Tactical Wireless Networks Research Articles

Federated Learning-Enabled Jamming Detection and Waveform Classification for Distributed Tactical Wireless Networks

In this paper, we propose a federated learning (FL)-based jammer detection and waveform classification algorithm for distributed tactical wireless networks (TWNs). More specifically, we consider a distributed TWN with multiple clusters and various types of waveforms used in the presence of a mobile jammer. We analyze the frequency domain of the waveforms received on local servers to extract the unique cyclic frequency from each waveform’s spectral correlation function (SCF). The method is used to detect the peak values in the frequency-cyclic frequency plane. The primary signal’s SCF exhibits peaks at the unique cyclic frequency and the zero cyclic frequency. These features are then used to train local convolutional neural networks (CNNs) to detect the jamming attacks and classify the waveforms. Moreover, a practical distributed TWN is considered in which each cluster head has a partial observation of the TWN with insufficient data samples, and the proposed algorithm exploits the distributed learning feature of FL, i.e., global learning aggregation to detect the existence of jammers and distinguish the types of waveforms received throughout the TWN. We implement a rigorous TWN simulation using MATLAB toolboxes and our proposed algorithm in TensorFlow Federated. The numerical results show that our proposed algorithm outperforms the standalone local SCF-CNN algorithm. We further demonstrate that the SCF feature yields more accuracy than the In-phase and Quadrature features.

Defense and Offence Strategies for Tactical Wireless Networks Using Recurrent Neural Networks

Network forces attempt to dominate the spectrum in tactical wireless networks while preventing their opponents from holding any communication. In this context, both the defensive and the offensive capabilities of a network force are critical. Therefore, in this paper, we study the communication competition between two network forces, denoted as blue force (BF) and red force (RF), where each force is equipped with a transmitter, a receiver, and a friendly jammer. We propose defense and offense strategies for the BF using recurrent neural networks (RNN)s where the occupied channels by the RF nodes in the future time slots are predicted. Then the entity of each occupied channel in terms of RF users and jammer is identified. As a result, the BF transmitter finds unoccupied channels, and the BF jammer jams the RF transmitter's channels. The performance of the proposed method is evaluated by calculating both the ergodic rate (ER) of the BF receiver and RF receiver as well as the prediction accuracy of RF future channels. Simulation results show that the BF receiver attains ER of at least <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$90\%$</tex-math></inline-formula> of the maximum achievable ER and a detection accuracy higher than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$85\%$</tex-math></inline-formula> for all the considered scenarios. Furthermore, the BF jammer can target the RF transmitter frequency channels and can reduce the RF receiver ER to less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10\%$</tex-math></inline-formula> of its maximum achievable value.

A Blockchain System for TDMA-Based Tactical Wireless Networks With Constrained Resources

This paper proposes a blockchain system with a consensus algorithm and timeslot allocation policy for TDMA-based tactical wireless networks with constrained resources. A blockchain can serve as a distributed database that ensures all nodes can store the same data even in unreliable network environments. Blockchain technology has numerous benefits, such as decentralization, tamper resistance, traceability, and audibility. Due to these characteristics, the application range of blockchains has dramatically expanded from cryptocurrency, financial services, risk management, and IoT to various services in both public and non-public domains. In addition, there has been an increasing demand for using blockchain technology in wireless network environments. Unlike wired networks, communication resources in wireless networks for data transmission and reception are relatively limited; as such, it is necessary to design a consensus algorithm with low resource consumption and an efficient resource allocation policy for these environments. The proposed system allocates timeslots to nodes based on their contribution to blockchain management, which prevents nodes from participating in an unnecessary competition for block generation, thereby preventing the associated waste of energy. We could verify the proposed system’s practicality through numerical analysis and computer simulations under various conditions.

Joint power and hopping rate adaption against follower jammer based on deep reinforcement learning

AbstractAs an effective anti‐jamming approach, frequency‐hopping (FH) technology has been widely applied to tactical communication system, providing reliable communication guarantee and improving resilience against conventional interference under strong confrontation environment. Key challenges for tactical wireless communication network face are the smart follower jammer with responsive spectrum reconnaissance and intelligent decision‐making capabilities. In response, this article investigates a deep reinforcement learning based anti‐jamming scheme, with the aim of maximizing the system throughput. The interactions between a radio transmitter and a smart follower jammer are formulated as a hierarchical anti‐jamming dynamic game model, in which the radio terminal decides transmission power and hopping rate according to the state feedback information, and the jammer chooses spectrum scanning rate accordingly to minimizing the rewards of the FH communication system. We prove that there is a Nash equilibrium (NE) strategy for static and dynamic environment in the game. A double deep Q‐network with prioritized experience reply (PDDQN) based anti‐jamming scheme is proposed to approximating the optimal power control and hopping strategy without being aware of the environment and jamming parameters. Finally, simulation results demonstrate that the proposed algorithm efficiently provide better throughput and jamming resistance.

Unmanned Agricultural Tractors in Private Mobile Networks

The need for high-quality communications networks is urgent in data-based farming. A particular challenge is how to achieve reliable, cost-efficient, secure, and broadband last-mile data transfer to enable agricultural machine control. The trialed ad hoc private communications networks built and interconnected with different alternative wireless technologies, including 4G, 5G, satellite and tactical networks, provide interesting practical solutions for connectivity. A remotely controlled tractor is exemplified as a use case of machine control in the demonstrated private communication network. This paper describes the results of a comparative technology analysis and a field trial in a realistic environment. The study includes the practical implementation of video monitoring and the optimization of the control channel for remote-controlled unmanned agricultural tractors. The findings from this study verify and consolidate the requirements for network technologies and for cybersecurity enablers. They highlight insights into the suitability of different wireless technologies for smart farming and tractor scenarios and identify potential paths for future research.

Delay aware downlink resource allocation scheme for future generation tactical wireless networks

&lt;span lang="EN-US"&gt;For a very long time protecting physical border integrity is considered to be a challenging thing. Government organizations must provide trade operations for economic growth and at the same time must prevent malicious activity. A different resource such as drones, sensors, and radars are used for monitoring border areas which must be communicated to the remote border security force. Efficient wireless communication is required for communicating information. However, these devices cannot connect to a centralized network directly; thus, are connected in an ad-hoc fashion to connect centralized server. Different tactical network applications require different quality of service (QoS); hus efficient resource scheduling plays a very important role. Existing resource scheduling adopting deep learning and reinforcement techniques fails to meet the quality of experience (QoE) of the user and doesn’t assure access fairness among contending users. Further, require network information in prior and induce high training time. For overcoming research issues, this paper presents a delay-aware downlink resource scheduling (DADRA) technique for future generation networks. The optimization problem of reducing buffer overflow and improving scheduling QoS performance is solved using a genetic algorithm with an improved crossover function. Experiment outcome shows DADRA achieves much better throughput, slot utilization, and packet failure performance when compared with standard resource allocation technique.&lt;/span&gt;

협대역 무선 전술 네트워크를 위한 고품질 동영상 전송 시스템의 설계, 구현 및 검증

본 논문은 협대역(수십kHz) 무선 전술 네트워크에서 동영상 스트리밍을 수행하는 영상 압축 및 전송 시스템의 설계, 구현 및 검증 결과에 대해 기술한다. 제안 시스템은 실시간 동영상 전송을 위한 충분한 주파수 대역폭 확보가 어려운 협대역 무선 전술 네트워크 환경에서 고품질의 동영상 서비스 제공을 목표로 설계되었으며, 이를 달성할 수 있도록 응용계층 부호화, 선택적 재전송 등의 영상전송 네트워크 기술, 소프트웨어기반 high efficiency video codec (HEVC) 코덱 및 영상 전처리 등의 영상 압축 기술 등을 통합하여 구현되었다. 구현된 시스템은 실내 및 실외 환경에서 검증되었으며 주어진 전송속도에 따라 설정된 영상 프로파일에 의해 영상품질 요구 성능을 만족하는 것을 확인하였다.

A Novel Self-Forming Virtual Sub-Nets Based Cross-Layer MAC Protocol for Multihop Tactical Network

A tactical network mainly consists of software-defined radios (SDRs) integrated with programmable and reconfigurable features that provide the addition and customization of different waveforms for different scenarios, e.g., situational awareness, video, or voice transmission. The network, which is mission-critical, congested, and delay-sensitive, operates in infrastructure-less terrains with self-forming and self-healing capabilities. It demands reliability and the need to survive by seamlessly maintaining continuous network connectivity during mobility and link failures. SDR platforms transfer large amounts of data that must be processed with low latency transmissions. The state-of-the-art solutions lack the capability to provide high data throughput and incorporate overhead in route discovery and resource distribution that is not appropriate for resource-constrained mission-critical networks. A cross-layer design exploits existing resources to react to environment changes efficiently, enable reliability, and escalate network throughput. A solution that integrates SDR benefits and cross-layer optimization can perform all the mentioned operations efficiently. In tactical networks, SDR’s maximum usable bandwidth can be utilized by exploiting radios’ autonomous behavior. This paper presents a novel virtual sub-nets based cross-layer medium access control (VSCL-MAC) protocol for self-forming multihop tactical radio networks. It is a MAC-centric design with cross-layer optimization that enables dynamic routing and autonomous time-slot scheduling in a multichannel network environment among SDRs. The cross-layer coupling uses link-layer information from the hybrid of time division multiple access and frequency division multiple access (TDMA/FDMA) MAC to proactively enable distributed intelligent routing at the network layer. The virtual sub-nets based distributed algorithm exploits spectrum resources and provides call setup with persistently available k-hop route information and simultaneous collision-free transmission of voice and data. The experimental results over extensive simulations show significant performance improvements in terms of minimum control overhead, processing time in relay nodes, a substantial increase in network throughput, and lower data latency (up to 76.98%) compared to conventional time-slotted MAC protocols. The design is useful for mission-critical, time-sensitive networks and exploits multihop simultaneous communication in a distributed manner.

CFFD-MAC: A Hybrid MAC for Collision Free Full-Duplex Communication in Wireless Ad-Hoc Networks

Infrastructure-less (sometimes known as ad-hoc) networking paradigm is very appealing and potentially shaping its future into almost all emerging networks (i.e., IoT, wireless sensor networks, vehicular ad-hoc networks, emergency, and tactical radio networks, etc.). However, when conventional networking protocols are used, such networks often perform poorly, mainly because of interference within the network and limited network throughput. Recent advancements in wireless communications have enabled full-duplex (FD) operation by suppressing self-interference, which can theoretically double the network throughput. However, conventional medium access control (MAC) protocols like carrier-sense multiple access with collision avoidance (CSMA/CA) favor half-duplex (HD) operation and fail to benefit from FD transmission opportunities. This article proposes a novel hybrid MAC protocol for full-duplex ad-hoc networks. The proposed MAC combines time division multiple access (TDMA) and IEEE 802.11 distributed coordination function (DCF) strengths in chains of time-slotted contention-based control frames and collision-free data frames. The aim is to fully utilize FD transmission opportunities to increase network throughput. The proposed protocol modifies request-to-send (RTS) and clear-to-send (CTS) frames in IEEE 802.11 DCF MAC to form FD-RTS/CTS frames. These frames are used to enable collision-free FD communications among neighbors. The proposed scheme mitigates conventional MAC issues like hidden-node problem (HNP) and exposed-node problem (ENP). It also allows concurrent FD data transmissions in a collision-free manner. The model is generic and can be applied to any ad-hoc wireless network. In this article, the design is applied to a single channel ad-hoc network with FD transceivers. We compared the proposed design with IEEE 802.11 CSMA/CA protocol with both HD and FD transceivers. The simulation results show a 30% gain in throughput, reduced latency, and fairness among participating wireless nodes.

Design and implementation of new security architecture for wireless network

Tactical Networks rely on modern communication technologies to connect soldiers and commanders engaged in the battlefield and enable enhanced information flow and data gathering, allowing for decision making based on real-time data analysis. Tactical network is a wireless communication network where wireless tactical network security is a milestone because a soldier does not know from where and when the attacks come.In this paper, a dangerous attack over the deployed tactical network is proposed through group of drones which are sent to the tactical network headquarter. The drone’s mission is to identify every device MAC, IP, Name and Location to intercept data or destroy the devices. Also, in this paper, a proposed solution is given for this proposed attack through changing MAC, IP, Name and Location for every device in the headquarter periodically according to the attack time and the devices importance. The MAC, IP, Name and Location must be changed before the drones return to enemy territories.A software program is developed to change MAC, IP, and Name periodically from centered server with no conflicts. The performance analysis for the proposed solution have been taken into consideration the metrics of packets drops, time delay, communication overhead and storage overhead during the changing time. A software tool verifies the changing of IP, MAC and Name for every device. This solution ensures that before the drones return to enemy territories all devices fixed parameters of MAC, IP, and Name are changed.

Efficient attack strategy for legitimate energy-powered eavesdropping in tactical cognitive radio networks

The cognitive radio network (CRN) is not only considered a useful medium for users, but it is also an environment vulnerable to proactive attackers. This paper studies an attack strategy for a legitimate energy-constrained eavesdropper (e.g., a government agency) to efficiently capture the suspicious wireless communications (i.e., an adversary communications link) in the physical layer of a CRN in tactical wireless networks. Since it is powered by an energy harvesting device, a full-duplex active eavesdropper constrained by a limited energy budget can simultaneously capture data and interfere with the suspicious cognitive transmissions to maximize the achievable wiretap rate while minimizing the suspicious transmission rate over a Rayleigh fading channel. The cognitive user operation is modeled in a time-slotted fashion. In this paper, we formulate the problem of maximizing a legitimate attack performance by adopting the framework of a partially observable Markov decision process. The decision is determined based on the remaining energy and a belief regarding the licensed channel activity in each time slot. Particularly, in each time slot, the eavesdropper can perform an optimal action based on two functional modes: (1) passive eavesdropping (overhearing data without jamming) or (2) active eavesdropping (overhearing data with the optimal amount of jamming energy) to maximize the long-term benefit. We illustrate the optimal policy and compare the performance of the proposed scheme with that of conventional schemes where the decision for the current time slot is only considered to maximize its immediate reward.

A Location Dependent Group Key Management Scheme for High Confidential Information in Tactical Wireless Networks

A Location Dependent Group Key Management Scheme for High Confidential Information in Tactical Wireless Networks

Data Capture of Cognitive Radio-Based Red Network by a Blue Network in Tactical Wireless Networks

In this paper, we consider data capture of a cognitive radio-based red network in tactical wireless networks. In the blue (friendly) network, an eavesdropping sensor node is deployed to capture data of the red (adversary) network, where the red network adopts cognitive radio for opportunistic data transmission. Since most wireless networks suffer energy constraints, we investigate the data capture (eavesdropping) performance of the blue network in two scenarios of energy management: no energy harvesting and energy harvesting. In both of the energy scenarios, we formulate the problem of maximizing data-capturing performance of blue network in the framework of a partially observable Markov decision process (POMDP) by considering feedback observations of actions. Furthermore, a recursive method is adopted to solve the problem by which the optimal action policy for the eavesdropping sensor nodes of blue network is obtained. Finally, we compare the performances of the proposed scheme with those of different reference methods under the two mentioned energy scenarios. Numerical results show that the proposed POMDP-based scheme can improve the data-capturing performance of the eavesdropping sensor node.

Cross-Layer Design and Performance Analysis of Tactical Radio Networks

In this paper, we investigate the performance of tactical radio networks, particularly for communication scenarios where multihop relaying along with spatial reuse techniques are applied. The tactical scenarios of concern have a diverse range of reliability and/or delay requirements. We first employ cross-layer protocol architecture with integrated time-division-multiple-access-based fast packet forwarding and automatic-repeat-request-based multihop error control to support tactical applications with a diverse range of reliability and/or delay requirements. Then, we develop analytical models to study the link-level and network-wide behaviors of the tactical radio networks. The developed models capture the effects of end-to-end channel memory due to multihop relays, interference due to spatial reuse, uneven interslot delays due to fast packet forwarding, and jamming attack in hostile network environment. It is shown that the protocol architecture with proposed fast packet forwarding and multihop error control mechanisms can significantly improve communication performance and support delay-sensitive applications. In addition, it is demonstrated that cross-layer adaptivity, where different network environments require different logical topologies and radio modes, is needed to achieve best performance tradeoffs among throughput, efficiency, delivery ratio, and transport capacity.

Research on Tactical Internet Real-Time Simulation for Training

Simulative training should include network simulation in information age, and network simulation needs to meet the real-time requirements. For the real-time implementation of Tactical Internet (TI) simulation, the paper proposed a "water-wave type" topology updating method for simulation, which solved the real-time problem of tactical radio network topology updating simulation. Secondly, the paper proposed a data packet transmission method based on characteristic information, which solved the large data problem of TI simulation, and then the real-time of simulation was improved. Finally, the paper proposed a transmission success-rate calculating method based on prediction, which solved the real-time simulation problem of transmission. The practical application proved that the paper’s methods had good effect.

Book reviews [2 books reviewed

The following books are reviewed: Tactical Wireless Communications and Networks: Design Concepts and Challenges (Elmasry, G.F) and FISMA and the Risk Management Framework: The new Practice of Federal Cyber Security (Gantz, S.D. and Philpott, D.R.).

Location and visualization of the communication problems in a simulated Slovenian Armed Forces tactical radio network

The article presents a concept of design, using the methods of simulation results, automatic analysis, and taking into account expert knowledge, and visualization of communication problems in the developed Tactical Player. The main emphasis is on the segment of simulation results evaluation on the basis of fuzzy sets, from which we have developed rules, the combination of which is used for evaluation of the quality of communication parameters between tactical radio stations. A special note should also be taken of the concept of modeling a tactical radio network and its characteristics, the mode of communication between radio stations, hierarchic organization, the problems of manual analysis of simulation results, etc. We present our solution for automatic analysis and the solution for visualization of problematic segments in the course of communication. The reader is acquainted with the problems of wireless communications and the key parameters influencing the connection between communicating entities, such as radio visibility, message transfer success, packet loss, deterioration of the signal–noise relation, etc. Because visualization of problematic time frames of the simulated communication on a virtual simulation field directly depends on the automatic analysis precision, we also used mathematical procedures (probability theory and possibility theory) as the basis of the fuzzy logic used. For a better understanding of the modeled prototype’s functioning, we also include a block scheme in the form of a process scheme, on the basis of which we can show the segments that are new and are a scientific contribution in the field of simulation techniques.

Stochastic Analysis and Modeling of a Tree-Based Group Key Distribution Method in Tactical Wireless Networks

A number of key management challenges are encountered when operating tactical communication systems using a group-wide shared key. A large portion of such communications occurs over low bit-rate channels, and all communication channels must be available at any moment for mission action. Current over-the-air rekeying protocols consume too much channel bit-rate to be practical for large tactical radio networks. This caused an off-line pre-placed key (PPK) approach to become most commonly used key distribution method in these environments. Unfortunately, with this key management scheme, revoking group membership requires a full intra-mission rekey, which can be dangerous in a battlefield situation. This paper introduces a new group key distribution method called Viral Electronic Key Exchange (VEKE). This paper examines the protocol as an extension to the Internet Key Exchange (IKE) protocol, but any electronic key exchange protocol can be used (Ex. IKE v2). A feature of this protocol is a parallel key distribution scheme enabled by propagating the key management role to authenticated nodes while establishing security associations across the network. We performed a comprehensive stochastic analysis to develop a model for computing the expected rekey time across the entire group, taking into account the likelihood of node jamming, channel failures, and message corruption. This model was verified with a Monte-Carlo simulation. Our results confirmed that the VEKE protocol can accomplish an over-the-air rekey in a short period of time, even over low bit-rate systems, while preserving rigid security and channel availability properties of the network. It also allows for the amount of pre-placed public-key material and other preparations necessary in tactical networks to be minimized.

Optimization of Location Aware Routing Protocol for Wireless Adhoc Tactical Networks

Optimization of Location Aware Routing Protocol for Wireless Adhoc Tactical Networks

Automated design algorithms for tactical wireless networks

To guide users who attempt to deploy wireless networks in military applications, there is an evolving need for developing systematic methodologies to analyze/predict the performance of mobile ad hoc networks (MANETs). In addition, the advance in cognitive networking research provides opportunities for exploiting unused spectrum to optimize throughput of MANETs. However, with the increasing number of parameters/constraints, there is even a more demanding need to develop automated methodologies to design/tune such networks.In this work, we study the concepts and challenges for automatic design/re-configuration of cognitive MANETs, in addition to proposing design automation algorithms. The paper is divided into two parts. In the first part, we describe the design objectives, imposed constraints, and involved parameters in MANET design. We discuss how cognitive techniques can be employed to exploit the unused spectrum in military architectures. We then discuss the challenges that face the design/re-configuration of a cognitive network and their implications at different network layers. We also describe possible implementation options for designing MANETs that employ cognitive features at all layers. In the second part of this work, we propose design automation algorithms for optimally setting parameters to achieve a desired objective and satisfy certain constraints. Despite providing the optimal configuration, the simple approach of testing all possible combinations of parameter settings has significant time complexity (the COMB approach). Thus, we propose a novel heuristic (Sequential Parameter Optimization or SEPO) for searching through the possible parameter settings and selecting the best design options. SEPO is efficient in terms of both convergence speed and parameter tuning. We also discuss the foundation for using supervised learning to speed up the design (search) process. By evaluating realistic design of military-like scenarios that require optimizing a diverse set of metrics, we show that SEPO generates comparable results to the optimal, straightforward (slow-converging) COMB approach that is based on exhaustive search.