Spatially Selective Artificial-Noise Aided Transmit Optimization for MISO Multi-Eves Secrecy Rate Maximization

By Qiang Li, Wing-Kin Ma. IEEE Transactions on Signal Processing, 2013

310 citations recorded by the source corpus.

Consider an MISO channel overheard by multiple eavesdroppers. Our goal is to design an artificial noise (AN)-aided transmit strategy, such that the achievable secrecy rate is maximized subject to the sum power constraint. AN-aided secure transmission has recently been found to be a promising approach for blocking eavesdropping attempts. In many existing studies, the confidential information transmit covariance and the AN covariance are not simultaneously optimized. In particular, for design convenience, it is common to prefix the AN covariance as a specific kind of spatially isotropic covariance. This paper considers joint optimization of the transmit and AN covariances for secrecy rate maximization (SRM), with a design flexibility that the AN can take any spatial pattern. Hence, the proposed design has potential in jamming the eavesdroppers more effectively, based upon the channel state information (CSI). We derive an optimization approach to the SRM problem through both analysis and convex conic optimization machinery. We show that the SRM problem can be recast as a single-variable optimization problem, and that resultant problem can be efficiently handled by solving a sequence of semidefinite programs. Our framework deals with a general setup of multiple multi-antenna eavesdroppers, and can cater for additional constraints arising from specific application scenarios, such as interference temperature constraints in interference networks. We also generalize the framework to an imperfect CSI case where a worst-case robust SRM formulation is considered. A suboptimal but safe solution to the outage-constrained robust SRM design is also investigated. Simulation results show that the proposed AN-aided SRM design yields significant secrecy rate gains over an optimal no-AN design and the isotropic AN design, especially when there are more eavesdroppers.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/ba904e406389186fb58c37b2b364977679c46760

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Citations in the corpus

Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey (2010, methodology): “If the eavesdropper’s CSIT is partially known, additional gai ns may be achieved by optimizing the AN transmit covariance [45] or relaxing the orthogonality constraint [46].”
A Survey on Multiple-Antenna Techniques for Physical Layer Security (2017, methodology): “power were regarded as the optimization objectives for jointly designing transmit beamforming and AN in [97] and [117], respectively.”
Robust Resource Allocation for MIMO Wireless Powered Communication Networks Based on a Non-Linear EH Model (2016, methodology): “The first approach is based on a deterministic model, while the second approach is based on a probabilistic model, where the CSI errors are modeled by continuous random variables following a certain distribution [32].”