In order to meet the exponentially increasing demand on mobile data traffic, self-backhaul ultra-dense networks(UDNs) combined with millimeter wave(mm Wave) communications are expected to provide high spatial multiple...In order to meet the exponentially increasing demand on mobile data traffic, self-backhaul ultra-dense networks(UDNs) combined with millimeter wave(mm Wave) communications are expected to provide high spatial multiplexing gain and wide bandwidths for multi-gigabit peak data rates. In selfbackhaul UDNs, how to make the radio access rates of small cells match their backhaul rates by user association and how to dynamically allocate bandwidth for the access links and backhaul links to balance two-hop link resources are two key problems on improving the overall throughputs. Based on this, a joint scheme of user association and resource allocation is proposed in self-backhaul ultra-dense networks. Because of the combinatorial and nonconvex features of the original optimization problem, it has been divided into two subproblems. Firstly, to make the radio access rates of small base stations match their backhaul rates and maximize sum access rates per Hz of all small cells, a proportional constraint is introduced, and immune optimization algorithm(IOA) is adopted to optimize the association indicator variables and the boresight angles of between users and base stations. Then, the optimal backhaul and access bandwidths are calculated by differentiating the general expression of overall throughput. Simulation results indicatethat the proposed scheme increases the overall throughputs significantly compared to the traditional minimum-distance based association scheme.展开更多
Interference alignment(IA) is one of the promising measures for the multi-user network to manage interference. The rank constraints rank minimization means that interference spans the lowest dimensional subspace and t...Interference alignment(IA) is one of the promising measures for the multi-user network to manage interference. The rank constraints rank minimization means that interference spans the lowest dimensional subspace and the useful signal spans all available spatial dimensions. In order to improve the performance of two-way relay network, we can use rank constrained rank minimization(RCRM) to solve the IA problem. This paper proposes left reweighted nuclear norm minimization-γalgorithm and selective coupling reweighted nuclear norm minimization algorithm to implement interference alignment in two-way relay networks. The left reweighted nuclear norm minimization-γ algorithm is based on reweighted nuclear norm minimization algorithm and has a novel γ choosing rule. The selective coupling reweighted nuclear norm minimization algorithm weighting methods choose according to singular value of interference matrixes. Simulation results show that the proposed algorithms considerably improve the sum rate performance and achieve the higher average achievable multiplexing gain in two-way relay interference networks.展开更多
Cooperation allows wireless network users to benefit from various gains such as an in- crease in the achieved rate or an improvement in the bit error rate. In the paper, we propose a distributed Hierarchical Game （HG...Cooperation allows wireless network users to benefit from various gains such as an in- crease in the achieved rate or an improvement in the bit error rate. In the paper, we propose a distributed Hierarchical Game （HG） theoretic framework over multi-user cooperative communication networks to stimulate cooperation and improve the network performance. First, we study a two- user decision making game in the OFDMA based subscriber cooperative relaying network, in which subscribers transmit their own data in the first phase, while helping to retransmit their partner＇s or choosing to freeride in the second phase. Instead of consulting to a global optimal solution, we decouple the cooperation resource allocation into two level subproblems： a user level Nash game for distributed cooperation decision and a Base Station （BS） level coalition game for centralized resource allocation. In the proposed HG algorithm, where mutual cooperation is preferred and total payoff is transferable, we prove it converges to a unique optimal equilibrium and resolve the subcarrier as-signment and power allocation among the couples. Besides, we discuss the existence of the publishing and rewarding coefficients in order to encourage cooperation. Then, we extend the HG to multi-user cases by coupling among subscribers according to the location information. The simulation results show that the proposed scheme with the distributed HG game achieves a well tradeoff between fairness and efficiency by improving the transmission efficiency of adverse users and outperforms those employing centralized schemes.展开更多
The user association and wireless backhaul bandwidth allocation for a two-tier heterogeneous network （HetNet） in the mil- limeter wave （mmWave） band is proposed in this article. The two-tier HetNet is built up wit...The user association and wireless backhaul bandwidth allocation for a two-tier heterogeneous network （HetNet） in the mil- limeter wave （mmWave） band is proposed in this article. The two-tier HetNet is built up with a macro base station （MBS） and several small cell SBSs, where the MBS is assumed to be equipped with large-scale antenna arrays but the SBSs only have single-antenna capa- bility and they rely on the wireless link to the MBS for backhaul. The sum of logarithmic user rate, which is established according to the result of multi-user Multiple Input Mul- tiple Output （MIMO） downlink employing Zero-Force Beamforming （ZFBF）, is chosen as the network utility for the objective func- tion. And a distributed optimization algorithm based on primal and dual decomposition is used to jointly optimize the user association variable xj,z and the wireless backhaul band- width factor α. Simulation results reveal that the distributed optimization algorithm jointly optimizing two variables outperforms the con- ventional SINR-based user association strate- gies.展开更多
E-mail communication network evolution model based on user information propagation is studied. First, mathematical representation of weighted e-mail communication network is proposed, and network center parameters of ...E-mail communication network evolution model based on user information propagation is studied. First, mathematical representation of weighted e-mail communication network is proposed, and network center parameters of Enron dataset and the distribution of node degree and strength are analyzed. Then, some rules of e-mail communication network evolution are found. Second, the model of e-mail information propagation is described, and e-mail communication network evolution model based on user information propagation is proposed. Lastly, the simulation proves the correctness of the distribution characteristic of degree and strength of the model proposed and then verifies that the model proposed is closer to the real situation of e-mail communication network through parameter comparison. This research provides the basis for other researches on social network evolution and data communication.展开更多
Similarity matching and this paper, a saliency-based information presentation are two matching algorithm is proposed key factors in information retrieval. In for user-oriented search based on the psychological studies...Similarity matching and this paper, a saliency-based information presentation are two matching algorithm is proposed key factors in information retrieval. In for user-oriented search based on the psychological studies on human perception, and major emphasis on the saliently similar aspect of objects to be compared is placed and thus the search result is more agreeable for users. After relevant results are obtained, the cluster-based browsing algorithm is adopted for search result presentation based on social network analysis. By organizing the results in clustered lists, the user can have a general understanding of the whole collection by viewing only a small part of results and locate those of major interest rapidly. Experimental results demonstrate the advantages of the proposed algorithm over the traditional work.展开更多
In the upcoming 5 G heterogeneous networks, leveraging multiple radio access technologies(RATs) shows to be a crucial issue in achieving RAT multiplexing gain to meet the explosive traffic demand. For always best conn...In the upcoming 5 G heterogeneous networks, leveraging multiple radio access technologies(RATs) shows to be a crucial issue in achieving RAT multiplexing gain to meet the explosive traffic demand. For always best connection(ABC), users tend to activate parallel transmission across all available RATs. However from a system-wide perspective, this might not be optimal given the context of network load, interference and diverse service requirements. To intelligently determine how to use these multi-RAT access resources concurrently, this paper proposes a joint multi-RAT user association and resource allocation strategy with triple decision and integrated context awareness of users and networks. A dynamic game based ant colony algorithm(GACA) is designed to simultaneously maximize the system utility and the fairness of resource allocation. Simulation results show that it's more reasonable to make multi-RAT association decision from a system-wide viewpoint than from an individual one. Compared to max-SNR based and ABC based strategies, the proposed method alleviates network congestion and optimizes resource allocation. It obtains 39%~70% performance improvement.展开更多
基金supported by NSFC under Grant 61471303EU FP7 QUICK project under Grant PIRSES-GA-2013-612652
文摘In order to meet the exponentially increasing demand on mobile data traffic, self-backhaul ultra-dense networks(UDNs) combined with millimeter wave(mm Wave) communications are expected to provide high spatial multiplexing gain and wide bandwidths for multi-gigabit peak data rates. In selfbackhaul UDNs, how to make the radio access rates of small cells match their backhaul rates by user association and how to dynamically allocate bandwidth for the access links and backhaul links to balance two-hop link resources are two key problems on improving the overall throughputs. Based on this, a joint scheme of user association and resource allocation is proposed in self-backhaul ultra-dense networks. Because of the combinatorial and nonconvex features of the original optimization problem, it has been divided into two subproblems. Firstly, to make the radio access rates of small base stations match their backhaul rates and maximize sum access rates per Hz of all small cells, a proportional constraint is introduced, and immune optimization algorithm(IOA) is adopted to optimize the association indicator variables and the boresight angles of between users and base stations. Then, the optimal backhaul and access bandwidths are calculated by differentiating the general expression of overall throughput. Simulation results indicatethat the proposed scheme increases the overall throughputs significantly compared to the traditional minimum-distance based association scheme.
基金supported by the National Science Foundation of China (NO.61271240, 61671253)
文摘Interference alignment(IA) is one of the promising measures for the multi-user network to manage interference. The rank constraints rank minimization means that interference spans the lowest dimensional subspace and the useful signal spans all available spatial dimensions. In order to improve the performance of two-way relay network, we can use rank constrained rank minimization(RCRM) to solve the IA problem. This paper proposes left reweighted nuclear norm minimization-γalgorithm and selective coupling reweighted nuclear norm minimization algorithm to implement interference alignment in two-way relay networks. The left reweighted nuclear norm minimization-γ algorithm is based on reweighted nuclear norm minimization algorithm and has a novel γ choosing rule. The selective coupling reweighted nuclear norm minimization algorithm weighting methods choose according to singular value of interference matrixes. Simulation results show that the proposed algorithms considerably improve the sum rate performance and achieve the higher average achievable multiplexing gain in two-way relay interference networks.
基金Acknowledgements This work is supported by the National Natural Science Foundation of China under Grant No. 60971083, National High-Tech Research and Development Plan of China under Grant No. 2009AA01Z206 and National International Science and Technology Cooperation Project under Granted NO.2008DFA12090.
文摘Cooperation allows wireless network users to benefit from various gains such as an in- crease in the achieved rate or an improvement in the bit error rate. In the paper, we propose a distributed Hierarchical Game （HG） theoretic framework over multi-user cooperative communication networks to stimulate cooperation and improve the network performance. First, we study a two- user decision making game in the OFDMA based subscriber cooperative relaying network, in which subscribers transmit their own data in the first phase, while helping to retransmit their partner＇s or choosing to freeride in the second phase. Instead of consulting to a global optimal solution, we decouple the cooperation resource allocation into two level subproblems： a user level Nash game for distributed cooperation decision and a Base Station （BS） level coalition game for centralized resource allocation. In the proposed HG algorithm, where mutual cooperation is preferred and total payoff is transferable, we prove it converges to a unique optimal equilibrium and resolve the subcarrier as-signment and power allocation among the couples. Besides, we discuss the existence of the publishing and rewarding coefficients in order to encourage cooperation. Then, we extend the HG to multi-user cases by coupling among subscribers according to the location information. The simulation results show that the proposed scheme with the distributed HG game achieves a well tradeoff between fairness and efficiency by improving the transmission efficiency of adverse users and outperforms those employing centralized schemes.
基金supported by NSFC under Grant (61725101 and 61771036)the ZTE Corporation, State Key Lab of Rail Traffic Control and Safety Project under Grant (RCS2017ZZ004 and RCS2017ZT008)+1 种基金Beijing Natural Science Foundation under Grant L161009supported by the Open Research Fund of National Mobile Communications Research Laboratory, Southeast University, under grant 2015D04
文摘The user association and wireless backhaul bandwidth allocation for a two-tier heterogeneous network （HetNet） in the mil- limeter wave （mmWave） band is proposed in this article. The two-tier HetNet is built up with a macro base station （MBS） and several small cell SBSs, where the MBS is assumed to be equipped with large-scale antenna arrays but the SBSs only have single-antenna capa- bility and they rely on the wireless link to the MBS for backhaul. The sum of logarithmic user rate, which is established according to the result of multi-user Multiple Input Mul- tiple Output （MIMO） downlink employing Zero-Force Beamforming （ZFBF）, is chosen as the network utility for the objective func- tion. And a distributed optimization algorithm based on primal and dual decomposition is used to jointly optimize the user association variable xj,z and the wireless backhaul band- width factor α. Simulation results reveal that the distributed optimization algorithm jointly optimizing two variables outperforms the con- ventional SINR-based user association strate- gies.
基金sponsored by the National Natural Science Foundation of China under grant number No. 61100008, 61201084the China Postdoctoral Science Foundation under Grant No. 2013M541346+3 种基金Heilongiiang Postdoctoral Special Fund (Postdoctoral Youth Talent Program) under Grant No. LBH-TZ0504Heilongjiang Postdoctoral Fund under Grant No. LBH-Z13058the Natural Science Foundation of Heilongjiang Province of China under Grant No. QC2015076Funds for the Central Universities of China under grant number HEUCF100602
文摘E-mail communication network evolution model based on user information propagation is studied. First, mathematical representation of weighted e-mail communication network is proposed, and network center parameters of Enron dataset and the distribution of node degree and strength are analyzed. Then, some rules of e-mail communication network evolution are found. Second, the model of e-mail information propagation is described, and e-mail communication network evolution model based on user information propagation is proposed. Lastly, the simulation proves the correctness of the distribution characteristic of degree and strength of the model proposed and then verifies that the model proposed is closer to the real situation of e-mail communication network through parameter comparison. This research provides the basis for other researches on social network evolution and data communication.
基金Supported by the Fund for Basic Research of National Non-Profit Research Institutes(No.XK2012-2,ZD2012-7-2)the Fund for Preresearch Project of ISTIC(No.YY201208)
文摘Similarity matching and this paper, a saliency-based information presentation are two matching algorithm is proposed key factors in information retrieval. In for user-oriented search based on the psychological studies on human perception, and major emphasis on the saliently similar aspect of objects to be compared is placed and thus the search result is more agreeable for users. After relevant results are obtained, the cluster-based browsing algorithm is adopted for search result presentation based on social network analysis. By organizing the results in clustered lists, the user can have a general understanding of the whole collection by viewing only a small part of results and locate those of major interest rapidly. Experimental results demonstrate the advantages of the proposed algorithm over the traditional work.
基金supported by the National Natural Science Fund of China(Grant NO.61771065,Grant NO.61571054 and Grant NO.61631005)Beijing Nova Program(NO.Z151100000315077)
文摘In the upcoming 5 G heterogeneous networks, leveraging multiple radio access technologies(RATs) shows to be a crucial issue in achieving RAT multiplexing gain to meet the explosive traffic demand. For always best connection(ABC), users tend to activate parallel transmission across all available RATs. However from a system-wide perspective, this might not be optimal given the context of network load, interference and diverse service requirements. To intelligently determine how to use these multi-RAT access resources concurrently, this paper proposes a joint multi-RAT user association and resource allocation strategy with triple decision and integrated context awareness of users and networks. A dynamic game based ant colony algorithm(GACA) is designed to simultaneously maximize the system utility and the fairness of resource allocation. Simulation results show that it's more reasonable to make multi-RAT association decision from a system-wide viewpoint than from an individual one. Compared to max-SNR based and ABC based strategies, the proposed method alleviates network congestion and optimizes resource allocation. It obtains 39%~70% performance improvement.
