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Modified-CS: Modifying Compressive Sensing for Problems With Partially Known Support
Open accessAbstract
We study the problem of reconstructing a sparse signal from a limited number of its linear projections when a part of its support is known, although the known part may contain some errors. The “known” part of the support, denoted T, may be available from prior knowledge. Alternatively, in a problem of recursively reconstructing time sequences of sparse spatial signals, one may use the support estimate from the previous time instant as the “known” part. The idea of our proposed solution (modified-CS) is to solve a convex relaxation of the following problem: find the signal that satisfies the data constraint and is sparsest outside of T. We obtain sufficient conditions for exact reconstruction using modified-CS. These are much weaker than those needed for compressive sensing (CS) when the sizes of the unknown part of the support and of errors in the known part are small compared to the support size. An important extension called regularized modified-CS (RegModCS) is developed which also uses prior signal estimate knowledge. Simulation comparisons for both sparse and compressible signals are shown.
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Sparse Signal Recovery With Temporally Correlated Source Vectors Using Sparse Bayesian Learning
Zhang, Z., & Rao, B. D. (2011) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2011.2159773 · Cited by 868
Signal Processing With Compressive Measurements
Davenport, M. A., Boufounos, P. T., Wakin, M. B., & Baraniuk, R. G. (2010) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2009.2039178 · Cited by 623
Compressed Sensing for Wireless Communications: Useful Tips and Tricks
Choi, J. W., Shim, B., Ding, Y., Rao, B., & Kim, D. I. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2664421 · Cited by 351
Compressed CSI Acquisition in FDD Massive MIMO: How Much Training is Needed?
Shen, J.-C., Zhang, J., Alsusa, E., & Letaief, K. B. (2016) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2016.2535310 · Cited by 99
Metadata
- Authors
- Vaswani, N., & Lu, W.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 2010-09
- Volume
- 58
- Issue
- 9
- Pages
- 4595-4607
- ISSN
- 1053-587X (ISSN-L)
- 1941-0476
- OpenAlex
- W2762625016
- Cited by
- 517
- References
- 26
- FWCI
- 46.43
- Type
- journal article
- Language
- en
- Open access
- green
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