Robust Optimization of Private Communication in Multi-Antenna Systems
Anne Wolf · Qucosa (Saxon State and University Library Dresden) · 2016
The thesis focuses on the privacy of communication that can be ensured by means of the physical layer, i.e., by appropriately chosen coding and resource allocation schemes. The fundamentals of physical-layer security have been already formulated in the 1970s by Wyner (1975), Csiszár and Körner (1978). But only nowadays we have the technical progress such that these ideas can find their way in current and future communication systems, which has driven the growing interest in this area of research in the last years. We analyze two physical-layer approaches that can ensure the secret transmission of private information in wireless systems in presence of an eavesdropper. One is the direct transmission of the information to the intended receiver, where the transmitter has to simultaneously ensure the reliability and the secrecy of the information. The other is a two-phase approach, where two legitimated users first agree on a common and secret key, which they use afterwards to encrypt the information before it is transmitted. In this case, the secrecy and the reliability of the transmission are managed separately in the two phases. The secrecy of the transmitted messages mainly depends on reliable information or reasonable and justifiable assumptions about the channel to the potential eavesdropper. Perfect state information about the channel to a passive eavesdropper is not a rational assumption. Thus, we introduce a deterministic model for the uncertainty about this channel, which yields a set of possible eavesdropper channels. We consider the optimization of worst-case rates in systems with multi-antenna Gaussian channels for both approaches. We study which transmit strategy can yield a maximum rate if we assume that the eavesdropper can always observe the corresponding worst-case channel that reduces the achievable rate for the secret transmission to a minimum. For both approaches, we show that the resulting max-min problem over the matrices that describe the multi-antenna system can be reduced to an equivalent problem over the eigenvalues of these matrices. We characterize the optimal resource allocation under a sum power constraint over all antennas and derive waterfilling solutions for the corresponding worst-case channel to the eavesdropper for a constraint on the sum of all channel gains. We show that all rates converge to finite limits for high signal-to-noise ratios (SNR), if we do not restrict the number of antennas for the eavesdropper. These limits are characterized by the quotients of the eigenvalues resulting from the Gramian matrices of both channels. For the low-SNR regime, we observe a rate increase that depends only on the differences of these eigenvalues for the direct-transmission approach. For the key generation approach, there exists no dependence from the eavesdropper channel in this regime. The comparison of both approaches shows that the superiority of an approach over the other mainly depends on the SNR and the quality of the eavesdropper channel. The direct-transmission approach is advantageous for low SNR and comparably bad eavesdropper channels, whereas the key generation approach benefits more from high SNR and comparably good eavesdropper channels. All results are discussed in combination with numerous illustrations.