Search Results (147)

Jamming introduces unintentional disruptions in the system to exploit the legitimate communicating equipment. Clustered jamming considers jammers that are present in multiple groups to disrupt the intended communication. Vehicle-to-everything (V2X) transmissions are critical for smart transportation. This research considers full-duplex environment, featuring unmanned aerial vehicles (UAVs) and cellular-base-station-aided V2X (C-V2X) systems exploiting clustered jamming using 3-dimensional (3-D) beam-forming millimeter-wave antennas. UAVs are modeled as a 3-D Poisson point process (PPP), and macro-based tower-mounted base-stations (MBSs) are modeled as a 2-D PPP. Roads are modeled as a Poisson line process. The vehicular nodes (V-Ns) are modeled on each road as a 1-D PPP. The deviations of the UAV’s millimeter-wave band antenna beam follow a Normal distribution. In this paper, for a full-duplex setting, the probabilities of coverage and equipment-association, along with the efficiency of the spectrum associated with various UAV and tower-based connections, are explored in the presence of clustered jamming. The probability of coverage and association of multiple links is derived with respect to the jamming clusters, V-Ns, MBSs, UAVs, jammers’ power, and antenna beams. The results demonstrated that jamming degrades system’s efficiency. This efficiency is further degraded whenever higher 3-D beam-width deviations of the millimeter waveband antenna and jammers are present. Therefore, robust counter-scenarios should be designed for the cases where jamming signals and varying beams disrupt the network. Full article

In-band full-duplex (FD) technology has emerged as a promising solution to the growing demand for higher spectrum efficiency. By enabling simultaneous transmission and reception at the same frequency, FD-based integrated sensing and communication (ISAC) architectures offer potential advantages in capacity, latency, and spectral efficiency. However, non-ideal hardware in transceivers introduces nonlinear self-interference (SI), which limits the practical deployment of FD systems. Conventional polynomial models are widely used to characterize nonlinear SI, but their computational complexity grows quadratically with the nonlinear order. To address these challenges, a complex-valued temporal convolutional network (CV-TCN) with wavelet activation function is proposed for nonlinear SI modeling in this paper. The CV-TCN canceller achieves stronger nonlinear SI cancellation (SIC) performance with lower inference complexity. Simulation results demonstrate that the proposed model surpasses traditional polynomial-based and other cancellers in nonlinear SIC performance with higher parameter efficiency. Moreover, the CV-TCN canceller suppresses the residual SI power by around 7.95 dB after linear SIC, leaving the residual SI 2.23 dB above the noise floor. Full article

Secure vehicle-to-vehicle communication is essential for electric-vehicle platoons because broadcast wireless links may expose safety and control messages to passive eavesdropping. This paper investigates a physical-layer security (PLS) framework for electric-vehicle (EV) platoons under Rician fading, representing the line-of-sight conditions common in highway platooning. The proposed Jamming-Aided Cooperative Relay Selection (JACRS) framework uses an amplify-and-forward relay, destination-assisted full-duplex friendly jamming, residual self-interference modelling, and a strict total transmit power budget. Relay selection is evaluated using a full-channel state information (CSI) secrecy-selection benchmark, a practical legitimate-link CSI rule, and a deterministic platoon-geometry-aware rule based on Cooperative Adaptive Cruise Control (CACC) position information without instantaneous eavesdropper CSI. Monte Carlo simulations, supported by semi-analytical secrecy-outage and deterministic-slot benchmarks, compare the proposed scheme with Rayleigh and no-jamming amplify-and-forward (AF) baselines. Under the simulated geometry, the scheme achieves a peak ergodic secrecy rate close to 5.0 bps/Hz at 40 dBm and reduces interception risk by 78.07% relative to the Rayleigh baseline. Relay diversity reduces secrecy outage from 14.14% to 0.04% under full CSI and to 0.22% using legitimate-link CSI. The geometry-aware rule reduces the gap between practical legitimate-link selection and the full-CSI benchmark, indicating that platoon position information can improve relay selection under the tested conditions. Full article

Full-duplex acoustic telemetry is important for real-time bidirectional measurement and control in intelligent coiled-tubing operations, but its reliability in deep horizontal wells is limited by long-range dispersion, asymmetric flow-induced noise, and severe near-end self-interference. This study proposes an orthogonal frequency-band planning and synergistic interference suppression method for full-duplex acoustic communication in coiled tubing. A dispersion model and an asymmetric attenuation model were first established for a fluid-filled coiled-tubing cylindrical-shell waveguide to characterize the physical transmission constraints. A multiphysics multi-objective cost function was then formulated by considering dispersion flatness, channel attenuation, asymmetric noise adaptability, and spectral isolation, and an improved simulated annealing algorithm was used to optimize the uplink and downlink frequency bands. In addition, a three-stage suppression architecture integrating mechanical decoupling, physical-layer frequency isolation, and CEEMDAN–wavelet denoising was developed to reduce self-interference and residual nonstationary noise. Full-scale experiments on a 457.2 m coiled-tubing surface circulation system showed that the proposed method improved the output signal-to-interference-plus-noise ratio from −15 dB to 18.5 dB and maintained a bit error rate below 1.2 × 10⁻⁴ at 400 L/min. These results indicate that the proposed approach can enhance the robustness of full-duplex acoustic telemetry under strong flow-induced noise. Full article

To address the limited communication capacity of the traditional time-division half-duplex (TDHD) systems in BDS-3 inter-satellite links (ISLs), this paper proposes a cooperative design of ranging and communication based on an in-band full-duplex (IBFD) architecture. By utilizing BDS broadcast ephemeris to assist signal acquisition and selecting the serial acquisition strategy with the lowest computational complexity, a 100% acquisition success rate can be achieved within milliseconds. This completely releases the 250 ms preamble originally used for acquisition in the traditional time slot. Adopting the IBFD system, the ISL time-slot structure is optimally redesigned: the preamble is used for signal acquisition and tracking to accomplish inter-satellite ranging, while the original measurement period is used for QPSK dual-channel parallel data transmission. This design extends the effective communication duration from 1 s to 2.5 s, expands the communication from single-channel to dual-channel, and theoretically achieves a 5-fold improvement in communication efficiency. Simulation analysis shows that, while the communication efficiency is significantly improved, the ranging accuracy remains essentially unchanged compared with the traditional TDHD system. Without altering the existing 3 s time-slot duration, this method achieves cooperative optimization of ranging and communication, providing a feasible technical solution for enhancing the communication capacity of BDS-3 ISLs. Full article

Full-duplex (FD) technology holds great promise for enhancing the spectral efficiency of Mobile Ad Hoc Networks (MANETs) and Wireless Sensor Networks (WSNs). However, the practical performance gain of FD over Half-Duplex (HD) is highly sensitive to the dynamic nature of traffic loads and residual self-interference. Existing Optimal Dynamic Selection Strategies (ODSS) often rely on static workload assumptions within a single time window, failing to capture long-term traffic fluctuations. Consequently, applying instantaneous switching strategies in highly bursty environments necessitates excessively frequent mode switching (e.g., the switching frequency can approach the total number of time windows), incurring prohibitive signaling overhead and unignorable MAC-layer adaptation delays. To overcome these concrete bottlenecks, this paper proposes a comprehensive traffic-aware adaptive duplex mode selection framework. First, we model the multi-scale dynamic workload using Dynamic Activated Probability in Short-term (DAPS) and Long-term (DAPL), effectively characterizing both bursty traffic (via Beta distribution) and Markov-modulated stable traffic. Second, by integrating physical layer performance analysis, we define the Break-even Workload Point (BWP) to partition traffic into Oversaturated (OZ) and Unsaturated (UZ) Workload Zones (WZs). Furthermore, to handle unknown future traffic with low complexity, we propose the Pre-scheduling Duplex selection based on the Workload zone Estimation (PDWE) algorithm. PDWE leverages a Hidden Markov Model (HMM) combined with a Rollout algorithm to estimate hidden traffic states and adaptively pre-schedule duplex modes. Simulation results demonstrate that the proposed strategy achieves near-optimal throughput (approximately 91% of the ideal ODSS) while reducing the duplex switching frequency by two orders of magnitude compared to instantaneous switching strategies. This approach offers a robust cross-layer solution for next-generation self-organizing networks. Full article

The integration of terrestrial and aerial components in future wireless networks is a key enabler for achieving wide-area coverage and providing ubiquitous services. In this context, and with the goal of enhancing spectral efficiency through opportunistic spectrum reuse, this paper investigates a cooperative spectrum sensing approach in which cognitive UAVs equipped with full-duplex (FD) MIMO technology operate as aerial base stations (ABS). Each UAV performs local detection using the sphericity test, then a push–sum consensus protocol is employed to fuse local test statistics without relying on a fusion center. Unlike conventional unweighted consensus or centralized hard-decision fusion, the proposed approach accounts for the heterogeneity introduced by residual self-interference in FD transceivers. Specifically, multipath in the self-interference channel induces temporal correlation, increasing the variance of the local test statistic and, consequently, the false-alarm probability. To mitigate this effect, we design variance-aware consensus weights proportional to the inverse of the sphericity test variance enhancing robustness to RSI-induced variability. Numerical results demonstrate that the proposed scheme outperforms both unweighted consensus and centralized OR-rule fusion in user capacity, while maintaining negligible communication overhead. Moreover, the operational altitude of the UAVs is evaluated to balance the coverage provided to users and the primary signal detection capability. Full article

This paper investigates the application of Reconfigurable Intelligent Surfaces (RIS) in Joint Communication, Sensing, and Multi-tier Computing (JCSMC). An RIS-assisted JCSMC framework is proposed, wherein a full-duplex multi-antenna Base Station (BS) is employed to sense targets and provide edge computation services to User Equipment (UE). To enhance computational efficiency, a Multi-Tier Computing (MTC) architecture is adopted, enabling joint processing of computing tasks through the deployment of both the BS and the Cloud Servers (CS). Meanwhile, this paper studies the potential advantages of RIS in the proposed framework. It can assist in enhancing the efficiency of resource sharing between sensing and computing functions and then maximize the ability of computing the offload. This study aims to maximize the computation rate by jointly optimizing the BS transmission beamformer, RIS reflection coefficients, and computational resource allocation. The ensuing non-convex optimization problems are addressed using an alternating optimization algorithm based on Block Coordinate Ascent (BCA) for partial offloading mode, which ensures convergence to a local optimum, then extending the proposed joint design algorithms to the scenario with imperfect Self-Interference Cancellation. The effectiveness of the proposed algorithm was confirmed by analyzing and contrasting the simulation results with the benchmark scheme. The simulation results show that, when the BS resources are limited, utilizing MTC architecture can significantly improve the computation rate. In addition, the proposed RIS-assisted JSCMC framework is superior to other benchmark schemes in dealing with resource utilization between different functions, achieving superior computing power while maintaining sensing quality. Full article

Time-division duplex (TDD) transceivers have found broad utility in millimeter-wave 5G communication, radar and imaging applications. The co-design of the switch and transmit/receive (T/R) amplifiers becomes essential in optimizing the passive loss and chip size. This work presents a Ka-band T/R amplifier with an embedded switch topology. The amplification cores from the TX and RX channels reuse the matching network to the T/R common port, and the full combination of switching and matching structures is enabled within a compact two-winding transformer. Implemented in 40 nm CMOS technology, the proof-of-concept Ka-band T/R amplifier occupies a core chip area of 0.163 mm². Experimental results show that it achieves a peak gain of 17.2 dB with a −3 dB bandwidth of 22.6–30.2 GHz in TX mode and a peak of 17.1 dB with a −3 dB bandwidth of 23.4–31.0 GHz in RX mode. The compact size and wideband gain response make the proposed T/R amplifier suitable for Ka-band TDD applications. Full article

In-band full-duplex (IBFD) communication systems offer a promising means of improving spectral efficiency by enabling simultaneous transmission and reception on the same frequency channel. Despite this advantage, self-interference (SI) remains a major challenge to their practical deployment. Among the different SI cancellation (SIC) techniques, this paper focuses on digital SIC methodologies tailored for multiple-input multiple-output (MIMO) wireless transceivers operating under digital beamforming architectures. Two distinct digital SIC approaches are evaluated, employing a generalized memory polynomial (GMP) model augmented with Itô–Hermite polynomial basis functions and a phase-normalized neural network (PNN) to effectively model the nonlinearities and memory effects introduced by transmitter and receiver hardware impairments. The robustness of the SIC is further evaluated under both single off-line training and closed-loop real-time adaptation, employing estimation techniques such as least squares (LS), least mean squares (LMS), and fast Kalman (FK) for model coefficient estimation. The performance of the proposed digital SIC techniques is evaluated through detailed simulations that incorporate realistic power amplifier (PA) characteristics, channel conditions, and high-order modulation schemes. Metrics such as error vector magnitude (EVM) and total bit error rate (BER) are used to assess the quality of the received signal after SIC under different signal-to-interference ratio (SIR) and signal-to-noise ratio (SNR) conditions. The results show that, for time-variant scenarios, a low-complexity adaptive SIC can be realized using a GMP model with FK parameter estimation. However, in time-invariant scenarios, an open-loop SIC approach based on PNN offers superior performance and maintains robustness across various modulation schemes. Full article

Unmanned aerial vehicles (UAVs) are a promising technology for future sixth-generation (6G) wireless networks. They are airborne vehicles that act either as as flying relays or base stations (BS) to provide the line-of-sight (LOS) transmission, enable wide-area coverage, and increase the spectral efficiency. In this work, a UAV is employed to forward information from the BS to distant users using a decode-and-forward (DF) protocol. The BS serves ground users through UAV by employing non-orthogonal multiple access (NOMA). The UAV relay will be wirelessly powered and harvests energy from the BS by applying a simultaneous wireless information and power transfer (SWIPT) technique. To further improve overall performance, the near user will act as a full-duplex (FD) relay to forward the far user’s information by applying cooperative non-orthogonal multiple access (C-NOMA). The proposed scheme considers a practical detection order using a feasible successive interference cancellation (SIC) operation. Additionally, a relay power control method is introduced for the near user to guarantee a reliable cooperative link. In the proposed scheme, a low-complexity closed-form power allocation is derived to maximize the minimum achievable rate. Numerical results demonstrate that the power allocation scheme significantly improves the far user’s rate performance, and the proposed scheme guarantees a higher target rate and outperforms the conventional NOMA, half-duplex (HD) C-NOMA, and FD C-NOMA with fixed power allocation (FPA) and fractional transmit power allocation (FTPA) schemes. Full article

Pre-embedded sensors for concrete structure monitoring face bottlenecks in power supply and data transmission. Existing power supply solutions such as photovoltaic systems and batteries suffer from drawbacks including energy randomness and structural damage to concrete caused by their installation methods. Additionally, commercial wireless communication signals exhibit issues like strong attenuation and poor security during propagation. This paper proposes a hybrid electromagnetic field decoupled parallel transmission technology for power and signals. It utilizes the inherent decoupling characteristic of electric and magnetic fields within the near-field range to construct independent power/signal transfer channels, and achieves independent full-duplex transmission of uplink/downlink data via orthogonal coupling plates. Mathematical models for the power and signal channels are established, and finite element simulations are conducted. A parameter design method for the power compensation network and signal filtering circuit is also proposed. An experimental setup is built, with a coupler outer dimension of 200 mm × 200 mm, a coupling distance of 10 mm, and a thickness of 16 mm for both the transmitting and receiving sides. Experimental results show that the system achieves power transmission with a power of 100 W and an efficiency of 82%, while simultaneously realizing full-duplex communication with a bidirectional rate of 9600 bit/s. Moreover, no bit errors occur within 300,000 characters of bidirectional data. Full article

This paper studies joint data collection and wireless power transfer in a UAV-assisted IoT network. A rotary-wing UAV follows a fly–hover–communicate cycle. At each hover, it simultaneously receives uplink data in full-duplex mode while delivering radio-frequency energy to nearby devices. Using a realistic propulsion-power model and a nonlinear energy-harvesting model, we formulate trajectory and hover control as a multi-objective optimization problem that maximizes the aggregate data rate and total harvested energy while minimizing the UAV’s energy consumption over the mission. To enable flexible trade-offs among these objectives under time-varying conditions, we propose a dynamic, state-adaptive weighting mechanism that generates environment-conditioned weights online, which is integrated into an enhanced deep deterministic policy gradient (DDPG) framework. The resulting dynamic-weight MODDPG (DW-MODDPG) policy adaptively adjusts the UAV’s trajectory and hover strategy in response to real-time variations in data demand and energy status. Simulation results demonstrate that DW-MODDPG achieves superior overall performance and a more favorable balance among the three objectives. Compared with the fixed-weight baseline, our algorithm increases total harvested energy by up to 13.8% and the sum data rate by up to 5.4% while maintaining comparable or even lower UAV energy consumption. Full article

The continuous evolution of advanced wireless IoT systems necessitates novel network protocols capable of enhancing resource efficiency and performance to support increasingly demanding applications. Full-duplex (FD) communication emerges as a key advanced wireless technology to address these needs by doubling spectral efficiency. However, unlocking this potential is non-trivial, as it introduces complex interference scenarios and requires sophisticated management of heterogeneous Quality of Service (QoS) demands, presenting a significant challenge for existing MAC protocols. To overcome these limitations through protocol optimization, this paper proposes IDA-FDMAC, a novel MAC architecture tailored for FD-enabled IoT networks. At its core, IDA-FDMAC employs a dynamic priority scheduling mechanism that concurrently manages interference and provisions for diverse QoS requirements. A comprehensive theoretical model is developed and validated through extensive simulations, demonstrating that our proposed architecture significantly boosts system throughput and ensures QoS guarantees. This work thus contributes a robust, high-performance solution aligned with the development of next-generation wireless IoT systems. Full article

To meet the dual demands of 6G cellular networks for high spectral efficiency and environmental sensing, this paper proposes a full-duplex (FD) integrated sensing and communication (ISAC) dynamic resource allocation framework. At the heart of the framework lies a dynamic frame structure that can self-adapt the time-domain resource ratio between sensing and communication, designed to flexibly handle complex traffic demands. In FD mode, however, the trade-off between communication and sensing performance, exacerbated by severe self-interference (SI), morphs into a non-convex, NP-hard multi-objective optimization problem (MOP). To tackle this, we propose an Adaptive Hybrid Memetic Multi-Objective Grey Wolf Optimizer (AM-MOGWO). Finally, simulations were conducted on a high-fidelity platform that integrates 3GPP-standardized channels, which was further extended to a challenging multi-cell interference scenario to validate the algorithm’s robustness. AM-MOGWO was systematically benchmarked against standard Grey Wolf Optimizer (GWO), random search (RS), and the genetic algorithm (GA). Simulation results demonstrate that in both the single-cell and the more complex multi-cell environments, the proposed algorithm excels in locating the Pareto-optimal solution set, where its solution set significantly outperforms the baseline methods. Its hypervolume (HV) metric surpasses the second-best approach by more than 93%. This result quantitatively demonstrates the algorithm’s superiority in finding a high-quality set of trade-off solutions, confirming the framework’s high efficiency in complex interference environments. Full article