Secure Full-Duplex Communication via Movable Antennas

This paper investigates physical layer security (PLS) for a movable antenna (MA)-assisted full-duplex (FD) system. In this system, an FD base station (BS) with multiple MAs for transmission and reception provides services for an uplink (UL) user and a downlink (DL) user. Each user operates in half-duplex (HD) mode and is equipped with a single fixed-position antenna (FPA), in the presence of a single-FPA eavesdropper (Eve). To ensure secure communication, artificial noise (AN) is transmitted to obstruct the interception of Eve. The objective of this paper is to maximize the sum secrecy rate (SSR) of the UL and DL users by jointly optimizing the beamformers of the BS and the positions of MAs. This paper also proposes an alternating optimization (AO) method to address the non-convex problem, which decomposes the optimization problem into three subproblems and solves them iteratively. Simulation results demonstrate a significant performance gain in the SSR achieved by the proposed scheme compared to the benchmark schemes.

Movable Antenna-Enabled Co-Frequency Co-Time Full-Duplex Wireless Communication

Movable antenna (MA) provides an innovative way to arrange antennas that can contribute to improved signal quality and more effective interference management. This method is especially beneficial for co-frequency co-time full-duplex (CCFD) wireless communication, which struggles with self-interference (SI) that usually overpowers the desired incoming signals. By dynamically repositioning transmit/receive antennas, we can mitigate the SI and enhance the reception of incoming signals. Thus, this paper proposes a novel MA-enabled point-to-point CCFD system and formulates the minimum achievable rate of two CCFD terminals. To maximize the minimum achievable rate and determine the near-optimal positions of the MAs, we introduce a solution based on projected particle swarm optimization (PPSO), which can circumvent common suboptimal positioning issues. Moreover, numerical results reveal that the PPSO method leads to a better performance compared to the conventional alternating position optimization (APO). The results also demonstrate that an MA-enabled CCFD system outperforms the one using fixed-position antennas (FPAs).

Movable Antenna-Enabled Full-Duplex Wireless

Movable antenna (MA) provides an innovative way to arrange antennas that can contribute to improved signal quality and more effective interference management. This method is especially beneficial for full-duplex (FD) wireless, which struggles with self-interference (SI) that usually overpowers the desired incoming signals. By dynamically repositioning transmit/receive antennas, we can mitigate the SI and enhance the reception of incoming signals. Thus, this paper proposes a novel MA-enabled point-to-point FD wireless system and formulates the minimum achievable rate of two FD terminals. To maximize the minimum achievable rate and determine the near-optimal positions of the MAs, we introduce a solution based on projected particle swarm optimization (PPSO), which can circumvent common suboptimal positioning issues. Moreover, numerical results reveal that the PPSO method leads to a better performance compared to the conventional alternating position optimization (APO). The results also demonstrate that an MA-enabled FD system outperforms the one using fixed-position antennas (FPAs).

High-Precision Channel Estimation for Sub-Noise Self-Interference Cancellation

Self-interference cancellation plays a crucial role in achieving reliable full-duplex communications. In general, it is essential to cancel the self-interference signal below the thermal noise level, which necessitates accurate reconstruction of the self-interference signal. In this paper, we propose a high-precision channel estimation method specifically designed for sub-noise self-interference cancellation. Exploiting the fact that all transmitted symbols are known to their respective receivers, our method utilizes all transmitted symbols for self-interference channel estimation. Through analytical derivations and numerical simulations, we validate the effectiveness of the proposed method. The results demonstrate the superior performance of our approach in achieving sub-noise self-interference cancellation.

Next-Generation Full Duplex Networking System Empowered by Reconfigurable Intelligent Surfaces

Full duplex (FD) radio has attracted extensive attention due to its co-time and co-frequency transceiving capability. {However, the potential gain brought by FD radios is closely related to the management of self-interference (SI), which imposes high or even stringent requirements on SI cancellation (SIC) techniques. When the FD deployment evolves into next-generation mobile networking, the SI problem becomes more complicated, significantly limiting its potential gains.} In this paper, we conceive a multi-cell FD networking scheme by deploying a reconfigurable intelligent surface (RIS) at the cell boundary to configure the radio environment proactively. To achieve the full potential of the system, we aim to maximize the sum rate (SR) of multiple cells by jointly optimizing the transmit precoding (TPC) matrices at FD base stations (BSs) and users and the phase shift matrix at RIS. Since the original problem is non-convex, we reformulate and decouple it into a pair of subproblems by utilizing the relationship between the SR and minimum mean square error (MMSE). The optimal solutions of TPC matrices are obtained in closed form, while both complex circle manifold (CCM) and successive convex approximation (SCA) based algorithms are developed to resolve the phase shift matrix suboptimally. Our simulation results show that introducing an RIS into an FD networking system not only improves the overall SR significantly but also enhances the cell edge performance prominently. More importantly, we validate that the RIS deployment with optimized phase shifts can reduce the requirement for SIC and the number of BS antennas, which further reduces the hardware cost and power consumption, especially with a sufficient number of reflecting elements. As a result, the utilization of an RIS enables the originally cumbersome FD networking system to become efficient and practical.

Auxiliary Factor Method to Remove ISI of Nyquist Filters

As has been known, the Nyquist first condition promises the zero-intersymbol (ISI) performance as derived in the frequency domain. However, the practical implementation using the FIR filter truncates the Fourier transformation by its window and, thus, prevents the mathematical calculation from reaching the ideal solution at zero-ISI. For obtaining better results, an increase in the window's length is required in general. To address this problem, a new approach is created by using auxiliary factors (AFs) to compensate shortcoming of the truncated Fourier transformation and nullify completely the ISI, regardless of the window's length. In addition, the performance in the presence of the timing jitter is also improved significantly. The closed-form solution of the AFs is derived and the effectiveness is confirmed by the simulation results. Finally, the problems of the transmission delay and additional calculation complexity are analysed.

Delay Aware Secure Offloading for NOMA-Assisted Mobile Edge Computing in Internet of Vehicles

In this paper, a multi-vehicle multi-task nonorthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system with passive eavesdropping vehicles is investigated. To heighten the performance of edge vehicles, we propose a vehicle grouping pairing method, which utilizes vehicles near the MEC as full-duplex relays to assist edge vehicles. For promoting transmission security, we employ artificial noise to interrupt eavesdropping vehicles. Furthermore, we derive the approximate expression of secrecy outage probability of the system. The combined optimization of vehicle task division, power allocation, and transmit beamforming is formulated to minimize the total delay of task completion of edge vehicles. Then, we design a power allocation and task scheduling algorithm based on genetic algorithm to solve the mixed-integer nonlinear programming problem. Numerical results demonstrate the superiority of our proposed scheme in terms of system security and transmission delay.

Application of Opportunistic Bit to Multilevel Codes

In this paper, we propose a new signal organization method to work in the structure of the multi level coding (MLC). The transmit bits are divided into opportunistic bit (OB) and conventional bit (CB), which are mapped to the lower level- and higher level signal in parallel to the MLC, respectively. Because the OB's mapping does not require signal power explicitly, the energy of the CB modulated symbol can be doubled. As the result, the overall mutual information of the proposed method is found higher than that of the conventional BPSK in one dimensional case. Moreover, the extension of the method to the two-complex-dimension shows the better performance over the QPSK. The numerical results confirm this approach.

A Practical Consideration on Convex Mutual Information

In this paper, we focus on the convex mutual information, which was found at the lowest level split in multilevel coding schemes with communications over the additive white Gaussian noise (AWGN) channel. Theoretical analysis shows that communication achievable rates (ARs) do not necessarily below mutual information in the convex region. In addition, simulation results are provided as an evidence.