CSI-based versus RSS-based Secret-Key Generation under Correlated Eavesdropping

Physical-layer security (PLS) has the potential to strongly enhance the overall system security as an alternative to or in combination with conventional cryptographic primitives usually implemented at higher network layers. Secret-key generation relying on wireless channel reciprocity is an interesting solution as it can be efficiently implemented at the physical layer of emerging wireless communication networks, while providing information-theoretic security guarantees. In this paper, we investigate and compare the secret-key capacity based on the sampling of the entire complex channel state information (CSI) or only its envelope, the received signal strength (RSS). Moreover, as opposed to previous works, we take into account the fact that the eavesdropper's observations might be correlated and we consider the high signal-to-noise ratio (SNR) regime where we can find simple analytical expressions for the secret-key capacity. As already found in previous works, we find that RSS-based secret-key generation is heavily penalized as compared to CSI-based systems. At high SNR, we are able to precisely and simply quantify this penalty: a halved pre-log factor and a constant penalty of about 0.69 bit, which disappears as Eve's channel gets highly correlated

MIMO channel capacity and configuration selection for switched parasitic antennas

MIMO systems offer a significant enhancement of data rate and channel capacity compared to traditional systems. But correlation degrades the system performance and puts a practical limit on the number of antennas that can be squeezed into portable wireless devices. Switched Parasitic Antennas (SPAs) is a possible solution especially where it is difficult to obtain enough signal decorrelation with conventional means. The covariance matrix represents the correlation present in the propagation channel and has significant impact on the MIMO channel capacity. The results of this work demonstrate a significant improvement in the MIMO channel capacity by using SPA with the knowledge of the covariance matrix for all pattern configurations. By employing the ‘Water-Pouring Algorithm’ (WPA) to modify the covariance matrix, the channel capacity is significantly improved as compared to traditional systems which just spread power equally among all the transmit antennas. A Condition Number (CN) is also proposed as a selection metric, to select the optimal pattern configuration for SPAs. CN is a channel quality indicator which represents the Eigen Value Spread (EVS) of the covariance matrix