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The fifth generation mobile communication technology (5G) coincides with the wave of big data, and the combination of the two technologies is considered to be one of the mainstream directions of the new generation mobile communication technology. The application of big data technology in 5G is still in the preliminary exploration stage. This paper studies the application status of big data technology in 5G key technology, base station construction and optimization, marketing scheme formulation and other aspects, analyzes the problems and challenges faced by big data technology in 5G application, and puts forward new application ideas.

With the development of modern cities, people’s traffic behaviors are on an ever-more increase. However, urban traffic is often congested due to bad road conditions or unreasonable road planning. To predict the trajectory of urban taxis, the taxi trajectories data are excavated based on the analysis of urban taxi behaviors. Then, the STTM (Spatio-Temporal Trajectory Model) is proposed using the LSTM (Long Short-Term Memory) and network residual. Meanwhile, the taxi is used for the urban road traffic perception and extraction, so that the taxi sensor and road traffic information can cooperate to construct a model for urban scale calculation. Afterward, the influence of the same model on the travel time predictions is compared for different urban roads. The results show that, based on the proposed STTM, the MRPE (Mean Relative Percentage Error) of the predicted value is 6.126%, the MAE (Mean Absolute Error) is 72.416 seconds, the MRE (Mean Relative Error) is 7.022%, the RMSE (Root Mean Square Error) is 293.977 seconds, and the coefficient of determination R2 is 0.884. This indicates that the model results have high goodness of fit, so it is a successful case of the application of urban computing in taxi trajectory prediction. Overall, the taxi ID (Identifier) and weather conditions have a great influence on the prediction results of urban taxi trajectory, and the STTM has a more obvious effect on improving the accuracy of travel time prediction for urban roads.

The power communication network service plays an important role in the production and operation of the power system. Therefore, the power communication department needs to solve the problem that how to reduce the security risk of the bearer service and distribute the service path properly. However, most of the existing algorithms do not take the difference of service importance into account, thus resulting in unbalanced traffic channel segment distribution and increase of the overall network risk. In this paper, a risk balancing routing assignment mechanism based power communication network service importance (SIRBRM) is proposed. And the analytic hierarchy process (AHP) is introduced and a model of risk balancing routing assignment problem is established. Then the routing decision based on the principle of maximum and minimum fairness constraint can choose the optimal route for the service. Finally, the simulation is carried out based on the power communication network topological data of a certain prefecture-level city. Simulation results show that compared with the other two methods, the SIRBRM can effectively reduce the link risk and the overall network risk, make the service distribution more uniform, and reduce the operational risk caused by excessive concentration of the service on some specific links. SIRBRM has broad application prospects in the existing routing optimization and future arrangements for new business methods.

Digital microfluidic biochips are revolutionizing the field of biochemistry experiment. Due to the rapidity and accuracy acquirement of the operation in its applications, the comprehensive online testing is necessary in order to enhance the reliability of the system. However, the existing testing methods which focus on the quality of droplets have the disadvantages of consuming a lot of time and resources, and the re-executed operations cannot be performed in pin-constrained biochips, leading to the expansion of chip scale and the increase of fabricating costs. This paper proposes an optimal structure design for testability, targeting for the real-time voltage sequences of electrode array as the feedback signals for online testing. By integrating shift register circuits into the original chip, the scheme can transmit feedback data to the microcontroller serially through minimum number of control pins to dynamically reconfigure the biochip. Furthermore, we propose a heuristic approach for large scale electrode array, further enhancing the efficiency of online testing. Experiments validate the effectiveness of the proposed scheme by real-life biochemical applications.

An integrated vehicle control system to improve vehicle handling and stability is developed based on the control authority of chassis key electronic control subsystems. First, a quantitative analysis of the control authority and the effective working region of the active front steering (AFS), active braking (AB) and active suspension (AS) subsystems is investigated based upon a full vehicle model. Then, an integrated control strategy is developed according to the control authority and the effective working region of chassis key electronic subsystems. The proposed strategy not only maximizes the benefits that each electronic subsystem offers but also minimizes the interactions between them. Computer simulation results confirm the rationality and effectiveness of the proposed integrated control system and the improvements in vehicle handling and stability.

The in-wheel motor electric vehicle (IWM-EV) is an overwhelming tendency in modern automobile due to its unmatched advantages. However, the new structure of IWM-EV which packets driving motor in wheel will induce the new problems, e.g. motor unbalanced radial force and airgap deformation of driving motor, etc. For the IWM-EV performance, these new problem is one of the major concerns. Taken switched reluctance motor (SRM) driving vehicle for example, this paper analytically investigates the effect regular of SRM unbalanced radial force, namely SRM vertical force, and airgap deformation IWM-EV performance. First, three comparison dynamics models of IWM-EV are proposed to include SRM vertical force and airgap deformation; then the analytical models are solved to predict vehicle dynamics responses at different models. It is conclude that SRM vertical force and airgap deformation has negative and coupling effects on IWM-EV performance.

Switched reluctance motor (SRM) has great application potential in in-wheel motor electric vehicle (IWM-EV) due to its advantages, such as a high starting torque for initial acceleration, a wide operating speed range and high efficiency to extend the battery service life. However, the new structure of IWM-EV, e.g. SRM vertical force, airgap deformation has negative effect on vehicle safety and comfort. On the other hand, the structure of IWM-EV will effect SRM vertical force and airgap, especially the representative parameters of SRM, e.g. Stator mass, rotor mass, airgap, SRM shaft stiffness, stator and rotor overlap angle, driving force of SRM. To obtain the effects of the parameters of SRM on vehicle dynamics, fully discussion is conducted from two aspects: the amplitude-frequency response comparison which is used to study SRM parameters effect on vehicle frequency response characteristic; and the parameter sensitivity analysis which is used research the trends of SRM parameters impact on vehicle performance. It is conclude that the representative parameters have different and coupling effect on IWM-EV performance.

Long test application time is an important problem in system-on-a-chip (SOC) design, and test scheduling is the main way to solve this problem. It is equivalent to the NP-complete 2-D bin-packing problem, each core test is represented by a rectangle with height equal to the TAM width and width equal to the test time. In this paper, we present a time-divided of IP test to solve SOC test scheduling problems. The main idea of the solution is to test the IP into several time periods, which makes the solution more flexible. Meanwhile, we use cross-entropy method and B*-Tree based floor planning technique to solve the test scheduling problem. Experimental results on ITC'02 SOC test benchmarks indicate that our method can provide shorter test time compared with recent works.

In view of low radar signal sorting accuracy in electronic support measures system (ESM), a new sparsity-based radar signal sorting method is put forward in this paper. Firstly, the pulse description words (PDW) of radar pulse sequence are analyzed and normalized, and then represented as a sparse linear combination of the sparse representation dictionary. Secondly, the sparse solution is calculated by solving an optimization problem under L1 norm. Finally, the linear correlation coefficients between the sparse solutions of test sample and standard samples are calculated and compared to determine the classification of radar signal. The experiment result showed that the radar signal sorting accuracy of this method is 96%, and the performance of the method is superior to other radar signal sorting algorithms. So this sparsity-based radar signal sorting method has high accuracy and strong anti-noise interference ability.

This paper focuses on the system implementation of Multicoset Sampling based on Compressed Sensing(CSMC), which can sample multiband signal with unknown carrier frequency at sub-Nyquist rate. In this paper, some nonideal system errors of implementing CSMC system are analyzed which leads to perturbation of sensing matrix. We propose a least square method that works reliably to estimate nonideal parameters in the system and thus calibrate the sensing matrix in the reconstruction algorithm. We also propose a prototype for CSMC system whose sampling parameters can be adjusted flexibly. The proposed system is capable of sampling multiband signal at a rate much lower than Nyquist rate, which proves the effectiveness of CSMC scheme in practice.