A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network...A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network.Due to the user mobility and the coverage of small cells,the network load often becomes unbalanced,resulting in poor network performance.Mobility management has become an important issue to ensure seamless communication when users move between cells,and proactive mobility management is one of the important functions of the active Self-Organizing Network(SON).This paper proposes a proactive mobility management framework for active SON,which transforms the original reactive load balancing into a forward-aware and proactive load balancing.The proposed framework firstly uses the BART model to predict the users’temporal and spatial mobility based on a weekly cycle and then formulate the MLB optimization problem based on the soft load.Two solutions are proposed to solve the above MLB problem.The simulation results show that the proposed method can better optimize the network performance and realize intelligent mobile management for the future network.展开更多
In heterogeneous networks(Het Nets), it is desirable to offload users from macro cells to small cells to achieve load balancing. However, the offloaded users suffer a strong inter-tier interference. To guarantee the...In heterogeneous networks(Het Nets), it is desirable to offload users from macro cells to small cells to achieve load balancing. However, the offloaded users suffer a strong inter-tier interference. To guarantee the performance of the offloaded users, the interference from macro cells should be carefully managed. In this paper, we jointly optimize load balancing and interference coordination in multi-antenna Het Nets. Different from previous works, instead of almost blank subframes(ABS) on which the macro cells waste time resource, the macro cells suppress the interference to the offloaded users by zero-forcing beamforming(ZFBF) on interference nulling subframes(INS). Considering user association cannot be conduct frequently, we derive the long-term throughput of users over Rayleigh fading channels while previous works focused on instantaneous rate. From the perspective of the spectrum efficiency and user fairness, we formulate a long-term network-wide utility maximization problem. By decomposing the problem into two subproblems, we propose an efficient joint load balancing and interference coordination strategy. Simulation results show that our proposal can achieve good system performance gains over counterparts in term of the network utility, cell edge throughput and average throughput.展开更多
Heterogeneous Networks(HetNets)and cell densification represent promising solutions for the surging data traffic demand in wireless networks.In dense HetNets,user traffic is steered toward the Low-Power Node(LPN)when ...Heterogeneous Networks(HetNets)and cell densification represent promising solutions for the surging data traffic demand in wireless networks.In dense HetNets,user traffic is steered toward the Low-Power Node(LPN)when possible to enhance the user throughput and system capacity by increasing the area spectral efficiency.However,because of the transmit power differences in different tiers of HetNets and irregular service demand,a load imbalance typically exists among different serving nodes.To offload more traffic to LPNs and coordinate the Inter-Cell Interference(ICI),Third-Generation Partnership Project(3GPP)has facilitated the development of the Cell Range Expansion(CRE),enhanced Inter-Cell Interference Coordination(eICIC)and Further enhanced ICIC(FeICIC).In this paper,we develop a cell clustering-based load-aware offsetting and an adaptive Low-Power Subframe(LPS)approach.Our solution allows the separation of User Association(UA)functions at the User Equipment(UE)and network server such that users can make a simple cell-selection decision similar to that in the maximum Received Signal Strength(max-RSS)based UA scheme,where the network server computes the load-aware offsetting and required LPS periods based on the load conditions of the system.The proposed solution is evaluated using system-level simulations wherein the results correspond to performance changes in different service regions.Results show that our method effectively solves the offloading and interference coordination problems in dense HetNets.展开更多
Because of different system capacities of base station (BS) or access point (AP) and ununiformity of traffic distribution in different cells, quantities of new call users may be blocked in overloaded cell in commu...Because of different system capacities of base station (BS) or access point (AP) and ununiformity of traffic distribution in different cells, quantities of new call users may be blocked in overloaded cell in communication hot spots. Whereas in some neighboring under-loaded cells, bandwidth may be superfluous because there are only few users to request services. In order to raise resource utilization of the whole heterogeneous networks, several novel load balancing strategies are proposed, which combine the call ad- mission control policy and multi-hop routing protocol of ad-hoc network for load balancing. These loadbalancing strategies firstly make a decision whether to admit a new call or not by considering some parameters like load index and route cost, etc., and then transfer the denied users into neighboring under-loaded cell with surplus channel according to optimum multi-hop routing algorithm. Simulation results show that the proposed load balancing strategies can distribute traffics to the whole heterogeneous wireless netorks, improve the load balance index efficiently, and avoid the call block phenomenon almost absolutely.展开更多
In order to solve the problem that determining decision factors weights is of subjectivity in heterogeneous wireless network selection algorithm, a network selection algorithm based on extension theory and fuzzy analy...In order to solve the problem that determining decision factors weights is of subjectivity in heterogeneous wireless network selection algorithm, a network selection algorithm based on extension theory and fuzzy analytic hierarchy process (FAHP) is proposed in this paper. In addition, user and operator codetermine the optimal network using the proposed algorithm, which can give consideration to user and operator benefits. The fuzzy judgment matrix is coustructed by membership degree of decision factors which is calculated according to extension theory. The comprehensive weight of each decision factor is obtained using FAHP. Finally, the optimal network is selected through total property value ranldng of each candidate network under user preference and operator preference. The simulation results show that the proposed algorithm can select the optimal network efficiently and accurately, satisfy user preference, and implement load balance between networks.展开更多
In Heterogeneous Networks (HetNets), Integrating Device-to-Device communication (D2D) techniques presents as a promising solution for improving system performance by offloading traffic from heavily loaded macro cell (...In Heterogeneous Networks (HetNets), Integrating Device-to-Device communication (D2D) techniques presents as a promising solution for improving system performance by offloading traffic from heavily loaded macro cell (MC) to small cells (SCs). For instance, D2D can be used to offload traffic from heavily-loaded cells to light-loaded small cells. However, offloading new users may result in an unfair load distribution among small cells and consequently may affect the quality of service of some users. To achieve better performance and reduce blocking probability load balancing among small cells should be considered when we offload traffic from macro to small cells. In this paper, we consider a centralized offloaded relay selection scheme, in which a cellular provider can decide whether users can assist each other to relay their traffic to small cells. We propose a joint user-relay selection with dynamic load balancing scheme based on D2D communications using the Kuhn-Munkres (K-M) method. The offloading process considers the load from MC to SCs and among SCs. Compared to previous works, our simulation results show that the proposed scheme increases the number of admitted users in the system, and achieves a higher load balancing fairness index among small cells. Also, our scheme achieves a higher rate fairness index among users by adjusting the signal to interference plus noise ratio (SINR) threshold.展开更多
Heterogeneous cellular networks improve the spectrum efficiency and coverage of wireless communication networks by deploying low power base station (BS) overlapping the conventional macro cell. But due to the dispar...Heterogeneous cellular networks improve the spectrum efficiency and coverage of wireless communication networks by deploying low power base station (BS) overlapping the conventional macro cell. But due to the disparity between the transmit powers of the macro BS and the low power BS, cell association strategy developed for the conventional homogeneous networks may lead to a highly unbalanced traffic loading with most of the traffic concentrated on the macro BS. In this paper, we propose a load-balance cell association scheme for heterogeneous cellular network aiming to maximize the network capacity. By relaxing the association constraints, we can get the upper bound of optimal solution and convert the primal problem into a convex optimization problem. Furthermore we propose a Lagrange multipliers based distributed algorithm by using Lagrange dual theory to solve the convex optimization, which converges to an optimal solution with a theoretical performance guarantee. With the proposed algorithm, mobile terminals (MTs) need to jointly consider their traffic type, received signal-to-interference-noise-ratios (SINRs) from BSs, and the load of BSs when they choose server BS. Simulation results show that the load balance between macro and pico BS is achieved and network capacity is improved significantly by our proposed cell association algorithm.展开更多
Cognitive radio(CR) is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques.However,c...Cognitive radio(CR) is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques.However,cognitive radio networks(CRNs)may also impose some challenges due to the ever increasing complexity of network architecture,the increasing complexity with configuration and management of large-scale networks,fluctuating nature of the available spectrum,diverse Quality-of-Service(QoS)requirements of various applications,and the intensifying difficulties of centralized control,etc.Spectrum management functions with self-organization features can be used to address these challenges and realize this new network paradigm.In this paper,fundamentals of CR,including spectrum sensing,spectrum management,spectrum mobility and spectrum sharing,have been surveyed,with their paradigms of self-organization being emphasized.Variant aspects of selforganization paradigms in CRNs,including critical functionalities of Media Access Control(MAC)- and network-layer operations,are surveyed and compared.Furthermore,new directions and open problems in CRNs are also identified in this survey.展开更多
The parallel computation capabilities of modern graphics processing units (GPUs) have attracted increasing attention from researchers and engineers who have been conducting high computational throughput studies. How...The parallel computation capabilities of modern graphics processing units (GPUs) have attracted increasing attention from researchers and engineers who have been conducting high computational throughput studies. However, current single GPU based engineering solutions are often struggling to fulfill their real-time requirements. Thus, the multi-GPU-based approach has become a popular and cost-effective choice for tackling the demands. In those cases, the computational load balancing over multiple GPU "nodes" is often the key and bottleneck that affect the quality and performance of the real=time system. The existing load balancing approaches are mainly based on the assumption that all GPU nodes in the same computer framework are of equal computational performance, which is often not the case due to cluster design and other legacy issues. This paper presents a novel dynamic load balancing (DLB) model for rapid data division and allocation on heterogeneous GPU nodes based on an innovative fuzzy neural network (FNN). In this research, a 5-state parameter feedback mechanism defining the overall cluster and node performance is proposed. The corresponding FNN-based DLB model will be capable of monitoring and predicting individual node performance under different workload scenarios. A real=time adaptive scheduler has been devised to reorganize the data inputs to each node when necessary to maintain their runtime computational performance. The devised model has been implemented on two dimensional (2D) discrete wavelet transform (DWT) applications for evaluation. Experiment results show that this DLB model enables a high computational throughput while ensuring real=time and precision requirements from complex computational tasks.展开更多
基金supported in part by the Guangdong Basic and Applied Basic Research Foundation under grant 2020A1515110269.
文摘A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network.Due to the user mobility and the coverage of small cells,the network load often becomes unbalanced,resulting in poor network performance.Mobility management has become an important issue to ensure seamless communication when users move between cells,and proactive mobility management is one of the important functions of the active Self-Organizing Network(SON).This paper proposes a proactive mobility management framework for active SON,which transforms the original reactive load balancing into a forward-aware and proactive load balancing.The proposed framework firstly uses the BART model to predict the users’temporal and spatial mobility based on a weekly cycle and then formulate the MLB optimization problem based on the soft load.Two solutions are proposed to solve the above MLB problem.The simulation results show that the proposed method can better optimize the network performance and realize intelligent mobile management for the future network.
基金supported by the National Natural Science Foundation of China (61672484)the National Hi-Tech Research and Development Program of China (2014AA01A702)
文摘In heterogeneous networks(Het Nets), it is desirable to offload users from macro cells to small cells to achieve load balancing. However, the offloaded users suffer a strong inter-tier interference. To guarantee the performance of the offloaded users, the interference from macro cells should be carefully managed. In this paper, we jointly optimize load balancing and interference coordination in multi-antenna Het Nets. Different from previous works, instead of almost blank subframes(ABS) on which the macro cells waste time resource, the macro cells suppress the interference to the offloaded users by zero-forcing beamforming(ZFBF) on interference nulling subframes(INS). Considering user association cannot be conduct frequently, we derive the long-term throughput of users over Rayleigh fading channels while previous works focused on instantaneous rate. From the perspective of the spectrum efficiency and user fairness, we formulate a long-term network-wide utility maximization problem. By decomposing the problem into two subproblems, we propose an efficient joint load balancing and interference coordination strategy. Simulation results show that our proposal can achieve good system performance gains over counterparts in term of the network utility, cell edge throughput and average throughput.
文摘Heterogeneous Networks(HetNets)and cell densification represent promising solutions for the surging data traffic demand in wireless networks.In dense HetNets,user traffic is steered toward the Low-Power Node(LPN)when possible to enhance the user throughput and system capacity by increasing the area spectral efficiency.However,because of the transmit power differences in different tiers of HetNets and irregular service demand,a load imbalance typically exists among different serving nodes.To offload more traffic to LPNs and coordinate the Inter-Cell Interference(ICI),Third-Generation Partnership Project(3GPP)has facilitated the development of the Cell Range Expansion(CRE),enhanced Inter-Cell Interference Coordination(eICIC)and Further enhanced ICIC(FeICIC).In this paper,we develop a cell clustering-based load-aware offsetting and an adaptive Low-Power Subframe(LPS)approach.Our solution allows the separation of User Association(UA)functions at the User Equipment(UE)and network server such that users can make a simple cell-selection decision similar to that in the maximum Received Signal Strength(max-RSS)based UA scheme,where the network server computes the load-aware offsetting and required LPS periods based on the load conditions of the system.The proposed solution is evaluated using system-level simulations wherein the results correspond to performance changes in different service regions.Results show that our method effectively solves the offloading and interference coordination problems in dense HetNets.
基金Supported by the National Natural Science Foundation of China (No. 60672059, 60496315 )the National High Technology Research and Development Programme of China (No.2006AA01Z233)
文摘Because of different system capacities of base station (BS) or access point (AP) and ununiformity of traffic distribution in different cells, quantities of new call users may be blocked in overloaded cell in communication hot spots. Whereas in some neighboring under-loaded cells, bandwidth may be superfluous because there are only few users to request services. In order to raise resource utilization of the whole heterogeneous networks, several novel load balancing strategies are proposed, which combine the call ad- mission control policy and multi-hop routing protocol of ad-hoc network for load balancing. These loadbalancing strategies firstly make a decision whether to admit a new call or not by considering some parameters like load index and route cost, etc., and then transfer the denied users into neighboring under-loaded cell with surplus channel according to optimum multi-hop routing algorithm. Simulation results show that the proposed load balancing strategies can distribute traffics to the whole heterogeneous wireless netorks, improve the load balance index efficiently, and avoid the call block phenomenon almost absolutely.
文摘In order to solve the problem that determining decision factors weights is of subjectivity in heterogeneous wireless network selection algorithm, a network selection algorithm based on extension theory and fuzzy analytic hierarchy process (FAHP) is proposed in this paper. In addition, user and operator codetermine the optimal network using the proposed algorithm, which can give consideration to user and operator benefits. The fuzzy judgment matrix is coustructed by membership degree of decision factors which is calculated according to extension theory. The comprehensive weight of each decision factor is obtained using FAHP. Finally, the optimal network is selected through total property value ranldng of each candidate network under user preference and operator preference. The simulation results show that the proposed algorithm can select the optimal network efficiently and accurately, satisfy user preference, and implement load balance between networks.
文摘In Heterogeneous Networks (HetNets), Integrating Device-to-Device communication (D2D) techniques presents as a promising solution for improving system performance by offloading traffic from heavily loaded macro cell (MC) to small cells (SCs). For instance, D2D can be used to offload traffic from heavily-loaded cells to light-loaded small cells. However, offloading new users may result in an unfair load distribution among small cells and consequently may affect the quality of service of some users. To achieve better performance and reduce blocking probability load balancing among small cells should be considered when we offload traffic from macro to small cells. In this paper, we consider a centralized offloaded relay selection scheme, in which a cellular provider can decide whether users can assist each other to relay their traffic to small cells. We propose a joint user-relay selection with dynamic load balancing scheme based on D2D communications using the Kuhn-Munkres (K-M) method. The offloading process considers the load from MC to SCs and among SCs. Compared to previous works, our simulation results show that the proposed scheme increases the number of admitted users in the system, and achieves a higher load balancing fairness index among small cells. Also, our scheme achieves a higher rate fairness index among users by adjusting the signal to interference plus noise ratio (SINR) threshold.
基金supported by the Beijing Higher Education Young Elite Teacher Project(YETP0432)
文摘Heterogeneous cellular networks improve the spectrum efficiency and coverage of wireless communication networks by deploying low power base station (BS) overlapping the conventional macro cell. But due to the disparity between the transmit powers of the macro BS and the low power BS, cell association strategy developed for the conventional homogeneous networks may lead to a highly unbalanced traffic loading with most of the traffic concentrated on the macro BS. In this paper, we propose a load-balance cell association scheme for heterogeneous cellular network aiming to maximize the network capacity. By relaxing the association constraints, we can get the upper bound of optimal solution and convert the primal problem into a convex optimization problem. Furthermore we propose a Lagrange multipliers based distributed algorithm by using Lagrange dual theory to solve the convex optimization, which converges to an optimal solution with a theoretical performance guarantee. With the proposed algorithm, mobile terminals (MTs) need to jointly consider their traffic type, received signal-to-interference-noise-ratios (SINRs) from BSs, and the load of BSs when they choose server BS. Simulation results show that the load balance between macro and pico BS is achieved and network capacity is improved significantly by our proposed cell association algorithm.
基金ACKNOWLEDGEMENT This work was supported by National Natural Science Foundation of China (No. 61172050), Program for New Century Excellent Talents in University (NECT-12-0774), the open research fund of National Mobile Communications Research Laboratory, Southeast University (No.2013D12), the Foundation of Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services. The corresponding author is Dr. Zhongshan Zhang.
文摘Cognitive radio(CR) is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques.However,cognitive radio networks(CRNs)may also impose some challenges due to the ever increasing complexity of network architecture,the increasing complexity with configuration and management of large-scale networks,fluctuating nature of the available spectrum,diverse Quality-of-Service(QoS)requirements of various applications,and the intensifying difficulties of centralized control,etc.Spectrum management functions with self-organization features can be used to address these challenges and realize this new network paradigm.In this paper,fundamentals of CR,including spectrum sensing,spectrum management,spectrum mobility and spectrum sharing,have been surveyed,with their paradigms of self-organization being emphasized.Variant aspects of selforganization paradigms in CRNs,including critical functionalities of Media Access Control(MAC)- and network-layer operations,are surveyed and compared.Furthermore,new directions and open problems in CRNs are also identified in this survey.
基金supported by National Natural Science Foundation of China(No.61203172)the SSTP of Sichuan(Nos.2018YYJC0994 and 2017JY0011)Shenzhen STPP(No.GJHZ20160301164521358)
文摘The parallel computation capabilities of modern graphics processing units (GPUs) have attracted increasing attention from researchers and engineers who have been conducting high computational throughput studies. However, current single GPU based engineering solutions are often struggling to fulfill their real-time requirements. Thus, the multi-GPU-based approach has become a popular and cost-effective choice for tackling the demands. In those cases, the computational load balancing over multiple GPU "nodes" is often the key and bottleneck that affect the quality and performance of the real=time system. The existing load balancing approaches are mainly based on the assumption that all GPU nodes in the same computer framework are of equal computational performance, which is often not the case due to cluster design and other legacy issues. This paper presents a novel dynamic load balancing (DLB) model for rapid data division and allocation on heterogeneous GPU nodes based on an innovative fuzzy neural network (FNN). In this research, a 5-state parameter feedback mechanism defining the overall cluster and node performance is proposed. The corresponding FNN-based DLB model will be capable of monitoring and predicting individual node performance under different workload scenarios. A real=time adaptive scheduler has been devised to reorganize the data inputs to each node when necessary to maintain their runtime computational performance. The devised model has been implemented on two dimensional (2D) discrete wavelet transform (DWT) applications for evaluation. Experiment results show that this DLB model enables a high computational throughput while ensuring real=time and precision requirements from complex computational tasks.