Compressive Sensing for Spread Spectrum Receivers

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Resumé

With the advent of ubiquitous computing there are two design parameters of wireless communication devices that become very important: power efficiency and production cost. Compressive sensing enables the receiver in such devices to sample below the Shannon-Nyquist sampling rate, which may lead to a decrease in the two design parameters. This paper investigates the use of Compressive Sensing (CS) in a general Code Division Multiple Access (CDMA) receiver. We show that when using spread spectrum codes in the signal domain, the CS measurement matrix may be simplified. This measurement scheme, named Compressive Spread Spectrum (CSS), allows for a simple, effective receiver design. Furthermore, we numerically evaluate the proposed receiver in terms of bit error rate under different signal to noise ratio conditions and compare it with other receiver structures. These numerical experiments show that though the bit error rate performance is degraded by the subsampling in the CS-enabled receivers, this may be remedied by including quantization in the receiver model. We also study the computational complexity of the proposed receiver design under different sparsity and measurement ratios. Our work shows that it is possible to subsample a CDMA signal using CSS and that in one example the CSS receiver outperforms the classical receiver.
OriginalsprogEngelsk
TidsskriftI E E E Transactions on Wireless Communications
Vol/bind12
Udgave nummer5
Sider (fra-til)2334 - 2343
ISSN1536-1276
DOI
StatusUdgivet - maj 2013

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Compressive Sensing
Spread Spectrum
Receiver
Bit error rate
Code division multiple access
Ubiquitous computing
Code Division multiple Access
Computational complexity
Signal to noise ratio
Parameter Design
Error Rate
Sampling
Communication
Subsampling
Ubiquitous Computing
Costs
Sparsity
Wireless Communication
Experiments
Quantization

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title = "Compressive Sensing for Spread Spectrum Receivers",
abstract = "With the advent of ubiquitous computing there are two design parameters of wireless communication devices that become very important: power efficiency and production cost. Compressive sensing enables the receiver in such devices to sample below the Shannon-Nyquist sampling rate, which may lead to a decrease in the two design parameters. This paper investigates the use of Compressive Sensing (CS) in a general Code Division Multiple Access (CDMA) receiver. We show that when using spread spectrum codes in the signal domain, the CS measurement matrix may be simplified. This measurement scheme, named Compressive Spread Spectrum (CSS), allows for a simple, effective receiver design. Furthermore, we numerically evaluate the proposed receiver in terms of bit error rate under different signal to noise ratio conditions and compare it with other receiver structures. These numerical experiments show that though the bit error rate performance is degraded by the subsampling in the CS-enabled receivers, this may be remedied by including quantization in the receiver model.We also study the computational complexity of the proposed receiver design under different sparsity and measurement ratios. Our work shows that it is possible to subsample a CDMA signal using CSS and that in one example the CSS receiver outperforms the classical receiver.",
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Compressive Sensing for Spread Spectrum Receivers. / Fyhn, Karsten; Jensen, Tobias Lindstrøm; Larsen, Torben; Jensen, Søren Holdt.

I: I E E E Transactions on Wireless Communications, Bind 12, Nr. 5, 05.2013, s. 2334 - 2343.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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