Bypassing a Reactive Jammer via NOMA-Based Transmissions in Critical Missions
- URL: http://arxiv.org/abs/2401.10387v2
- Date: Wed, 24 Jan 2024 17:17:36 GMT
- Title: Bypassing a Reactive Jammer via NOMA-Based Transmissions in Critical Missions
- Abstract summary: Wireless networks can be vulnerable to radio jamming attacks.
This paper analyzes the effect of a reactive jammer on reliability, average transmission delay, and the effective sum rate (ESR)
It is shown that by adjusting the allocated transmit power to UEs by gNB, the gNB can bypass the jammer effect to fulfill the 0.99999 reliability and the latency of 5ms without the need for packet re-transmission.
- Score: 13.784352398504343
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Wireless networks can be vulnerable to radio jamming attacks. The quality of service under a jamming attack is not guaranteed and the service requirements such as reliability, latency, and effective rate, specifically in mission-critical military applications, can be deeply affected by the jammer's actions. This paper analyzes the effect of a reactive jammer. Particularly, reliability, average transmission delay, and the effective sum rate (ESR) for a NOMA-based scheme with finite blocklength transmissions are mathematically derived taking the detection probability of the jammer into account. Furthermore, the effect of UEs' allocated power and blocklength on the network metrics is explored. Contrary to the existing literature, results show that gNB can mitigate the impact of reactive jamming by decreasing transmit power, making the transmissions covert at the jammer side. Finally, an optimization problem is formulated to maximize the ESR under reliability, delay, and transmit power constraints. It is shown that by adjusting the allocated transmit power to UEs by gNB, the gNB can bypass the jammer effect to fulfill the 0.99999 reliability and the latency of 5ms without the need for packet re-transmission.
Related papers
- AmbSentry: Mitigating Sensing Eavesdropping in ISAC Systems by Harnessing Ambient IoT Devices [60.083979780396014]
Integrated sensing and communication (ISAC) has emerged as a pivotal paradigm for 6G networks.<n>This paper proposes AmbSentry, an ISAC system that prevents the leakage of sensing information to sensing eavesdroppers.
arXiv Detail & Related papers (2026-08-12T08:42:05Z) - Blockchain-Enabled Routing for Zero-Trust Low-Altitude Intelligent Networks [77.17664010626726]
We focus on the routing with multiple UAV clusters in low-altitude intelligent networks (LAINs)<n>To minimize the damage caused by potential threats, we present the zero-trust architecture with the software-defined perimeter and blockchain techniques.<n>We show that the proposed framework reduces the average E2E delay by 59% and improves the TSR by 29% on average compared to benchmarks.
arXiv Detail & Related papers (2026-02-27T04:30:35Z) - Uncertainty-Aware Jamming Mitigation with Active RIS: A Robust Stackelberg Game Approach [65.06640919319413]
This paper investigates the jamming mitigation by leveraging an active reconfigurable intelligent surface (ARIS)<n>We adopt the Stackelberg game formulation to model the strategic interaction between the legitimate side and the adversary.<n>We first derive the optimal jamming policy as the follower's best response, which is then incorporated into the legitimate-side optimization for robust anti-jamming design.
arXiv Detail & Related papers (2026-02-20T12:02:01Z) - Multi-Agent-Driven Cognitive Secure Communications in Satellite-Terrestrial Networks [58.70163955407538]
Malicious eavesdroppers pose a serious threat to private information via satellite-terrestrial networks (STNs)<n>We propose a cognitive secure communication framework driven by multiple agents that coordinates spectrum scheduling and protection through real-time sensing.<n>We exploit generative adversarial networks to produce adversarial matrices, and employ learning-aided power control to set real and adversarial signal powers for protection layer.
arXiv Detail & Related papers (2026-01-06T10:30:41Z) - PASS-Enhanced MEC: Joint Optimization of Task Offloading and Uplink PASS Beamforming [67.78883135636657]
pinching-antenna system (PASS)-enhanced mobile edge computing (MEC) architecture is investigated.<n>PASS establishes short-distance line-of-sight (LoS) links while effectively mitigating the significant path loss and potential signal blockage.<n>We formulate a network latency minimization problem to joint optimize uplink PASS beamforming and task offloading.
arXiv Detail & Related papers (2025-10-27T03:04:46Z) - Quantum Skyshield: Quantum Key Distribution and Post-Quantum Authentication for Low-Altitude Wireless Networks in Adverse Skies [36.14072181405793]
Low-altitude wireless networks (LAWNs) have emerged as a critical backbone for supporting the low-altitude economy.<n>To meet growing data demands, some LAWN deployments incorporate free-space optical (FSO) links, which offer exceptional bandwidth and beam directivity.<n>Quantum Skyshield is proposed to enable reliable communication between the base transceiver station (BTS) and LAWN.
arXiv Detail & Related papers (2025-07-20T04:43:33Z) - Distributionally Robust Wireless Semantic Communication with Large AI Models [120.29419104482793]
6G wireless systems are expected to support massive volumes of data with ultra-low latency.<n> conventional bit-level transmission strategies cannot support the efficiency and adaptability required by modern, data-intensive applications.<n>The concept of semantic communication (SemCom) addresses this limitation by focusing on transmitting task-relevant semantic information instead of raw data.
arXiv Detail & Related papers (2025-05-28T04:03:57Z) - Efficient and Trustworthy Block Propagation for Blockchain-enabled Mobile Embodied AI Networks: A Graph Resfusion Approach [60.80257080226662]
We propose a graph Resfusion model-based trustworthy block propagation optimization framework for consortium blockchain-enabled MEANETs.
Specifically, we propose an innovative trust calculation mechanism based on the trust cloud model.
By leveraging the strengths of graph neural networks and diffusion models, we develop a graph Resfusion model to effectively and adaptively generate the optimal block propagation trajectory.
arXiv Detail & Related papers (2025-01-26T07:47:05Z) - Active RIS-Assisted URLLC NOMA-Based 5G Network with FBL under Jamming Attacks [5.715528540446773]
We tackle the challenge of jamming attacks in Ultra-Reliable Low Communication (URLLC) networks under Finite Blocklength (FBL) conditions.
We introduce an innovative approach that employs ReReliable Intelligent Surfaces (RIS) with active elements to enhance energy efficiency.
Our results indicate that increasing the number of RIS elements from 4 to 400 can improve signal-to-jamming-plus-noise ratio (SJNR) by 13.64%.
arXiv Detail & Related papers (2025-01-22T21:31:21Z) - Voltage Profile-Driven Physical Layer Authentication for RIS-aided Backscattering Tag-to-Tag Networks [14.41899731953023]
Backscattering tag-to-tag networks (BTTNs) are emerging passive radio frequency identification (RFID) systems.
BTTNs face significant security vulnerabilities, which remain their primary concern to enable reliable communication.
This paper proposes a physical layer authentication (PLA) scheme, where a Talker tag (TT) and a Listener tag (LT) can authenticate each other in the presence of an adversary.
arXiv Detail & Related papers (2025-01-20T11:07:34Z) - Communication-Efficient Federated Learning by Quantized Variance Reduction for Heterogeneous Wireless Edge Networks [55.467288506826755]
Federated learning (FL) has been recognized as a viable solution for local-privacy-aware collaborative model training in wireless edge networks.
Most existing communication-efficient FL algorithms fail to reduce the significant inter-device variance.
We propose a novel communication-efficient FL algorithm, named FedQVR, which relies on a sophisticated variance-reduced scheme.
arXiv Detail & Related papers (2025-01-20T04:26:21Z) - The impact of mobility, beam sweeping and smart jammers on security vulnerabilities of 5G cells [13.784352398504343]
The vulnerability of 5G networks to jamming attacks has emerged as a significant concern.
This paper investigates the effect of a multi-jammer on 5G cell metrics, specifically throughput and goodput.
arXiv Detail & Related papers (2024-11-07T19:45:15Z) - Conformal Distributed Remote Inference in Sensor Networks Under Reliability and Communication Constraints [61.62410595953275]
Communication-constrained distributed conformal risk control (CD-CRC)
CD-CRC is a novel decision-making framework for sensor networks under communication constraints.
arXiv Detail & Related papers (2024-09-12T10:12:43Z) - On the Potential of Re-configurable Intelligent Surface (RIS)-assisted Physical Layer Authentication (PLA) [0.0]
Re-configurable Intelligent Surfaces (RIS) technology is increasingly becoming a potential component for next-generation wireless networks.
However, the broadcast nature of RIS-assisted wireless communication makes it vulnerable to malicious attacks at the physical layer.
This paper investigates RIS-assisted wireless communication systems to unlock the potential of using RIS for physical layer authentication (PLA)
arXiv Detail & Related papers (2024-05-01T10:17:24Z) - Multiagent Reinforcement Learning with an Attention Mechanism for
Improving Energy Efficiency in LoRa Networks [52.96907334080273]
As the network scale increases, the energy efficiency of LoRa networks decreases sharply due to severe packet collisions.
We propose a transmission parameter allocation algorithm based on multiagent reinforcement learning (MALoRa)
Simulation results demonstrate that MALoRa significantly improves the system EE compared with baseline algorithms.
arXiv Detail & Related papers (2023-09-16T11:37:23Z) - Enhancing Reliability in Federated mmWave Networks: A Practical and
Scalable Solution using Radar-Aided Dynamic Blockage Recognition [14.18507067281377]
This article introduces a new method to improve the dependability of millimeter-wave (mmWave) and terahertz (THz) network services in dynamic outdoor environments.
In these settings, line-of-sight (LoS) connections are easily interrupted by moving obstacles like humans and vehicles.
The proposed approach, coined as Radar-aided blockage Dynamic Recognition (RaDaR), leverages radar measurements and federated learning (FL) to train a dual-output neural network (NN) model.
arXiv Detail & Related papers (2023-06-22T10:10:25Z) - Performance Limits of a Deep Learning-Enabled Text Semantic
Communication under Interference [89.91583691993071]
We study the performance limits of a popular text SemCom system named DeepSC in the presence of (multi-interferer) RFI.
We show that DeepSC produces semantically irrelevant sentences as the power of (multi-interferer) RFI gets very large.
We also derive DeepSC's practical limits and a lower bound on its outage probability under multi-interferer RFI.
arXiv Detail & Related papers (2023-02-15T05:43:08Z) - Over-the-Air Federated Learning with Privacy Protection via Correlated
Additive Perturbations [57.20885629270732]
We consider privacy aspects of wireless federated learning with Over-the-Air (OtA) transmission of gradient updates from multiple users/agents to an edge server.
Traditional perturbation-based methods provide privacy protection while sacrificing the training accuracy.
In this work, we aim at minimizing privacy leakage to the adversary and the degradation of model accuracy at the edge server.
arXiv Detail & Related papers (2022-10-05T13:13:35Z) - Covert Communications via Adversarial Machine Learning and
Reconfigurable Intelligent Surfaces [46.34482158291128]
The reconfigurable intelligent surfaces (RISs) rely on arrays of unit cells to control the scattering and reflection profiles of signals.
In this paper, covert communication is considered in the presence of the RIS.
arXiv Detail & Related papers (2021-12-21T18:23:57Z) - Quantized Federated Learning under Transmission Delay and Outage
Constraints [30.892724364965005]
Federated learning is a viable distributed learning paradigm which trains a machine learning model collaboratively with massive mobile devices in the wireless edge.
In practical systems with limited radio resources, transmission of a large number of model parameters inevitably suffers from quantization errors (QE) and transmission outage (TO)
We propose a robust FL scheme, named FedTOE, which performs joint allocation of wireless resources and quantization bits across the clients to minimize the QE while making the clients have the same TO probability.
arXiv Detail & Related papers (2021-06-17T11:29:12Z) - Interference Distribution Prediction for Link Adaptation in
Ultra-Reliable Low-Latency Communications [71.0558149440701]
Link adaptation (LA) is considered to be one of the bottlenecks to realize URLLC.
In this paper, we focus on predicting the signal to interference plus noise ratio at the user to enhance the LA.
We show that exploiting time correlation of the interference is an important enabler of URLLC.
arXiv Detail & Related papers (2020-07-01T07:59:35Z) - Reinforcement Learning for Mitigating Intermittent Interference in
Terahertz Communication Networks [4.999585439793266]
Uncoordinated transmissions by a large number of users can cause substantial interference in terahertz networks.
New framework based on reinforcement learning is proposed that uses an adaptive multi-thresholding strategy.
arXiv Detail & Related papers (2020-03-10T16:28:45Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.