能量收集型短包通信LoRa网络的信息年龄建模与优化

肖舒予; 孙兴华; 袁岸珊; 詹文; 陈翔

doi:10.11999/JEIT250814

能量收集型短包通信LoRa网络的信息年龄建模与优化

doi: 10.11999/JEIT250814 cstr: 32379.14.JEIT250814

1.
中山大学电子与通信工程学院深圳 518107
2.
中山大学电子与信息工程学院广州 510000

基金项目: 深圳市科技计划项目 (CJGJZD20240729142100001)，广东省基础与应用基础研究基金 (2025A1515010235, 2024A1515012015)

详细信息

作者简介:
肖舒予：女，硕士生，研究方向为随机接入的性能分析与优化等

孙兴华：男，副教授，博士生导师，研究方向为下一代无线通信网络、智能无线网络等

袁岸珊：男，博士生，研究方向为通感一体化、通信系统性能分析与优化、强化学习等

詹文：男，副教授，硕士生导师，研究方向为物联网、下一代无线通信网络、强化学习、排队论及其在无线通信中的应用等

陈翔：男，教授，博士生导师，5G/6G移动通信与物联网、卫星通信、电信大数据等

通讯作者:
孙兴华　sunxinghua@mail.sysu.edu.cn

1¹⁾尽管功率控制可使节点在接收端维持近似恒定的平均功率，但大尺度衰落仍会引入信道异构性。对此，本文分析框架具有良好的可扩展性：将信道条件相近的节点划分为同构节点组，为各组设置相应的接收端信噪比，分别评估其性能，并按节点数量加权得到异构网络的平均 AoI。类似的分组加权方法已在相关研究中采用，例如文献[16]用于系统吞吐量分析。
2²⁾文献[10]对接收端进行了有效的模型简化，假设一旦网络中出现并发传输，当前所有传输均失败。由此得到的碰撞模型可合理近似并发传输条件下解码错误概率急剧上升的物理层特性，且已被广泛应用于随机接入网络的理论分析中^[5]。³⁾尽管碰撞模型忽略了并发传输数量变化对解码错误概率的细微影响，本文结论在SINR模型下仍然成立，因为AoI本质上由更新间隔、成功传输概率与能量收集过程的权衡所决定，该关系不因接收模型而改变。文献[15]的分析亦表明，在SINR模型中较高的成功传输概率通常AoI性能更佳。相比之下，碰撞模型在刻画AoI性能下限的同时提升了模型的可解析性。
中图分类号: TN926.1
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- 被引次数: 0
出版历程
- 收稿日期: 2025-08-28
- 修回日期: 2025-12-29
- 录用日期: 2025-12-29
- 网络出版日期: 2026-01-04

Age of Information for Energy Harvesting-Driven LoRa Short-Packet Communication Networks

1.
School of Electronics and Communication Engineering, Sun Yat-sen Univ., Shenzhen 518107, China
2.
School of Electronics and Information Technology, Sun Yat-sen Univ., Guangzhou 510000, China

Funds: Shenzhen Science and Technology Program (CJGJZD20240729142100001), Guangdong Basic and Applied Basic Research Foundation (2025A1515010235, 2024A1515012015)

摘要

摘要: 针对工业物联网短包通信的应用场景，该文研究了能量收集驱动短包通信LoRa网络中的信息新鲜度问题。该文将能量队列建模为马尔可夫链，推导出平均信息年龄的一般表达式。进一步地，在最小电池容量与理想无限电池容量两种情况下，给出平均信息年龄优化策略及最优参数的解析解。最后，仿真验证了理论优化结果，并分析了网络各参数对系统性能的影响，为能量收集驱动的工业物联网的设计与优化提供了理论参考。
- 信息年龄 /
- 能量收集 /
- 短包通信 /
- 时隙Aloha /
- 工业物联网
Abstract: Objective In short-packet communication scenarios for the Industrial Internet of Things (IIoT), devices operate under stringent energy constraints, whereas certain applications require timely data delivery, which makes real-time performance difficult to guarantee. To address this issue, this study analyzes information freshness in Energy Harvesting (EH) networks and examines the effects of energy storage capacity, random access strategies, and packet block length on the Age of Information (AoI). The objective is to provide effective optimization guidelines for the design of practical IIoT communication systems. Methods An accurate system model is established based on short-packet communication theory, random access mechanisms, and EH models. The charging and discharging processes of the energy queue are characterized as a Markov chain, from which the steady-state distribution of energy states is derived, followed by a general expression for the average AoI. A mathematical optimization problem is then formulated to minimize the average AoI. To improve practical applicability, two extreme battery-capacity scenarios are considered. For the minimum battery capacity case, a closed-form analytical solution for the optimal packet generation probability is obtained. For the ideal infinite battery capacity case, the packet generation probability and packet block length are jointly optimized, yielding closed-form optimal solutions for both parameters. Extensive simulations are conducted to evaluate the average AoI under different network parameter settings and to verify the effectiveness of the proposed optimization strategies. Results and Discussions An analytical expression for the average AoI is derived, and its optimization is investigated under two extreme battery-capacity conditions. For the minimum battery capacity case, the optimal packet generation probability balances update frequency and channel collision (Fig. 5). As the network size increases, the optimal packet generation probability decreases, which significantly improves the average AoI (Theorem 1; Fig. 6). For the ideal infinite battery capacity case, both packet block length and packet generation probability affect the average AoI (Fig. 7). With a fixed packet generation probability, optimizing the packet block length reduces the AoI, which indicates the existence of an optimal block length that balances transmission reliability and energy consumption. When the packet block length is fixed, a low packet generation probability leads to infrequent updates and increased delay, whereas a high probability increases collision in the Energy-Sufficient Regime (ESR) but enables more efficient utilization of energy and channel resources in the Energy-Limited Regime (ELR). Joint optimization of the packet block length and packet generation probability is consistent with the solution obtained via exhaustive search (Theorem 2; Fig. 8). The optimal packet block length increases with network size. In the ELR, the optimal packet generation probability remains equal to one, whereas it decreases with network size to balance update frequency and collision risk (Fig. 9, Fig. 10). In addition, the average AoI varies with the energy arrival rate, which reveals the effects of battery capacity and packet generation probability on overall system performance (Fig. 11). Conclusions For the minimum battery capacity case, the average AoI is minimized when the packet generation probability is set to its theoretical optimal value. Under ideal infinite battery capacity, both the packet generation probability and the packet block length must be jointly configured to their respective theoretical optimal values to achieve the minimum average AoI. Theoretical analysis shows that the selection of the optimal packet block length requires a trade-off between decoding error probability and energy consumption. In the ELR, when the packet block length is preconfigured to its optimal value, an energy buffer supporting a single transmission is sufficient, which allows network nodes to adapt effectively to external energy supply limitations. Network nodes should actively access the channel to fully utilize harvested energy and maintain timely information updates, thereby achieving the optimal average AoI. In contrast, under abundant energy conditions or in large-scale networks, network nodes should adjust the packet generation probability to balance channel collision and update frequency. Simulation results further confirm the proposed optimization strategy and demonstrate that the optimized LoRa network significantly improves information timeliness, which provides theoretical guidance for the design of low-power short-packet communication systems.
- Age of Information (AoI) /
- Energy Harvesting (EH) /
- Short-packet communications /
- Slotted aloha /
- Industrial Internet of Things (IIoT)

HTML全文

图 1 系统模型示例图

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图 2 信息年龄演变过程示意图

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图 3 小电池容量情况下状态转移示意图

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图 4 理想无限电池容量情况下状态转移示意图

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图 5 平均信息年龄$ \bar \varDelta _{B=N_x}$关于数据包生成概率的模拟仿真图

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图 6 最小电池容量情况下优化前后平均信息年龄对比以及对应最优参数

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图 7 平均信息年龄$ \bar \varDelta _{B\to\infty }$分别与码长N和数据包生成概率q的模拟仿真图

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图 8 平均信息年龄$\bar \varDelta_{B\to \infty}$与码长N和数据包生成概率q的关系

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图 9 ELR 下优化前后平均信息年龄对比以及联合最优参数

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图 10 ESR 下优化前后平均信息年龄对比以及联合最优参数

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图 11 平均信息年龄$ \bar \varDelta $关于能量到达概率$ \delta$的模拟仿真图

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