Full-duplex Mode Research Articles

Digital nonlinear self-interference cancellation using SW-GRU-TPA

In order to enhance spectrum utilization and decrease transmission delay, the 6th generation mobile networks (6G) system adopts full-duplex (FD) mode. Simultaneous operation of the same frequency inevitably causes the receiver to receive the signal sent by the transmitter, leading to serious nonlinear self-interference due to the nonlinear distortion generated by the power amplifier (PA). This paper proposes hybrid layer structures SW-GRU-TPA for the implementation of digital self-interference cancellation (SIC), combined with Sliding Window (SW), Gated Recurrent Unit (GRU), and Temporal Pattern Attention (TPA). The model can not only effectively utilize the influence of historical information on the signal, but also capture the spatial and temporal dependencies in the data to fit the nonlinear characteristics of the PA and the delay effect in multipath transmission. Meanwhile, by utilizing the L1 norm model pruning, the model parameters can be optimized, leading to improved processing efficiency. The model is verified using two methods: injection and antenna reception. Compared to the SW-GRU model with Attention Mechanism (AM), the Interference Cancellation Ratio (ICR) of injection and antenna increases by 3.13 dB and 2.01 dB, respectively. When the TPA is compressed by 42.17%, the ICR of injection and antenna decreases by 1.58% and 2.6%.

Full-Duplex Unmanned Aerial Vehicle Communications for Cellular Spectral Efficiency Enhancement Utilizing Device-to-Device Underlaying Structure

Unmanned aerial vehicle (UAV) communications have gained recognition as a promising technology due to their unique characteristics of rapid deployment and flexible configuration. Meanwhile, device-to-device (D2D) and full-duplex (FD) technologies have emerged as promising methods for enhancing spectral efficiency and offloading traffic. One significant advantage of UAVs is their ability to partition suitable D2D pairs to increase cell capacity. In this paper, we present a novel network model in which UAVs are considered D2D pairs underlaying cellular networks, integrating FD into the communication links between UAVs to improve spectral efficiency. We then investigate a resource allocation problem for the proposed FD-UAV D2D underlaying structure model, with the objective of maximizing the system’s sum rate. Specifically, the UAVs in our model operate in full-duplex mode as D2D users (DUs), allowing the reuse of both the uplink and downlink subcarrier resources of cellular users (CUs). This optimization challenge is formulated as a mixed-integer nonlinear programming problem, known for its NP-hard and intractable nature. To address this issue, we propose a heuristic algorithm (HA) that decomposes the problem into two steps: power allocation and user pairing. The optimal power allocation is solved as a nonlinear programming problem by searching among a finite set, while the user pairing problem is addressed using the Kuhn–Munkres algorithm. The numerical results indicate that our proposed FD-MaxSumCell-HA (full-duplex UAVs maximizing the cell sum rate with a heuristic algorithm) scheme for FD-UAV D2D underlaying models outperforms HD-UAV underlaying cellular networks, with improved access rates for UAVs in FD-MaxSumCell-HA compared to HD-UAV networks.

Joint beamforming design for full‐duplex wireless powered over‐the‐air computation systems with self‐energy recycling

AbstractFor over‐the‐air computation (AirComp) systems, energy‐constrained sensors become a bottleneck to improve the performances. To address this issue, in this letter, a full‐duplex (FD) wireless powered AirComp system with self‐energy recycling is proposed, where all the nodes operate in the FD mode and the sensors can harvest energy from the hybrid access point (HAP)' signal and it's own transmit signal by self‐energy recycling. A joint beamforming design problem is formulated and an effective iterative algorithm is proposed to solve the non‐convex optimization problem, aiming to minimize the computation mean square error at the HAP under the transmit power constraints of the HAP and sensors. Simulation results are presented to demonstrate the effectiveness of the proposed scheme.

A Novel A-RoF and VLC-based Full-Duplex FiWi System for B5G Applications

We propose the concept and report the implementation of a Gbps hybrid full-duplex analog radio-over-fiber (A-RoF)/visible light communication (VLC) laser diode (LD)-based system for beyond the fifth generation (B5G) of mobile network applications. Such hybrid optical wireless architecture is composed of a 3-km single-mode fiber fronthaul based on the A-RoF technology, followed by a 1.3 m VLC-LD-based access network. The latter one employs two counter-propagating visible light beams by using dichroic cube filters (DCFs) at the transmitter and receiver side, enabling the full-duplex mode, and avoiding the use of individual optical filters. As a proof of concept, we experimentally demonstrate a successful deployment of 5G New Radio (NR) hybrid full-duplex A-RoF/VLC system. The system performance is evaluated in terms of root mean square error vector magnitude (EVMRMS), in accordance with the 3rd Generation Partnership Project (3GPP) requirements, and as a function of modulation order. The experimental results demonstrate a downlink throughput of 600 Mbit/s and an uplink throughput of 420 Mbit/s, aligning with the digital performance requirements set by 3GPP.

Joint Hybrid Beamforming Design for Millimeter Wave Amplify-and-Forward Relay Communication Systems

Hybrid beamforming (HBF) has been regarded as one of the most promising technologies in millimeter Wave (mmWave) communication systems. In order to guarantee the communication quality in non-line-of-sight (NLOS) scenarios, joint HBF design for the mmWave amplify-and-forward (AF) relay communication system is studied in this paper. The ideal case is first considered where the mmWave half-duplex (HD) AF relay system operates with channel state information (CSI) accurately known. In order to tackle the non-convex problem, a manifold optimization (MO)-based alternating optimization algorithm is proposed, where an optimization problem containing only constant modulus constraints in Euclidean space can be converted to an unconstrained optimization problem in a Riemann manifold. Furthermore, considering more practical cases with estimation errors of CSI, we investigate the robust joint HBF design with the system operating in full-duplex (FD) mode to obtain higher spectral efficiency (SE). A null-space projection (NP) based self-interference cancellation (SIC) algorithm is developed to attenuate the self-interference (SI). Different from the traditional SI suppression algorithm, there’s no limit on the number of RF chains. Numerical results reveal that our proposed algorithms has a good convergence and can effectively deal with the influence of different CSI estimation errors. A significant performance improvement can be achieved in contrast with other approaches.

Full/half-duplex unmanned aerial vehicles assisted wireless systems: Performance analysis and optimization

In this paper, we explore the utilization of both full-duplex (FD) and half-duplex (HD) transmission modes on unmanned aerial vehicles (UAVs) to enhance wireless system performance. We consider two practical scenarios: one without a direct transmitter-user link and the other with such a link. For both cases, we derive mathematical expressions of outage probabilities (OPs) and throughputs of FD-UAV and HD-UAV systems, employing a realistic channel model aligned with the fifth and beyond generations (5G-B5G) standards. In cases where imperfect self-interference cancellation (SIC) occurs in FD-UAV systems, we introduce an optimal power allocation approach to enhance system performance. Numerical results underscore the benefits of cooperative communications, particularly when combining the direct link with the UAV link at the user, leading to an overall enhancement in system performance. Furthermore, we conduct a comprehensive analysis of various system parameters, including predefined rates, residual self-interference (RSI) levels, high carrier frequencies of Wi-Fi networks, and high altitudes of UAVs. The impact of RSI is particularly notable, and the proposed optimal power allocation approach significantly improves system performance in such cases. Specifically, the introduced scheme helps avoid error floors in regions of high transmit power, enabling throughputs to reach desired targets in FD-UAV systems. Crucially, the optimal power value is considerably lower than the traditional value often used without optimal power allocation, extending the operational duration of FD-UAV. Finally, to validate the derived mathematical expressions and affirm the effectiveness of the proposed approaches, we conduct Monte-Carlo simulations.

A Simultaneous Wireless Power and Data Transfer System With Full-Duplex Mode for Underwater Wireless Sensor Networks

A Simultaneous Wireless Power and Data Transfer System With Full-Duplex Mode for Underwater Wireless Sensor Networks

Efficient symbol level precoding design for full-duplex integrated sensing and communication systems

Full-duplex (FD) integrated sensing and communication (ISAC) system attracts much attention because adopting the FD mode can enhance the transmission efficiency and reduce the transmission time of the ISAC system. However, the inevitable self-interference (SI) in FD mode would result in severe performance degradation. This paper considers the FD ISAC system and investigates a symbol-level precoding (SLP) design, which minimizes the Cramér-Rao Bound of target angle estimation while considering the constant-envelope power restraint, SI suppression and the quality of service requirement. Due to the non-convex fractional problem and the unit-modulus constraint, the optimization problem is reformulated by implementing the Schur complement, where the optimal waveform is obtained via the semidefinite programming algorithm. The SLP design that optimizes each symbol vector for all users may suffer high computational complexity of matrix multiplication with high numbers of users. A grouped SLP strategy in which the communication users are divided into several groups on the basis of channel correlation is proposed to reduce the complexity. The proposed grouped SLP design only suppresses group-to-group interference and converts the intra-group interference into a constructive interference, which can reduce the dimension of each precoded signal significantly, resulting in a low computational complexity. Simulation results illustrate that the proposed SLP design can effectively mitigate SI, which can improve the accuracy of target detection. Moreover, the proposed grouped-SLP design can further reduce computational complexity without dramatic performance degradation.

Wireless Body Area Nanonetworks via Vascular Molecular Communication.

Advancements in biotechnology and molecular communication have enabled the utilization of nanomachines in Wireless Body Area Networks (WBAN2) for applications such as drug delivery, cancer detection, and emergency rescue services. To study these networks effectively, it is essential to develop an ideal propagation model that includes the channel response between each pair of in-range nanomachines and accounts for the interference received at each receiver node. In this paper, we employ an advection-diffusion equation to obtain a deterministic channel matrix through a vascular WBAN2. Additionally, the closed forms of inter-symbol interference (ISI) and co-channel interference (CCI) are derived for both full duplex (FDX) and half duplex transmission (HDX) modes. By applying these deterministic formulations, we then present the stochastic equivalents of the ideal channel model and interference to provide an innovative communication model by simultaneously incorporating CCI, ISI, and background noise. Finally, we evaluate the results with numerous experiments and use signal-to-interference-plus-noise ratio (SINR) and capacity as metrics.

Spectrum sharing framework in full duplex mode with minimum interference in 5G cellular network

Spectrum sharing framework in full duplex mode with minimum interference in 5G cellular network

Securing cooperative vehicular networks amid obstructing vehicles and mixed fading channels

Smart cities (SCs) were founded on the basis of the Internet of Vehicles paradigm, aiming to enhance the quality of life. Despite not having a unique composition, the intelligent transportation services (ITS) is a key component in most of the SCs. The ITS integrates the new communication systems along with the traditional transportation systems, forming a universal network of static and vehicular entities communicating over wireless broadcast channels. In addition to its vulnerability to co-channel interference (CCI), eavesdropping, and fading, the vehicle-to-vehicle communication channels could be subjected to shadowed fading. That is due to the probabilistic obstruction by big vehicles. Hence, degrading the signal-to-noise ratio at the receiving vehicle severely. This work evaluates the secrecy performance of a practical cooperative vehicular relaying network in terms of its secrecy outage probability (SOP). Due to the probabilistic existence of a vehicular obstacle, three different communication scenarios are considered and a novel closed-form analytical expression for the SOP is obtained over mixed Nakagami-m fading and Nakagami-N-Gamma shadowed fading channels. The system comprises legitimate source and destination operating in full-duplex mode, thus imposing CCI on both the relay and the passive eavesdropper. The result demonstrate the impacts of the secrecy data rate threshold, the strength of shadowing, the density of the obstructing vehicles, and several parameters on the SOP. High levels of shadowing strength and density of obstructing vehicles significantly degrades the secrecy performance by increasing the SOP. Accordingly, adopting the mixed fading channel model is of great importance for practical network modeling.

Optimizing Cellular Network Binary Rate and Fairness: Examination of a Two-Tier Hybrid Duplex Architecture Employing Full-Duplex and Half-Duplex Modes

Optimizing Cellular Network Binary Rate and Fairness: Examination of a Two-Tier Hybrid Duplex Architecture Employing Full-Duplex and Half-Duplex Modes

Simultaneous Wireless Power and Data Transfer System With Full-Duplex Mode Based on Half-Cycle OFDM

Simultaneous Wireless Power and Data Transfer System With Full-Duplex Mode Based on Half-Cycle OFDM

A multi-user cognitive radio full-duplex channel under imperfect spectrum sensing: Achievable rates and energy efficiency

In this work, the achievable rates and energy efficiency of a multi-user cognitive radio (CR) uplink channel with full-duplex (FD) are studied. For this multi-user CR channel, secondary users can work in FD mode to simultaneously transmit and listen to the channel. We consider a realistic scenario in which both FD operation and spectrum sensing are imperfect. At first, we examine the sensing performance and the rate region through the evaluation of the probability of miss-detection and the probability of false alarm when the primary user (PU) activity is assumed to be non-time-slotted. Due to an imperfect sensing operation, the cognitive radio channel is modeled as a non-Gaussian channel impacted by a Gaussian-mixture (GM) noise plus PU interference. Under this practical assumption, it is not possible to calculate the achievable rates and the rate region directly. Instead, we derive simple approximations of these metrics which can be easily calculated with arbitrarily small errors. In the second part of the paper, we further evaluate the derivatives of these achievable rates at low-power regimes. This calculation helps us evaluate the energy efficiency and obtain the minimum energy per bit Eb/N0min when Gaussian and discrete input signals are used.

Secrecy performance evaluation and enhancement of vehicle-to-vehicle communications in the presence of big vehicles

Despite its significant role in providing and developing reliable and safe intelligent transportation services, the Internet of Vehicles faces several challenges and security threats, such as co-channel interference (CCI), node self-interference (SI), and eavesdropping. This paper investigates the secrecy performance of vehicular networks in terms of their secrecy outage probability (SOP) and average secrecy capacity (ASC) in the presence of an eavesdropper. The legitimate vehicles are assumed to operate in full-duplex mode. Hence, the impacts of CCI and SI are considered for practical modeling and performance evaluation. Moreover, the wireless communications among vehicles are assumed to be either subjected to Nakagami-m fading or Nakagami-N-Gamma shadowed fading due to the existence of a big vehicle and its location. Accordingly, closed-form mathematical expressions are derived for the SOP and the ASC. Furthermore, a power allocation (PA) model is proposed to improve the secrecy performance by maximizing the derived ASC. The numerical results validate the derived expressions by demonstrating the impact of the channel condition, the secrecy data rate threshold, the SI cancellation capability at the legitimate destination, the location of the eavesdropper, the location of the big vehicle, and the strength of shadowing on the SOP and the ASC. Also, it is shown that the proposed PA model can significantly enhance the secrecy performance.

Radio Map-Based Trajectory Design for UAV-Assisted Wireless Energy Transmission Communication Network by Deep Reinforcement Learning

In this paper, we consider a wireless energy-carrying communication network of a UAV. In this communication network, the internet of things (IoT) devices maintain their work via the power supply of batteries. The energy of batteries is slowly consumed over time. The UAV adopts the full-duplex working mode and the flight hover protocol, that is, they can power the target device in the hover position and collect base station data at the same time. Unlike traditional methods, which seek to achieve wireless energy transmission, this paper adopts deep reinforcement learning. On the one hand, the deep reinforcement learning algorithm seeks to solve the dynamic programming problem without a model. The traditional method often requires a prior channel model, to form a formula about variables for convex optimization, while reinforcement learning only requires the interaction between agents and the environment. Then, the strategy is optimized according to the reward function feedback. On the other hand, traditional optimization methods generally solve static programming problems. Since IoT devices constantly collect information from the surrounding physical environment, and their requirements for power supply change dynamically, traditional methods are relatively complex and require huge computational overhead, while deep reinforcement learning performs well in complex problems. The purpose of our work is that with the assistance of the radio map, a UAV can find the best hover position, maximize the energy supplied by the UAV, maximize the data throughput collected, and minimize the energy consumption. The simulation results show that the proposed algorithm can well find the best hovering position of the UAVs and significantly improve the performance of the UAV-assisted wireless energy transmission communication network.

Optimization of Full-Duplex UAV Secure Communication with the Aid of RIS

Recently, unmanned aerial vehicles (UAVs) have gained significant popularity and have been extensively utilized in wireless communications. Due to the susceptibility of wireless channels to eavesdropping, interference and other security attacks, UAV communication security faces serious challenges. Therefore, novel solutions need to be investigated for handling corresponding issues. Note that the UAV with full-duplex (FD) mode can actively improve spectral efficiency, and reconfigurable intelligent surface (RIS) can enable the intelligent control of signal reflection for improving transmission quality. Accordingly, the security of UAV communications may be considerably improved by combining the two techniques mentioned above. In this paper, we investigate the performance of secure communication in urban areas, assisted by a FD UAV and an RIS, where the UAV receives sensitive information from the ground users and sends jamming signals to the ground eavesdroppers. Particularly, we propose an approach to jointly optimize the user scheduling, user transmit power, UAV jamming power, RIS phase shift, and UAV trajectory for maximizing the worst-case secrecy rate. However, the non-convexity of the problem makes it difficult to solve. Combining alternating optimization (AO), slack variable techniques, successive convex approximation (SCA), and semi-definite relaxation (SDR), we propose an effective algorithm to obtain a suboptimal solution. According to the simulation results, in contrast to other benchmark schemes, we show that our proposed algorithm can significantly improve the overall secrecy rate.

Covert Rate Study for Full-Duplex D2D Communications Underlaid Cellular Networks

Device-to-device (D2D) communications underlaid cellular networks have emerged as a promising network architecture to provide extended coverage and high data rate for various Internet of Things (IoT) applications. However, because of the inherent openness and broadcasting nature of wireless communications, such networks face severe risks of data privacy disclosure. This paper investigates the covert communications in such networks for providing enhanced privacy protection. Specifically, this paper explores the critical covert rate performance in a full-duplex D2D communication underlaid cellular network consisting of a base station, a cellular user, a D2D pair with a transmitter and a full-duplex receiver, and a warden, where the D2D receiver can operate over either the full-duplex (FD) mode or the half-duplex (HD) mode. We first derive transmission outage probabilities of cellular and D2D links under the FD and HD modes, respectively. Based on these probabilities, we further provide theoretical modelling for the covert rate under each mode and explore the corresponding covert rate maximization by jointly optimizing the transmit powers of the D2D pair and the cellular user. To improve the covert rate performance, we propose a general mode in which the D2D receiver can flexibly switch between these two modes. Under the general mode, we also investigate the theoretical modelling and maximization problems of covert rate. Finally, we present extensive numerical results to illustrate the covert rate performances under the FD, HD, and general modes.

QoS-Aware User Association and Transmission Scheduling for Millimeter-Wave Train-Ground Communications

With the development of wireless communication, people have put forward higher requirements for train-ground communications in the high-speed railway (HSR) scenarios. With the help of mobile relays (MRs) installed on the roof of the train, the application of Millimeter-Wave (mm-wave) communication which has rich spectrum resources to the train-ground communication system can realize high data rate, so as to meet users’ increasing demand for broad-band multimedia access. Also, full-duplex (FD) technology can theoretically double the spectral efficiency. In this paper, we formulate the user association and transmission scheduling problem in the mm-wave train-ground communication system with MR operating in the FD mode as a nonlinear programming problem. In order to maximize the system throughput and the number of users meeting quality of service (QoS) requirements, we propose an algorithm based on coalition game to solve the challenging NP-hard problem, and also prove the convergence and Nash-stable structure of the proposed algorithm. Extensive simulation results demonstrate that the proposed coalition game based algorithm can effectively improve the system throughput and meet the QoS requirements of as many users as possible, so that the communication system has a certain QoS awareness.

Performance Analysis of Full Duplex Bidirectional Machine Type Communication System Using IRS with Discrete Phase Shifter

In this paper, passive Intelligent Reflecting Surface (IRS) is used to enhance the performance of a Full Duplex (FD) bidirectional Machine Type Communication (MTC) system with two source nodes. Each node is equipped with two antennas to operate in FD mode. In reality, self-interference and discrete phase shifting are two major impairments in FD and IRS-assisted communication, respectively. The self-interference at source nodes operating in FD mode is mitigated by increasing the number of meta-surface elements at the IRS. Bit Error Rate (BER) and outage performances are analyzed with continuous phase shifting and discrete phase shifting in IRS. Closed-form analytical expressions are derived for the outage probability and BER performances of the IRS-assisted bidirectional FD-MTC system with a continuous phase shifter. The outage and BER performances of the IRS-assisted bidirectional MTC system in the FD mode have Signal-to-Noise Ratio (SNR) improvement compared with the IRS-assisted bidirectional MTC system in Half Duplex (HD) mode, as the number of reflecting elements in IRS is doubled in the FD mode. The outage and BER performances are degraded by a discrete phase shifter. Hence, performance degradation of the proposed IRS-assisted bidirectional FD-MTC is examined for 1-bit shifter (0, π), 2-bit shifter (0, π/2, π, 3π/2), and for 3-bit shifter (0, π/4, π/2, 3π/4, π, 5π/4, 3π/2, 7π/4). The performance degradation when a discrete phase shifter is employed in IRS is compared with the ideal continuous phase shifter in IRS. Further, achievable rate analysis is carried out for finding the best location of the IRS in a bidirectional FD-MTC system.