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Computing functions via simo multiple-access channels: Howmuch channel knowledge is needed?

机译:通过simo多路访问通道计算功能:需要多少通道知识?

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We view a wireless sensor network as a collection of sensor nodes that observe sources of information, process the picked up data and send it to a sink node, with the goal of computing a desired function of the measurements. To this end, we consider a previously proposed coding scheme that exploits the underlying fading multiple-access channel (MAC) to efficiently estimate the function values. The main problem addressed in this paper is how much channel state information (CSI) is needed at the sensor nodes to obtain sufficiently good estimates? First we show that there is no performance loss, independent of fading distributions, if, instead of perfect CSI, each sensor node has only access to the modulus of its channel coefficient. In the case of multiple antenna elements at the sink node and specific independent distributed fading environments, it is shown that CSI at sensor nodes is not necessary and a very simple correction of fading effects can be performed at the sink based on some statistical channel knowledge. In many cases, fading improves the estimation accuracy due to the multiple-access nature of the channel.
机译:我们将无线传感器网络视为传感器节点的集合,这些传感器节点观察信息源,处理所采集的数据并将其发送到接收器节点,目的是计算所需的测量功能。为此,我们考虑一种先前提出的编码方案,该方案利用底层的衰落多址信道(MAC)有效地估计功能值。本文解决的主要问题是,在传感器节点上需要多少通道状态信息(CSI)才能获得足够好的估计?首先,我们证明,如果每个传感器节点只能访问其信道系数的模数而不是完美的CSI,则不会有性能损失,与衰落分布无关。对于在宿节点上有多个天线元件和特定的独立分布式衰落环境,情况表明,传感器节点上的CSI并不是必需的,并且可以基于一些统计信道知识在宿处执行非常简单的衰落效应校正。在许多情况下,由于信道的多址访问性质,衰落可提高估计准确性。

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