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Topology Maps for 3D Millimeter Wave Sensor Networks with Directional Antennas

机译：带定向天线的3D毫米波传感器网络的拓扑图

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Millimeter wave communication shows promise in realizing next generation wireless sensor networks for bandwidth demanding applications. Despite its support of multi Gbps data rates, MmWaves requires unobstructed line-of-sight and suffers from heavy path losses. Overcoming these in complex 3D environments requires sectored antenna arrays with narrow beam widths and adaptive beamforming. Therefore, network topology maps would be significant than ever in millimeter wave sensor networks. Traditional topology mapping algorithms rely on omnidirectional transmission and reception and are thus not tailored to such networks. A novel topology mapping algorithm, Millimeter Wave Topology Map (MmTM) is proposed for 3D deployments, which take advantage of the directional information available from beamforming antennas as well as their beam steering capability. An autonomous robot traverses the network recording the packet reception from different nodes along with the receiving antenna sector ID that delivers the packet with highest signal quality. The techniques used in standard IEEE 802.11ad protocol are used for the optimum sector selection and collision avoidance. MmTM is evaluated using two realistic sensor network environments and compared with prominent localization approaches based on received signal strength and hop count. The results show that proposed algorithm has a less than 0.7m distance error and more than 50% of nodes are located in the correct direction, which is 7m and 35% improvement in distance error and sector displacement matrices compared to other algorithms.
机译：毫米波通信显示出在为带宽要求苛刻的应用实现下一代无线传感器网络方面的前景。尽管MmWaves支持多Gbps数据速率，但仍要求视线通畅，并且路径损耗很大。要在复杂的3D环境中克服这些问题，就需要具有窄波束宽度和自适应波束形成的扇形天线阵列。因此，在毫米波传感器网络中，网络拓扑图将比以往任何时候都重要。传统的拓扑映射算法依赖于全向传输和接收，因此不适用于此类网络。针对3D部署，提出了一种新颖的拓扑映射算法毫米波拓扑图（MmTM），该算法利用了波束成形天线可获得的方向信息及其波束控制能力。自主机器人遍历网络，记录来自不同节点的数据包接收以及接收天线扇区ID，该信号以最高信号质量传递数据包。标准IEEE 802.11ad协议中使用的技术用于最佳扇区选择和避免冲突。使用两种现实的传感器网络环境对MmTM进行评估，并与基于接收信号强度和跳数的突出定位方法进行比较。结果表明，所提出的算法距离误差小于0.7m，且正确方向的节点数量超过50％，与其他算法相比，距离误差和扇区位移矩阵分别提高了7m和35％。

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