Abstract
In this paper, we present a greedy sensor selection algorithm for minimum variance distortionless response (MVDR) beamforming under a modular budget constraint. In particular, we propose a submodular set-function that can be maximized using a linear-time greedy heuristic that is near optimal. Different from the convex formulation that is typically used to solve the sensor selection problem, the method in this paper neither involves computationally intensive semidefinite programs nor convex relaxation of the Boolean variables. While numerical experiments show a comparable performance between the convex and submodular relaxations, in terms of output signal-to-noise ratio, the latter finds a near-optimal solution with a significantly reduced computational complexity.
Original language | English |
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Title of host publication | 25th European Signal Processing Conference, EUSIPCO 2017 |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Pages | 1981-1985 |
Number of pages | 5 |
ISBN (Electronic) | 978-0-9928626-7-1 |
DOIs | |
Publication status | Published - 2017 |
Event | EUSIPCO 2017: 25th European Signal Processing Conference - Kos Island, Greece Duration: 28 Aug 2017 → 2 Sept 2017 Conference number: 25 https://www.eusipco2017.org/ |
Conference
Conference | EUSIPCO 2017 |
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Abbreviated title | EUSIPCO |
Country/Territory | Greece |
City | Kos Island |
Period | 28/08/17 → 2/09/17 |
Internet address |
Keywords
- submodularity
- MVDR beamforming
- greedy algorithm
- budget constraint
- sensor selection