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
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
In remote terrestrial-satellite networks, caching is a very promising technique to alleviate the burden of space cloudlet(e.g., cache-enabled satellite user terminal) and to improve subscribers' quality of experie...In remote terrestrial-satellite networks, caching is a very promising technique to alleviate the burden of space cloudlet(e.g., cache-enabled satellite user terminal) and to improve subscribers' quality of experience(Qo E) in terms of buffering delay and achievable video streaming rate. In this paper, we studied a Qo E-driven caching placement optimization problem for video streaming that takes into account the required video streaming rate and the social relationship among users. Social ties between users are used to designate a set of helpers with caching capability, which can cache popular files proactively when the cloudlet is idle. We model the utility function of Qo E as a logarithmic function. Then, the caching placement problem is formulated as an optimization problem to maximize the user's average Qo E subject to the storage capacity constraints of the helpers and the cloudlets. Furthermore, we reformulate the problem into a monotone submodular optimization problem with a partition matroid constraint, and an efficient greedy algorithm with 1-1 e approximation ratio is proposed to solve it. Simulation results show that the proposed caching placement approach significantly outperforms the traditional approaches in terms of Qo E, while yields about the same delay and hit ratio performance compare to the delay-minimized scheme.展开更多
In relay-assisted multi-user system, relay coding is important to enhance the robustness and reliability of cooperative transmission. For better adaptability and efficiency, two joint network and fountain coding(JNFC)...In relay-assisted multi-user system, relay coding is important to enhance the robustness and reliability of cooperative transmission. For better adaptability and efficiency, two joint network and fountain coding(JNFC) schemes are proposed. When the condition of all direct channels is worse, JNFC scheme based on distributed LT(DLT) codes is used. Otherwise, JNFC scheme based on multi-dimensional LT(MD-LT) codes is suited. For both two above-mentioned schemes, the united degree distribution design method for short-length fountain codes is proposed. For the latter scheme, MD-LT codes are proposed for equal error protection(EEP) of each user. Simulation results and analysis show that the united degree distribution need less decoding overhead compared with other degree distribution for short-length fountain codes. And then, all users are protected equally in despite of asymmetric uplinks.展开更多
The Internet of things(IoT) as an important application of future communication networks puts a high premium on delay issues. Thus when Io T applications meet heterogeneous networks(HetNets) where macro cells are over...The Internet of things(IoT) as an important application of future communication networks puts a high premium on delay issues. Thus when Io T applications meet heterogeneous networks(HetNets) where macro cells are overlaid with small cells, some traditional problems need rethinking. In this paper, we investigate the delay-addressed association problem in two-tier Het Nets considering different backhaul technologies. Specifically, millimeter wave and fiber links are used to provide high-capacity backhaul for small cells. We first formulate the user association problem to minimize the total delay which depends on the probability of successful transmission, the number of user terminals(UTs), and the number of base stations(BSs). And then two algorithms for active mode and mixed mode are proposed to minimize the network delay. Simulation results show that algorithms based on mutual selection between UTs and BSs have better performance than those based on distance. And algorithms for mixed modes have less delay than those for active mode when the number of BSs is large enough, compared to the number of UTs.展开更多
With the popularity of smart handheld devices, mobile streaming video has multiplied the global network traffic in recent years. A huge concern of users' quality of experience(Qo E) has made rate adaptation method...With the popularity of smart handheld devices, mobile streaming video has multiplied the global network traffic in recent years. A huge concern of users' quality of experience(Qo E) has made rate adaptation methods very attractive. In this paper, we propose a two-phase rate adaptation strategy to improve users' real-time video Qo E. First, to measure and assess video Qo E, we provide a continuous Qo E prediction engine modeled by RNN recurrent neural network. Different from traditional Qo E models which consider the Qo E-aware factors separately or incompletely, our RNN-Qo E model accounts for three descriptive factors(video quality, rebuffering, and rate change) and reflects the impact of cognitive memory and recency. Besides, the video playing is separated into the initial startup phase and the steady playback phase, and we takes different optimization goals for each phase: the former aims at shortening the startup delay while the latter ameliorates the video quality and the rebufferings. Simulation results have shown that RNN-Qo E can follow the subjective Qo E quite well, and the proposed strategy can effectively reduce the occurrence of rebufferings caused by the mismatch between the requested video rates and the fluctuated throughput and attains standout performance on real-time Qo E compared with classical rate adaption methods.展开更多
Femtocell is a promising technology for improving indoor coverage and offloading the macrocell.Femtocells tend to be densely deployed in populated areas such as the dormitories.However,the inter-tier interference seri...Femtocell is a promising technology for improving indoor coverage and offloading the macrocell.Femtocells tend to be densely deployed in populated areas such as the dormitories.However,the inter-tier interference seriously exists in the co-channel Densely Deployed Femtocell Network(DDFN).Since the Femtocell Access Points(FAPs) are randomly deployed by their customers,the interference cannot be predicted in advance.Meanwhile,new characteristics such as the short radius of femtocell and the small number of users lead to the inefficiency of the traditional frequency reuse algorithms such as Fractional Frequency Reuse(FFR).Aiming for the downlink interference coordination in the DDFN,in this paper,we propose a User-oriented Graph based Frequency Allocation(UGFA)algorithm.Firstly,we construct the interference graph for users in the network.Secondly,we study the conventional graph based resources allocation algorithm.Then an improved two steps graph based frequency allocation mechanism is proposed.Simulation results show that UGFA has a high frequency reuse ratio mean while guarantees a better throughput.展开更多
This paper presents a novel spec- trum sharing design aiming at optimising the performance of a Multiuser Orthogonal Freq- uency-Division Multiplexing （MU-OFDM） Co- gnitive Radio Network （CRN） that consists of mul...This paper presents a novel spec- trum sharing design aiming at optimising the performance of a Multiuser Orthogonal Freq- uency-Division Multiplexing （MU-OFDM） Co- gnitive Radio Network （CRN） that consists of multiple secondary Transmitter-Receiver （Tx-Rx） pairs. For most MU-OFDM systems, the Exc- lusive Subchannel Assignment （ESA） is an efficient resource allocation method. Noneth- eless, it is inappropriate for the network consi- dered in this paper, because subchannels shar- ing among secondary Tx-Rx pairs can further improve the system performance. We investi- gate the Weighted Sum Rate （WSR） maximi- zation problem under the Shared Subchannel Assignment （SSA）, where each subchannel is shared by multiple secondary Tx-Rx pairs. With Lagrangian duality technique, we decompose the original resource allocation problem into sev- eral sub-problems on each subchannel and pro- pose a duality-based suhchannel sharing ap- proach. For practical realisation in the cogni- tive systems without central control entity, a distributed duality-based WSR maximization scheme is presented. Simulation results mani- fest that the proposed scheme achieves sig- nificantly better performance than ESA duality scheme.展开更多
The small-cell technology is promising for spectral-efficiency enhancement. However, it usually requires a huge amount of energy consumption. In this paper, queue state information and channel state information are jo...The small-cell technology is promising for spectral-efficiency enhancement. However, it usually requires a huge amount of energy consumption. In this paper, queue state information and channel state information are jointly utilized to minimize the time average of overall energy consumption for a multi-carrier small-cell network, where the inter-cell interference is an intractable problem. Based on the Lyapunov optimization theory, the problem could be solved by dynamically optimizing the problem of user assignment, carrier allocation and power allocation in each time slot. As the optimization problem is NP-hard, we propose a heuristic iteration algorithm to solve it. Numerical results verify that the heuristic algorithm offers an approximate performance as the brute-force algorithm. Moreover, it could bring down the overall energy consumption to different degrees according to the variation of traffic load. Meanwhile, it could achieve the same sum rate as the algorithm which focuses on maximizing system sum rate.展开更多
The effective radio resource allocation al-gorithms, which satisfy diversiform requirements of mobile naltimedia services in wireless cellular net-works, have recently attracted more and more at-tention. This paper pr...The effective radio resource allocation al-gorithms, which satisfy diversiform requirements of mobile naltimedia services in wireless cellular net-works, have recently attracted more and more at-tention. This paper proposes a service-aware scheduling algorithm, in which the Mean Opinion Score （MOS） is chosen as the unified metric of the Quality of Experience （QoE）. As the network needs to provide satisfactory services to all the users, the fairness of QoE should be considered. The Propor- tional Fair （PF） principle is adopted to achieve the trade-off between the network perfonmnce and us- er fairness. Then, an integer progranming problem is formed and the QoE-aware PF scheduling princi-ple is derived by solving the relaxed problem. Simu-lation results show that the proposed scheduling principle can perform better in terms of user fair-ness than the previous principle maximizing the sum of MOS. It also outperfoms the max-rain scheduling principle in terms of average MOS.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 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.
基金supported by Natural Science Foundation of China under Grant No.91738202,91438206
文摘In remote terrestrial-satellite networks, caching is a very promising technique to alleviate the burden of space cloudlet(e.g., cache-enabled satellite user terminal) and to improve subscribers' quality of experience(Qo E) in terms of buffering delay and achievable video streaming rate. In this paper, we studied a Qo E-driven caching placement optimization problem for video streaming that takes into account the required video streaming rate and the social relationship among users. Social ties between users are used to designate a set of helpers with caching capability, which can cache popular files proactively when the cloudlet is idle. We model the utility function of Qo E as a logarithmic function. Then, the caching placement problem is formulated as an optimization problem to maximize the user's average Qo E subject to the storage capacity constraints of the helpers and the cloudlets. Furthermore, we reformulate the problem into a monotone submodular optimization problem with a partition matroid constraint, and an efficient greedy algorithm with 1-1 e approximation ratio is proposed to solve it. Simulation results show that the proposed caching placement approach significantly outperforms the traditional approaches in terms of Qo E, while yields about the same delay and hit ratio performance compare to the delay-minimized scheme.
基金supported in part by a grant from the Ph.D. Programs Foundation of Ministry of Education of China under Grants No. 20094307110004National Natural Science Foundation of China under Grants No.61372098, No.61101074Natural Science Foundation of Hunan Province, China under Grants No.12jj2037
文摘In relay-assisted multi-user system, relay coding is important to enhance the robustness and reliability of cooperative transmission. For better adaptability and efficiency, two joint network and fountain coding(JNFC) schemes are proposed. When the condition of all direct channels is worse, JNFC scheme based on distributed LT(DLT) codes is used. Otherwise, JNFC scheme based on multi-dimensional LT(MD-LT) codes is suited. For both two above-mentioned schemes, the united degree distribution design method for short-length fountain codes is proposed. For the latter scheme, MD-LT codes are proposed for equal error protection(EEP) of each user. Simulation results and analysis show that the united degree distribution need less decoding overhead compared with other degree distribution for short-length fountain codes. And then, all users are protected equally in despite of asymmetric uplinks.
基金supported by the National Natural Science Foundation of China (NSFC) under Grants 61427801 and 61671251the Natural Science Foundation Program through Jiangsu Province of China under Grant BK20150852+3 种基金the open research fund of National Mobile Communications Research Laboratory, Southeast University under Grant 2017D05China Postdoctoral Science Foundation under Grant 2016M590481Jiangsu Planned Projects for Postdoctoral Research Funds under Grant 1501018Asupported by NSFC under Grants 61531011 and 61625106
文摘The Internet of things(IoT) as an important application of future communication networks puts a high premium on delay issues. Thus when Io T applications meet heterogeneous networks(HetNets) where macro cells are overlaid with small cells, some traditional problems need rethinking. In this paper, we investigate the delay-addressed association problem in two-tier Het Nets considering different backhaul technologies. Specifically, millimeter wave and fiber links are used to provide high-capacity backhaul for small cells. We first formulate the user association problem to minimize the total delay which depends on the probability of successful transmission, the number of user terminals(UTs), and the number of base stations(BSs). And then two algorithms for active mode and mixed mode are proposed to minimize the network delay. Simulation results show that algorithms based on mutual selection between UTs and BSs have better performance than those based on distance. And algorithms for mixed modes have less delay than those for active mode when the number of BSs is large enough, compared to the number of UTs.
基金supported by the National Nature Science Foundation of China(NSFC 60622110,61471220,91538107,91638205)National Basic Research Project of China(973,2013CB329006),GY22016058
文摘With the popularity of smart handheld devices, mobile streaming video has multiplied the global network traffic in recent years. A huge concern of users' quality of experience(Qo E) has made rate adaptation methods very attractive. In this paper, we propose a two-phase rate adaptation strategy to improve users' real-time video Qo E. First, to measure and assess video Qo E, we provide a continuous Qo E prediction engine modeled by RNN recurrent neural network. Different from traditional Qo E models which consider the Qo E-aware factors separately or incompletely, our RNN-Qo E model accounts for three descriptive factors(video quality, rebuffering, and rate change) and reflects the impact of cognitive memory and recency. Besides, the video playing is separated into the initial startup phase and the steady playback phase, and we takes different optimization goals for each phase: the former aims at shortening the startup delay while the latter ameliorates the video quality and the rebufferings. Simulation results have shown that RNN-Qo E can follow the subjective Qo E quite well, and the proposed strategy can effectively reduce the occurrence of rebufferings caused by the mismatch between the requested video rates and the fluctuated throughput and attains standout performance on real-time Qo E compared with classical rate adaption methods.
基金supported by the National Natural Science Foundation of China under Grant No.61372092the China National Science and Technology Major Projects on New Generation Broadband Wireless Mobile Communications Network under Grants No.2011ZX03005-004,No.2012ZX03001029-003,No.2012ZX03001008-003
文摘Femtocell is a promising technology for improving indoor coverage and offloading the macrocell.Femtocells tend to be densely deployed in populated areas such as the dormitories.However,the inter-tier interference seriously exists in the co-channel Densely Deployed Femtocell Network(DDFN).Since the Femtocell Access Points(FAPs) are randomly deployed by their customers,the interference cannot be predicted in advance.Meanwhile,new characteristics such as the short radius of femtocell and the small number of users lead to the inefficiency of the traditional frequency reuse algorithms such as Fractional Frequency Reuse(FFR).Aiming for the downlink interference coordination in the DDFN,in this paper,we propose a User-oriented Graph based Frequency Allocation(UGFA)algorithm.Firstly,we construct the interference graph for users in the network.Secondly,we study the conventional graph based resources allocation algorithm.Then an improved two steps graph based frequency allocation mechanism is proposed.Simulation results show that UGFA has a high frequency reuse ratio mean while guarantees a better throughput.
基金ACKNOWLEDGEMENT This work was supported in part by the Na- tional Natural Science Foundation of China un- der Grants No. 60972072, No. 61340033 and the 111 Project of China under Grant No. B08038.
文摘This paper presents a novel spec- trum sharing design aiming at optimising the performance of a Multiuser Orthogonal Freq- uency-Division Multiplexing （MU-OFDM） Co- gnitive Radio Network （CRN） that consists of multiple secondary Transmitter-Receiver （Tx-Rx） pairs. For most MU-OFDM systems, the Exc- lusive Subchannel Assignment （ESA） is an efficient resource allocation method. Noneth- eless, it is inappropriate for the network consi- dered in this paper, because subchannels shar- ing among secondary Tx-Rx pairs can further improve the system performance. We investi- gate the Weighted Sum Rate （WSR） maximi- zation problem under the Shared Subchannel Assignment （SSA）, where each subchannel is shared by multiple secondary Tx-Rx pairs. With Lagrangian duality technique, we decompose the original resource allocation problem into sev- eral sub-problems on each subchannel and pro- pose a duality-based suhchannel sharing ap- proach. For practical realisation in the cogni- tive systems without central control entity, a distributed duality-based WSR maximization scheme is presented. Simulation results mani- fest that the proposed scheme achieves sig- nificantly better performance than ESA duality scheme.
基金partially supported by National Basic Research Program of China (2013CB329002)National Natural Science Foundation of China (61631013)+6 种基金The National High Technology Research and Development Program of China(2014AA01A703)Science Fund for Creative Research Groups of NSFC (61321061)National Major Project (2017ZX03001011)International Science and Technology Cooperation Program (2014DFT10320)National Science Foundation of China (61701457 \& 61771286)Tsinghua-Qualcomm Joint Research ProgramHuawei Innovation Research Program
文摘The small-cell technology is promising for spectral-efficiency enhancement. However, it usually requires a huge amount of energy consumption. In this paper, queue state information and channel state information are jointly utilized to minimize the time average of overall energy consumption for a multi-carrier small-cell network, where the inter-cell interference is an intractable problem. Based on the Lyapunov optimization theory, the problem could be solved by dynamically optimizing the problem of user assignment, carrier allocation and power allocation in each time slot. As the optimization problem is NP-hard, we propose a heuristic iteration algorithm to solve it. Numerical results verify that the heuristic algorithm offers an approximate performance as the brute-force algorithm. Moreover, it could bring down the overall energy consumption to different degrees according to the variation of traffic load. Meanwhile, it could achieve the same sum rate as the algorithm which focuses on maximizing system sum rate.
基金This paper was supported partially by the Program for New Century Excellent Talents in University under Crant No. NCET-11-0600 the National Natural Science Foundation of China under Crant NN76022 and the France Telecom R ＆ D Beijing Co. Ltd.
文摘The effective radio resource allocation al-gorithms, which satisfy diversiform requirements of mobile naltimedia services in wireless cellular net-works, have recently attracted more and more at-tention. This paper proposes a service-aware scheduling algorithm, in which the Mean Opinion Score （MOS） is chosen as the unified metric of the Quality of Experience （QoE）. As the network needs to provide satisfactory services to all the users, the fairness of QoE should be considered. The Propor- tional Fair （PF） principle is adopted to achieve the trade-off between the network perfonmnce and us- er fairness. Then, an integer progranming problem is formed and the QoE-aware PF scheduling princi-ple is derived by solving the relaxed problem. Simu-lation results show that the proposed scheduling principle can perform better in terms of user fair-ness than the previous principle maximizing the sum of MOS. It also outperfoms the max-rain scheduling principle in terms of average MOS.
