能量收集节点的最优压缩传输策略

Hamed Mirghasemi, I. Stupia, L. Vandendorpe
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引用次数: 1

摘要

我们考虑一个能量收集发射机,它可能需要压缩接收到的数据包,然后在一个平坦的衰落信道上转发它们。数据压缩需要满足带宽或能量的限制,但代价是数据失真。目标是设计最优的压缩和传输策略,即最优的传输和压缩功率、传输和压缩率以及传输和压缩时间,从而使总失真最小化。本文考虑了一个时隙系统,该系统在每个时隙(TS)的开始都有新的数据和能量包到达,并且在每个时隙期间信道增益保持不变。在能量和数据到达以及信道增益非因果已知的假设下,对应于离线优化,我们将压缩和传输调度优化表述为一个凸优化问题,并表征了最优调度的性质。对于严格延迟情况下,每个数据包的传输和压缩必须在相应的TS内执行,我们提供了一种模拟迭代定向充水(IDWF)算法的迭代算法。数值结果说明了我们的结果和最优调度的性质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Compression and Transmission Policies for Energy Harvesting Nodes
We consider an energy harvesting transmitter which may need to compress received packets before forwarding them over a flat fading channel. Data compression is required to meet the bandwidth or energy constraint at the cost of data distortion. The objective is to design optimal compression and transmission policies, namely optimal transmission and compression powers, transmission and compression rates and transmission and compression times, such that the total distortion is minimized. In this paper, we consider a time slotted system where new data and energy packets arrive at the beginning of each time slot (TS) and channel gains are assumed to remain constant during each TS. Under the assumption that the energy and data arrivals and channel gains are known non-causally which corresponds to offline optimization, we formulate the compression and transmission scheduling optimization as a convex optimization problem and characterize the properties of optimal scheduling. For the strict delay case where the transmission and compression of each packet must be executed within the corresponding TS, we provide an iterative algorithm which mimics the iterative directional water-filling (IDWF) algorithm. Numerical results are provided to illustrate our results and the properties of optimal scheduling.
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