Reconfigurable intelligent surface (RIS) is a promising technique to enhance the performance of physical-layer key generation (PKG) due to its ability to smartly customize the radio environments. Existing RIS-assisted PKG methods are mainly based on the idealistic assumption of an independent and identically distributed (i.i.d.) channel model at both the transmitter and the RIS. However, the i.i.d. model is inaccurate for a typical RIS in an isotropic scattering environment. Also, neglecting the existence of channel spatial correlation would degrade the PKG performance. In this paper, we establish a general spatially correlated channel model in multi-antenna systems and propose a new PKG framework based on the transmit and the reflective beamforming at the base station (BS) and the RIS. Specifically, we derive a closed-form expression for characterizing the key generation rate (KGR) and obtain a globally optimal solution of the beamformers to maximize the KGR. Furthermore, we analyze the KGR performance difference between the one adopting the assumption of the i.i.d. model and that of the spatially correlated model. It is found that the beamforming designed for the correlated model outperforms that for the i.i.d. model while the KGR gain increases with the channel correlation. Simulation results show that compared to existing methods based on the i.i.d. fading model, our proposed method achieves about 5 dB performance gain when the BS antenna correlation$\rho$is 0.3 and the RIS element spacing is half of the wavelength.
Reconfigurable intelligent surface (RIS) is a promising technique to enhance the performance of physical-layer key generation (PKG) due to its ability to smartly customize the radio environments. Existing RIS-assisted PKG methods are mainly based on the idealistic assumption of an independent and identically distributed (i.i.d.) channel model at both the transmitter and the RIS. However, the i.i.d. model is inaccurate for a typical RIS in an isotropic scattering environment. Also, neglecting the existence of channel spatial correlation would degrade the PKG performance. In this paper, we establish a general spatially correlated channel model in multi-antenna systems and propose a new PKG framework based on the transmit and the reflective beamforming at the base station (BS) and the RIS. Specifically, we derive a closed-form expression for characterizing the key generation rate (KGR) and obtain a globally optimal solution of the beamformers to maximize the KGR. Furthermore, we analyze the KGR performance difference between the one adopting the assumption of the i.i.d. model and that of the spatially correlated model. It is found that the beamforming designed for the correlated model outperforms that for the i.i.d. model while the KGR gain increases with the channel correlation. Simulation results show that compared to existing methods based on the i.i.d. fading model, our proposed method achieves about 5 dB performance gain when the BS antenna correlationρis 0.3 and the RIS element spacing is half of the wavelength.
Abstract Reconfigurable intelligent surface (RIS)‐assisted physical layer key generation plays an important role in the eavesdropping problem on a typical multi‐user scenario of wireless networks. Existing RIS‐assisted physical key generation technology mainly solved the security issues in the single‐antenna and multi‐user scenario, which is based on the idealistic assumption of a spatially independent channel model at the RIS. It limits the degrees of freedom and neglects the existence of channel spatial correlation, which would possibly degrade the sum key generation rate (SKGR). To solve the above problem, this paper proposes a secret key generation scheme for RIS‐assisted multiple‐input single‐output multi‐user system. This scheme establishes a spatial correlation channel model, which comprehensively considers the influence of spatial correlation among antennas of the base station (BS), multi‐user, and RIS elements on SKGR. Based on this, a key generation framework is designed to generate a more secure secret key with the maximum SKGR. Specifically, a closed‐form SKGR expression and an optimization problem formulation are obtained to obtain the joint optimal coefficient of the BS and RIS. Then, the difference convex‐successive convex approximation based alternating optimization algorithm is proposed to solve this optimization problem. The simulation results show that the proposed scheme has improved 10‐bit/channel use compared with the randomization scheme of BS precoding and RIS reflection coefficient. It also has an improvement of 12‐bit/channel use compared with the spatially independent scheme.
By exploiting the entropy of wireless channels, physical layer key generation (PLKG) has gained considerable attention in recent years. Due to the characteristic of dynamic controlling of wireless channels, reconfigurable intelligent surface (RIS) can improve the key generation rate (KGR). Simultaneous transmission and reflection reconfigurable intelligent surface (STAR- RIS) can extend the half-space coverage to full-space coverage. This paper proposes a STAR-RIS-assisted physical layer key generation (SRKG) scheme in a multi-user case. The objective is to maximize the sum KGR by jointly designing the transmitting and reflecting coefficients (TARCs). We propose an iterative algorithm based on alternating optimization (AO), utilizing successive convex approximation (SCA) and semi-definite relaxation (SDR) methods, to solve the non-convex optimization problem in the presence of correlated channels. We also propose a low-complexity algorithm based on Lagrange multipliers to jointly optimize TARCs considering independent fading. Finally, the simulation results validate that, compared with the PLKG scheme assisted by traditional RIS (T-RIS), the proposed SRKG scheme can achieve higher sum KGR in a wider range under correlated and independent channel conditions.
Due to the limited coverage of reflecting-only reconfigurable intelligent surfaces (RIS), the existing RIS-assisted physical-layer key generation (PKG) scheme limits its overall performance in the full space. This paper proposes a novel simultaneously transmitting and reflecting (STAR)-RIS-assisted PKG protocol for multiple-input multiple-output (MIMO) systems, where the closed-form sum secret key rate is derived in the presence of full-space eavesdroppers. Two optimization problems are formulated to maximize the sum secret key rate by designing the transmit beamforming (TBF) and transmitting and reflecting coefficients (TRCs) for energy splitting (ES) with coupled phase-shift and mode switching (MS) mode. For ES mode with coupled phase-shift, a penalty-based alternating optimization (AO) algorithm is proposed to address its non-convexity. For MS mode, the semidefinite relaxation-successive convex approximation-based AO algorithm is utilized to achieve continuous solutions and then quantize to binary value for the MS mode. Simulation results demonstrate that the coupled phase-shift STAR-RIS incurs a slight KGR loss in comparison to the independent phase-shift STAR-RIS. Additionally, the ES mode outperforms the MS mode in terms of KGR performance. Finally, STAR-RIS can achieve a higher sum secret key rate than traditional reflecting-only RIS.
Physical-layer key generation (PKG) technology offers a lightweight encryption solution for device-to-device (D2D) communications. However, it faces significant challenges due to the high correlation between the eavesdropping and legitimate channels, as well as the imperfect estimated channel, which cause substantial degradation of secret key capacity. To address the challenges, we propose a novel PKG framework that leverages the reflective beamforming of reconfigurable intelligent surface (RIS) for D2D communications. Specifically, we first derive closed-form expression for the secret key capacity under correlated and imperfect estimated channels. Then, we propose to maximize the minimum secret key capacity by optimizing the reflection coefficient matrix (O-RCM) of RIS, which is a non-convex optimization problem. Next, a semi-definite relaxation and successive convex approximation-based method for O-RCM (SSO-RCM) is proposed to tackle the non-convex max-min-min problem. To further reduce the computational complexity, we propose a low-complexity method based on the path-following algorithm for O-RCM (PFO-RCM). Simulation results show that under correlated and imperfect channels, both proposed methods significantly improve the minimum secret key capacity compared to the existing RIS-assisted methods. Moreover, the PFO-RCM method, while exhibiting lower computational complexity than the SSO-RCM method, incurs a small performance loss.
A conventional secret key generation scheme achieves a low secret key rate in static environments. To solve this problem, the reconfigurable intelligent surface (RIS) antenna is merged with the device at the base station and is firstly proposed for secret key generation. By tuning the phase shifts at the RIS, a random varying beam can be generated and combined with the original wireless channel to form a new equivalent channel so that the key capacity is not subject to the time variance of the wireless channel. Then the closed-form solution is derived. Theoretical analysis and simulation show that the performance can be increased to that of a fast varying channel with limited radiating units. Moreover, the proposed scheme is superior to the existing schemes, in which the RIS is used as a reflective surface, over performance gain and preventing information disclosure. To further develop the gain of RIS, a joint design scheme is proposed, where some units are used for key generation, and some units are used for beamforming. Finally, the joint's closed-form solution scheme is derived. Finally, on the basis of satisfying the key capacity and communication performance, an optimal resource allocation strategy is proposed. Simulation results illustrate that the key capacity and communication performance can be improved simultaneously.
Recently, there has been a growing interest in utilizing reconfigurable intelligent surfaces (RIS) for physical layer key generation (PLKG) due to their ability to intelligently configure the wireless medium. However, to the best of our knowledge, no study has explored the potential of active RIS (ARIS) in aiding PLKG. Motivated by this gap, this letter investigates the application of ARIS in PLKG. Furthermore, most existing RIS-aided PLKG techniques are based on the idealistic assumption of independent and identically distributed (i.i.d.) fading model at the RIS. Accordingly, we further consider the intrinsic correlated fading among the RIS elements. We derive the secret key rate (SKR) of the ARIS-aided PLKG and propose a sequential convex approximation (SCA) based optimization method to jointly optimize the phase and gain of the ARIS to reach maximum SKR. Additionally, we compare the performance of passive RIS (PRIS) aided PLKG with ARIS-aided PLKG. We show that with an equal total power budget, ARIS leads to significantly higher SKR, thereby offering promisingly high energy efficiency (EE) compared to PRIS.