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Reduced complexity crosscorrelation interference mitigation in GPS-enabled collaborative ad-hoc wireless networks - Theory

机译:具有GPS功能的协作式自组织无线网络中降低了复杂度的互相关干扰缓解-理论

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摘要

Localization based services rely on Global Positioning System (GPS) receivers embedded in the network nodes, but the satellite signal availability is often limited in indoors environment. Collaborative network-assisted GPS algorithms addressed this issue by communicating various assistance data between the nodes or transforming open-sky nodes into virtual GPS satellite transmitters (pseudolites). Even though such approach improves the coverage, the crosscorrelation problem surfaces due to masking of relatively weak available satellite signals by stronger pseudolites. This paper proposes reduced complexity algorithms to mitigate such a self-jamming (near/far) effect in ad hoc networks. The idea is based on adaptive modifications of dispreading GPS codes in receiver nodes to minimize interference caused by strong pseudolite signals. An optimization problem is formulated for the minimization of interference using mean squared error (MSE) as a cost function. Then computational optimization is achieved through adaptive implementation and parameterized dimension reduction of the optimization problem.
机译:基于本地化的服务依赖于嵌入在网络节点中的全球定位系统(GPS)接收器,但是在室内环境中,卫星信号的可用性通常受到限制。协作式网络辅助GPS算法通过在节点之间传递各种辅助数据或将露天节点转换为虚拟GPS卫星发射机(伪卫星)来解决此问题。即使这种方法改善了覆盖范围,但由于较强的伪卫星掩盖了相对较弱的可用卫星信号,互相关问题仍然浮出水面。本文提出了降低复杂度的算法,以减轻自组织网络中的这种自干扰(近/远)效应。这个想法是基于对接收器节点中GPS编码的自适应修改,以最小化强伪卫星信号引起的干扰。使用均方误差(MSE)作为成本函数,提出了一个用于最小化干扰的优化问题。然后,通过自适应实现和优化问题的参数化降维来实现计算优化。

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