Secret Key Generation Rates over Frequency Selective Channels

The emergence of Internet of things (IoT) applications brings the challenge of finding lightweight schemes for secret key distribution. A promising solution coming from the physical layer is the so called secret key generation (SKG) from shared randomness. SKG allows two communicating parties to extract the shared randomness already present in wireless channels. This work investigates the achievable SKG rates using received signal strength (RSS) as a key generation parameter. A multi-path scenario is considered and the probability density function of the RSS in different channel conditions is evaluated. Next, through a numerical evaluation, the SKG rates are derived in the form of mutual information (MI) estimates, using a 3GPP standard channel model. The simulations are performed for different values of bandwidth and delay spread. We demonstrate that while both parameters have similar impact on how multi-path components are resolved, their effect on the MI is opposite.