Artificial Noise Aided Secure Cognitive Beamforming for Cooperative MISO-NOMA Using SWIPT (1802.09609v1)

Abstract: Cognitive radio (CR) and non-orthogonal multiple access (NOMA) have been deemed two promising technologies due to their potential to achieve high spectral efficiency and massive connectivity. This paper studies a multiple-input single-output NOMA CR network relying on simultaneous wireless information and power transfer (SWIPT) conceived for supporting a massive population of power limited battery-driven devices. In contrast to most of the existing works, which use an ideally linear energy harvesting model, this study applies a more practical non-linear energy harvesting model. In order to improve the security of the primary network, an artificial-noise-aided cooperative jamming scheme is proposed. The artificial-noise-aided beamforming design problems are investigated subject to the practical secrecy rate and energy harvesting constraints. Specifically, the transmission power minimization problems are formulated under both perfect channel state information (CSI) and the bounded CSI error model. The problems formulated are non-convex, hence they are challenging to solve. A pair of algorithms either using semidefinite relaxation (SDR) or a cost function are proposed for solving these problems. Our simulation results show that the proposed cooperative jamming scheme succeeds in establishing secure communications and NOMA is capable of outperforming the conventional orthogonal multiple access in terms of its power efficiency. Finally, we demonstrate that the cost function algorithm outperforms the SDR-based algorithm.

• The paper proposes an artificial-noise-aided cooperative scheme to enhance security and energy transfer in MISO-NOMA cognitive radio networks using SWIPT.
• It develops two algorithms, based on SDR and a cost function approach, to optimize beamforming under varying CSI conditions, showing that the cost function approach performs better.
• This work demonstrates that the proposed AN cooperative strategy significantly improves NOMA's power efficiency over OMA, even with imperfect CSI, advancing secure beamforming techniques for next-generation networks.

Artificial Noise Aided Secure Cognitive Beamforming for Cooperative MISO-NOMA Using SWIPT: A Technical Overview

This paper investigates the problem of enhancing security in MISO-NOMA cognitive radio networks (CRNs) through the innovative use of simultaneous wireless information and power transfer (SWIPT). The paper explores optimizing the beamforming strategy, intending to achieve minimum transmission power while adhering to stringent requirements for secrecy rates and energy harvesting in secondary networks. A notable distinction from previous research is the incorporation of a non-linear energy harvesting model, offering a more pragmatic reflection of energy harvesting scenarios.

Research Methodology and Contributions

The paper centers around several significant research contributions:

1. Artificial-Noise-Aided Cooperative Scheme: The authors propose a novel AN-aided cooperative scheme. This scheme involves the secondary network generating artificial noise to jam potential eavesdropping energy harvesting receivers (EHRs) within the network. This approach is coupled with a reward-based mechanism allowing secondary users access to the frequency bands of primary networks, thereby improving overall security while supporting simultaneous power transfer to energy harvesting receivers (EHRs).
2. Optimization Under Varying CSI Conditions: Two core beamforming design problems are formulated under both perfect and bounded CSI error models. Contrasting with past research that assumes perfect CSI (Channel State Information), this paper takes a more realistic approach by considering channel estimation errors. This is paramount for practical implementations of the proposed system.
3. Suboptimal Algorithm Development: The paper presents two algorithms adept at handling the non-convex nature of these problems. The first utilizes semidefinite relaxation (SDR), and the second employs a newly devised cost function approach. Comparative simulations emphasize that the cost function algorithm demonstrates better performance in maintaining lower transmission power levels than the SDR counterpart.
4. Performance Gains with NOMA over OMA: The simulation results in the paper underscore that the proposed AN cooperative strategy notably enhances the power efficiency of NOMA over OMA even as the system grapples with imperfect CSI. This highlights NOMA's superior potential in cognitive radio scenarios, primarily when substantial secrecy rates are required.

Implications and Future Research Directions

The implications of this research straddle both theoretical and practical spectrums. Theoretically, the integration of SWIPT with security-oriented beamforming strategies within a MISO-NOMA setup portrays a promising approach to heightened spectral efficiency and energy autonomy. Practically, the results denote potential deployment pathways in scenarios with dense mobile connectivity requiring stringent data security measures.

Future investigations could pivot toward exploring multi-user settings with more complex interference management strategies and broader network topologies. Extending the simulations and further refining the algorithms to handle dynamic network conditions and real-time CSI feedback might also yield essential insights. Moreover, considering other more complex non-linear models and the battery dynamics of EHRs could deepen understanding and enhance the practical deployment of these solutions.

In conclusion, this work advances the discourse in secure beamforming techniques for cognitive radio networks. It melds theoretical robustness with practical attention to non-linear energy harvesting and imperfect CSI conditions, promising enhanced security and efficiency in next-generation wireless networks.