Millimeter-wave (mmWave) communication technology offers a potential and promising solution to support 5G and B5G wireless networks in dynamic scenarios and applications. However, mobility introduces many challenges as well as opportunities to mmWave applications. To address these problems, we conduct a survey of the opportunities and technologies to support mmWave communications in mobile scenarios. Firstly, we summarize the mobile scenarios where mmWave communications are exploited, including indoor wireless local area network (WLAN) or wireless personal area network (WPAN), cellular access, vehicle-to-everything (V2X), high speed train (HST), unmanned aerial vehicle (UAV), and the new space-air-ground-sea communication scenarios. Then, to address users’ mobility impact on the system performance in different application scenarios, we introduce several representative mobility models in mmWave systems, including human mobility, vehicular mobility, high speed train mobility and ship mobility. Next we survey the key challenges and existing solutions to mmWave applications, such as channel modeling, channel estimation, anti-blockage, and capacity improvement. Lastly, we discuss the open issues concerning mobility-aware mmWave communications that deserve further investigation. In particular, we highlight future heterogeneous mobile networks, dynamic resource management, artificial intelligence (AI) for mobility and integration of geographical information, deployment of large intelligent surface and reconfigurable antenna technology, and finally, the evolution to Terahertz (THz) communications.

Public blockchain network (PBN) has been widely used in wired networks such as bitcoin network, in which Proof-of-Work (PoW) algorithm is deployed among miners to reach consensus on users data during the mining process. However, the PoW consensus mechanism is computation-consuming which obstacles the application of PBN in wireless mobile networks since most Internet of Things/mobile devices (IMDs) are resource-limited. Recently, mobile edge computing (MEC) has been regarded as a promising technology which can allow IMDs to offload their computation tasks to the edge nodes. Although IMDs can offload their computation tasks to the edge nodes, there is still lots of competition among enormous solo mining IMDs when reaching consensus. In this paper, we first formulate the computation resource allocation problem of PBN from the viewpoint of coalition game theory under the MEC environment. Then, we propose a coalition formation game-based algorithm to maximize the system sum utility and take both the individual profit of IMD and coalition profit into consideration. Furthermore, we prove the proposed algorithm converges to a Nash-stable partition in a fast convergence rate and finally reaches the near-optimal solution with low computational complexity. The simulation results demonstrate the optimality and convergence of the proposed algorithm, and the proposed algorithm outperforms other schemes in terms of system sum profit and ratio of rewarded IMDs to overall IMDs.

To deal with the explosive growth of mobile traffic, millimeter-wave (mmWave) communications with abundant bandwidth resources have been applied to vehicular networks. As mmWave signal is sensitive to blockage, we introduce the unmanned aerial vehicle (UAV)-aided two-way relaying system for vehicular connection enhancement and coverage expansion. How to improve transmission efficiency and to reduce latency time in such a dynamic scenario is a challenging problem. In this paper, we formulate the joint optimization problem of relay selection and transmission scheduling, aiming to reduce transmission time while meeting the throughput requirements. To solve this problem, two schemes are proposed. The first one is the random relay selection with concurrent scheduling (RCS), a low-complexity algorithm implemented in two steps. The second one is the joint relay selection with dynamic scheduling (JRDS), which fully avoids relay contentions and exploits potential concurrent ability, to obtain further performance enhancement over RCS. Through extensive simulations under different environments with various flow numbers and vehicle speeds, we demonstrate that both RCS and JRDS schemes outperform the existing schemes significantly in terms of transmission time and network throughput. We also analyze the impact of threshold selection on achievable performance.

With the rapid development of high-speed railway systems and railway wireless communication, the application of ultra-wideband millimeter wave band is an inevitable trend. However, the millimeter wave channel has large propagation loss and is easy to be blocked. Moreover, there are many problems such as eavesdropping between the base station (BS) and the train. As an emerging technology, reconfigurable intelligent surface (RIS) can achieve the effect of passive beamforming by controlling the propagation of the incident electromagnetic wave in the desired direction. We propose a RIS-assisted scheduling scheme for scheduling interrupt flows and improving quality of service (QoS). In the propsed scheme, an RIS is deployed between the BS and multiple mobile relays (MRs). By jointly optimizing the beamforming vector and the discrete phase shift of the RIS, the constructive interference between direct link signals and reflected link signals can be achieved, and the channel capacity of eavesdroppers is guaranteed to be within a controllable range. Finally, the purpose of maximizing the number of successfully scheduled flows and satisfying their QoS requirements can be practically realized. Extensive simulations demonstrate that the proposed scheme has superior performance regarding the number of completed flows and the system secrecy capacity over four baseline schemes in literature.

To exploit richer spectrum resources for even better service quality, millimeter wave (mmWave) communication has been considered for high-speed railway (HSR) communication systems. In this paper, we focus on scheduling as many flows as possible while satisfying their QoS requirements. Due to interference, eavesdropping, or other problems, some flows may not be directly transmitted from the track-side BS. In this paper, we propose an UAV-assisted scheduling scheme which utilizes a UAV to serve as relay for such flows. The proposed scheme also utilize two mmWave bands, one for the BS links and the other for the UAV links. The proposed algorithm aims to maximize the number of flows with their QoS requirements satisfied. Simulations demonstrate that the proposed scheme achieves a superior performance on the number of completed flows and the system throughput over two baseline schemes.