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Non-orthogonal multiple access (NOMA) technology is expected to effectively improve the spectrum efficiency of fifth-generation and later wireless networks. As a new technology, reconfigurable Intelligent surfaces (RIS) can achieve high spectral and energy efficiency with a low cost in wireless networks. These are achieved by integrating a great quantity of low-cost passive reflective units (RUs) on the plane. In this article, in order to meet the needs of high efficiency, low power consumption, and wide coverage, we combine RIS-assisted NOMA technology with the internet of things (IoT). Because in the actual wireless communication system, the residual hardware impairment (RHI) characteristics of the actual transceiver equipment will have an important impact on system secrecy performance. Therefore, the study will propose a single eavesdropper RIS-assisted downlink NOMA system with RHI (E-RHI-RIS-NOMA). The study will also investigate the impact of RHI on the physical layer security (PLS) performance of the system and the closed-form expression of the user’s secrecy outage probability (SOP) is derived. Finally, the simulation results show that 1) the main factors affecting the SOP are the quantity of RUs in RIS, the transmit SNR, and the target data rate, 2) it is proved that the hardware impairment of the transceiver harms the system’s secrecy outage performance while the severity of the impact of RHI on the system performance depends on the transmit SNR and target data rate. Moreover, RHI at different nodes has a different influence on system secrecy performance. 3) the system performance of RIS relying on NOMA is improved compared with orthogonal multiple access (OMA) and conventional NOMA.

Alighting and boarding efficiency (A&Be) of passengers plays an important role in the formulation of subway timetable. This paper studies the impact of alighting area width on A&Be based on the improved social force model. This improved model adopts the fuzzy logic theory considering factors of train dwell time and passengers ahead to determine the desired speeds of passengers instead of setting fixed values. The $t$ -test method verifies the validity of the model. The passenger movement dynamics characterized by the alighted or boarded passenger quantities, the desired speeds, and the actual speeds over time is then analyzed. The simulation results indicate when people keep to the civilized rules of alighting first, A&Be will be improved significantly with increasing the alighting area width. Otherwise, the arbitrary increase of alighting area width does not necessarily improve A&Be. The alighting area width during the actual design should be determined by the specific passenger volume and passenger civility. Whether the countermeasure of adding the fences to separate the alighting passengers from the boarding passengers is effective to improve the travel efficiency is finally explored through analyzing the simulation results. Our findings could provide theoretical supports for decision-making of waiting area division on the subway platform and passenger flow management in reality.

The exit selection behavior of pedestrians plays an important part in the process of evacuation. This paper proposes a cellular automata model based on fuzzy logic method for simulating the evacuation of pedestrians from a multiple-exit room. When pedestrians select the exit, the distance and density are adopted as two important input variables in the fuzzy logic method, and the probability of selecting each exit is defined as the output variable of fuzzy logic method. The output variable of fuzzy logic, exit width and herding behavior are combined to determine the target exit. The competitiveness of each pedestrian is calculated by logit model to solve the position conflicts among pedestrians. The validation of the model is demonstrated by comparing the simulation data with the real data. The effects of attributes of pedestrians, exits and obstacles on evacuation are studied in simulations. Results show that large public facilities should control the inflows of pedestrians, and the reasonable increase of the exit quantity and exit width are effective for improving the evacuation efficiency. In the design of buildings, obstacles need to be designed reasonably, which should not be too large or too small. At the same time, obstacles should be kept at a certain distance from the exit, so as to ease the exit congestion and improve the evacuation efficiency. This paper takes the advantages of fuzzy logic method to solve the exit selection problem, which can effectively integrate the robustness with physiological-based “perception-action” behavior, the experience knowledge of pedestrians and the perception information of the surrounding environment into the decision-making process.

This paper investigates the energy efficiency (EE) optimization for massive multiple-input multiple-output (MIMO) systems powered by wireless power transfer (WPT) with hardware impairments at sensor nodes (SNs). In the considered system, the SNs are first powered by the WPT from power beacon (PB). Then, the SNs use the harvested energy to transmit data to the base station (BS) with large scale of multiple antennas. Finally, the BS employs maximal-ratio combining (MRC) to detect the data symbols transmitted by the SNs. As the EE optimization problem is a non-convex problem which is difficult to solve directly. A lower bound approximation and variable substitution method are used to transform the EE maximization problem into a concave-linear fractional programming. Then, an energy efficient resource allocation algorithm that combines time and power allocation is proposed by fractional programming to maximize the EE of the system. Finally, simulation results are presented to show the effectiveness of the proposed algorithm and the impact of the hardware impairments on the system performance.