资源受限的无线传感器网络基于衰减信道的决策融合

研究了无线传感器网络中衰减信道下的决策融合规则.由于信道衰减,由节点传输到融合中心的本地决策会丢失或产生差错,要求融合中心的融合规则能够结合信道模型作出最优判决.在Rayleigh分布的信道模型下,对一系列融合算法作了理论和仿真分析.似然比融合算法性能最优,但是它占用的系统资源大,需要预知的信息多,性价比不高,不适合资源受限的无线传感器网络.提出了3种次优算法,它们比似然比规则耗费的信息代价要小.在不同的信噪比(signal-to-noise ratio,简称SNR)范围下,它们的性能有各自的优劣.综合分析发现,在资源受限的无线传感器网络中,最终选择的融合规则应在性能、耗费资源量和复杂度之间获得折衷.

Decision Fusion Under Fading Channel in Resource-Constrained Wireless Sensor Networks

Decision fusion rules under fading channel in wireless sensor networks are investigated in this paper. Local decisions made by local sensor nodes may be lost or corrupted while transmitted to the fusion center via a fading channel. A series of fusion rules are proposed under the assumption of Rayleigh channel model. Likelihood ratio rule has been shown optimal through theoretical analysis and simulation. However, it consumes system resource and requires good knowledge of local and channel information, which is not easily available in resource-constrained sensor networks. Three sub-optimal alternatives are proposed, which have less computation and information cost. They perform well in their respective SNR (signal-to-noise ratio) range. Finally, it is found that in resource-constrained wireless sensor networks, a tradeoff should be considered among performance, resource cost and computation complexity while choosing the fusion rules.