Chuangeng Tian

Bio: Chuangeng Tian is an academic researcher from Xuzhou Institute of Technology. The author has contributed to research in topics: Rank (linear algebra) & Wireless network. The author has an hindex of 1, co-authored 3 publications receiving 4 citations.

Bursty data service latency analysis under fractional calculus fluid model of Multi-hop Wireless Networks

Abstract: A fractional calculus fluid model can be used to better explain the bursty data service traffic, which is long-range dependence and has a fractal like the feature of network data flow. The heavy-tailed delay distributions, the hyperbolic decay of the packet delay auto-covariance function and fractional differential equations are shown to be formally related. Effective capacity is a useful model to describe wireless networks with QoS constraints. This paper builds a fluid model to describe the traffic of multi-hop wireless networks under QoS constraints. The proposed method could analyze the relationship between latency and a complicated traffic model, which is more similar to the real scenario.

Research on Image Data Clustering Algorithm Based on Low Rank Subspace Clustering

Abstract: At present, the scale and types of data collected by people have shown explosive growth. It is very difficult to obtain specific and effective classification labels for high-dimensional data. By using subspace clustering method with low rank representation, the linear representation matrix of the data with the lowest rank is found, and the global structure of the original data is preserved to achieve the purpose of optimizing clustering. By comparing K-means clustering, LRR clustering and the improved LRR clustering method of self-adapting graph regularization low rank representation, the experiment proves that the latter has better effect in clustering image data collected from different angles.

Linear wireless sensor network load balancing and converging method

Abstract: The invention discloses a linear wireless sensor network load balancing and converging method, which belongs to the field of sensors and comprises the following steps of: (1) deploying a linearly arranged wireless sensor network on site; (2) periodically acquiring data of a sensor by an acquisition node, and periodically transmitting the acquired data to an aggregation node through a neighbor nodein a multi-hop forwarding manner by the acquisition node; (3) traversing the forwarding rate from each acquisition node to the neighbor node, and calculating the delivery rate of the acquisition nodes at the aggregation node; 4, introducing a node delivery rate to construct an energy consumption model, and calculating energy consumption; 5, constructing an energy balance model. According to the invention, the delivery rate of the nodes is brought into the calculation of the energy consumption model, and the delivery rate of each node at the aggregation node is taken as one of the conditions of equilibrium calculation, so that the upper limit of the energy consumption absolute difference between the nodes, the lower limit of the delivery of the acquisition nodes to the aggregation node areaccurately reflected; and the effectiveness and the accuracy of the load balancing calculation of the network are improved.

Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated?

Abstract: Massive MIMO is a promising technique for increasing the spectral efficiency (SE) of cellular networks, by deploying antenna arrays with hundreds or thousands of active elements at the base stations and performing coherent transceiver processing. A common rule-of-thumb is that these systems should have an order of magnitude more antennas $M$ than scheduled users $K$ because the users’ channels are likely to be near-orthogonal when $M/K > 10$ . However, it has not been proved that this rule-of-thumb actually maximizes the SE. In this paper, we analyze how the optimal number of scheduled users $K^\star$ depends on $M$ and other system parameters. To this end, new SE expressions are derived to enable efficient system-level analysis with power control, arbitrary pilot reuse, and random user locations. The value of $K^\star$ in the large- $M$ regime is derived in closed form, while simulations are used to show what happens at finite $M$ , in different interference scenarios, with different pilot reuse factors, and for different processing schemes. Up to half the coherence block should be dedicated to pilots and the optimal $M/K$ is less than 10 in many cases of practical relevance. Interestingly, $K^\star$ depends strongly on the processing scheme and hence it is unfair to compare different schemes using the same $K$ .

A Survey of Image Clustering: Taxonomy and Recent Methods

Abstract: Image clustering is a fundamental problem in computer vision domains. In this survey, we provide a comprehensive overview of image clustering. Specifically, we first discuss the applications of image clustering across various domains. Then, we summarize the common algorithms and propose a classification of image clustering. The existing methods are classified from four aspects: autoencoder based methods, subspace clustering, graph convolution network (GCN) based methods and some other clustering methods. We introduce the main research contents and existing problems of various image clustering methods. We also introduce some recent methods and summarize the experimental results. Based on our taxonomy and analysis, creating and verifying new methods is more straightforward. Finally, we propose the future opportunities in this fast developing field.

Fractional Modeling of Non-Newtonian Casson Fluid between Two Parallel Plates

Abstract: In this manuscript, fractional modeling of non-Newtonian Casson fluid squeezed between two parallel plates is performed under the influence of magneto-hydro-dynamic and Darcian effects. The Casson fluid model is fractionally transformed through mixed similarity transformations. As a result, partial differential equations (PDEs) are transformed to a fractional ordinary differential equation (FODE). In the current modeling, the continuity equation is satisfied while the momentum equation of the integral order Casson fluid is recovered when the fractional parameter is taken as α = 1 . A modified homotopy perturbation algorithm is used for the solution and analysis of highly nonlinear and fully fractional ordinary differential equations. Obtained solutions and errors are compared with existing integral order results from the literature. Graphical analysis is also performed at normal and radial velocity components for different fluid and fractional parameters. Analysis reveals that a few parameters are showing different behavior in a fractional environment as compared to existing integer-order cases from the literature. These findings affirm the importance of fractional calculus in terms of more generalized analysis of physical phenomena.