This paper addresses the power con- trol problems of Cognitive Radio （CR） trader transmission power and interference tempera- ture constraints. First, we propose the interfer- ence constraint which ensures that the ...This paper addresses the power con- trol problems of Cognitive Radio （CR） trader transmission power and interference tempera- ture constraints. First, we propose the interfer- ence constraint which ensures that the Quality of Service （QoS） standards for primary users is considered and a non-cooperative game power control model. Based on the proposed model, we developed a logical utility function based on the Signal-to-Interference-Noise Ratio （S/NR） and a novel algorithm network power control. that is suitable for CR Then, the existence and uniqueness of the Nash Equilibrium （NE） in our utility function are proved by the principle of game theory and the corresponding optimi- zations. Compared to traditional algorithms, the proposed one could converge to an NE in 3-5 iterative operations by setting an appropriate pricing factor. Finally, simulation results ver- ified the stability and superiority of the novel algorithm in flat-fading channel environments.展开更多
The performance of uplink distributed massive multiple-input multiple-output(MIMO)systems with crosslayer design(CLD) is investigated over Rayleigh fading channel, which combines the discrete rate adaptive modulation ...The performance of uplink distributed massive multiple-input multiple-output(MIMO)systems with crosslayer design(CLD) is investigated over Rayleigh fading channel, which combines the discrete rate adaptive modulation with truncated automatic repeat request. By means of the performance analysis, the closed-form expressions of average packet error rate(APER)and overall average spectral efficiency(ASE)of distributed massive MIMO systems with CLD are derived based on the conditional probability density function of each user’s approximate effective signal-to-noise ratio(SNR)and the switching thresholds under the target packet loss rate(PLR)constraint.With these results,using the approximation of complementary error functions,the approximate APER and overall ASE are also deduced. Simulation results illustrate that the obtained theoretical ASE and APER can match the corresponding simulations well. Besides,the target PLR requirement is satisfied,and the distributed massive MIMO systems offer an obvious performance gain over the co-located massive MIMO systems.展开更多
For the issue of flow control for Available Bit Rate (ABR) traffic in ATM network,a new improved Explicit Rate (ER) algorithm named Dynamic Double Threshold Congestion Indication (DDTCI) algorithm is presented based o...For the issue of flow control for Available Bit Rate (ABR) traffic in ATM network,a new improved Explicit Rate (ER) algorithm named Dynamic Double Threshold Congestion Indication (DDTCI) algorithm is presented based on the Explicit Forward Congestion Indication (EFCI) Current Cell Rate (CCR) algorithm and Relative Rate (RR) algorithm. Different from the early ER algorithm, both the high-level and the low-level threshold is dynamically changing according to the state of the bottleneck node. We determinate the congestion state with the information of the two dynamic threshold, and control the cell rate of the source by feed back mechanism. Except for the well performance in both link utilization and fairness in distribution of available bandwidth, the improved algorithm can alleviate the fluctuation of sending rate dramatically. The mechanism is modeled by a fluid model, and the useful expressions are derived.Simulation results show up our conclusion.展开更多
Based on the cross-layer design, the power-optimization problem of Macro-Femto Heterogeneous Networks （HetNets） has been formulated. The constraints of power and re-source block allocation in the physical layer, del...Based on the cross-layer design, the power-optimization problem of Macro-Femto Heterogeneous Networks （HetNets） has been formulated. The constraints of power and re-source block allocation in the physical layer, delay and target data rate in the medium ac-cess control layer, urgent queue length in the network layer, and packet error rate in the transport layer, have been considered. The original problem is non-deterministic polyno-mial time hard, which cannot be solved practi-cally. After the restrictions of upper layers are translated into constraints with physical layer parameters, and the integer restrictions are relaxed, the original problem can be decom- posed into convex optimization subproblems. The optimal solutions of resource block allo-cation and power allocation can be obtained by using the Lagrangian optimization. Simula-tion results show that the proposed scheme is better than both the round robin algorithm and the max-rain one in terms of energy efficiency, throughput and service fairness. The round robin algorithm and the max-min one only focus on the user fairness rather than quality of service fairness. Compared to the round robin scheme （the max-min one）, the proposed scheme improves the energy efficiency 58.85% （62.41%）, the throughput 19.09% （25.25%）, the service fairness 57.69% （35.48%）.展开更多
Abstract：Aiming at achieving better Quality of Service （QoS） provisioning in distributed wireless cooperative networks, a novel energy efficient jammer selection approach is proposed in this pa per. We employ Secre...Abstract：Aiming at achieving better Quality of Service （QoS） provisioning in distributed wireless cooperative networks, a novel energy efficient jammer selection approach is proposed in this pa per. We employ Secrecy Capacity （SC） to charac terize the security of transmission. In order to ac curately describe the timevarying characteristic, related channels are modeled as FiniteState M ark ov Channels （FSMCs）. The remaining energy of candidate node is considered in a similar way.展开更多
Efficient spectrum resource allocation in wireless heterogeneous networks is important for improving the system throughput and guaranteeing the user's Quality-of-Service(QoS).In this paper,we propose an enhanced a...Efficient spectrum resource allocation in wireless heterogeneous networks is important for improving the system throughput and guaranteeing the user's Quality-of-Service(QoS).In this paper,we propose an enhanced algorithm for spectrum resource allocation in heterogeneous networks.First,the bandwidth of each user is determined by the user's rate demand and the channel state.Second,graph theory is enhanced and used to improve the spectrum efficiency.Third,spectrum resource is dynamically split between macrocell and femtocells with the changes of users' conditions.Our simulation results show that the proposed algorithm improves the system throughput significantly and also guarantees the fairness for the users.展开更多
Naive Bayes(NB) is one of the most popular classification methods. It is particularly useful when the dimension of the predictor is high and data are generated independently. In the meanwhile, social network data are ...Naive Bayes(NB) is one of the most popular classification methods. It is particularly useful when the dimension of the predictor is high and data are generated independently. In the meanwhile, social network data are becoming increasingly accessible, due to the fast development of various social network services and websites. By contrast, data generated by a social network are most likely to be dependent. The dependency is mainly determined by their social network relationships. Then, how to extend the classical NB method to social network data becomes a problem of great interest. To this end, we propose here a network-based naive Bayes(NNB) method, which generalizes the classical NB model to social network data. The key advantage of the NNB method is that it takes the network relationships into consideration. The computational efficiency makes the NNB method even feasible in large scale social networks. The statistical properties of the NNB model are theoretically investigated. Simulation studies have been conducted to demonstrate its finite sample performance.A real data example is also analyzed for illustration purpose.展开更多
基金partially supported by the National Natural Science Foundation of China under Grant No.61172073the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University under Grant No.2012D19+1 种基金the Fundamental Research Funds for the Central Universities,Beijing Jiaotong University under Grant No.2013JBZ01the Program for New Century Excellent Talents in University of Ministry of Education of China under Grant No.NCET-12-0766
文摘This paper addresses the power con- trol problems of Cognitive Radio （CR） trader transmission power and interference tempera- ture constraints. First, we propose the interfer- ence constraint which ensures that the Quality of Service （QoS） standards for primary users is considered and a non-cooperative game power control model. Based on the proposed model, we developed a logical utility function based on the Signal-to-Interference-Noise Ratio （S/NR） and a novel algorithm network power control. that is suitable for CR Then, the existence and uniqueness of the Nash Equilibrium （NE） in our utility function are proved by the principle of game theory and the corresponding optimi- zations. Compared to traditional algorithms, the proposed one could converge to an NE in 3-5 iterative operations by setting an appropriate pricing factor. Finally, simulation results ver- ified the stability and superiority of the novel algorithm in flat-fading channel environments.
基金supported in part by the National Natural Science Foundation of China (No. 61971220)the Fundamental Research Funds for the Central Universities of Nanjing University of Aeronautics and Astronautics(NUAA)(No.kfjj20200414)Natural Science Foundation of Jiangsu Province in China (No. BK20181289)。
文摘The performance of uplink distributed massive multiple-input multiple-output(MIMO)systems with crosslayer design(CLD) is investigated over Rayleigh fading channel, which combines the discrete rate adaptive modulation with truncated automatic repeat request. By means of the performance analysis, the closed-form expressions of average packet error rate(APER)and overall average spectral efficiency(ASE)of distributed massive MIMO systems with CLD are derived based on the conditional probability density function of each user’s approximate effective signal-to-noise ratio(SNR)and the switching thresholds under the target packet loss rate(PLR)constraint.With these results,using the approximation of complementary error functions,the approximate APER and overall ASE are also deduced. Simulation results illustrate that the obtained theoretical ASE and APER can match the corresponding simulations well. Besides,the target PLR requirement is satisfied,and the distributed massive MIMO systems offer an obvious performance gain over the co-located massive MIMO systems.
文摘For the issue of flow control for Available Bit Rate (ABR) traffic in ATM network,a new improved Explicit Rate (ER) algorithm named Dynamic Double Threshold Congestion Indication (DDTCI) algorithm is presented based on the Explicit Forward Congestion Indication (EFCI) Current Cell Rate (CCR) algorithm and Relative Rate (RR) algorithm. Different from the early ER algorithm, both the high-level and the low-level threshold is dynamically changing according to the state of the bottleneck node. We determinate the congestion state with the information of the two dynamic threshold, and control the cell rate of the source by feed back mechanism. Except for the well performance in both link utilization and fairness in distribution of available bandwidth, the improved algorithm can alleviate the fluctuation of sending rate dramatically. The mechanism is modeled by a fluid model, and the useful expressions are derived.Simulation results show up our conclusion.
基金supported in part by the project of National Natural Science Foundation of China under Grant No. 61071075National Science and Technology Major Project of China under Grant No. 2010ZX03003-001-02+1 种基金National Science and Technology Major Project of China under Grant No. 2011ZX03004003the Chinese Ministry of Education in the project of the Fundamental Research Funds for the Central Universities under Grant No.2011YJS216
文摘Based on the cross-layer design, the power-optimization problem of Macro-Femto Heterogeneous Networks （HetNets） has been formulated. The constraints of power and re-source block allocation in the physical layer, delay and target data rate in the medium ac-cess control layer, urgent queue length in the network layer, and packet error rate in the transport layer, have been considered. The original problem is non-deterministic polyno-mial time hard, which cannot be solved practi-cally. After the restrictions of upper layers are translated into constraints with physical layer parameters, and the integer restrictions are relaxed, the original problem can be decom- posed into convex optimization subproblems. The optimal solutions of resource block allo-cation and power allocation can be obtained by using the Lagrangian optimization. Simula-tion results show that the proposed scheme is better than both the round robin algorithm and the max-rain one in terms of energy efficiency, throughput and service fairness. The round robin algorithm and the max-min one only focus on the user fairness rather than quality of service fairness. Compared to the round robin scheme （the max-min one）, the proposed scheme improves the energy efficiency 58.85% （62.41%）, the throughput 19.09% （25.25%）, the service fairness 57.69% （35.48%）.
基金This paper was jointly supported by the National Natural Science Foundation of China，the State Major Science and Technology Special Projects，the Science Technology Innovation Foundation for Young Teachers in BUPT
文摘Abstract：Aiming at achieving better Quality of Service （QoS） provisioning in distributed wireless cooperative networks, a novel energy efficient jammer selection approach is proposed in this pa per. We employ Secrecy Capacity （SC） to charac terize the security of transmission. In order to ac curately describe the timevarying characteristic, related channels are modeled as FiniteState M ark ov Channels （FSMCs）. The remaining energy of candidate node is considered in a similar way.
基金supported in part by National Natural Science Foundation(61231008)Natural Science Foundation of Shannxi Province(2015JQ6248)+1 种基金National S&T Major Project(2012ZX03003005-005)the 111 Project (B08038)
文摘Efficient spectrum resource allocation in wireless heterogeneous networks is important for improving the system throughput and guaranteeing the user's Quality-of-Service(QoS).In this paper,we propose an enhanced algorithm for spectrum resource allocation in heterogeneous networks.First,the bandwidth of each user is determined by the user's rate demand and the channel state.Second,graph theory is enhanced and used to improve the spectrum efficiency.Third,spectrum resource is dynamically split between macrocell and femtocells with the changes of users' conditions.Our simulation results show that the proposed algorithm improves the system throughput significantly and also guarantees the fairness for the users.
基金supported by National Natural Science Foundation of China (Grant Nos. 11701560, 11501093, 11631003, 11690012, 71532001 and 11525101)the Fundamental Research Funds for the Central Universities+5 种基金the Fundamental Research Funds for the Central Universities (Grant Nos. 130028613, 130028729 and 2412017FZ030)the Research Funds of Renmin University of China (Grant No. 16XNLF01)the Beijing Municipal Social Science Foundation (Grant No. 17GLC051)Fund for Building World-Class Universities (Disciplines) of Renmin University of ChinaChina’s National Key Research Special Program (Grant No. 2016YFC0207700)Center for Statistical Science at Peking University
文摘Naive Bayes(NB) is one of the most popular classification methods. It is particularly useful when the dimension of the predictor is high and data are generated independently. In the meanwhile, social network data are becoming increasingly accessible, due to the fast development of various social network services and websites. By contrast, data generated by a social network are most likely to be dependent. The dependency is mainly determined by their social network relationships. Then, how to extend the classical NB method to social network data becomes a problem of great interest. To this end, we propose here a network-based naive Bayes(NNB) method, which generalizes the classical NB model to social network data. The key advantage of the NNB method is that it takes the network relationships into consideration. The computational efficiency makes the NNB method even feasible in large scale social networks. The statistical properties of the NNB model are theoretically investigated. Simulation studies have been conducted to demonstrate its finite sample performance.A real data example is also analyzed for illustration purpose.
