Abstract : Channel Reciprocity-based Key Generation (CRKG) technique has gained significant attention among researchers in the field of Physical Layer Security (PLS). While existing methods in this area typically use raw channel information as input for secret key generation, we propose a novel approach that derives features from the raw material for key generation. In our comprehensive study, we explore a wide range of features derived from the reciprocal components of the Channel Impulse Responses (CIRs) in both the time and frequency domains. Our findings demonstrate that the derived feature set exhibits better channel characteristics compared to the raw key material, even in the presence of eavesdroppers. To validate the efficiency of our proposed feature set, we evaluate it using several performance metrics in a new feature-based key generation scheme. The results highlight the potential of this feature set for future key-generation applications.
Index terms : Physical layer security, Channel reciprocity- based key generation, randomness sharing, feature extraction