arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1408.2302cs.ITmath.IT
收藏

能量、时延和缓存约束下的信源-信道编码

Source-Channel Coding under Energy, Delay and Buffer Constraints

Oner Orhan, Deniz Gunduz, Elza Erkip

摘要:

研究了能量受限的无线传感器节点的信源-信道编码.传感器节点观察独立的高斯源样本的方差随时隙变化,并通过平坦衰落信道发送到目的地。衰落在每个时隙期间是恒定的。压缩样本存储在有限大小的数据缓冲器中,并且需要在最多$d$时隙中传送。我们的目标是设计最佳的传输策略,即最佳的功率和失真分配,在时隙,使在目的地的平均失真最小化。特别是,各种能量约束的最优传输策略进行了研究。首先,电池供电的系统中,传感器节点有一个有限的能量在开始传输的影响。然后,能量收集的影响,处理和采样的能量成本被考虑。对于每个能量约束,一个凸优化问题,制定和最优传输策略的属性。对于严格延迟情况,给出了$d=1$、$2D$充水解释。数值结果来说明最优传输策略的结构,分析延迟约束,数据缓冲区大小,能量收集,处理和采样成本的影响。

英文摘要:

Source-channel coding for an energy limited wireless sensor node is investigated. The sensor node observes independent Gaussian source samples with variances changing over time slots and transmits to a destination over a flat fading channel. The fading is constant during each time slot. The compressed samples are stored in a finite size data buffer and need to be delivered in at most $d$ time slots. The objective is to design optimal transmission policies, namely, optimal power and distortion allocation, over the time slots such that the average distortion at destination is minimized. In particular, optimal transmission policies with various energy constraints are studied. First, a battery operated system in which sensor node has a finite amount of energy at the beginning of transmission is investigated. Then, the impact of energy harvesting, energy cost of processing and sampling are considered. For each energy constraint, a convex optimization problem is formulated, and the properties of optimal transmission policies are identified. For the strict delay case, $d=1$, $2D$ waterfilling interpretation is provided. Numerical results are presented to illustrate the structure of the optimal transmission policy, to analyze the effect of delay constraints, data buffer size, energy harvesting, processing and sampling costs.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑