Most data collection methods based on Compressive Sensing(CS) usually assume that the network has no interference or it can take effective conflict avoidance measures.When these methods are applied to the network with interference or noise,they cannot balance the energy efficiency and reliability.Therefore,based on the compression theory,the data collection problem under the physical interference model is studied,which is modeled as the combined problem of forwarding-tree construction and link scheduling combined problem,and a distributed algorithm for forwarding-tree construction and link scheduling is proposed to determine a set of forwarding-tree and send the measured data to the sink after forwarding-tree scheduling in the shortest scheduling cycle,so as to achieve balance between the transmission delay and collection energy efficiency.Simulation results show that the proposed algorithm can effectively reduce the data transmission delay and improve energy efficiency of data collection.%多数基于压缩感知的数据收集方法假设网络无干扰或能够采取有效的冲突避免措施,当网络存在干扰或噪声时,难以同时兼顾效率和可靠性.为此,以压缩感知理论为基础,研究物理干扰模型下的数据收集问题,将其建模为转发树构建和链路调度联合问题,并设计可构建转发树的分布式求解算法,确定一组转发树并在调度后于最短调度周期内将测量数据发往汇点,实现传输延时和采集能效间的平衡.仿真结果表明,该算法能有效降低数据传输延时,提高数据采集能效.
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