Full-duplex System Research Articles

A Joint Design for Full-Duplex OFDM AF Relay System With Precoded Short Guard Interval

A Joint Design for Full-Duplex OFDM AF Relay System With Precoded Short Guard Interval

Drone-based mobile full-duplex optical communication

Wireless optical communication plays a vital role in mobile communication networks, and both drones and vehicles are essential mobile communication nodes. Here, image identification technology, gimbal, and full-duplex optical communication systems are integrated to manage the challenging issues of light alignment and target tracking for mobile full-duplex optical communication under the transmission control protocol/internet protocol (TCP/IP) scheme. Both drones and vehicles are equipped with the proposed setup to realize full-duplex wireless optical data transmission at a communication rate of 2 Mbps in both air-to-ground and air-to-air scenarios. By further integrating wireless-fidelity (Wi-Fi) modules, drone-based mobile optical communication systems (MOCSs) can be interconnected with the network via the TCP/IP scheme, and real-time video transmission can be demonstrated. This work provides a feasible route toward a mobile optical communication network (MOCN) for diverse applications.

Successive interference cancellation-based channel estimation for self-interference cancellation in in-band full-duplex systems

Successive interference cancellation-based channel estimation for self-interference cancellation in in-band full-duplex systems

Performance Analysis of IRS Assisted Full-Duplex Systems With Different Downlink and Uplink Users

Performance Analysis of IRS Assisted Full-Duplex Systems With Different Downlink and Uplink Users

Analyzing error probability in aerial full-duplex relay systems: Exact formulations and optimization techniques

In this study, we investigate the performance of aerial full-duplex relay (AFDR) systems. In particular, we examine two practical scenarios: one where there is no direct link between the transmitter and user, and another where such a link exists. For both scenarios, we develop mathematical models to calculate the closed-form expressions of symbol error probabilities (SEPs) for AFDR systems, using a realistic channel aligned with the fifth generation (5G) and beyond yardsticks. To take care of residual self-interference (RSI) in AFDR, we propose an optimal power allocation strategy. Our numerical findings indicate that the performance in the case with a direct link is considerably higher than that in the case without this link. Additionally, we analyze thoroughly the effects of key parameters such as transmit power, RSI levels, carrier frequencies, and AFDR positions. The effect of RSI is significantly strong, and our proposed optimal power allocation method substantially improves system performance, especially in high transmit power scenarios where error floors may occur. Importantly, the optimal power level is dramatically lower than the conventional value where the optimal power cannot be found. Thus, besides reducing the SEPs, optimal power also helps to prolong the time of operation of AFDR. Monte-Carlo simulations are performed to confirm the accuracy of our derived expressions and demonstrate the efficacy of the proposed approaches in practical scenarios.

Channel Estimation for Full-Duplex OFDM-Based Ambient Backscatter Communication Systems With I/Q Imbalance

Channel Estimation for Full-Duplex OFDM-Based Ambient Backscatter Communication Systems With I/Q Imbalance

An experimental study on beamforming architecture and full-duplex wireless across two operational outdoor massive MIMO networks

Full-duplex (FD) wireless communication refers to a communication system in which both ends of a wireless link transmit and receive data simultaneously in the same frequency band. One of the major challenges of FD communication is self-interference (SI), which refers to the interference caused by transmitting elements of a radio to its own receiving elements. Fully digital beamforming is a technique used to conduct beamforming and has been recently repurposed to also reduce SI. However, the cost of fully digital systems dramatically increases with the number of antennas, as each antenna requires an independent Tx-Rx RF chain. Hybrid beamforming systems use a much smaller number of RF chains to feed the same number of antennas, and hence can significantly reduce the deployment cost. In this paper, we aim to quantify the performance gap between these two radio architectures in terms of SI cancellation and system capacity in FD multi-user Multiple Input Multiple Output (MIMO) setups. We first obtained over-the-air channel measurement data on two outdoor massive MIMO deployments over the course of three months. We next study SoftNull and M-HBFD as two state-of-the-art transmit (Tx) beamforming based FD systems, and introduce two new joint transmit-receive (Tx-Rx) beamforming based FD systems named TR-FD2 and TR-HBFD for fully digital and hybrid radio architectures, respectively. We show that the hybrid beamforming systems can achieve 80%–99% of the fully digital systems capacity, depending on the number of users. Our results show that it is possible to get many benefits associated with fully digital massive MIMO systems with a hybrid beamforming architecture at a fraction of the cost.

Joint wireless energy transmission and dynamic power management for full-duplex relay system

The rapid deployment of fifth-generation (5G) mobile communication systems demands sustainable power solutions. This paper introduces a novel joint design for wireless energy transmission and dynamic power management in full-duplex relay systems, aiming to ensure a continuous power supply for relay nodes. Our approach integrates energy harvesting from RF signals and dynamic battery management, focusing on optimizing throughput via energy allocation and precoding design. Simulation results demonstrate that our scheme significantly outperforms conventional non-battery half-duplex schemes in system throughput. Notably, we observe performance increments in throughput compared to all mentioned traditional methods, highlighting the efficacy of our design in enhancing 5G network sustainability and efficiency. This innovative approach presents a promising solution for effective power management in next-generation mobile networks.

Digital Self-Interference Cancellation for Full-Duplex Systems Based on CNN and GRU

Digital Self-Interference Cancellation for Full-Duplex Systems Based on CNN and GRU

Bilayer Intelligent Omni-Surface-Assisted Full-Duplex Systems: Simultaneous Self-Interference Cancellation and Sum Rate Maximization.

Recently, reconfigurable intelligent surfaces (RISs) have attracted increasing attentions in the design of full-duplex (FD) systems due to their novel capability of propagation environment reconfiguration. However, in conventional RIS-assisted FD systems, the beamforming for self-interference cancellation (SIC) and sum rate maximization (SRM) are highly coupled during RIS optimization, which significantly degrades the system performance. To tackle this issue, we exploit a novel bilayer intelligent omni-surface (BIOS) structure in FD systems. Compared with the conventional RIS designs, the BIOS provides independent beams on both sides, thus enabling more flexible achievement of SRM and SIC. For the BIOS-assisted FD system, we first formulate an optimization problem to achieve SRM and efficient SIC simultaneously. Then, we exploit the relationship between the SRM and mean square error (MSE), and propose a weighted MSE minimization with SIC algorithm to solve the problem. Specifically, we jointly design the beamforming at the base station and the BIOS with manifold optimization while guaranteeing an SIC constraint. Furthermore, we theoretically derive a lower band for the BIOS size required for efficient SIC in FD systems. Simulation results indicate that the BIOS outperforms the conventional RIS designs in FD systems, and verify the accuracy of the derived lower bound for the BIOS size.

Proximal Policy Optimization for RIS-Assisted Full Duplex 6G-V2X Communications

In this work, we consider a novel reconfigurable intelligent surface (RIS)-assisted full-duplex (FD) sixth generation (6G)-vehicle-to-everything (V2X) communication network having a FD base station (BS) simultaneously communicating with a uplink (UL) and a downlink (DL) mobile vehicles with the aide of two RISs, one for each link. We provide an analytical framework to investigate the performance of this network and, consequently, formulate an optimization problem to jointly optimize the phase shift matrices at both the RISs that maximize the achievable sum-rate. Thereafter, due to the non-convex nature of the problem, we propose a low complexity proximal policy optimization (PPO)-based deep reinforcement learning (DRL) algorithm that solves the problem in continuous action spaces by reducing the overall training overhead and provides optimum values of phase-shift matrix at each RIS. Further, we extend the analysis considering multiple transmit and receive antennas at the BS that simultaneously serves multiple UL and DL vehicles. We present exhaustive simulations-based graphical results to validate the effectiveness and accuracy of the proposed algorithm compared to deep deterministic policy gradient (DDPG) and successive refinement (SR)-based solutions. Accordingly, we demonstrate the dominance of the considered FD system over its half-duplex (HD) counterpart. We also discuss the impact of the number of elements at each RIS, each vehicle's velocity and their distance from the RIS and the BS on the performance of the respective links. Moreover, we also highlight the impact of imperfect self-interference cancellation and discuss the trade-off between the UL and DL performances due to this imperfection. Additionally, it is shown that the proposed algorithm is approximately <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10 \times$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ 40 \times$</tex-math></inline-formula> faster than DDPG and SR, respectively. Finally, for the multiple vehicle case, we demonstrate the effect of co-channel interference on the DL rate and the impact of RIS elements, the number of UL and DL vehicles on the system performance.

Security Performance Analysis of Full-Duplex UAV Assisted Relay System Based on SWIPT Technology

In this paper, a new methodology is developed for modeling and analyzing a full-duplex UAV-assisted relay system to facilitate solving the problems of UAV energy constraints and the vulnerability of UAVs to eavesdropping in the air. Combining simultaneous wireless information and power transfer (SWIPT) technology, we model the downlink UAV eavesdropping channel and propose a secure transmission protocol for a full-duplex UAV-assisted relay system. Using this transmission protocol, we analyze and derive the connectivity and security of the entire communication link, including connection probability and lower bounds on secrecy outage probability. A key intermediate step in our analysis is to derive the signal-to-digital noise ratio of the destination and eavesdropping nodes of the full-duplex UAV relay link. The analyses show that the power allocation factor λ is a trade-off between system connectivity and security, while greater eavesdropping interference needs to be sacrificed for an equal magnitude of security performance improvement under high security demand conditions.

Frequency-Domain Differential Interference Cancellation for Full-Duplex OFDM ISAC Systems

Frequency-Domain Differential Interference Cancellation for Full-Duplex OFDM ISAC Systems

A diplexer antenna with extremely high isolation for co-site duplex applications

Co-site full-duplex communication system is facing self-interference (SI) issues caused by tremendous gap between Tx power and Rx sensitivity. SI suppression in the propagation domain is addressed by a co-polarized diplexer antenna with high port isolation in this paper. It shares a dual-band microstrip antenna with a small frequency ratio, at 1.5 and 2.0 GHz as an example. A shorting pin directly connects the antenna and diplexer, avoiding 50-Ω interface and impedance matching circuit. The diplexer is composed of open-loop resonators (OLRs) and step-impedance resonators (SIRs). Compact channel filters are constituted by OLRs, and SIRs are adopted to improve the filtering response of the diplexer. General guidelines of the diplexer are given through rigorous analysis. The fractional bandwidths of the lower and higher channels of the diplexer are 4% and 3%, and the fractional bandwidths of the diplexer antenna are 1.5% and 1%, respectively. The port isolation is greater than 53 dB for both channels. Size of the diplexer antenna is 0.65 λ×0.60 λ×0.016 λ, where λ is the free-space wavelength at the lowest operation frequency. Potential advantages of the proposed antenna in suppressing SI are validated using Software-Defined Radio, which is potentially useful in full-duplex communications.

Deep Learning-Driven Interference Perceptual Multi-Modulation for Full-Duplex Systems

In this paper, a novel data transmission scheme, interference perceptual multi-modulation (IP-MM), is proposed for full-duplex (FD) systems. In order to unlink the conventional uplink (UL) data transmission using a single modulation and coding scheme (MCS) over the entire assigned UL bandwidth, IP-MM enables the transmission of UL data channels based on multiple MCS levels, where a different MCS level is applied to each subband of UL transmission. In IP-MM, a deep convolutional neural network is used for MCS-level prediction for each UL subband by estimating the potential residual self-interference (SI) according to the downlink (DL) resource allocation pattern. In addition, a subband-based UL transmission procedure is introduced from a specification point of view to enable IP-MM-based UL transmission. The benefits of IP-MM are verified using simulations, and it is observed that IP-MM achieves approximately 20% throughput gain compared to the conventional UL transmission scheme.

Intelligent Reflecting Surface Empowered Self-Interference Cancellation in Full-Duplex Systems

Intelligent Reflecting Surface Empowered Self-Interference Cancellation in Full-Duplex Systems

Deep learning based detection of signal of interest of uplink NOMA multi-users in NOMA In-band Full-duplex Radio communication

The research focuses on investigating the symbol error rate (SER) performance of the Non Orthogonal Multiple Access (NOMA) In-band Full-duplex Radio communication system, which is considered a promising technology for 5G/6G. This system facilitates simultaneous transmission and reception of data over the same resource block for multiple users via power domain multiplexing. However, the system faces a significant challenge in the form of self-interference signal (SI). The SI signal transmitted from the NOMA In-band full-duplex radio transmitting antenna is also received by its own receiving antenna. It limits perfect successive interference cancellation (SIC) for channel estimation and signal detection of the signal of interest (SoI) from uplink NOMA multi-users at the receiver of NOMA In-band Full-duplex radio. Furthermore the SER performance is significantly degraded due to various SI and SoI channel imperfections. To address this, a three-phase-based efficient approach has been proposed for simultaneous non-linear SI cancellation and detection of the SoI from uplink NOMA two users under aforementioned SI and SoI channel imperfections. The approach uses the Least Square-SIC Estimator, Minimum Mean Square Error-SIC Estimator, and deep learning (DL) methods. The reported 4 dB SNR gain compared to least square-SIC/minimum mean square error SIC and DNN-based methods demonstrate the robustness of the proposed DL-aided approach against various SI and SoI channel imperfections for NOMA In-band Full-duplex Radio communication.

Dual-polarization MZM-based photonic nonlinear analog self-interference cancellation for in-band full-duplex radios

In this paper, we propose a dual-polarization Mach-Zehnder modulator-based photonic nonlinear analog self-interference cancellation (SIC) technique for in-band full duplex (IBFD) systems. By using the proposed technique, an arbitrary 4th order nonlinear transfer function can be generated, meaning the performance limitation caused by the nonlinearity of the analog SIC circuit can be overcome by imitating the nonlinear transfer function of the analog SIC circuit before cancellation. This paper also presents a performance analysis through simulations and the results of a proof-of-concept demonstration. In the experiment, the proposed nonlinear SIC technique could achieve 29 dB cancellation over 500 MHz bandwidth centered at 1.25 GHz frequency along various degree of distortion caused by nonlinearity. In addition, the performance enhancements achieved by the proposed technique are evaluated in terms of error vector magnitudes (EVMs) and constellations of the signal-of-interest (SOI) in the simulation which is based on the experimental SIC results. More than 3 dB of SOI power gain could be obtained in evaluated EVM performances.

Reinforcement learning-based energy efficiency optimization for RIS-Assisted UAV hybrid uplink and downlink system

As Reconfigurable Intelligent Surface (RIS) technology can intelligently reflect the incident signal, it can be deployed to maintain a line-of-sight connection and improve the signal strength between unmanned Aerial Vehicles (UAV) and users. Current researches on RIS-assisted UAV communication typically consider optimizing data rates for single-line communications and do not focus on the energy consumption of the UAV. Furthermore, it is frequently challenging to apply conventional algorithms to RIS-assisted UAV optimization problems in a timely way, and the two-dimensional trajectory design cannot fully utilize the 3D mobility of the UAV. In order to increase the data rates for all ground users while improving the energy efficiency of the system, we consider a RIS-assisted full-duplex UAV communication system, in which a DDQN-based algorithm is proposed to jointly optimize the phase shift of the RIS and the 3D trajectory of the UAV. Simulation results demonstrate that the proposed algorithm can achieve a significant data rate gain and energy efficiency compared to time-division duplex systems and other deep reinforcement learning algorithms.

Full-duplex wireless light communication using green laser diodes

The integration of wireless light communication into a wireless fidelity (Wi-Fi) module and gateway enables real-time integrated communication networks that satisfy practical application demands. In particular, wireless green light communication tools can operate underwater and in free-space environments. Here, we design, fabricate, and characterize a full-duplex light communication system using green laser diodes (LDs). Operating within the transmission control protocol/internet protocol (TCP/IP), full-duplex wireless data transmission is confirmed in underwater and free-space environments at a communication rate of 10 Mbps. Through connections to a Wi-Fi module and gateway, the system is accessed by the network via the TCP/IPv4 internet scheme, and real-time video transmission is demonstrated.