Journal
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 63, Issue 4, Pages 1678-1690Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2013.2285244
Keywords
Convex optimization; multiple-input-multiple-output (MIMO) system; physical-layer secrecy; robust optimization; secrecy capacity
Categories
Funding
- U.K. EPSRC [EP/I037423/1]
- FP7 IRSES project HEMOW [269202]
- Marie Curie Outgoing International Fellowship within European Community
- EPSRC [EP/E005071/1, EP/I037423/1, EP/F06151X/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/I037423/1, EP/E005071/1, EP/F06151X/1] Funding Source: researchfish
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This paper studies different secrecy rate optimization problems for a multiple-input-multiple-output (MIMO) secrecy channel. In particular, we consider a scenario where a communication through a MIMO channel is overheard by a multiple-antenna eavesdropper. In this secrecy network, we first investigate two secrecy rate optimization problems: 1) power minimization and 2) secrecy rate maximization. These optimization problems are not convex due to the nonconvex secrecy rate constraint. However, by approximating this secrecy rate constraint based on Taylor series expansion, we propose iterative algorithms to solve these secrecy rate optimization problems. In addition, we provide the convergence analysis for the proposed algorithms. These iterative optimization approaches are developed under the assumption that the transmitter has perfect channel state information. However, there are practical difficulties in having perfect channel state information at the transmitter. Hence, robust secrecy rate optimization techniques based on the worst-case secrecy rate are considered by incorporating channel uncertainties. By exploiting the S-Procedure, we show that these robust optimization problems can be formulated into semidefinite programming at low signal-to-noise ratios (SNRs). Simulation results have been provided to validate the convergence of the proposed algorithms. In addition, numerical results show that the proposed robust optimization techniques outperform the nonrobust schemes in terms of the worst-case secrecy rates and the achieved secrecy rates.
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