With the rapid development of the fifthgeneration wireless communication systems, a profound revolution in terms of transmission capacity, energy efficiency, reliability, latency, and connectivity is highly expected to support a new batch of industries and applications. To achieve this goal, wireless networks are becoming extremely dynamic, heterogeneous, and complex. The modeling and optimization for the performance of realworld wireless networks are extremely challenging due to the difficulty to predict the network performance as a function of network parameters, and the prohibitively huge number of parameters to optimize. The conventional network modeling and optimization approaches rely on drive test, trial-and-error, and engineering experience, which are labor intensive, error-prone, and far from optimal. On the other hand, while the research community has spent significant efforts in understanding the fundamental limits of radio channels and developing physical layer techniques to operate close to it, very little is known about the performance limits of wireless networks, where millions of radio channels interact with one another in complex manners. This paper reviews the very recent mathematical and learning based techniques for modeling and optimizing the performance of real-world wireless networks in five aspects, including channel modeling, user demand and traffic modeling, throughput modeling and prediction, network parameter optimization, and IRS empowered performance optimization, and also presents the corresponding notable performance gains.

With the demand for Internet connectivity in remote areas, the space-air-ground integrated network (SAGIN) was proposed to achieve ubiquitous coverage and enhance service capabilities of extant terrestrial networks. The paradigm of virtual network element placement (NEP) is applied into SAGIN. It can save energy and operating costs by placing specific network elements (NEs) as software instances. In addition, it helps to provide services in end-to-end networks with its ability to allocate and manage resources flexibly. However, NEP faces some challenges in SAGIN. The network topologies can be dynamic, and links such as the satellite-to-ground and air-to-ground ones are prone to fail. These will make NEP management more complicated. Moreover, the static NEP schemes are hard to accommodate the time-varying traffic. In this context, this work explains the NEP problem in SAGIN from three aspects, i.e., the SAGIN radio access network (RAN), the SAGIN core network (CN), and the SAGIN barrier network (BN). First, the physical and networking architectures of SAGIN are introduced. Then the status of the network element placement and corresponding challenges are described from these two aspects. Finally, this paper discusses future research directions and key technical challenges.

Thinking space came into being with the emergence of human civilization. With the emergence and development of cyberspace, the interaction between those two spaces began to take place. In the collision of thinking and technology, new changes have taken place in both thinking space and cyberspace. To this end, this paper divides the current integration and development of thinking space and cyberspace into three stages, namely Internet of brain (IoB), Internet of thought (IoTh), and Internet of thinking (IoTk). At each stage, the contents and technologies to achieve convergence and connection of spaces are discussed. Besides, the Internet of creation (IoC) is proposed to represent the future development of thinking space and cyberspace. Finally, a series of open issues are raised, and they will become thorny factors in the development of the IoC stage.