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Jamming-Resistant Receivers for the Massive MIMO Uplink
Linköping University, Department of Electrical Engineering. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7599-4367
Iran University of Science and Technology, Iran.
2018 (English)In: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 13, no 1, p. 210-223Article in journal (Refereed) Published
Abstract [en]

We design a jamming-resistant receiver scheme to enhance the robustness of a massive MIMO uplink system against jamming. We assume that a jammer attacks the system both in the pilot and data transmission phases. The key feature of the proposed scheme is that, in the pilot phase, the base station estimates not only the legitimate channel, but also the jamming channel by exploiting a purposely unused pilot sequence. The jamming channel estimate is used to construct linear receiver filters that reject the impact of the jamming signal. The performance of the proposed scheme is analytically evaluated using the asymptotic properties of massive MIMO. The best regularized zero-forcing receiver and the optimal power allocations for the legitimate system and the jammer are also studied. Numerical results are provided to verify our analysis and show that the proposed scheme greatly improves the achievable rates, as compared with conventional receivers. Interestingly, the proposed scheme works particularly well under strong jamming attacks, since the improved estimate of the jamming channel outweighs the extra jamming power.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. Vol. 13, no 1, p. 210-223
Keyword [en]
Massive MIMO; jamming attack; receiver filter; optimal power allocation
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-143986DOI: 10.1109/TIFS.2017.2746007ISI: 000417725500016Scopus ID: 2-s2.0-85028560448OAI: oai:DiVA.org:liu-143986DiVA, id: diva2:1170232
Conference
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Note

Funding Agencies|ELLIIT; CENIIT

Available from: 2018-01-02 Created: 2018-01-02 Last updated: 2018-01-12Bibliographically approved

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Do, Tan TaiBjörnson, EmilLarsson, Erik G.

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  • apa
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