Environment-aware streaming media transmission method in high-speed mobile networks

With technological advancements, high-speed rail has emerged as a prevalent mode of transportation. During travel, passengers exhibit a growing demand for streaming media services. However, the high-speed mobile networks environment poses challenges, including frequent base station handoffs, which significantly degrade wireless network transmission performance. Improving transmission efficiency in high-speed mobile networks and optimizing spatiotemporal wireless resource allocation to enhance passengers' media experiences are key research priorities. To address these issues, we propose an Adaptive Cross-Layer Optimization Transmission Method with Environment Awareness (ACOTM-EA) tailored for high-speed rail streaming media. Within this framework, we develop a channel quality prediction model utilizing Kalman filtering and an algorithm to identify packet loss causes. Additionally, we introduce a proactive base station handoff strategy to minimize handoff-related disruptions and optimize resource distribution across adjacent base stations. Moreover, this study presents a wireless resource allocation approach based on an enhanced genetic algorithm, coupled with an adaptive bitrate selection mechanism, to maximize passenger Quality of Experience (QoE). To evaluate the proposed method, we designed a simulation experiment and compared ACOTM-EA with established algorithms. Results indicate that ACOTM-EA improves throughput by 11% and enhances passengers' media experience by 5%.