2011/10/24 by Karsten Fyhn, Thomas Arildsen, Fyhn, Karsten +6
Computer Science · Engineering · Mathematics · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Techniques #Blind Source Separation Techniques #FOS: Computer and information sciences #Information Theory (cs.IT) #Networking and Internet Architecture (cs.NI) #Sparse and Compressive Sensing Techniques #Wireless Communication Networks Research #cs.IT #cs.NI #math.IT
paper · pdf · doi:10.48550/arxiv.1110.5176
5 pages, 2 figures, presented at EUSIPCO 2012
openalex publication_date 2011/10/24 · arxiv created 2012/10/10 · arxiv updated 2012/10/11 · openalex created_date 2025/10/24 · openalex updated_date 2026/07/28
We show that to lower the sampling rate in a spread spectrum communication system using Direct Sequence Spread Spectrum (DSSS), compressive signal processing can be applied to demodulate the received signal. This may lead to a decrease in the power consumption or the manufacturing price of wireless receivers using spread spectrum technology. The main novelty of this paper is the discovery that in spread spectrum systems it is possible to apply compressive sensing with a much simpler hardware architecture than in other systems, making the implementation both simpler and more energy efficient. Our theoretical work is exemplified with a numerical experiment using the IEEE 802.15.4 standard's 2.4 GHz band specification. The numerical results support our theoretical findings and indicate that compressive sensing may be used successfully in spread spectrum communication systems. The results obtained here may also be applicable in other spread spectrum technologies, such as Code Division Multiple Access (CDMA) systems.