Priority-Aware Secure Precoding Based on Multi-Objective Symbol Error Ratio Optimization

The secrecy capacity based on the assumption of having continuous distributions for the input signals constitutes one of the fundamental metrics for the existing physical layer security (PHYS) solutions. However, the input signals of real-world communication systems obey discrete distributions. Furthermore, apart from the capacity, another ultimate performance metric of a communication system is its symbol error ratio (SER). In this paper, we pursue a radically new approach to PHYS by considering rigorous direct SER optimization exploiting the discrete nature of practical modulated signals. Specifically, we propose a secure precoding technique based on a multi-objective SER criterion, which aims for minimizing the confidential messages’ SER at their legitimate user, while maximizing the SER of the confidential messages leaked to the illegitimate user. The key to this challenging multi-objective optimization problem is to introduce a priority factor that controls the priority of directly minimizing the SER of the legitimate user against directly maximizing the SER of the leaked confidential messages. Furthermore, we define a new metric termed as the security-level, which is related to the conditional symbol error probability of the confidential messages leaked to the illegitimate user. Additionally, we also introduce the secure discrete-input continuous-output memoryless channel (DCMC) capacity referred to as secure-DCMC-capacity, which serves as a classical security metric of the confidential messages, given a specific discrete modulation scheme. The impacts of both the channel’s Rician factor and the correlation factor of antennas on the security-level and the secure-DCMC-capacity are investigated. Our simulation results demonstrate that the proposed priority-aware secure precoding based on the direct SER metric is capable of securing transmissions, even in the challenging scenario, where the eavesdropper has three receive antennas, while the legitimate user only has a single one

MBER transmit precoding for the rank-deficient MIMO-aided Internet of Things

The Internet of Things (IoT) will support a massive number of devices, which will be connected to the wireless network. In the wireless IoT, the base station serves a wide variety of devices in the same time-frequency resource, where it is expected that the number of devices will be greater than the number of base station antennas. This results in a rank-deficient system. In this paper, we propose a minimum bit error ratio (MBER) precoder for rank-deficient MIMO systems in the context of the IoT, where the IoT devices are generally stationary. We invoke the particle swarm optimization (PSO) algorithm for solving the non-linearly constrained MBER problem and we show that the PSO assisted MBER precoder outperforms the conventional zero forcing and linear minimum mean squared error (LMMSE) precoders, which produce an error floor in these challenging rank-deficient scenarios