IEEE 802.11ax, as a new generation of wireless local area network (WLAN) standard, has great development potential for multi-service access in industrial WLAN with its characteristics of low-cost, quick-deployment and high-efficiency. However, it still faces the problem of quick and efficient access point (AP) seamless handover for multi-service communications due to terminal mobility and channel degradation. To solve the problem, combining the characteristics of orthogonal frequency division multiple access (OFDMA) technology and multi-user multiple-input multiple-output (MU-MIMO) technology, this paper firstly proposes an edge computing based IEEE 802.11ax multi-service bearer mechanism by dynamically allocating channel resource units (RUs). Secondly, a multi-service AP seamless handover mechanism based on edge computing is proposed, which consists of a channel scanning delay optimization method based on virtual AP sentinel, a handover trigger judgment algorithm considering mobility and RU reallocation, a multi-objective optimized AP handover model considering load balancing, transmission rate optimization and handover cost minimization with service attributes. Finally, we propose a multi-service AP seamless handover algorithm based on improved particle swarm optimization (PSO) to get optimized handover making-decision. Simulation results show that the proposed handover mechanism can reduce the handover delay significantly while realizing seamless handover accurately in multi-service industrial WLAN.

The widespread application of terminal sensors in power pipe galleries (PPGs) has significantly improved our ability to monitor power equipment status. However, the difficulties in battery replacement caused by confined space and energy loss caused by communication conflicts between sensors due to existing low-power communication strategies results in a lack of reliable energy supply for terminal sensors. In this context, a low-power communication strategy for terminal sensors is proposed. Firstly, a demand analysis is conducted on the status monitoring of PPGs, and a technical framework for low-power communication of terminal sensors is proposed. Afterward, a system model for the low-power communication of terminal sensors is established based on cognitive backscatter technology. Subsequently, key technologies, such as RF energy harvesting of terminal sensors and distance–energy level coupling analysis, are proposed to achieve continuous energy supply and avoid communication conflicts in the system model. Finally, a wireless communication simulation environment for PPGs is established to simulate the status monitoring process, based on terminal sensors, in order to verify the effectiveness of the proposed method.