With the development of mobile Internet technology and the popularity of intelligent mobile terminals, the data traffic load of mobile client users on the smart campus network platform has surged. How to reduce the data traffic of the smart campus network platform is an urgent problem to be solved. First, this paper discussed the key technologies of smart campus network teaching platform under the background of the 5G network, expounded the critical technologies of the transport layer of the Internet of Things (IoT) technology, and analyzed from the development perspective of the IoT platform. Second, by investigating the online classroom data of five types of colleges and universities in China and comparing the advantages and disadvantages of online classroom teaching and traditional classroom teaching, it is found that the number of online courses in colleges and universities has exploded in the second half of 2017. Next, this paper analyzed the demand of smart campus online teaching platform under the background of the 5G network, thus established an online teaching platform based on the four initiatives operation model (government-led, college sponsor, teacher subject, and academic director). Finally, this paper adopted the improved VIRE localization algorithm to obtain the specific location information of the student users in the classroom and, then, compared with the error obtained by the VIRE algorithm, and the error of the improved VIRE algorithm is smaller. In the process of obtaining information, the 5G network technology is used for data transmission, which can shorten the check-in time and can improve the positioning accuracy. INDEX TERMS 5G network, smart campus, online teaching platform, improved VIRE location algorithm.

Cognitive radio (CR) paradigm was introduced, towards addressing challenges,related with radio spectrum scarcity and increased needs for wireless networking services provision. In this direction, CR networks exploit novel networking architectures, as well as dynamic radio spectrum access techniques and methods, alleviating problems, regarding limited wireless networking resources and their inefficient usage/exploitation. CR terminals exploit innovative mechanisms to identify unused parts of radio spectrum, such as TV white spaces (TVWS) in ultra-high frequency/ frequency bands following an interference-free opportunistic manner. However, introduction of CR networks creates new challenges that are highly related to the fluctuation of TVWS, as they vary over time and location, as well as issues related to diverse Quality of Service requirements. In this context, this paper proposes two radio resource management (RRM) algorithms, enabling for the opportunistic exploitation of TVWS in a centralised CR networking architecture. Efficient administration of radio spectrum resources is achieved, by exploiting a novel RRM framework, adopted in a spectrum broker, which is in charge to effectively orchestrate the available wireless networking resources. Efficient RRM algorithms performance, as a matter of maximum-possible spectrum broker benefit and radio spectrum utilisation, as well as minimum-possible spectrum fragmentation is evaluated, by considering a fixed-price and an auction-based optimization approach. Experimental tests that were conducted under controlled simulation conditions, confirmed the validity of both RRM algorithms adopted in the proposed CR networking architecture, identifying fields for further research and experimentation.

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Aiming at the problem of device-to-device (D2D) communication mode selection and resource optimization under the joint resource allocation mode in the 5G communication network, a probabilistic integrated resource allocation strategy and a quasi-convex optimization algorithm based on channel probability statistical characteristics are proposed. This strategy and algorithm guarantee D2D. Communication maximizes total system throughput while maximizing access. The analysis results show that this algorithm can significantly optimize the total throughput of the system and reduce the communication interference between the users, which proves the rationality and efficiency of the communication model. The research results obtained in Muwen can provide a theoretical basis for analyzing more complex D2D communication systems and provide a numerical basis for designing heuristic algorithms.

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