发表机构
Uppsala University; RISE Sweden; Politecnico di Milano（乌普萨拉大学; 瑞典RISE研究院; 米兰理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究针对无电池移动物联网的反向散射通信问题，设计轻量决策系统结合NVM存储，实现吞吐量提升、能耗降低，性能优于仅考虑瞬时信道的速率自适应基线。
AI 中文摘要
我们在无电池移动物联网（IoT）中实现了反向散射通信。反向散射通信已在静态场景中得到广泛研究，但现有设计与移动性和时变能量模式存在根本性不匹配：信道条件快速波动，影响可达数据速率及传输成本；能量可用性不可预测，可能迫使设备静止以补充能量缓冲。这两个问题相互加剧：无电池移动IoT设备充电时可能错过更优信道条件。我们设计了轻量决策系统，通过检查信号强度短期趋势动态决定何时传输，同时使用非易失性存储器（NVM）在不利信道条件及能量故障时保留数据包。基于自建原型及真实移动性与功率轨迹，我们将该设计与仅考虑瞬时信道条件的速率自适应基线对比，实验结果显示，本系统吞吐量提升最高达5.16倍，传输能耗降低最高达47.3%，仅产生0.23%至7.3%的额外能量开销。
英文摘要
We enable backscatter communication in the battery-less mobile Internet of Things (IoT). Backscatter communication is extensively studied in static settings. Existing designs are, however, fundamentally mismatched with mobility and time-varying energy patterns. Channel conditions rapidly fluctuate, impacting the achievable data rates and thus transmission costs. Energy availability varies unpredictably, possibly forcing devices to remain quiescent to recharge energy buffers. The two issues compound each other: while recharging, a battery-less mobile IoT device may miss more favorable channel conditions. We design a lightweight decision system that dynamically determines when to transmit by checking short-term trends in signal strength, while using Non-volatile Memory (NVM) to retain packets in unfavorable channel conditions and across energy failures. Using a prototype we built and real-world mobility and power traces, we compare our design against a rate-adaptive baseline that only considers the instantaneous channel conditions. Experimental results show that our system improves throughput by up to 5.16x while reducing transmission energy consumption by up to 47.3%, with only 0.23% - 7.3% additional energy overhead.
Comments11 pages, 20 figures. Extended version of the paper accepted at MSWiM 2026
