### Abstract

Original language | English |
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Title of host publication | Data Compression Conference (DCC), 2015 |

Number of pages | 10 |

Publisher | IEEE Press |

Publication date | Apr 2015 |

Pages | 293 - 302 |

ISBN (Electronic) | 978-1-4799-8430-5 |

DOIs | |

Publication status | Published - Apr 2015 |

Event | 2015 Data Compression Conference (DCC) - Snowbird, UT, United States Duration: 7 Apr 2015 → 9 Apr 2015 |

### Conference

Conference | 2015 Data Compression Conference (DCC) |
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Country | United States |

City | Snowbird, UT |

Period | 07/04/2015 → 09/04/2015 |

Series | Data Compression Conference. Proceedings |
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ISSN | 1068-0314 |

### Fingerprint

### Cite this

*Data Compression Conference (DCC), 2015*(pp. 293 - 302). IEEE Press. Data Compression Conference. Proceedings https://doi.org/10.1109/DCC.2015.20

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*Data Compression Conference (DCC), 2015.*IEEE Press, Data Compression Conference. Proceedings, pp. 293 - 302, 2015 Data Compression Conference (DCC), Snowbird, UT, United States, 07/04/2015. https://doi.org/10.1109/DCC.2015.20

**Coding and Enhancement in Wireless Acoustic Sensor Networks.** / Zahedi, Adel; Østergaard, Jan; Jensen, Søren Holdt; Naylor, Patrick; Bech, Søren.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Coding and Enhancement in Wireless Acoustic Sensor Networks

AU - Zahedi, Adel

AU - Østergaard, Jan

AU - Jensen, Søren Holdt

AU - Naylor, Patrick

AU - Bech, Søren

PY - 2015/4

Y1 - 2015/4

N2 - We formulate a new problem which bridges between source coding and enhancement in wireless acoustic sensor networks. We consider a network of wireless microphones, each of which encoding its own measurement under a covariance matrix distortion constraint and sending it to a fusion center. To process the data at the center, we use a recent spatio-temporal prediction filter. We assume that a weighted sum-rate for the network is specified. The problem is to allocate optimal distortion matrices to the nodes in order to achieve a maximum output SNR at the fusion center after processing the received data, while the weighted sum-rate for the network is no more than the specified value. We formulate this problem as an optimization problem for which we derive a set of equalities imposed on the solution by studying the KKT conditions. In particular, for the special case of scalar sources with two microphones and a sum-rate constraint, we derive the distortion allocation in closed form and will show that if the given sum-rate is higher than a critical value, the stationary points from the KKT conditions lead to distortion allocations which maximize the output SNR of the filter

AB - We formulate a new problem which bridges between source coding and enhancement in wireless acoustic sensor networks. We consider a network of wireless microphones, each of which encoding its own measurement under a covariance matrix distortion constraint and sending it to a fusion center. To process the data at the center, we use a recent spatio-temporal prediction filter. We assume that a weighted sum-rate for the network is specified. The problem is to allocate optimal distortion matrices to the nodes in order to achieve a maximum output SNR at the fusion center after processing the received data, while the weighted sum-rate for the network is no more than the specified value. We formulate this problem as an optimization problem for which we derive a set of equalities imposed on the solution by studying the KKT conditions. In particular, for the special case of scalar sources with two microphones and a sum-rate constraint, we derive the distortion allocation in closed form and will show that if the given sum-rate is higher than a critical value, the stationary points from the KKT conditions lead to distortion allocations which maximize the output SNR of the filter

U2 - 10.1109/DCC.2015.20

DO - 10.1109/DCC.2015.20

M3 - Article in proceeding

T3 - Data Compression Conference. Proceedings

SP - 293

EP - 302

BT - Data Compression Conference (DCC), 2015

PB - IEEE Press

ER -