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Stochastic Geometric Analysis of Handover Based on Fuzzy Logic in MIMO IoT Systems

High-density base station (BS) will bring the problem of frequent handover to mobile Internet of Things (IoT) devices. Frequent handover will lead to Quality-of-Service (QoS) problems, such as increased handover delay and reduced data transmission rate. In order to overcome the limitation of mobile IoT devices’ QoS caused by frequent handover BSs, the multiple-input–multiple-output (MIMO) systems can be used to improve the channel capacity and reduce the BS density. However, because the handover decision of mobile IoT devices will affect the data rate and network stability, how to implement the handover to reduce the impact of handover on mobile IoT devices is a problem worthy of study. Therefore, this article proposes a handover strategy based on fuzzy logic in MIMO systems, which are used to reduce the handover frequency and improve the average data rate of mobile IoT devices. First, the mobile IoT devices convert the devices’s speed, the distance from the devices to the MIMO systems, and the transmission power of the MIMO systems to fuzzy values. Then, the fuzzy values obtained in the first step are taken as the input, and the fuzzy-logic-based handover algorithm is implemented through the fuzzy logic controller. Finally, according to the results of the handover algorithm and the theoretical results about the average throughput of mobile IoT devices derived in this article, the number of antennas used to provide transmission services for IoT devices with different data rate requirements and different mobile speeds can be allocated more flexibly. Simulation results show that the proposed scheme achieves a better performance.