Compressive Sensing for Spread Spectrum Receivers

Karsten Fyhn, Tobias Lindstrøm Jensen, Torben Larsen, Søren Holdt Jensen

Research output: Contribution to journalJournal articleResearchpeer-review

22 Citations (Scopus)
2084 Downloads (Pure)


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.
Original languageEnglish
JournalI E E E Transactions on Wireless Communications
Issue number5
Pages (from-to)2334 - 2343
Publication statusPublished - May 2013


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