Friendly Jamming in a MIMO Wiretap Interference Network: A Nonconvex Game Approach

Abstract

We consider joint optimization of artificial noise (AN) and information signals in a MIMO wiretap interference network, wherein the transmission of each link may be overheard by several MIMO-capable eavesdroppers. Each information signal is accompanied with AN, generated by the same user to confuse nearby eavesdroppers. Using a noncooperative game, a distributed optimization mechanism is proposed to maximize the secrecy rate of each link. The decision variables here are the covariance matrices for the information signals and ANs. However, the nonconvexity of each link's optimization problem (i.e., best response) makes conventional convex games inapplicable, even to find whether a Nash Equilibrium (NE) exists. To tackle this issue, we analyze the proposed game using a relaxed equilibrium concept, called quasi-Nash equilibrium (QNE). Under a constraint qualification condition for each player's problem, the set of QNEs includes the NE of the proposed game. We also derive the conditions for the existence and uniqueness of the resulting QNE. It turns out that the uniqueness conditions are too restrictive, and do not always hold in typical network scenarios. Thus, the proposed game often has multiple QNEs, and convergence to a QNE is not always guaranteed. To overcome these issues, we modify the utility functions of the players by adding several specific terms to each utility function. The modified game converges to a QNE even when multiple QNEs exist. Furthermore, players have the ability to select a desired QNE that optimizes a given social objective (e.g., sum-rate or secrecy sum-rate). Depending on the chosen objective, the amount of signaling overhead as well as the performance of resulting QNE can be controlled. Simulations show that not only we can guarantee the convergence to a QNE, but also due to the QNE selection mechanism, we can achieve a significant improvement in terms of secrecy sum-rate and power efficiency, especially in dense networks.

Asymptotic Bound of Secrecy Capacity for MIMOME‐Based Transceivers: A Suboptimally Tractable Solution for Imperfect CSI

“…In general, from (14) it can be seen that lim SNR (dB)→∞ SOP = 0 since SNR ≫ D With respect to the main advantages thoroughly discussed in relation to the proposed scheme, its outperformance, correctness, and effectiveness are obviously highlighted over the existing methods (conventionally utilised in the literature, specifically the worst-case one).…”

“…In [14], a secure game theorydriven transmission framework was conducted for MIMOMEs proposing three algorithms aimed at maximising sum secrecy rate. A trade-off was theoretically defined in [15] for the principles sum secrecy rate reinforcement and energy efficiency which could provide a balance in physical-layersecurity-based transceiver designs.…”

A Cooperative Jamming Based Joint Transceiver Design for Secure Communications in MIMO Interference Channels

“…However, in MIMO system, if the transmitters and receivers use the same number of antennas to transmit data symbols, the null space is not existent and the zero-forcing is infeasible. Except for zero-forcing, although some AN designs in MIMO interference networks have been proposed to ensure PLS while reducing the impact on legitimate receivers by as much as possible [19][20], but the optimization problem of the secrecy rate is non-convex and the complexity remains fairly high. Therefore, how to design cooperative jamming considering both security performance and computing efficiency is still an unsolved problem.…”