To promote reliable and secure communications in the cognitive radio network,the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation.In this paper,we address the cl...To promote reliable and secure communications in the cognitive radio network,the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation.In this paper,we address the classification of superimposed modulations dedicated to 5G multipleinput multiple-output(MIMO)two-way cognitive relay network in realistic channels modeled with Nakagami-m distribution.Our purpose consists of classifying pairs of users modulations from superimposed signals.To achieve this goal,we apply the higher-order statistics in conjunction with the Multi-BoostAB classifier.We use several efficiency metrics including the true positive(TP)rate,false positive(FP)rate,precision,recall,F-Measure and receiver operating characteristic(ROC)area in order to evaluate the performance of the proposed algorithm in terms of correct superimposed modulations classification.Computer simulations prove that our proposal allows obtaining a good probability of classification for ten superimposed modulations at a low signal-to-noise ratio,including the worst case(i.e.,m=0.5),where the fading distribution follows a one-sided Gaussian distribution.We also carry out a comparative study between our proposal usingMultiBoostAB classifier with the decision tree(J48)classifier.Simulation results show that the performance of MultiBoostAB on the superimposed modulations classifications outperforms the one of J48 classifier.In addition,we study the impact of the symbols number,path loss exponent and relay position on the performance of the proposed automatic classification superimposed modulations in terms of probability of correct classification.展开更多
In this paper, we consider a three-hop relay system based on interference cancellation technique in Underlay cognitive radio (CR) network. Although underlay CR has been shown as a promising technique to better utilize...In this paper, we consider a three-hop relay system based on interference cancellation technique in Underlay cognitive radio (CR) network. Although underlay CR has been shown as a promising technique to better utilize the source of primary users (PUs), its secondary performance will be severely degraded. On one hand, by adapting the Underlay spectrum sharing pattern, secondary users (SUs) would observe the strict power constraints and be interfered by primary users. On the other hand, limited transmit power results in limited transmission range, which greatly degrade the secondary transmission capacity. To solve the problems above, we propose an interference cancellation protocol for multi-hop wireless communication networks in underlay CR, which could develop the long-distance transmission performance and improve the transmission efficiency significantly. As simulation results shows, proposed scheme significantly reduce the secondary outage probability and increase the secondary diversity than the traditional cases.展开更多
This paper focuses on the energy efficiency of cognitive relay (CR) networks with cooperative sensing, joint optimization of the sensing time and the signal-to-noise ratio (SNR) is studied to maximize the energy e...This paper focuses on the energy efficiency of cognitive relay (CR) networks with cooperative sensing, joint optimization of the sensing time and the signal-to-noise ratio (SNR) is studied to maximize the energy efficiency of CR network. Theoretical analysis shows that there exists an optimal sensing time and optimal SNR to make the energy efficiency maximized under a constraint of detection probability. Simulation results illustrate that the optimal fusion rule performs better than the OR rule and the AND rule in terms of the energy efficiency. By properly designing the fusion rule threshold as well as the number of cooperative sensing users, the energy efficiency of CR networks can be further improved.展开更多
文摘To promote reliable and secure communications in the cognitive radio network,the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation.In this paper,we address the classification of superimposed modulations dedicated to 5G multipleinput multiple-output(MIMO)two-way cognitive relay network in realistic channels modeled with Nakagami-m distribution.Our purpose consists of classifying pairs of users modulations from superimposed signals.To achieve this goal,we apply the higher-order statistics in conjunction with the Multi-BoostAB classifier.We use several efficiency metrics including the true positive(TP)rate,false positive(FP)rate,precision,recall,F-Measure and receiver operating characteristic(ROC)area in order to evaluate the performance of the proposed algorithm in terms of correct superimposed modulations classification.Computer simulations prove that our proposal allows obtaining a good probability of classification for ten superimposed modulations at a low signal-to-noise ratio,including the worst case(i.e.,m=0.5),where the fading distribution follows a one-sided Gaussian distribution.We also carry out a comparative study between our proposal usingMultiBoostAB classifier with the decision tree(J48)classifier.Simulation results show that the performance of MultiBoostAB on the superimposed modulations classifications outperforms the one of J48 classifier.In addition,we study the impact of the symbols number,path loss exponent and relay position on the performance of the proposed automatic classification superimposed modulations in terms of probability of correct classification.
基金This work is supported by Sichuan science and Technology Program(2019YFG0212)China Postdoctoral Science Foundation(2019M653401)Sichuan Science and Technology Program(2018GZ0184).
文摘In this paper, we consider a three-hop relay system based on interference cancellation technique in Underlay cognitive radio (CR) network. Although underlay CR has been shown as a promising technique to better utilize the source of primary users (PUs), its secondary performance will be severely degraded. On one hand, by adapting the Underlay spectrum sharing pattern, secondary users (SUs) would observe the strict power constraints and be interfered by primary users. On the other hand, limited transmit power results in limited transmission range, which greatly degrade the secondary transmission capacity. To solve the problems above, we propose an interference cancellation protocol for multi-hop wireless communication networks in underlay CR, which could develop the long-distance transmission performance and improve the transmission efficiency significantly. As simulation results shows, proposed scheme significantly reduce the secondary outage probability and increase the secondary diversity than the traditional cases.
基金supported by the National Science Fund under Grant No. 6087215the Yunnan Research Program of Application Foundation under Grant No.2011FB035the School training fund under granted No.KKZ3201403010
文摘This paper focuses on the energy efficiency of cognitive relay (CR) networks with cooperative sensing, joint optimization of the sensing time and the signal-to-noise ratio (SNR) is studied to maximize the energy efficiency of CR network. Theoretical analysis shows that there exists an optimal sensing time and optimal SNR to make the energy efficiency maximized under a constraint of detection probability. Simulation results illustrate that the optimal fusion rule performs better than the OR rule and the AND rule in terms of the energy efficiency. By properly designing the fusion rule threshold as well as the number of cooperative sensing users, the energy efficiency of CR networks can be further improved.