LASGP algorithm. Solutions of LASGP are provably convergent and globally optimal point can be observed as well as the channel allocation always outperforms power or timeslot allocation from simulations. Compared with schemes without any allocation, the scheme with joint channel, power and timeslot allocation significantly increases the overall end-to-end throughput by no less than 70% under same simulation conditions. This scheme can not only maximize the throughput by increasing total maximum power of relay node, but also outperform other resource allocation schemes when lower total maximum power of source and relay nodes is restricted. As the total maximum power of source node increases, the scheme with joint channel and timeslot allocation performs best in all schemes.展开更多
To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-lea...To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is proposed.First,dividing the distance between the missile and the target into multiple states to increase the quantity of state spaces.Second,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference parameters.The interference effect is determined by detecting whether the fuze signal disappears.Finally,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference form.The effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile rendezvous.The optimal interference form for each distance state has been obtained.Compared with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.展开更多
A joint power control and relay selection scheme is considered for a cooperative and cognitive radio system where a secondary network shares spectrum with the primary network. In the secondary network, two secondary u...A joint power control and relay selection scheme is considered for a cooperative and cognitive radio system where a secondary network shares spectrum with the primary network. In the secondary network, two secondary users （SUs） communicate with each other via an assist relay. The main point is to provide the best system performance to SUs while maintaining the interference power at primary user （PU） under a certain level. Using convex optimization, a closed-form solution is obtained when optimizing the power allocation among the two nodes and relay. Based on this result, a joint power control and relay selection scheme with fewer variable dimensions is proposed to maximize the achievable rate of the secondary system. Simulation results demonstrate that the sum rate of the cognitive two-way relay network increases compared with a random relay selection and fixed power allocation.展开更多
Automatic modulation classification is the process of identification of the modulation type of a signal in a general environment. This paper proposes a new method to evaluate the tracking performance of large margin c...Automatic modulation classification is the process of identification of the modulation type of a signal in a general environment. This paper proposes a new method to evaluate the tracking performance of large margin classifier against signal-tonoise ratio （SNR）, and classifies all forms of primary user＇s signals in a cognitive radio environment. For achieving this objective, two structures of a large margin are developed in additive white Gaussian noise （AWGN） channels with priori unknown SNR. A combination of higher order statistics and instantaneous characteristics is selected as effective features. Simulation results show that the classification rates of the proposed structures are well robust against environmental SNR changes.展开更多
In order to effectively solve combinatorial optimization problems,a membrane-inspired quantum bee colony optimization(MQBCO)is proposed for scientific computing and engineering applications.The proposed MQBCO algorith...In order to effectively solve combinatorial optimization problems,a membrane-inspired quantum bee colony optimization(MQBCO)is proposed for scientific computing and engineering applications.The proposed MQBCO algorithm applies the membrane computing theory to quantum bee colony optimization(QBCO),which is an effective discrete optimization algorithm.The global convergence performance of MQBCO is proved by Markov theory,and the validity of MQBCO is verified by testing the classical benchmark functions.Then the proposed MQBCO algorithm is used to solve decision engine problems of cognitive radio system.By hybridizing the QBCO and membrane computing theory,the quantum state and observation state of the quantum bees can be well evolved within the membrane structure.Simulation results for cognitive radio system show that the proposed decision engine method is superior to the traditional intelligent decision engine algorithms in terms of convergence,precision and stability.Simulation experiments under different communication scenarios illustrate that the balance between three objective functions and the adapted parameter configuration is consistent with the weights of three normalized objective functions.展开更多
To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping（MQSFL） algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane...To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping（MQSFL） algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane computing and quantum computing to the shuffled frog leaping algorithm,which is an effective discrete optimization algorithm.Then the proposed MQSFL algorithm is used to solve the spectrum allocation problem of cognitive radio systems.By hybridizing the quantum frog colony optimization and membrane computing,the quantum state and observation state of the quantum frogs can be well evolved within the membrane structure.The novel spectrum allocation algorithm can search the global optimal solution within a reasonable computation time.Simulation results for three utility functions of a cognitive radio system are provided to show that the MQSFL spectrum allocation method is superior to some previous spectrum allocation algorithms based on intelligence computing.展开更多
Many studies have been done in cognitive radios to maximize the network efficiency. There is always a trade-off between sensing and transmission time which has been addressed fully in the literature. There is also som...Many studies have been done in cognitive radios to maximize the network efficiency. There is always a trade-off between sensing and transmission time which has been addressed fully in the literature. There is also some missed idle times during the waiting phase when secondary user finds the channel busy. Therefore, the longer the transmission time is, the higher the successfully delivered bits would be and the higher the missed idle times in the waiting stage would be expected. In this work, we formulate these missed idle times to addressed this trade-off. Furthermore, interference due to PU re-occupancy is modelled in successful transmitted time and in collision probability. Moreover, we derive secondary user's packet delay distribution using phase type model at which retransmission due to collision results from both sensing error and PU re-occupancy is considered. Thanks to derived delay distribution, any statistical moments of delay could be found as a closed form mathematical expression. These moments can be used as constraints for applications with delay sensitive packets. Numerical results are given to clarify the network metrics. Finally, the optimized values for sensing and transmission time are computed using genetic algorithm in order to maximize access efficiency.展开更多
基金Project(61071104) supported by the National Natural Science Foundation of China
文摘A novel distributed cognitive radio multichannel medium access protocol without common control channel was proposed.The protocol divided a transmission interval into two parts for exchanging control information and data,respectively.In addition to evaluating system saturation throughput of the proposed protocol,a three-dimensional multi channel Markov chain model to describe the sate of the cognitive users (CUs) in dynamic spectrum access was presented.The proposed analysis was applied to the packet transmission schemes employed by the basic,RTS/CTS access mechanism adopted in the normal IEEE 802.11.Analyzing the advantage of the two methods,a hybrid access mechanism was proposed to improve the system throughput.The simulation results show that the experiment results are close to the value computed by the model (less than 5%),and the proposed protocol significantly improves the performance of the system throughput by borrowing the licensed spectrum.By analyzing the dependence of throughput on system parameters,hybrid mechanism dynamically selecting access mechanism can maintain high throughput.
基金supported by the National Natural Science Foundation of China (61073183)the Natural Science Foundation for the Youth of Heilongjiang Province (QC2012C070)
文摘In order to avoid the system performance deterioration caused by the wireless fading channel and imperfect channel estimation in cognitive radio networks, the spectrum sharing problem with the consideration of feedback control information from the primary user is analyzed. An improved spectrum sharing algorithm based on the combination of the feedback control information and the optimization algorithm is proposed. The relaxation method is used to achieve the approximate spectrum sharing model, and the spectrum sharing strategy that satisfies the individual outage probability constraints can be obtained iteratively with the observed outage probability. Simulation results show that the proposed spectrum sharing algorithm can achieve the spectrum sharing strategy that satisfies the outage probability constraints and reduce the average outage probability without causing maximum transmission rate reduction of the secondary user.
基金Foundation item： Projects（61102106, 61102105） supported by the National Natural Science Foundation of China Project（2013M530148） supported by China Postdoctoral Science Foundation Project（HEUCF120806） supported by the Fundamental Research Funds for the Central Universities of China
文摘In order to solve discrete multi-objective optimization problems, a non-dominated sorting quantum particle swarm optimization (NSQPSO) based on non-dominated sorting and quantum particle swarm optimization is proposed, and the performance of the NSQPSO is evaluated through five classical benchmark functions. The quantum particle swarm optimization (QPSO) applies the quantum computing theory to particle swarm optimization, and thus has the advantages of both quantum computing theory and particle swarm optimization, so it has a faster convergence rate and a more accurate convergence value. Therefore, QPSO is used as the evolutionary method of the proposed NSQPSO. Also NSQPSO is used to solve cognitive radio spectrum allocation problem. The methods to complete spectrum allocation in previous literature only consider one objective, i.e. network utilization or fairness, but the proposed NSQPSO method, can consider both network utilization and fairness simultaneously through obtaining Pareto front solutions. Cognitive radio systems can select one solution from the Pareto front solutions according to the weight of network reward and fairness. If one weight is unit and the other is zero, then it becomes single objective optimization, so the proposed NSQPSO method has a much wider application range. The experimental research results show that the NSQPS can obtain the same non-dominated solutions as exhaustive search but takes much less time in small dimensions; while in large dimensions, where the problem cannot be solved by exhaustive search, the NSQPSO can still solve the problem, which proves the effectiveness of NSQPSO.
基金Projects(61362018,61861019)supported by the National Natural Science Foundation of ChinaProject(1402041B)supported by the Jiangsu Province Postdoctoral Scientific Research Project,China+1 种基金Project(16A174)supported by the Scientific Research Fund of Hunan Provincial Education Department,ChinaProject([2016]283)supported by the Research Study and Innovative Experiment Project of College Students,China
文摘In this paper,a blind multiband spectrum sensing(BMSS)method requiring no knowledge of noise power,primary signal and wireless channel is proposed based on the K-means clustering(KMC).In this approach,the KMC algorithm is used to identify the occupied subband set(OSS)and the idle subband set(ISS),and then the location and number information of the occupied channels are obtained according to the elements in the OSS.Compared with the classical BMSS methods based on the information theoretic criteria(ITC),the new method shows more excellent performance especially in the low signal-to-noise ratio(SNR)and the small sampling number scenarios,and more robust detection performance in noise uncertainty or unequal noise variance applications.Meanwhile,the new method performs more stablely than the ITC-based methods when the occupied subband number increases or the primary signals suffer multi-path fading.Simulation result verifies the effectiveness of the proposed method.
基金supported by the Beijing Natural Science Foundation of China (4102050)
文摘Cognitive radio（CR） technology is considered to be an effective solution to allocate spectrum resources,whereas the primary users of a network do not fully utilize available frequency bands.Spectrum auction framework has been recognized as an effective way to achieve dynamic spectrum access.From the perspective of spectrum auction,multi-band multi-user auction provides a new challenge for spectrum management.This paper proposes an auction framework based on location information for multi-band multi-user spectrum allocation.The performance of the proposed framework is compared with that of traditional auction framework based on a binary interference model as a benchmark.Simulation results show that primary users will obtain more total system revenue by selling their idle frequency bands to secondary users and the spectrum utilization of the proposed framework is more effective and fairer.
基金Project(61471194)supported by the National Natural Science Foundation of ChinaProject(BK20140828)supported by the Natural Science Foundation of Jiangsu Province,ChinaProjects(NS2015088,DUT16RC(3)045)supported by the Fundamental Research Funds for the Central Universities,China
文摘In cognitive radio network(CRN), a secondary user(SU) may utilize the spectrum resource of the primary user(PU) and avoid causing harmful interference to the primary network(PN) via spectrum sensing. In the traditional time spectrum sensing, the SU cannot detect the PU's presence during its transmission, thus increasing interference to the PN. In this work, a novel weighed cooperative bandwidth spectrum sensing method is proposed, which allows multiple SUs to use part of the bandwidth to perform cooperative spectrum sensing throughout the whole frame in order to detect the PU's reappearance in time. The SU's spectrum efficiency is maximized by jointly optimizing sensing bandwidth proportion, number of cooperative SUs and detection probability, subject to the constraints on the SU's interference and the false alarm probability. Simulation results show significant decrease on the interference and improvement on the spectrum efficiency using the proposed weighed cooperative bandwidth spectrum sensing method.
基金supported by the National Natural Science Foundation of China(61571149)the Special China Postdoctoral Science Foundation(2015T80325)+2 种基金the Heilongjiang Postdoctoral Fund(LBH-Z13054)the China Scholarship Council and the Fundamental Research Funds for the Central Universities(HEUCFP201772HEUCF160808)
文摘For acquiring high energy efficiency and the maximal throughput, a new time slot structure is designed for energy harvesting(EH) cognitive radio(CR). Considering the CR system with EH and cooperative relay, a best cooperative mechanism(BCM)is proposed for CR with EH. To get the optimal estimation performance, a quantum fireworks algorithm(QFA) is designed to resolve the difficulties of maximal throughput and EH, and the proposed cooperative mechanism is called as QFA-BCM. The proposed QFA combines the advantages of quantum computation theory with the fireworks algorithm(FA). Thus the QFA is able to obtain the optimal solution and its convergence performance is proved. By using the new cooperation mechanism and computing algorithm, the proposed QFA-BCM method can achieve comparable maximal throughput in the new timeslot structure. Simulation results have proved that the QFA-BCM method is superior to previous non-cooperative and cooperative mechanisms.
基金supported by the National Natural Science Foundation of China(61071104)the National High Technology Research and Development Program(2008AA12Z305)
文摘The spectrum sharing problem between primary and cognitive users is mainly investigated. Since the interference for primary users and the total power for cognitive users are constrained, based on the well-known water-filling theorem, a novel one-user water-filling algorithm is proposed, and then the corresponding simulation results are given to analyze the feasibility and validity. After that this algorithm is used to solve the communication utility optimization problem subject to the power constraints in cognitive radio network. First, through the gain to noise ratio for cognitive users, a subcarrier and power allocation algorithm based on the optimal frequency partition is proposed for two cognitive users. Then the spectrum sharing algorithm is extended to multiuser conditions such that the greedy and parallel algorithms are proposed for spectrum sharing. Theory and simulation analysis show that the subcarrier and power allocation algorithms can not only protect the primary users but also effectively solve the spectrum and power allocation problem for cognitive users.
基金Project(61471194)supported by the National Natural Science Foundation of ChinaProject(BK20140828)supported by the Natural Science Foundation of Jiangsu Province,ChinaProject supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars,Ministry of Education,China
文摘In order to improve the throughput of cognitive radio(CR), optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing was investigated in a CR network that includes multiple users and one fusion center. The frame structure of cooperative spectrum sensing was divided into multiple transmission time slots and one sensing time slot consisting of local energy detection and cooperative overhead. An optimization problem was formulated to maximize the throughput of CR network, subject to the constraints of both false alarm probability and detection probability. A joint optimization algorithm of sensing time and number of users was proposed to solve this optimization problem with low time complexity. An allocation algorithm of cooperative users was proposed to preferentially allocate the users to the channels with high utilization probability. The simulation results show that the significant improvement on the throughput can be achieved through the proposed joint optimization and allocation algorithms.
基金Project(61071104) supported by the National Natural Science Foundation of China
文摘Based on the analysis of the feature of cognitive radio networks, a relevant interference model was built. Cognitive users should consider especially the problem of interference with licensed users and satisfy the signal-to-interference noise ratio （SINR） requirement at the same time. According to different power thresholds, an approach was given to solve the problem of coexistence between licensed user and cognitive user in cognitive system. Then, an uplink distributed power control algorithm based on traditional iterative model was proposed. Convergence analysis of the algorithm in case of feasible systems was provided. Simulations show that this method can provide substantial power savings as compared with the power balancing algorithm while reducing the achieved SINR only slightly, since 6% S1NR loss can bring 23% power gain. Through further simulations, it can be concluded that the proposed solution has better effect as the noise power or system load increases.
文摘A most promising solution to the expansion of spectrum efficiency is cognitive radio(CR)and this expansion is achieved by permitting the licensed frequency bands to be accessed by unlicensed secondary users(SUs)with a lack of interference with licensed primary users(PUs).This utilization of CR networks in the spectrum sensing causes vulnerable attacks like primary user emulation(PUE)attack and here PUs play the role of malicious user and do not permit other users to utilize PUs channel even in their unavailability.On the basis of the traditional single-threshold energy detection algorithm,a novel modified double-threshold energy detector is formulated in the CR network and the detection probability,miss detection probability,probability of false alarm,and their inter-relationship are analyzed.This paper develops a modified double threshold energy detection cooperative spectrum sensing technique to alleviate the PUE attack.Finally,performance-based evaluation is carried out between the proposed and the existing energy detection spectrum sensing method that had no consideration on PUE attack.The resultant of the simulation in MATLAB has revealed that the proposed model has significantly mitigated PUE attack by means of providing outstanding performance.
基金Project(60902092) supported by the National Natural Science Foundation of China
文摘Different schemes, which performed channel, power and time allocation to enhance the network performance of overall end-to-end throughput for cooperative cognitive radio network, were investigated. Interference temperature limit of corresponding primary users was considered. Due to the constraints caused by multiple dual channels, the power allocation problem is non-convex and NP-hard. Based on geometric programming (GP), a novel and general algorithm, which turned the problem into a series of GP problems by logarithm approximation (LASGP), was proposed to efficiently solve it. Numerical results verify the efficiency and availability of the LASGP algorithm. Solutions of LASGP are provably convergent and globally optimal point can be observed as well as the channel allocation always outperforms power or timeslot allocation from simulations. Compared with schemes without any allocation, the scheme with joint channel, power and timeslot allocation significantly increases the overall end-to-end throughput by no less than 70% under same simulation conditions. This scheme can not only maximize the throughput by increasing total maximum power of relay node, but also outperform other resource allocation schemes when lower total maximum power of source and relay nodes is restricted. As the total maximum power of source node increases, the scheme with joint channel and timeslot allocation performs best in all schemes.
基金National Natural Science Foundation of China(61973037)National 173 Program Project(2019-JCJQ-ZD-324).
文摘To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is proposed.First,dividing the distance between the missile and the target into multiple states to increase the quantity of state spaces.Second,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference parameters.The interference effect is determined by detecting whether the fuze signal disappears.Finally,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference form.The effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile rendezvous.The optimal interference form for each distance state has been obtained.Compared with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.
基金supported by the National Natural Science Foundation of China (61250005)Jiangxi Postdoctoral Science Foundation(2013KY07)
文摘A joint power control and relay selection scheme is considered for a cooperative and cognitive radio system where a secondary network shares spectrum with the primary network. In the secondary network, two secondary users （SUs） communicate with each other via an assist relay. The main point is to provide the best system performance to SUs while maintaining the interference power at primary user （PU） under a certain level. Using convex optimization, a closed-form solution is obtained when optimizing the power allocation among the two nodes and relay. Based on this result, a joint power control and relay selection scheme with fewer variable dimensions is proposed to maximize the achievable rate of the secondary system. Simulation results demonstrate that the sum rate of the cognitive two-way relay network increases compared with a random relay selection and fixed power allocation.
文摘Automatic modulation classification is the process of identification of the modulation type of a signal in a general environment. This paper proposes a new method to evaluate the tracking performance of large margin classifier against signal-tonoise ratio （SNR）, and classifies all forms of primary user＇s signals in a cognitive radio environment. For achieving this objective, two structures of a large margin are developed in additive white Gaussian noise （AWGN） channels with priori unknown SNR. A combination of higher order statistics and instantaneous characteristics is selected as effective features. Simulation results show that the classification rates of the proposed structures are well robust against environmental SNR changes.
基金supported by the National Natural Science Foundation of China(1127105011371183+2 种基金61403036)the Science and Technology Development Foundation of CAEP(2013A04030202013B0403068)
基金Projects(61102106,61102105)supported by the National Natural Science Foundation of ChinaProject(2013M530148)supported by China Postdoctoral Science Foundation+1 种基金Project(HEUCF140809)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(LBH-Z13054)supported by Heilongjiang Postdoctoral Fund,China
文摘In order to effectively solve combinatorial optimization problems,a membrane-inspired quantum bee colony optimization(MQBCO)is proposed for scientific computing and engineering applications.The proposed MQBCO algorithm applies the membrane computing theory to quantum bee colony optimization(QBCO),which is an effective discrete optimization algorithm.The global convergence performance of MQBCO is proved by Markov theory,and the validity of MQBCO is verified by testing the classical benchmark functions.Then the proposed MQBCO algorithm is used to solve decision engine problems of cognitive radio system.By hybridizing the QBCO and membrane computing theory,the quantum state and observation state of the quantum bees can be well evolved within the membrane structure.Simulation results for cognitive radio system show that the proposed decision engine method is superior to the traditional intelligent decision engine algorithms in terms of convergence,precision and stability.Simulation experiments under different communication scenarios illustrate that the balance between three objective functions and the adapted parameter configuration is consistent with the weights of three normalized objective functions.
基金supported by the National Natural Science Foundation of China (61102106,61102105)the Fundamental Research Funds for the Central Universities (HEUCF100801,HEUCFZ1129)
文摘To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping（MQSFL） algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane computing and quantum computing to the shuffled frog leaping algorithm,which is an effective discrete optimization algorithm.Then the proposed MQSFL algorithm is used to solve the spectrum allocation problem of cognitive radio systems.By hybridizing the quantum frog colony optimization and membrane computing,the quantum state and observation state of the quantum frogs can be well evolved within the membrane structure.The novel spectrum allocation algorithm can search the global optimal solution within a reasonable computation time.Simulation results for three utility functions of a cognitive radio system are provided to show that the MQSFL spectrum allocation method is superior to some previous spectrum allocation algorithms based on intelligence computing.
基金supported by Islamic Azad University,Boroujerd Branch,Iran
文摘Many studies have been done in cognitive radios to maximize the network efficiency. There is always a trade-off between sensing and transmission time which has been addressed fully in the literature. There is also some missed idle times during the waiting phase when secondary user finds the channel busy. Therefore, the longer the transmission time is, the higher the successfully delivered bits would be and the higher the missed idle times in the waiting stage would be expected. In this work, we formulate these missed idle times to addressed this trade-off. Furthermore, interference due to PU re-occupancy is modelled in successful transmitted time and in collision probability. Moreover, we derive secondary user's packet delay distribution using phase type model at which retransmission due to collision results from both sensing error and PU re-occupancy is considered. Thanks to derived delay distribution, any statistical moments of delay could be found as a closed form mathematical expression. These moments can be used as constraints for applications with delay sensitive packets. Numerical results are given to clarify the network metrics. Finally, the optimized values for sensing and transmission time are computed using genetic algorithm in order to maximize access efficiency.
