Compressive Sensing for Spread Spectrum Receivers

TL;DR

This paper explores the application of compressive sensing in CDMA receivers, proposing a simplified measurement scheme called Compressive Spread Spectrum that reduces power and cost while maintaining acceptable performance.

Contribution

It introduces a novel CSS measurement scheme for CDMA receivers, demonstrating potential for simplified design and improved performance over classical methods in certain conditions.

Findings

CSS can effectively subsample CDMA signals

CSS receiver outperforms classical receiver in some scenarios

Bit error rate can be maintained with quantization

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.