Physical layer key generation (PKG) technology leverages reciprocal channel randomness to generate shared secret keys. However, multipath fading at the receiver may degrade the correlation between legitimate uplink and downlink channels, resulting in a low key generation rate (KGR). In this paper, we propose a PKG scheme based on the pattern-reconfigurable antenna (PRA) to boost the secret key capacity. First, we propose a reconfigurable intelligent surface (RIS) based PRA architecture with the capability of flexible and reconfigurable antenna patterns. Then, we present the PRA-based PKG protocol to improve the KGR via mitigation of the effects of multipath fading. Specifically, a novel algorithm for estimation of the multipath channel parameters is proposed based on atomic norm minimization. Thereafter, a novel optimization method for the matching reception of multipath signals is formulated based on the improved binary particle swarm optimization (BPSO) algorithm. Finally, simulation results show that the proposed scheme can resist multipath fading and achieve a high KGR compared to existing schemes. Moreover, our findings indicate that the increased degree of freedom of the antenna patterns can significantly increase the secret key capacity.

Abstract The propagation of electromagnetic waves will produce multi‐path fading of wireless channel, which degrades communication performance substantially. If multi‐path can be separated, better signal transmission and reception strategies can be designed to weaken or eliminate fading and improve signal transmission performance. However, it is challenging for communication nodes with limited number of antennas. A general multi‐path separation and measurement framework based on single dynamic metasurface antenna is established which rapidly changes patterns within a single pilot symbol period so that equivalent multi‐dimensional received signals can be obtained. Based on the framework, a multi‐path channel estimation scheme is proposed. Specifically, the parameter estimation problem is formulated and present the algorithm based on atomic norm minimisation to estimate parameters including angle of arrival and complex gain of each propagation path. Simulation results illustrate that single dynamic metasurface antenna can approach the capability of a conventional multi‐antenna array, and even using single dynamic metasurface antenna with 1‐bit coding can estimate angle of arrivals and complex gains of multi‐path components accurately.

Focusing on the problem of information leakage in information reconciliation (IR), this paper proposes an IR method based on systematic secure polar code (SSPC), which can ensure the security of transmitted check bits. First, the upper and lower bounds of decoded bit error ratio are derived through Gaussian approximation. Then, the generic algorithm is utilized to design suitable SSPC for IR based on the initial quantified bit error ratios, key strength and IR outage probability (IROP). At last, the completely IR procedures are simulated to evaluate the performances of proposed IR method. Simulation results show that the proposed method not only satisfies the requirements of key strength and IROP threshold, but also achieves higher IR efficiency, compared with traditional low density parity check (LDPC) code based IR method.

In this paper, we investigate D2D underlaying cellular networks in which both the D2D links and the cellular downlink links have secrecy requirement. We aim to enhance the secrecy sum rate of D2D pairs(DUs) and cellular users(CUs)by sharing the downlink resources of cellular users and exploiting artificial noise. We achieve the design principle for the downlink signal and artificial noise, which provide guidance on secrecy sum rate maximization. Moreover, a pricing-based pairing and D2D power control algorithm is proposed to pair the DUs and CUs for maximizing system secrecy throughput. Finally, simulation results indicate that the secrecy sum rates of DUs and CUs are improved efficiently by injected artificial noise. The proposed pricing-based scheme obtains better performance of system secrecy throughput than random or graph-based algorithms.

In this work, a robust artificial noise (AN) aided transmit method is proposed for a multicast multiple-input single-output (MISO) system in the presence of multiple single-antenna eavesdroppers. With the imperfect covariance-based channel state information (CSI), we aim to minimize the transmit power at the transmitter under the multicast secrecy rate constraint and the maximum transmit power constraint. The resulting optimization problem involves the joint optimization of the beamforming vector and AN covariance matrix. After using the semidefinite relaxation (SDR) technique, we derive the exact reformulation of the original optimization through the Lagrange duality. Then this non-convex problem is transformed into a one-variable optimization problem, which can be handled by solving a series of semidefinite programs (SDPs). Simulation results demonstrate the effectiveness of the proposed robust transmit method.

Sensor plays an important role in context-aware computing. While sensor modeling is usually isolated from former researches on context modeling and sensor type is always restricted to physical ones, this paper aims to provide a more comprehensive insight into the relationships between sensor and context. Based on a more generic definition of sensor and a corresponding sensor category in context-aware computing, main characteristics of sensor and the relations between sensor and context are analyzed in details. In particular, a multi-sensor oriented context model based on ontology approach is proposed. The model which has been applied to a middleware supporting for rapid context-aware applications development is proved to be effective.