186 results about "Ultra dense" patented technology

Embodiments of the invention relate to producing spike-timing dependent plasticity in an ultra-dense synapse cross-bar array for neuromorphic systems. An aspect of the invention includes when an electronic neuron spikes, an alert pulse is sent from the spiking electronic neuron to each electronic neuron connected to the spiking electronic neuron. When the spiking electronic neuron sends the alert pulse, a gate pulse is sent from the spiking electronic neuron to each electronic neuron connected to the spiking electronic neuron. When each electronic neuron receives the alert pulse, a response pulse is sent from each electronic neuron receiving the alert pulse to the spiking electronic neuron. The response pulse is a function of time since a last spiking of the electronic neuron receiving the alert pulse. In addition, the combination of the gate pulse and response pulse is capable increasing or decreasing conductance of a variable state resistor.

The invention belongs to the technical field of the communication 5G and the edge computing, specifically an edge computing method for a 5G ultra-dense networking scene. The basic thought of the invention is to provide the edge computing service for a cellular user of a microcell by placing a MEC sever at a small base station; and meanwhile, the cellular user can select the cloud computing service connected with a macro base station according to the feature of the to-be-executed task. The edge computing method disclosed by the invention has the advantages that the user can select the most suitable computing service, and the delay performance is improved.

A resource allocation method for reinforcement learning in an ultra-dense network is provided. The invention relates to the field of ultra-dense networks in 5G (fifth generation) mobile communications and provides a method for allocating resources between a home node B and a macro node B, between a home node B and another home node B and between a home node B and a mobile user in a dense deployment network; the method is implemented through power control, each femotcell is considered as an intelligent body to jointly adjust transmitting powers of home node Bs, the densely deployed home node Bs are avoided causing severe jamming to a macro node B and an adjacent B when transmitting at maximum powder, and system throughput is maximized; user delay QoS is considered, and traditional 'Shannon capacity' is replaced with 'available capacity' that may ensure user delay; a supermodular game model is utilized such that whole network power distribution gains Nash equilibrium; the reinforcement learning method Q-learning is utilized such that the home node B has learning function, and optimal power distribution can be achieved; by using the resource allocation method, it is possible to effectively improve the system capacity of an ultra-dense network at the premise of satisfying user delay.

The invention discloses a method for reducing switch failures in an ultra-dense wireless network and belongs to the mobility optimization technique in wireless communication. The method comprises the following steps: configuring different initial switching parameters for UE at different speeds, and then automatically adjusting the switching parameters according to the switching history; calculating the failure times and the success times of switching within the given time window length, and thus providing a new method for dynamically adjusting switch parameters. In the ultra-dense network, under the condition that Picocells are densely deployed in the area, the method can realize self-adaptative adjustment for the switch parameters, effectively reduces the switch failure rates when the UE passes through the area with the densely-deployed Picocells, and can realize the balance of reducing the switch failure rates and reducing small ping-pong ball rate.

The invention provides an energy efficient resource distribution algorithm based on interference coordination in an ultra-dense wireless network. A clustering-based ultra-dense wireless network is analyzed and given; inter-cluster and in-cluster interference coordination strategies are provided; inter-cluster interference coordination is carried out by adopting a graph colouring theory; and in-cluster interference coordination is carried out in a partial information interaction manner. The energy efficient resource distribution algorithm based on interference coordination in the ultra-dense wireless network is provided. Joint optimization of sub-channels and power of the ultra-dense wireless network is carried out through the algorithm. Firstly, the sub-channels are distributed by utilization of a user quality experience function and maximum and minimum algorithms; and secondly, optimization distribution of the power is carried out by optimizing an improved particle swarm algorithm, wherein to prevent particle swarm optimization from getting into local solution defect, a particle swarm optimization algorithm is improved by introducing damped vibration and fitness variation.

The invention relates to a video service classification buffer method based on user mobility in an ultra-dense heterogeneous network. The method belongs to the technical field of wireless communication. The method divides the buffer space of each small base station into two regions to respectively provide common network video and typical streaming media video for users, and adopts different bufferstrategies for two different types of video service services. For the common network video, the caching problem is described as an optimization problem to minimize the average transmission cost of the cached content by using the encoding caching and delayed offload strategy. For a typical streaming video, uncoded video segments of the requested video are pre-positioned in a small base station through which the user passes with a high probability. The invention can remarkably reduce the average transmission cost of the buffer content and greatly reduce the traffic in the backhaul network. In addition, the designed caching strategy takes into account the mobility of the user and the time limit of the connection between the user and the small base station, which is more in line with the actual network scenario.

The invention discloses a software definition based ultra-dense wireless network system structure and an implementation method thereof. A whole network framework is realized by a cloud platform; network resources, computing resources and storage resources are managed in a centralized mode, so that network control function reconstruction can be quickly realized; and a future operator also can combine the network resources, the computing resources and the storage resources according to needs, so that quick development and deployment of new business are facilitated. On an access part, virtual cells are used as control planes, a local centralized control node is arranged in each virtual cell, and access nodes of the cell are controlled in the centralized mode, so that unified disposition and coordination of the nodes are completed, and the nodes are used as virtual connecting anchor points. A service transmission carrier of a user terminal is dynamically positioned in the access node close to the user terminal; and when the user terminal moves, a transmission node list set serving a user plane is dynamically updated along with movement of the user terminal. The two nodes separately have two different functions, so that a self-adaptive networking strategy for the control plane and a user data plane is realized.

The invention discloses a load balancing method based on integral optimization of user connection and interference management in an ultra-dense heterogeneous network. The load balancing method comprises the following steps that: an optimization model is established; a load balancing model for integrally optimizing the user connection and an ABS (Almost Blank Subframe) rate is established targeting the sum of all user logarithmic rates in a maximal ultra-dense heterogeneous network; a user connection method is that optimal user connection is solved by using a discrete dual decomposition method under a fixed ABS rate; an ABS rate calculation method is that a calculation expression of an optimal ABS rate is solved under a fixed user connection condition; then, a final result is obtained; and a global second-best solution is obtained through a method by solving the user connection and the ABS rate through iteration. By adopting the method disclosed by the invention, the balance of a load and the fairness of the user rate in the ultra-dense heterogeneous network can be improved; and simultaneously, the utilization rate of ultra-dense heterogeneous network resources can be improved.

The invention relates to a seamless handover method based on collaborative base station clustering in an ultra-dense network. The method comprises the steps of firstly, collaboratively clustering small base stations deployed in an ultra-dense manner; implementing overlapped clustering to acquire an overlapped cluster node; when a user moves in a cluster, adopting a dynamically self-updating method for a service base station group to meet the intra-cluster handover requirement of the user; and when the user moves across the clusters, adopting a handover pre-warning mechanism to perform pretreatment early for handover, thus reducing preparation time for handover, then executing a handover process, and finally completing seamless handover. According to the method, the collaborative base station clustering and handover pre-warning serve as entry points, according to the moving conditions of the mobile user such as moving in the cluster, and moving across the clusters, the different handover strategies are used for performing efficient cell handover, the handover delay is reduced, the handover failure rate is lowered, and the seamless handover experience of the user is enhanced.

The invention discloses a distributed ultra-dense heterogeneous network interference coordination method based on a non-cooperative game. A network interference problem is modeled as a non-cooperative game problem by analyzing a dynamic feature of an ultra-dense network, cells in the network are used as game participants, and autointerference is minimized to be a utility function. In order to deduce existence of a Nash equilibrium solution, building of a game model is deduced into a potential game problem, and a feedback method based on random learning is provided accordingly to solve the Nash equilibrium solution. According to the method, a probability matrix is built according to the utility function of each cell for each time of iteration, and the final Nash equilibrium solution is acquired by continuously updating the probability matrix. According to the method provided by the invention, the closed-form solution can achieved by convergence without information exchange between the cells, so that at last the whole network interference is minimal, when all the cells are converged to the Nash equilibrium solution, network capacity is improved, and the requirement of dynamic variation of user speed is met, and the difficulty among network densification, network capacity and spectrum efficiency is effectively solved with relatively low complexity.

The invention discloses an ultra-dense heterogeneous network small station coding cooperative caching method based on value function approximation. The method includes the following steps: adopting areinforcement learning method based on value function approximation, expressing a value function as a function of state and action, taking the operation of maximizing the number of file requests directly served by the average cumulative small stations as an optimization objective, continuously interacting with the environment to adapt to the dynamic changes of the environment, mining a potential file request transfer mode, obtaining an approximate expression of the value function, and further obtaining a cooperative caching decision that matches the file request transfer mode; and encoding thecooperative caching decision by a macro base station, and transmitting encoded cooperative caching results to each small station. The scheme of the invention formulates the caching decision by meansof the transfer mode of the file requests in a real network mined by reinforcement learning, does not need any assumptions about the prior distribution of data, and is more suitable for an actual system; and moreover, through the real-time interaction with the environment, the time-varying file popularity can be tracked, the corresponding caching strategy is made, the process is simple and feasible, and the operation of solving NP-hard problems is not required.

The invention relates to a topology control method based on unsupervised learning for an ultra-dense wireless sensor network. On the basis of a framework of a genetic algorithm, network nodes are clustered, and the optimal clustering network topology is searched through continuous unsupervised learning. In the optimization process, the three factors of node energy, node distance and node density of the network are important input data sets, and different factor weights are determined by using a hierarchical analysis method to establish a fitness function. By adoption of the topology control method provided by the invention, the node energy consumption can be effectively improved, and the network life of the wireless sensor network is improved at last.

The embodiment of the invention provides a radio resource distribution method of an ultra-dense small cell network system. The method mainly comprises: in each small cell, distributing a channel, corresponding to a maximum channel gain, of the small cell to a designated user terminal; calculating the channel capacity of the small cell on each channel; and calculating the transmitting power of each channel of the small cell based on a principle that the sum of the channel capacity of all small cells is maximum and according to a distributed power control algorithm. According to the embodiment of the invention, by using a distributed radio resource distribution algorithm, solution of the optimum transmitting power of the small cell base station on each channel can be locally carried out; complex bloat and mass signalling overhead, which result from centralized control of resource distribution of all small cells by a macro base station, are avoided; and flexibility, effectiveness, and robustness of the system are increased. The method is adapted to the development trend of a modernization flat network structure and enables green communication realized.

The invention provides a user task unloading and resource allocation joint optimization method under a 5G ultra-dense heterogeneous network, and the method comprises the steps: in the first part, introducing an interference management mechanism, and carrying out the clustering of micro base stations based on an improved K-means clustering algorithm; and in the second part, obtaining system cost functions about the macro user and the micro user according to the local processing model and the unloading processing model respectively, and decomposing the system cost functionsinto a plurality of sub-problems to be optimized, so as to achieve reasonable allocation of communication resources and computing resources. According to the invention, the fairness of channels divided by users can be ensured; the unloading scheme based on the cost value comparison method is simple in algorithm and low in time complexity.

The present invention discloses a user connection and virtual resource distribution method for maximizing benefits of all service providers as a target. The method comprises: based on a benefit function, defining the users' and service providers' benefits; employing the Lagrange to perform dual to obtain necessary and sufficient conditions of optimal resource distribution in a mixing business scene; and employing a low-complexity method to perform iteration solution of a resource distribution result, and finally combining the resource distribution result. A user connection scheme is designed according to the greedy strategy, about a new user arrival condition, the new user selects the optimal base station for connection according to local information in the condition of keeping constant original user connection; and moreover, because the Lagrange dual and the heuristic idea, the user connection and virtual resource distribution method in the ultra dense heterogeneous network can reduce the number of iterations and computation complexity so as to rapidly find the resource distribution scheme.

A bandwidth brokering system and method incorporating methodology for supporting self-healing communication rings is disclosed. The present invention utilizes state-based tokens that are transmitted on a separate communication channel between network nodes to monitor and correct communication failures occurring at a link, interface, and network node level. The invention as taught permits generic brokering of all available network bandwidth in a granular method without the need for fixed designations of “protection” or “working” communication paths. As such, the present invention permits integration of “protection” and “working” communication data paths to permit full utilization of available system bandwidth with graceful recovery in the event of system or link malfunctions. While the present invention is optimally adapted to use in optical communications systems and specifically those incorporating wavelength division multiplexing (WDM), dense wavelength division multiplexing (DWDM), and ultra-dense wavelength division multiplexing, the teachings presented are equally well adapted to situations where other communications mediums are utilized in a multi-carrier, wireless, or spread-spectrum environment, among others.

The invention discloses a method for discovering small stations based on graph coloring in an ultra-dense wireless network. The method comprises the steps that the number of small station groups, namely the available color number Ncolors, is determined by an operator; a multiplex distance dreuse which is as big as possible is found under the premise that the used color number is not larger than the Ncolors; an interference relation graph is established according to the dreuse, and a Brelaz algorithm is used for coloring; the small stations are grouped according to coloring results, and all groups of small stations are made to send synchronous signals in turn; when network topology changes, the interference relation graph is reestablished, coloring is conducted again, the small stations are regrouped, and the small stations are made to send synchronous signals in turn according to the new groups. According to the method, the small stations are grouped, the interference of the synchronous signals of different small stations is reduced; the interference relations between the small stations are reflected through the interference relation graph, so that the small stations which interfere with each other seriously are prevented from being distributed in the same group, and the interference between the small stations is further reduced; the probability that UE discovers weak small stations is improved, and the number of the small stations discovered by the UE is increased.

Disclosed is a method and apparatus for optically modulating and transmitting source data. An optical comb comprising optical tones having a frequency spacing equal to Δf is generated by an optical comb generator. Selected ones of the optical tones in the optical comb are modulated according to the source data to produce a comb of modulated optical tones. At least one optical tone in the optical comb is frequency shifted by a frequency less than Δf to produce a frequency shifted unmodulated optical reference tone. The optical comb, the frequency shifted unmodulated optical reference tone and the comb of modulated tones are multiplexed onto at least one optical path.

The invention discloses a Gibbs sampling-based ultra-dense heterogeneous network optimal cell range expansion bias adjustment method. The method includes the following steps that: inter-cell bias influence relation diagram is constructed; small cells are grouped based on the bias influence relation diagram; a user judges candidate service cells; user number, signal to interference plus noise power and effectiveness update information are interacted between adjacent cells; and cell range expansion bias sampling is carried out based on Gibbs sampling. With the method adopted, ultra-dense heterogeneous network optimal cell range expansion bias, with optimizing any rate related system effectiveness adopted as a target, can be obtained with linear complexity and minimal iterations.

The present invention discloses an ultra-dense heterogeneous network energy efficiency based resource allocation method. According to the method, a resource segmentation coefficient of a macro base station in an ultra-dense heterogeneous network is associated with a transmit power of a picocell, a cell edge expansion bias of the picocell and a particle position in a particle swarm optimization algorithm; a global energy efficiency is taken as a target, and the resource segmentation coefficient of the macro base station, the transmit power of the picocell and the cell edge expansion bias of the picocell are jointly adjusted by using the particle swarm optimization algorithm, so as to achieve the objective of maximum global energy efficiency; in optimization of problem modeling, each user rate requirement in the global network is used as a constraint condition, so that the user rate requirement is ensured while the maximum global energy efficiency is ensured; and an optimization process is ensured to be converged through limitation of an inertial weight of the particle swarm and a value range of an acceleration coefficient, and the optimization process is ensured to be converged within a global optimal value through multiple times of re-initialization.

An ultra-dense electrode-based brain imaging system with high spatial and temporal resolution. A Sparsity and Smoothness enhanced Method Of Optimized electrical TomograpHy (s-SMOOTH) based reconstruction technique to improve the spatial resolution and localization accuracy of reconstructed brain images is described. Also described is a graph Fractional-Order Total Variation (gFOTV) based reconstruction technique to improve the spatial resolution and localization accuracy of reconstructed brain images.

The invention discloses a transmission system for an ultra-dense wavelength division multiplexing passive optical fiber network, and relates to the technical field of high-speed optical access networks. According to the transmission system for the ultra-dense wavelength division multiplexing passive optical fiber network, a wavelength division multiplexing and demultiplexing device and an opticalbeam splitter are mixed for use, thereby avoiding the problem that high loss occurs when using the optical beam splitter alone for multiple users, and avoiding the problem that the number of users islimited when using a wavelength division multiplexer alone; meanwhile, by ingeniously designing the upstream and downstream wavelength, the bandwidth limitation of the wavelength division multiplexer/demultiplexer can be effectively avoided, so that the system performance of multipath downstream signals and multipath upstream signals in each group of wavelength division multiplexing channels are guaranteed; and a crosstalk is not introduced in a single-fiber two-way transmission, thereby remarkably improving the capacity and the number of users of the upstream and downstream access signals. The invention further discloses a transmission method based on the transmission system for the ultra-dense wavelength division multiplexing passive optical fiber network.