Physical-layer key generation (PKG) exploits the reciprocity and randomness of wireless channels to generate a symmetric key between two legitimate communication ends. However, in multi-cell systems, PKG suffers from severe pilot contamination due to the reuse of pilots in different cells. In this paper, we invoke multiple reconfigurable intelligent surfaces (RISs) for adaptively shaping the environment and enhancing the PKG performance. To this end, we formulate an optimization problem to maximize the weighted sum key rate (WSKR) by jointly optimizing the precoding matrices at the base stations (BSs) and the phase shifts at the RISs. For addressing the non-convexity of the problem, we derive an upper bound of the WSKR and prove its tightness. To tackle the upper bound maximization problem, we apply an alternating optimization (AO)-based algorithm to divide the joint optimization into two sub-problems. We apply the Lagrangian dual approach based on the Karush-Kuhn-Tucker (KKT) conditions for the sub-problem of precoding matrices and adopt a projected gradient ascent (PGA) algorithm for the sub-problem of phase shifts. Simulation results confirm the near-optimal performance of the proposed algorithm and the effectiveness of RISs for improving the WSKR via mitigating pilot contamination.
翻译:物理层密钥生成(PKG)利用无线信道的互易性和随机性在两个合法通信端之间生成对称密钥。然而,在多小区系统中,由于在不同小区中重用导频,PKG面临严重的导频污染问题。本文调用多个可重构智能表面(RIS)来适应性地塑造环境和提高PKG性能。为此,我们制定了一个最大化加权和密钥速率(WSKR)的优化问题,通过联合优化基站(BS)的预编码矩阵和RIS的相移来实现。为了解决问题的非凸性,我们推导出WSKR的上界,并证明其紧密性。为了解决上界最大化问题,我们采用交替优化(AO)算法将联合优化分成两个子问题。我们采用基于收缩-昆-塔克(KKT)条件的Lagrangian对偶方法来解决预编码矩阵的子问题,并采用投影梯度上升(PGA)算法解决相移的子问题。仿真结果证实了所提算法的近似最优性和通过减轻导频污染来提高WSKR的RIS效果的有效性。