Millimeter Wave Communications with Reconfigurable Antennas

He, Biao; Jafarkhani, Hamid

doi:10.1109/icc.2018.8422418

Cited by 3 publications

(13 citation statements)

References 26 publications

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“…12(a) and Fig. 12(b) display the contours of the metrics, χ L in (33) and χ H in (34). Larger χ L (χ H ) means better secrecy performance can be achieved.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…For example, the channel measurements in [40] showed an average number of 10 distinct clusters and 9 rays in each cluster for a practical 60 GHz mmWave communication scenario. Thus, it is reasonable to approximate the elements ofḠ by zero-mean independent complex Gaussian variables [34], [35], as further validated by the experimental measurement results in [41]. Without loss of generality, we assume that long-term power control is employed to compensate for the large-scale fading of Bob such that the entries ofḠ have unit variance.…”

Section: B Secure Transmission Over a Sparse Channelmentioning

confidence: 97%

“…where we apply (33) and (34) and consider ρ < 1 − Mr Nt for common sparse scenarios. This implies that both χ L and χ H decrease slightly with η.…”

Section: ) Effect Of ρ: When the Difference Between The Nondominant mentioning

confidence: 99%

“…For χ H in(34), the derivative w.r.t. ρ is Generally, ∂χ H ∂ρ > 0 for small ρ while ∂χ H ∂ρ < 0 for large ρ.…”

mentioning

confidence: 99%

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Secure Communication for Spatially Sparse Millimeter-Wave Massive MIMO Channels via Hybrid Precoding

et al. 2020

IEEE Trans. Commun.

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In this paper, we investigate secure communication over sparse millimeter-wave (mm-Wave) massive multiple-input multiple-output (MIMO) channels by exploiting the spatial sparsity of legitimate user's channel.We propose a secure communication scheme in which information data is precoded onto dominant angle components of the sparse channel through a limited number of radio-frequency (RF) chains, while artificial noise (AN) is broadcast over the remaining nondominant angles interfering only with the eavesdropper with a high probability. It is shown that the channel sparsity plays a fundamental role analogous to secret keys in achieving secure communication. Hence, by defining two statistical measures of the channel sparsity, we analytically characterize its impact on secrecy rate. In particular, a substantial improvement on secrecy rate can be obtained by the proposed scheme due to the uncertainty, i.e., "entropy", introduced by the channel sparsity which is unknown to the eavesdropper. It is revealed that sparsity in the power domain can always contribute to the secrecy rate. In contrast, in the angle domain, there exists an optimal level of sparsity that maximizes the secrecy rate. The effectiveness of the proposed scheme and derived results are verified by numerical simulations. Index TermsPhysical layer security, massive multiple-input multiple-output (MIMO), millimeter-wave (mm-Wave), artificial noise (AN), radio-frequency (RF) chains.

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“…12(a) and Fig. 12(b) display the contours of the metrics, χ L in (33) and χ H in (34). Larger χ L (χ H ) means better secrecy performance can be achieved.…”

Section: Numerical Resultsmentioning

confidence: 99%

Section: B Secure Transmission Over a Sparse Channelmentioning

confidence: 97%

“…where we apply (33) and (34) and consider ρ < 1 − Mr Nt for common sparse scenarios. This implies that both χ L and χ H decrease slightly with η.…”

Section: ) Effect Of ρ: When the Difference Between The Nondominant mentioning

confidence: 99%

“…For χ H in(34), the derivative w.r.t. ρ is Generally, ∂χ H ∂ρ > 0 for small ρ while ∂χ H ∂ρ < 0 for large ρ.…”

mentioning

confidence: 99%

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Secure Communication for Spatially Sparse Millimeter-Wave Massive MIMO Channels via Hybrid Precoding

et al. 2020

IEEE Trans. Commun.

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“…Meanwhile, the small wavelength enables a large number of antennas to be closely packed to form mmWave large multi-antenna systems, which can be utilized to overcome the propagation challenges and provide reasonable signal to noise ratios (SNRs) [7]. The multi-input multi-output (MIMO) This work was presented in part at the 2018 IEEE International Conference on Communications (ICC) [1].…”

Section: Introductionmentioning

confidence: 99%

Low-Complexity Reconfigurable MIMO for Millimeter Wave Communications

Jafarkhani

2018

IEEE Trans. Commun.

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The performance of millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems is limited by the sparse nature of propagation channels and the restricted number of radio frequency chains at transceivers. The introduction of reconfigurable antennas offers an additional degree of freedom on designing mmWave MIMO systems. This paper provides a theoretical framework for studying the mmWave MIMO with reconfigurable antennas. Based on the virtual channel model, we present an architecture of reconfigurable mmWave MIMO with beamspace hybrid analog-digital beamformers and reconfigurable antennas at both the transmitter and the receiver. We show that employing reconfigurable antennas can provide throughput gain for the mmWave MIMO. We derive the expression for the average throughput gain of using reconfigurable antennas in the system, and further derive the expression for the outage throughput gain for the scenarios where the channels are (quasi) static. Moreover, we propose a low-complexity algorithm for reconfiguration state selection and beam selection. Our numerical results verify the derived expressions for the throughput gains and demonstrate the near-optimal throughput performance of the proposed low-complexity algorithm.Index Terms-Reconfigurable antennas, millimeter wave, sparse channels, virtual channel model, throughput gain.

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