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Secrecy Fairness Aware NOMA for Untrusted Users

机译:面向不信任用户的保密公平意识NOMA

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Spectrally-efficient secure non-orthogonal multiple access (NOMA) has recently attained a substantial research interest for fifth generation development. This work explores crucial security issue in NOMA which is stemmed from utilizing the decoding concept of successive interference cancellation. Considering untrusted users, we design a novel secure NOMA transmission protocol to maximize secrecy fairness among users. A new decoding order for two users' NOMA is proposed that provides positive secrecy rate to both users. Observing the objective of maximizing secrecy fairness between users under given power budget constraint, the problem is formulated as minimizing the maximum secrecy outage probability (SOP) between users. In particular, closed-form expressions of SOP for both users are derived to analyze secrecy performance. SOP minimization problems are solved using pseudoconvexity concept, and optimized power allocation (PA) for each user is obtained. Asymptotic expressions of SOPs, and optimal PAs minimizing these approximations are obtained to get deeper insights. Further, globally-optimized power control solution from secrecy fairness perspective is obtained at a low computational complexity and, asymptotic approximation is obtained to gain analytical insights. Numerical results validate the correctness of analysis, and present insights on optimal solutions. Finally, we present insights on global-optimal PA by which fairness is ensured and gains of about 55.12%, 69.30%, and 19.11%, respectively are achieved, compared to fixed PA and individual users' optimal PAs.
机译:频谱效率高的安全非正交多路访问(NOMA)最近在第五代开发中获得了巨大的研究兴趣。这项工作探索了NOMA中的关键安全问题,该问题源于利用连续干扰消除的解码概念。考虑到不受信任的用户,我们设计了一种新颖的安全NOMA传输协议,以最大程度地提高用户之间的保密公平性。提出了针对两个用户的NOMA的新解码顺序,该顺序为两个用户提供了正的保密率。观察到在给定的功率预算约束下使用户之间的保密公平性最大化的目标,将问题表述为使用户之间的最大保密中断概率(SOP)最小化。特别是,导出了两个用户的SOP的闭式表达式,以分析保密性能。使用伪凸概念解决了SOP最小化问题,并获得了每个用户的优化功率分配(PA)。获得SOP的渐近表达式以及使这些近似最小化的最佳PA,以获取更深入的见解。此外,从保密公平角度出发,以较低的计算复杂度获得了全局优化的功率控制解决方案,并获得了渐近逼近以获得分析见解。数值结果验证了分析的正确性,并提供了关于最佳解决方案的见解。最后,与固定功率放大器和个人用户的最佳功率放大器相比,我们提供了关于全球最优功率放大器的见解,该方法可确保公平性,并分别获得约55.12%,69.30%和19.11%的收益。

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