In internet of things, a central node to multiple sensor nodes is usually a short-range communication network, which generally uses random multiple access to resolve collision at a media access control (MAC) layer. In this case, the communication efficiency is not optimal. On the other hand, its efficiency can be improved in separated collision resolution, where collision signals can be separated and then decoded. For the resolution, good coding techniques can improve the performance of collision resolution. However, the conventional coding techniques usually need the signal fading coefficient estimated or be known in advance. The condition is not always satisfied in the short-range network. This paper proposes a finite-symbol separation Viterbi decoder (FSVD) which does not need to know the fading coefficient. Through the estimation of a dictionary matrix, the uncertainty of signal separation can be eliminated, and thus obtain more accurate likelihood distances and improve the decoding accuracy. In experiments, we establish two ultra-high frequency (UHF) short-range wireless networks based on an FM0 code, using a simulation and a software radio platform, respectively. The experimental results show that the throughput of FSVD reaches about 0.61, which is about 0.25 higher than that of a traditional ALOHA network.

中文翻译：

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通过 FM0 信号分离解决短距离随机多址无线网络的冲突


在物联网中，多个传感器节点的中心节点通常是短距离通信网络，其通常使用随机多址来解决媒体访问控制（MAC）层的冲突。在这种情况下，通信效率并不是最佳的。另一方面，在分离冲突解决方面可以提高其效率，其中可以分离冲突信号然后进行解码。对于解决而言，良好的编码技术可以提高冲突解决的性能。然而，传统的编码技术通常需要估计或预先知道信号衰落系数。在短距离网络中并不总是满足该条件。本文提出了一种不需要知道衰落系数的有限符号分离维特比解码器（FSVD）。通过字典矩阵的估计，可以消除信号分离的不确定性，从而获得更准确的似然距离，提高解码精度。在实验中，我们分别使用仿真和软件无线电平台建立了两个基于 FM0 代码的超高频 (UHF) 短程无线网络。实验结果表明，FSVD的吞吐量达到约0.61，比传统ALOHA网络高约0.25。