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The secret rate difference approaches 2 b/s/Hz.
Meanwhile, the saved power can then be used for information beamforming to obtain a bigger secret rate.
With the increase of P, the secret rate for both algorithms will monotonically increase with P increasing.
Interestingly, the secret rate obtained by the algorithm with artificial noise increases fast when P≤5 dBm.
We designed zero-forcing-based joint information beamforming and energy beamforming to maximize the secret rate under the transmit power constraint and the energy harvesting constraint.
Furthermore, Ignatenko et al. show how to compute a bound on possible secret rate and privacy leakage rate for helper data schemes [49].
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Figure 2 Secret rate-energy region with P =10 (dBm).
In the second example, assuming the harvested energy Q is relatively constant, we can obtain the secret rate-power region for the proposed algorithms.
In the first example, assuming the transmit power P is constant, we can obtain the secret rate-energy region for the proposed algorithms.
Simulations results demonstrate the trade-off between the maximum secret information rate and the transferred energy, which is characterized by the boundary of secret rate-energy (R-E) region.
The reason lies in that when P≤5 dBm, θ decreases fast, which is demonstrated in Figure 5. Figure 4 Secret rate-energy region with Q = Q max /50. Figure 5 Optimal θ ∗ with Q = Q max /50.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com