Spread spectrum orthogonalization of superimposed training signals in OFDM systems

Julio C. Manco-Vasquez, Martin M. Soto-Cordova

Research output: Contribution to conferencePaper

Abstract

© 2017 IEEE. In this paper, we propose a novel Superimposed Training (ST) technique for Orthogonal Frequency Division Multiplexing (OFDM) systems, where data and training signals are divided in orthogonal code domains in order to mitigate the interference between them. The data signal is partitioned into disjoint bins, which are spread using orthogonal codes and multiplexed in code domain. Then, the new data signal is added to the spread training signal. This novel proposal, named Spread Spectrum Orthogonalization (SSO), exploits these properties to outperform conventional schemes in terms of channel estimation reliability and symbol detection performance, with a lower complexity. Moreover, it turns out to be robust against narrowband interferences.
Original languageAmerican English
Pages1-5
Number of pages5
DOIs
StatePublished - 19 Dec 2017
Externally publishedYes
Event2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 - Proceedings -
Duration: 19 Dec 2017 → …

Conference

Conference2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 - Proceedings
Period19/12/17 → …

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  • Cite this

    Manco-Vasquez, J. C., & Soto-Cordova, M. M. (2017). Spread spectrum orthogonalization of superimposed training signals in OFDM systems. 1-5. Paper presented at 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2017 - Proceedings, . https://doi.org/10.1109/CHILECON.2017.8229584