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Training Sequence Design for NBI Mitigation in Compressive Sensing UWB Systems

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Abstract

Ultra wideband (UWB) is a promising technology in delivering high data rate for short range wireless communication systems. Because of their large bandwidth, UWB signals may encounter some problems especially with high sampling rate requirements. Moreover, coherence existence with other narrowband systems is a major concern which needs to be addressed through proper mechanisms. The problem becomes so complex if multiple users exist. Since narrowband interference (NBI) signals have sparse representation in the discrete cosine transform (DCT) domain, they can be estimated and suppressed using Compressive Sensing (CS). CS also has the ability to reduce the high sampling rate requirements. For training based NBI mitigation with CS, three groups of pilot symbols are used to estimate the NBI signal subspace, the UWB signal subspace, and to provide information about the channel. In this paper, the distribution of pilot symbols among the three groups is investigated in the presence of strong NBI. The investigation is based on the bit error rate performance and throughput. The influence of each pilot symbols group is studied. The performance is also evaluated in the presence of multiuser interference in addition to the NBI. Simulation results show that the size of the third group of pilot symbols which is used to estimate the channel is the most dominant one.

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Acknowledgments

This work is supported and funded by the Deanship of Scientific Research (DSR) at King Fahd University of Petroleum & Minerals (KFUPM) through Project No. SB121014. The authors would like to thank Mr. Mohammad T. Alkhodary for his valuable help.

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  1. Electrical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Eastern Province, Saudi Arabia

    Ali H. Muqaibel & Saleh A. Alawsh

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  1. Ali H. Muqaibel
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  2. Saleh A. Alawsh
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Correspondence to Saleh A. Alawsh.

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Muqaibel, A.H., Alawsh, S.A. Training Sequence Design for NBI Mitigation in Compressive Sensing UWB Systems. Wireless Pers Commun 78, 1539–1554 (2014). https://doi.org/10.1007/s11277-014-1833-9

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  • DOI: https://doi.org/10.1007/s11277-014-1833-9

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