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Antenna selection with erroneous covariance matrices under secrecy constraints

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Antenna selection with erroneous covariance matrices under secrecy constraints. / Hanif, Muhammad Fainan; Juntti, Markku; Tran, Le-Nam.
In: IEEE Transactions on Vehicular Technology, Vol. 65, No. 1, 22.01.2016, p. 414-420.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Hanif, MF, Juntti, M & Tran, L-N 2016, 'Antenna selection with erroneous covariance matrices under secrecy constraints', IEEE Transactions on Vehicular Technology, vol. 65, no. 1, pp. 414-420. https://doi.org/10.1109/TVT.2015.2395873

APA

Hanif, M. F., Juntti, M., & Tran, L-N. (2016). Antenna selection with erroneous covariance matrices under secrecy constraints. IEEE Transactions on Vehicular Technology, 65(1), 414-420. https://doi.org/10.1109/TVT.2015.2395873

Vancouver

Hanif MF, Juntti M, Tran L-N. Antenna selection with erroneous covariance matrices under secrecy constraints. IEEE Transactions on Vehicular Technology. 2016 Jan 22;65(1):414-420. doi: 10.1109/TVT.2015.2395873

Author

Hanif, Muhammad Fainan ; Juntti, Markku ; Tran, Le-Nam. / Antenna selection with erroneous covariance matrices under secrecy constraints. In: IEEE Transactions on Vehicular Technology. 2016 ; Vol. 65, No. 1. pp. 414-420.

Bibtex

@article{c7290b71a58545ae94df6fdedf1d1c5b,
title = "Antenna selection with erroneous covariance matrices under secrecy constraints",
abstract = "We maximize achievable secrecy rate while performing antenna selection (AS) when we do not have perfect availability of instantaneous channel covariance matrices of the legitimate (L) and eavesdropper/ wiretapper (E) nodes. Instead, we have at our disposal corrupted estimates of the channel covariance matrices. The error component of the estimated matrices is assumed to be weighted by a norm-bounded error vector. For a class of norms, irrespective of the distribution of the error vector, we devise a so-called convex inner approximation (CIA) semidefinite program (SDP)-based solution that yields a transmit precoder with the desired sparsity as dictated by the number of antennas to be selected. Our numerical results reveal that the CIA procedure works close to exhaustive results and possesses amenable polynomial complexity properties. We conclude our numerical investigations by demonstrating the effectiveness of AS under the circumstances considered in this paper.",
author = "Hanif, {Muhammad Fainan} and Markku Juntti and Le-Nam Tran",
year = "2016",
month = jan,
day = "22",
doi = "10.1109/TVT.2015.2395873",
language = "English",
volume = "65",
pages = "414--420",
journal = "IEEE Transactions on Vehicular Technology",
issn = "0018-9545",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - Antenna selection with erroneous covariance matrices under secrecy constraints

AU - Hanif, Muhammad Fainan

AU - Juntti, Markku

AU - Tran, Le-Nam

PY - 2016/1/22

Y1 - 2016/1/22

N2 - We maximize achievable secrecy rate while performing antenna selection (AS) when we do not have perfect availability of instantaneous channel covariance matrices of the legitimate (L) and eavesdropper/ wiretapper (E) nodes. Instead, we have at our disposal corrupted estimates of the channel covariance matrices. The error component of the estimated matrices is assumed to be weighted by a norm-bounded error vector. For a class of norms, irrespective of the distribution of the error vector, we devise a so-called convex inner approximation (CIA) semidefinite program (SDP)-based solution that yields a transmit precoder with the desired sparsity as dictated by the number of antennas to be selected. Our numerical results reveal that the CIA procedure works close to exhaustive results and possesses amenable polynomial complexity properties. We conclude our numerical investigations by demonstrating the effectiveness of AS under the circumstances considered in this paper.

AB - We maximize achievable secrecy rate while performing antenna selection (AS) when we do not have perfect availability of instantaneous channel covariance matrices of the legitimate (L) and eavesdropper/ wiretapper (E) nodes. Instead, we have at our disposal corrupted estimates of the channel covariance matrices. The error component of the estimated matrices is assumed to be weighted by a norm-bounded error vector. For a class of norms, irrespective of the distribution of the error vector, we devise a so-called convex inner approximation (CIA) semidefinite program (SDP)-based solution that yields a transmit precoder with the desired sparsity as dictated by the number of antennas to be selected. Our numerical results reveal that the CIA procedure works close to exhaustive results and possesses amenable polynomial complexity properties. We conclude our numerical investigations by demonstrating the effectiveness of AS under the circumstances considered in this paper.

U2 - 10.1109/TVT.2015.2395873

DO - 10.1109/TVT.2015.2395873

M3 - Journal article

VL - 65

SP - 414

EP - 420

JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

SN - 0018-9545

IS - 1

ER -