Secrecy sum-rate
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Secrecy sum-rate
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WebThe aim of this study is to maximize the secrecy sum rate (SSR) for a multiple-input multiple-output (MIMO)-NOMA uplink network under the maximum total transmit power … WebOuter Bounds on the Sum Rate of the K-User MIMO Gaussian Interference Channel IEEE Transactions on Communications Jan 2013 Other authors. See publication ... The paper titled “Outer bounds on the secrecy rate of the 2-user symmetric deterministic interference channel with transmitter cooperation" was shortlisted for best paper award for the ...
WebSecrecy may diminish stigma through impression management or strategic disclosure. The present study ... The total score was computed by calculating the sum biological parents. ... Older parents self-report measure asks participants to rate each item using endorsed secrecy coping less (r = 0.28, p < 0.05) and parents a 7-point Likert ... Web20 Jan 2024 · Under the aid of AN, a RSMA-based secure design was investigated in [cai2024secureRA] to maximize the secrecy sum-rate by jointly optimizing beamforming and power allocation. Overall, RSMA is expected to enable a better management of MUI for intercepting potential adversarial user and enhancing legal users’ performance.
WebRate-splitting multiple access (RSMA) is a general multiple access scheme for downlink multi-antenna systems embracing both classical spatial division multiple access and more recent non-orthogonal multiple access. Finding a linear precoding strategy that maximizes the sum spectral efficiency of RSMA is a challenging yet significant problem. Web13 Apr 2024 · The calculation equates this decision with the consumer choosing whether to “borrow” the minimum payment due, such that the “cost” of this borrowing is the late fee. Thus, annualized percentage rates (APRs) are calculated for hypothetical “borrowed” amounts and brief “borrowing” periods subject to the $8 late fee.
Web22 Sep 2024 · This robust sum secrecy rate maximization (SSRM) problem is formulated as a max-min semi-infinite problem and is tackled by the semidefinite relaxation (SDR) method. In particular, we first convert the max-min semi-infinite problem into a maximization problem with a finite number of constraints.
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