Maximizing the Secrecy Energy Efficiency of the Cooperative Rate-Splitting Aided Downlink in Multi-Carrier UAV Networks
Maximizing the Secrecy Energy Efficiency of the Cooperative Rate-Splitting Aided Downlink in Multi-Carrier UAV Networks
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DOI：
10.1109/tvt.2022.3192298
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发表时间：
2022-11-01
影响因子：
6.8
通讯作者：
Hanzo, Lajos
中科院分区：
文献类型：
--
作者：
Bastami, Hamed;Moradikia, Majid;Hanzo, Lajos
尽管无人机（UAV）能够通过检测窃听者的位置来显着提高信息安全性，但其有限的能量促使我们的研究提出一种安全且节能的方案。由于速率分割（RS）引入的公共消息原理，我们不再需要分配一部分发射功率来辐射人工噪声（AN），而且能源效率（EE）和保密性都可以得到提高。因此，我们定义并研究多载波多无人机网络的保密能源效率（SEE），其中每个多天线无人机基站（UAV-BS）采用协作速率分割（CRS）来保护其下行链路传输免受外部窃听者（$Eve$）的侵害。此外，我们还考虑了具有挑战性的场景，其中每个多天线 UAV-BS 使用 CRS 来保护其相应的下行链路传输免受外部 $Eve$ 的影响。我们进一步考虑安全性方面的困难场景，其中 Tx 上仅提供 $Eve$ 的不完美通道状态信息。因此，我们构思了一种鲁棒的安全资源分配算法，通过联合优化用户关联矩阵和网络参数分配问题（包括RS预编码器、时隙共享和功率分配）来最大化SEE。由于问题的非凸性，将其解耦为一对凸子问题。首先，制定新的两层单元内优化问题，通过迭代块坐标体规划实现 $\xi$ 最优解。然后，通过制定相关的功率控制问题来优化每个子信道的功率。
Although Unmanned Aerial Vehicles (UAVs) are capable of significantly improving the information security by detecting the eavesdropper's location, their limited energy motivates our research to propose a secure and energy efficient scheme. Thanks to the common-message philosophy introduced by Rate-Splitting (RS), we no longer have to allocate a portion of the transmit power to radiate Artificial Noise (AN), and yet both the Energy Efficiency (EE) and secrecy can be improved. Hence we define and study the Secrecy Energy Efficiency (SEE) of a multi-carrier multi-UAV network, in which Cooperative Rate-Splitting (CRS) is employed by each multi-antenna UAV Base-Station (UAV-BS) for protecting their downlink transmissions against an external eavesdropper ($Eve$). Furthermore, we consider the challenging scenario in which CRS is employed by each multi-antenna UAV-BS to protect their corresponding downlink transmissions against an external $Eve$. We further consider a difficult scenario in terms of security in which only imperfect channel state information of $Eve$ is available at the Tx. Accordingly, we conceive a robust secure resource allocation algorithm, which maximizes the SEE by jointly optimizing both the user association matrix and the network parameter allocation problem, including the RS precoders, time slot sharing and power allocation. Due to the non-convexity of the problem, it is decoupled into a pair of convex sub-problems. Firstly, new two-tier intra-cell optimization problems are formulated for achieving $\xi$-optimal solutions by iterative block coordinate decent programming. Then, the power of each sub-channel is optimized by formulating the associated power control problem.