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Light Detection and Ranging (LiDAR) is a high-price system for wide-usage automotive driving requirements. The design, implementation, and validation of a performance-complexity efficient LiDAR system are introduced in this paper. A Time-to-Digit (TDC) chip with a low-cost Data-Processing (DP) chip is utilized in this system. The proposed chips have been well validated and can be utilized as processing cores for a generic LiDAR system. The measurement accuracy is a comparison with a high-price commercial product of Time-Correlated Single-Photon-Counting (TCSPC). The values show the proposed system accuracy is respectable for the comparison by many distances from 4.8m to 44.6m, the maximum difference is 0.3%.

Information technology development leads to the data explosion in many industries. In the era of big data, telecom operator stores huge amount of data, namely telecom big data. Telecom operator can employ data mining and analysis to seek the valuable information from telecom big data. In this paper, we design a novel big data assisted analysis architecture for telecom operator. The proposed architecture collects operation support system data and business support system data of telecom operator. Based on these data, the architecture draws the portrait of each user. Then, the user trajectory is analyzed. Furthermore, the proposed architecture takes the service behavior analysis. Finally, we apply the proposed big data assisted analysis architecture to the local telecom operator.

In the past thirty years, China experiences fast development in terms of economic and technology. This leads to the frequent exchange and communication among different cities. Specifically, meetings, sports, and industry exchanges at various levels are becoming more frequent and popular. Above events have significant impact on the city, hence, government/organizer should quantitatively evaluate the impact of events. Based on the various data of telecom operators, this paper proposes an insight scheme for large-scale events of the city. The proposed scheme can analyze the changes of the users scale and the business volume. In addition, this scheme also analyzes the aggregation areas of users before and after events and other characteristics. Especially, for the characteristics of external users from other cities, the proposed scheme can provide the data analysis results, in this way to support both the organizer and the government of the host city. Finally, the organizer and the government can provide good services.

Pollution prevention and control is one of the three key issues in China recently. Telecom operators have the data of millions of users, including identity attributes, mobile trajectories, and service behavior characteristics etc. On the premise of guaranteeing user data security, pollution prevention and control work can be extended from the source control, transmission characteristics and other aspects to the impact on the population. Thus, it can realize the comprehensive assessment of pollution prevention and control. This paper focuses on the field of air pollution prevention and control. We propose a refined pollution prevention and control method based on telecom operator data. This method can predict the users' distribution. Furthermore, it can analyze and predict the impacted users of air pollution, and finally to assist the Chinese "Blue Sky Plan".

The operation condition of wireless system directly impacts both the system performance and the quality of experience (QoE). On the basis of telecom operator data, this paper designs a comprehensive operation and revenue analysis (CORA) algorithm for LTE/5G wireless system. The objective of the proposed CORA algorithm is to analyze and evaluate both the operation state and the revenue of base station (BS) in the wireless system. The designed CORA algorithm is applied in the realistic 4G wireless system. The CORA algorithm can assist telecom operator to effectively analyze and evaluate the BS comprehensive state of operation and revenue.

The next-generation (5G) wireless networks have been evolving into very complex systems due to the diversified service requirements, heterogeneity in applications, devices, and networks. The network operators need to make the best use of the available resources, for example, power, spectrum, infrastructures, as well as data. Large amounts of data, generated from the network and the subscribers, would dramatically help make the system smart and efficient by advanced exploiting. Besides, the synergy of the 5G and the big data would create new services, which promotes a faster digital transformation of the vertical industries. In this paper, we first present the evolution of the big data in the uprising 5G era. Then, an overview of the interplay between the 5G and the big data is provided. Following gives the discussion on challenges and trends of the development of 5G and big data. To further illustrate the benefits, data-driven services are studied.

With the development of information technology, we are living in a society of data explosion. In precise marketing field, how to classify the population and identify the target users has attracted much concern. Based on telecom big data, this paper has proposed a precise user classification scheme using decision tree. According to the classification result, potential users can be identified and focused on, which can dramatically improve the marketing efficiency and effectiveness with limited marketing expense.

An interesting phenomenon, I D /I G intensity ratios between D mode and G mode increase around micro-wells, is observed in defective graphene sensors. A modified phenomenological model depicting the relation between I D /I G and the built-in stress is developed to reveal the physical mechanism of the above phenomenon. It is demonstrated that the initial defects in graphene gas sensors arising from fabrication processes can further propagate under the built-in tension resulting in increasing the defect density. The underlying mechanism is that the built-in stress provides the energy for the defect propagation of stretched graphene. The work could be helpful for applications of defective graphene-based devices.

Employee turnover indicates the staff decides to leave the company. Along with the fast development of economic and industries, employee turnover phenomenon becomes popular gradually in recent years. On one hand, the staff decides to leave the company due to various reasons. On the other hand, staff retention and job stability impact the normal operation of the company. Companies need to grasp the major factors of employee turnover, and then take relevant measures to deal with this problem. This paper employs machine learning technique to sort out the characteristics of employee turnover. Furthermore, we adopt GBDT algorithm and LR algorithm to fit the characteristic model which influences employee turnover. Finally, this paper implements the employee turnover prediction in realistic companies, which provides an effective reference for companies to reduce the turnover rate of employees.

The mobile advertising industry in China has developed rapidly in recent years. Many companies and brands tend to employ mobile advertising in order to reach the target customers accurately. However, the conversion rates associated with the advertising campaigns are usually quite low due to the low quality of the datasets and impropriate predictive model. In this paper, we propose a novel mobile advertising system architecture based on telecom big data analytics. The defined multi-dimensional user portrait is introduced for user label oriented ad display strategy or as the basic database for the further user classification algorithm. We also adopt the widely used logistic regression algorithm in this paper to improve the target accuracy. The result of use case, which is calculated from the real-time collected cellular network data, also shows the superior performance of the proposed mobile advertising system.

Traffic offloading is a widely used technique to address the unbalanced traffic distribution between pico cells and macro cells in heterogeneous cellular networks. However, the shifted users may result in the macro cell receiving large traffic from multiple pico cells and then becoming heavily loaded. This phenomenon is called the exacerbation problem in this paper. In order to address this problem and balance load effectively, this paper proposes a self-optimised joint traffic offloading (JTO) scheme. The JTO scheme jointly employs two traffic offloading techniques, including cell biasing technique to offload traffic between pico cell and macro cell, and mobility load balancing among macro cells. Simulation results show the JTO scheme can effectively deal with the cell exacerbation problem, in terms of handover failure and call dropping. The JTO scheme can also reduce the call blocking probability.

Telecom big data implies abundant user information. In this paper, it employs the telecom data and proposes a user clustering and influence power ranking scheme. The scheme is implemented through three stages, i.e. the user portrait analysis stage, the user clustering analysis stage and the ranking stage of user influence power. Experimental results have shown that, marketing promotion effectiveness based on this scheme has been improved significantly, while the advertising costs are also considerably reduced.

Mobility load balancing (MLB) is widely used to address the uneven load distribution problem. The basic idea is that a hot-spot cell selects less-loaded neighbouring cells as assistant cells, and thenshiftsitsedge users to assistant cells via the handover region adjustment. However, shifted users receive the reduced signal power after MLB, which may result in the poor link quality problem for shifted users. In order to deal with this problem, this paper proposes a mobility load balancing aware radio resource allocation (MLBRRA) scheme. In the MLBRRA scheme, the assistant cell jointly considers the MLB factor of the shifted user and that of the hot-spot cell, as well as the proportional fairness scheduling factor. More specifically, the assistant cell preferentially allocates radio resources to shifted users, which are suffering poor link quality or previously served by a hot-spot cell with large handover region. Simulation results show that the proposed MLBRRA scheme can effectively deal with the poor link quality problem in terms of handover failure and call dropping. The proposed scheme can also reduce the call blocking probability.

Traffic shifting is an efficient load balancing method to offload traffic from a hot-spot cell to neighbouring cells. This paper proposes a channel-aware optimised traffic shifting (COTS) scheme in LTE-Advanced relay networks. The COTS scheme employs a channel-aware assistant cell selection mechanism, which considers users' channel condition, received from the relay station (RS) in neighbouring cells, to select assistant cells and address the weak assistant cell problem. The optimal traffic offloading algorithm analyses and calculates the shifted traffic from the hot-spot cell to its assistant cells. Simulation results show that the COTS scheme can select a small number of neighbouring cells as assistant cells to effectively offload users, and can efficiently reduce the call blocking probability as well as the call dropping probability.

The gradual formation of mining right evaluation method system has provided a solid prop for domestic mining right evaluation activities. But, the results of practices have shown that the existing mining right evaluation method still has room for further improvement. Starting from basic principles, the paper analyses the shortcomings of discount cash flow method, comparable sales method and option valuation method, believing that, in the calculation method using the discount cash flow method, the advance deduction of the amount contributed for annual net cash flow or return on investment will cause the under valuation of mining right prices and greatly increase the uncertainty and complexity of the relevant administrative work of the mining industry, in the option evaluation method, the treatment method of directly using the validity term of mining right as the term of option overlooks the periodic characteristics of mining right implementation and is in obvious deviation from the reality of mining development. The paper then suggests ideas for improvement, i.e., in the utilization of the discount cash flow method, the safeguarding of the reasonable interests of mining investors should be incorporated into the setting of discount rate, while in the utilization of option evaluation method, the validity term of option should be the term after deduction of the basic cycle necessary for mining and development of the resources in the tenement from the validity term of mining right. Based on this thinking, the paper has improved the calculation methods of the discount cash flow method and the option evaluation method.

With the emergence of large-scale and super-large- scale dense residential areas, indoor and outdoor radio propagation environments are becoming increasingly complex, and the wireless communication needs of residential users is also gradually increasing. The wireless coverage of the WCDMA network in dense residential area is becoming the focus of the operators. This article puts forward a WCDMA propagation model for typical residential area based on COST-231- Walfisch-Ikegami pattern. This model is established by solving corresponding parameters and will forecast wireless coverage in those areas we cannot enter because of various reasons. Also the model will provide references of network assessment and optimization for the operators.

With the rapid growth of WCDMA users, channel element resources of mobile stations have appeared congestions in different degree, which has seriously affected the quality of user experience. At present, for the situation of channel element resources congestion of mobile stations, we commonly analyze the stations and make an expansion plan after a complaint in this area or many accesses failure or a lot drop calls of the stations. Meanwhile, when there are channel element expansion plans, we usually choose a region no matter if there are stations that need channel element expansion really. Thus, it will make the waste of resources inevitably. This paper will analyze the channel element resource utilization ratio deeply, build specific simulation model, and quantify the effect of channel element resource utilization ratio on the key indexes of the WCDMA/HSPA network. Then, the paper will give suggestions on configuring channel element resources of network more reasonably, to improve network performance, save network investment, provide important references on network optimization and operating maintenance for mobile operators.

The principle of antenna array distribution of two-dimensional synthetic aperture microwave radiometer is presented. The optimization technique based on differential evolution algorithm (DE) is presented for the design of antenna array. The object function is designed by minimizing redundant array and maximizing the distance between spatial frequency coverage samples, the stochastic array distributed on two-dimensional grid points are optimized, and the optimal results are obtained. Comparing with two-dimensional regular antenna array, the results show that the optimal array can obtain more spatial frequency samples and larger spatial frequency coverage.

With the continuous expansion of network scale and the growth of customer demands, the burst of data services brings a greater impact onto the network. The configuration and optimization of data services have also become a difficult point to operators. This paper analyzes the impact of the HSPA introduction into WCDMA R99 commercial network from theoretic calculation and simulation analysis, and then puts forward the suggestions on the basis of simulation results.

Analysis of synthetic aperture microwave radiometer errors in channel such as mutual-coupling, channel imbalance, system noise based on two-dimensional 16 cells array arrangement is given, and the simulation models are established. Then the error compensation method, noise elimination and Image reconstruction based on BG Algorithm is given. Simulations show compensation method of channel error is valid.

A new optimization technique based on the differential evolution algorithm is presented for the design of two-dimensional synthetic aperture microwave radiometer circle array. The object function is designed by minimizing redundant array and maximizing the distance between spatial frequency coverage samples and the optimal results of 16~32 elements circle array are obtained. Compare with simulated annealing algorithm and symmetrical distribution array, the numerical results show that the differential evolution algorithm can obtain a better solution and observably decrease computational run time. The image reconstruction and inversion algorithm of two-dimensional synthetic aperture microwave radiometer is G matrix algorithm. Compare with the symmetrical circle array, the image reconstruction of the optimal array is better.

A new optimization technique based on the hybrid algorithm combining ant colony optimization algorithm with microgenetic algorithm is presented for the design of multilayered radar absorbing materials. During the optimization procedure the optimization constrained conditions are different in order to meet the practical requirements in the different frequency bands between 2 GHz and 18 GHz, and the multilayered radar absorbing materials is also designed for a given maximum total thickness. The effects of the thickness and the number of layers on the optimization results are discussed in detail. The numerical results show that this new hybrid algorithm can obtain a better solution than that of the genetic algorithm.

A novel compact broadband multilayer microstrip antenna is presented in this paper. The VSWR, gain and radiation pattern of this antenna are simulated. The measured VSWR of it is also shown in the paper. The results are discussed in detail.

A novel eighth wavelength patch antenna is presented in this paper. The VSWR, gain and radiation pattern of this antenna are simulated. The results are discussed in detail.

An optimization method based on the microgenetic algorithm (MGA) is presented for the design of multilayered radar absorbing materials made of tetrapod-shaped ZnO whisker. The optimization procedure is designed for a given thickness and the optimization conditions, which are different in order to meet the practical requirements in the different frequency bands (the range of 2~18GHz). The effects of the thickness, the number of layers, and the restrained conditions on the optimization results are discussed in detail.

An optimization technique based on the microgenetic algorithm (MGA) is presented for the design of multilayered radar absorbing materials made of tetrapod-shaped ZnO whisker in this paper. The fast optimization procedure is designed for a given maximum thickness and the optimization conditions are different in order to meet the practical requirements in the different frequency bands (the range of 2/spl sim/18GHz). The effects of the thickness, the number of layers, and the restrained conditions on the optimization results are discussed in detail.