{
  "id": "1601.06208",
  "version": "v1",
  "published": "2016-01-22T23:55:44.000Z",
  "updated": "2016-01-22T23:55:44.000Z",
  "title": "Improved Active Sensing Performance in Wireless Sensor Networks via Channel State Information - Extended Version",
  "authors": [
    "Alessandro Biason",
    "Urbashi Mitra",
    "Michele Zorzi"
  ],
  "comment": "Partially submitted to 2016 IEEE International Symposium on Information Theory (ISIT)",
  "categories": [
    "cs.IT",
    "math.IT"
  ],
  "abstract": "Active sensing refers to the process of choosing or tuning a set of sensors in order to track an underlying system in an efficient and accurate way. In a wireless environment, among the several kinds of features extracted by traditional sensors, the communication channel can be used to further boost the tracking performance and save energy. A joint tracking problem which considers traditional measurements and channel together for tracking purposes is set up and solved. The system is modeled as a partially observable Markov decision problem and the properties of the cost-to-go function are used to reduce the problem complexity. Numerical results show the advantages of our proposal.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2016-01-22T23:55:44.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "channel state information",
      "wireless sensor networks",
      "active sensing performance",
      "observable markov decision problem",
      "extended version"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}