Wireless Channel Estimation With Applications to Secret Key Generation

Kang Liu

As an alternative and appealing approach to providing information security in wireless communication systems, secret key generation at physical layer has demonstrated its potential in terms of efficiency and reliability over traditional cryptographic methods. Without the necessity of a management centre for key distribution or reliance on computational complexity, physical layer key generation protocols enable two wireless entities to extract identical and dynamic keys from the randomness of the wireless channels associated with them.\nIn this thesis, the reliability of secret key generation at the physical layer is examined in practical wireless channels with imperfect channel state information (CSI). Theoretical analyses are provided to relate key match rate with channel's signal-to-noise ratio (SNR), degrees of channel reciprocity, and iterations of information reconciliation.\nIn order to increase key match rate of physical layer secret key generation, improved schemes in the steps of channel estimation and sample quantization are proposed respectively. In the channel estimation step, multiple observations of the wireless channels are integrated with a linear processor to provide a synthesized and more accurate estimation of the wireless channel. In the sample quantization step, a magnitude based quantization method with two thresholds is proposed to quantize partial samples, where specific quantization areas are selected to reduce cross-over errors. Significant improvements in key match rate are proven for both schemes in theoretical analysis and numerical simulations. Key match rate can even achieve 100% in both schemes with the assistance of information reconciliation process.\nIn the end, a practical application of physical layer secret key generation is presented, where dynamic keys extracted from the wireless channels are utilized for securing secret data transmission and providing efficient access control.

Xiaofu Wu, Dongming Dai, Xunjian Yu +1 more

Syed Taha Ali and Vijay Sivaraman

Marco Zoli, Miroslav Mitev, Andre Noll Barreto +1 more

In this work we investigate the problem of secret key generation (SKG) between two communicating wireless devices, according to the physical-layer security paradigm. We propose a general framework for any communication channel or waveform. In details, we study a filterbank-based method, which allows the generation of secret security keys from a wideband radio channel, independently from the baseband modem implementation. We believe that channel awareness is of utmost importance to understand the applicability of SKG methods, i.e., knowing their secret bit-rate under different channel scenarios. For that purpose, we investigate the SKG performance by means of Monte Carlo simulations that collect radio channel statistics and obtain the SKG performance through mutual information numerical estimation.

Syed Syed, Taha Anwar Taha, Ali +2 more

Toshiki Matsumine, Hideki Ochiai, Junji Shikata

This letter considers a data-driven approach to a secret key rate analysis of physical layer secret key generation based on mutual information neural estimator (MINE), which achieves the state-of-the-art estimation accuracy. Since MINE does not require any statistical knowledge of randomness sources, the proposed approach is applicable to any source model and even real data which cannot be fully expressed by a simple model. We first demonstrate by simulations that the proposed estimation provides good approximations to the theoretical secret key rate for a simple model, and then show that the achievable secret key rate highly depends on sources of randomness and employed channel estimation schemes for a realistic wireless channel model. As an application of our analysis, we present a method to train quantization through backpropagation that maximizes the estimated secret key rate.