Broadcast Nature Of Wireless Communication Research Articles

Ultra-Reliable and Low-Latency Wireless Hierarchical Federated Learning: Performance Analysis.

Wireless hierarchical federated learning (WHFL) is an implementation of wireless federated Learning (WFL) on a cloud-edge-client hierarchical architecture that accelerates model training and achieves more favorable trade-offs between communication and computation. However, due to the broadcast nature of wireless communication, the WHFL is susceptible to eavesdropping during the training process. Apart from this, recently ultra-reliable and low-latency communication (URLLC) has received much attention since it serves as a critical communication service in current 5G and upcoming 6G, and this motivates us to study the URLLC-WHFL in the presence of physical layer security (PLS) issue. In this paper, we propose a secure finite block-length (FBL) approach for the multi-antenna URLLC-WHFL, and characterize the relationship between privacy, utility, and PLS of the proposed scheme. Simulation results show that when the eavesdropper's CSI is perfectly known by the edge server, our proposed FBL approach not only almost achieves perfect secrecy but also does not affect learning performance, and further shows the robustness of our schemes against imperfect CSI of the eavesdropper's channel. This paper provides a new method for the URLLC-WHFL in the presence of PLS.

Anti-Jamming Resource-Allocation Method in the EH-CIoT Network through LWDDPG Algorithm.

In the Energy-Harvesting (EH) Cognitive Internet of Things (EH-CIoT) network, due to the broadcast nature of wireless communication, the EH-CIoT network is susceptible to jamming attacks, which leads to a serious decrease in throughput. Therefore, this paper investigates an anti-jamming resource-allocation method, aiming to maximize the Long-Term Throughput (LTT) of the EH-CIoT network. Specifically, the resource-allocation problem is modeled as a Markov Decision Process (MDP) without prior knowledge. On this basis, this paper carefully designs a two-dimensional reward function that includes throughput and energy rewards. On the one hand, the Agent Base Station (ABS) intuitively evaluates the effectiveness of its actions through throughput rewards to maximize the LTT. On the other hand, considering the EH characteristics and battery capacity limitations, this paper proposes energy rewards to guide the ABS to reasonably allocate channels for Secondary Users (SUs) with insufficient power to harvest more energy for transmission, which can indirectly improve the LTT. In the case where the activity states of Primary Users (PUs), channel information and the jamming strategies of the jammer are not available in advance, this paper proposes a Linearly Weighted Deep Deterministic Policy Gradient (LWDDPG) algorithm to maximize the LTT. The LWDDPG is extended from DDPG to adapt to the design of the two-dimensional reward function, which enables the ABS to reasonably allocate transmission channels, continuous power and work modes to the SUs, and to let the SUs not only transmit on unjammed channels, but also harvest more RF energy to supplement the battery power. Finally, the simulation results demonstrate the validity and superiority of the proposed method compared with traditional methods under multiple jamming attacks.

Security Enhancement for Deep Reinforcement Learning-Based Strategy in Energy-Efficient Wireless Sensor Networks.

Energy efficiency and security issues are the main concerns in wireless sensor networks (WSNs) because of limited energy resources and the broadcast nature of wireless communication. Therefore, how to improve the energy efficiency of WSNs while enhancing security performance has attracted widespread attention. In order to solve this problem, this paper proposes a new deep reinforcement learning (DRL)-based strategy, i.e., DeepNR strategy, to enhance the energy efficiency and security performance of WSN. Specifically, the proposed DeepNR strategy approximates the Q-value by designing a deep neural network (DNN) to adaptively learn the state information. It also designs DRL-based multi-level decision-making to learn and optimize the data transmission paths in real time, which eventually achieves accurate prediction and decision-making of the network. To further enhance security performance, the DeepNR strategy includes a defense mechanism that responds to detected attacks in real time to ensure the normal operation of the network. In addition, DeepNR adaptively adjusts its strategy to cope with changing network environments and attack patterns through deep learning models. Experimental results show that the proposed DeepNR outperforms the conventional methods, demonstrating a remarkable 30% improvement in network lifespan, a 25% increase in network data throughput, and a 20% enhancement in security measures.

SCIM: Incorporating secure communication and interference management in one operation

Due to the broadcast nature of wireless communications, users’ data transmitted wirelessly is susceptible to security/privacy threats. Meanwhile, as a result of the limitation of spectrum resources, massive wireless connections will incur serious interference, which may damage the efficiency of data transmission. Therefore, improving both efficiency and secrecy of data transmission is of research significance. In this paper, we propose a wireless transmission scheme by taking both Secure Communication (SC) and Interference Management (IM) into account, namely SCIM. With this scheme, an SCIM signal is generated by the legitimate transmitter (Tx) and sent along with the desired signal, so that the SCIM signal can interact with and suppress the environmental interference at the legitimate receiver (Rx). Meanwhile, the SCIM signal may interfere with the eavesdropper in the coverage of legitimate transmission so as to deteriorate the eavesdropping performance. Therefore, the secrecy of desired transmission is improved. In this way, both the transmission efficiency and privacy are enhanced. Then, by taking various transmission preferences into account, we develop different implementations of SCIM, including Interference Suppression First SCIM (ISF-SCIM), Data Transmission First SCIM (DTF-SCIM), Anti-Eavesdropping First SCIM (AEF-SCIM), and Secrecy Rate Maximization SCIM (SRM-SCIM). Our in-depth simulation results have shown the proposed methods to effectively improve the efficiency and secrecy of the legitimate transmission.

Pulse jamming attack detection using swarm intelligence in wireless sensor networks

A Wireless Sensor Networks consists of small, inexpensive, battery powered wireless sensors, which self configure and collaborate with each other to support cost effective sensing in situations where human observation or wired systems deployment can be inefficient, expensive, dangerous, or otherwise untenable. Unfortunately, the desirable nature of a WSN introduces many security challenges. The broadcast nature of wireless communication introduces various attacks in WSN. This research work mainly focus on lack of issues regarding achievement of security for certain attacks like jamming attack, denial of sleep attack, tampering and cheating attack in IEEE802.15.4 based wireless sensor networks. Swarm intelligence algorithm is proficient enough to adapt change in network topology and traffic.Using the swarm intelligence technique, the forward ants either unicast or broadcast at each node depending on the availability of the channel information for end of the channel. If the channel information is available, the ants randomly choose the next hop. The source on receiving the channel information from the backward ant verifies the prevalence of the attacker for long time and avoids the particular channel for transmission in order to improve the performance of wireless sensor network. The proposed approach attains packet delivery of 0.4441 and 0.6633. The effective packet delivery ratio shows the effectiveness of the proposed approach. Simulation results assessing the performance of the proposed Swarm Based Defense Technique based on rate, time and number of attackers proves the efficiency of the proposed scheme compared to the existing techniques.

Reinforcement Learning-Based Dynamic Anti-Jamming Power Control in UAV Networks: An Effective Jamming Signal Strength Based Approach

Unmanned aerial vehicle (UAV) assisted air-to-ground (A2G) communication is vulnerable to malicious jamming due to the broadcast nature of wireless communications. In this letter, an anti-jamming power control framework with an unknown jamming model and unknown transmission power is proposed. In particular, the probability density function (PDF) of the effective jamming signal strength (EJSS) is first estimated via kernel density estimation (KDE). Then, utilizing the EJSS, a deep deterministic policy gradient (DDPG) based framework is proposed to acquire the power control strategy in real time. Moreover, a trajectory design scheme based on K-means++ is proposed to track the location of users. The simulation results show that the proposed framework yields an improved sum rate and energy efficiency over the reference schemes.

A Coalition Formation Game-Based Multi-User Grouping Approach in the Jamming Environment

Due to the broadcast nature of wireless communication, it is vulnerable to malicious jamming attacks. Meanwhile, multiple users need to share the limited spectrum resources to enhance the spectrum utilization efficiency because of the scarcity of wireless spectrum resources. Therefore, wireless communication systems need to deal with the malicious jamming attacks and mutual interference among different users. In this paper, a multi-user anti-jamming grouping approach based on a coalition formation game is studied. The proposed approach can maximize users’ transmission rate while avoiding channel jamming through optimization of the coalition formation strategy under the influence of malicious jamming. With the help of the exact potential energy game, we demonstrate that the proposed game model can obtain stable Nash equilibrium solutions. Lastly, the effectiveness of the proposed algorithm is demonstrated through numerical.

Physical Layer Authentication Scheme in Beamspace MIMO Systems

The broadcast nature of wireless communication makes it vulnerable to various security threats such as spoofing attacks. Physical layer (PL) authentication has emerged as a promising and powerful approach to secure future wireless technologies for next-generation communication networks. In this work, we propose a PL authentication scheme against spoofing attacks based on a novel distance signature that exploits the properties of beamspace multiple-input multiple-output (MIMO) channels in millimeter-wave (mmWave) networks. The proposed signature is derived from the positions of the principal components in beamspace channel domain by measuring their displacement from the original point and sorting the distance values in descending order based on the phases of the principal components. In addition, a mutual coupling effect is introduced into the system, which is a hardware property of multiple antenna design. This is then combined with the proposed distance signature to form a hybrid signature that further improves the authentication performance. Simulation results have confirmed the validity and effectiveness of our proposed system in terms of detection rate and false alarm.

Realizing Opportunistic Routing in Multi-Channel Environments

Opportunistic Routing (OR), which utilizes the broadcast nature of wireless communication to route packets in a dynamic way, significantly improves the transmission quality. Most of the researches focus on the single channel scenario; however, multi-channel (MC) is widely adopted over wireless communication systems. How to apply OR over MC environments is quite challenging and still an unsolved issue. OR operating over single channel environments collects acknowledgements mainly through overhearing data packets. In contrast, MC environments increase the performance by reducing interference and providing more bandwidth. Since users scatter over multiple channels, the chance of overhearing is reduced. Without overhearing acknowledgements (ACKs), the performance of OR degrades due to duplicate transmissions. To better understand the behavior of OR over MC environments, this paper first surveys current OR methods and constructs a simplified scenario to observe how they behave as the number of interfaces and channels increases. Then, analyze and compare their costs and penalties to find out a potential method. Finally, refine the potential method for MC environments. It is observed that token passing is the most potential method for its high efficiency of utilizing control packets. To apply token passing to OR in MC environments, this paper proposed multi-channel token passing (MCTP) to resolve the hazards of token passing paths and dynamic rate for multiple flows. Simulation results show that MCTP has high performance with low and consistent overheads. In addition, MCTP is scalable with increasing interface and channel numbers, which makes it a prototype for the future OR research in MC environments.

A cooperative protocol for pervasive underwater acoustic networks

The novel Underwater Wireless Sensor Network (UWSN) can contribute to monitor and explore aquatic environments. But, communicating in these environments is still hard and has many challenges. For example, optical and electromagnetic waves deteriorate from high-attenuation. Moreover, acoustic communication has a large packet error rate and low throughput. A large number of solutions to improve aquatic communication refers to routing protocols, medium access control protocols, and designing acoustic modems. Cooperative communication explores the broadcast nature of wireless transmission and enhances its performance. However, cooperative communication has not been fully explored in UWSNs. In this work, we present COPPER, a Cooperative Protocol for Pervasive Underwater Acoustic Networks. COPPER considers LLC and MAC sub-layers and operates synchronously or asynchronously over Time Division Multiple Access using a selective repeat ARQ scheme. COPPER exploits the broadcast nature of wireless communication and, sensor nodes that are idle can operate as a relay, enhancing communication by space diversity. Simulation results show that COPPER improves network performance. For example, the network goodput improves by 17% and the packet error rate decreases by 65%.

D2D-enabled resource management in secrecy-ensured 5G and beyond Heterogeneous networks

Integration of Device-to-Device communication in 5G Heterogeneous networks (HetNets) promises to increase resource utilization and spectrum efficiency (SE). However, the broadcast nature of wireless communication makes it vulnerable to an eavesdropper, who can steal useful information from the transmission channel. Hence, ensuring secure communication for both cellular users (CUs) and D2D pairs is the need of the time. In this paper, we study the optimization problem of resource allocation in 5G and beyond wireless networks to maximize the secrecy rate of both CUs and D2D links from the physical layer security perspective. We consider multiple eavesdroppers overhearing the CUs and D2D pairs. Two optimization problems are formulated: one considering separate channels for CUs and D2D user (DU), and second, considering the shared channel between CU and DU. The nature of the formulated problems is mixed-integer non-linear programming (MINLP) problem and to solve it, we propose an ϵ-optimal based successive linearization algorithm. This algorithm decomposes our original problem into finite sub-problem branches and solves each separately. Simulation results show that the proposed technique can significantly improve the secrecy rate, throughput, and energy efficiency of the network especially in the case of separate channels for CUs and DUs.

Defending wireless communication against eavesdropping attacks using secret spreading codes and artificial interference

The broadcast nature of wireless communication makes it intrinsically vulnerable to eavesdropping attacks. This article suggests the using of secret spreading codes (i.e. only a legitimate receiver knows the spreading sequence) and artificial interference (i.e. by intentionally adding noise to the broadcast channel) on countering eavesdropping attacks. We have made a theoretical analysis on the potential performance degradation at the eavesdropper and at the legitimate receiver for a point-to-point wireless communication system using direct-sequence spread spectrum (DSSS) with coherent phase-shift keying (PSK) modulation. We have also proposed a lightweight non-cryptographic secret code generation scheme which leads to low correlation between the spreading codes used at the transmitter and at the eavesdropper. Simulation results confirms the good anti-eavesdropping performance on using the proposed non-cryptographic secret code generation scheme. Simulation results also conform with the theoretical analysis and motivate the using of artificial interference on countering eavesdropping attacks.

Wireless secure communication involving UAV: an overview of physical layer security

Unmanned aerial vehicle (UAV) is a flight device with power and energy based on computer program control, which has the characteristics of small size, light weight, high maneuverability and low cost. With its characteristics, UAV can play an important role in military and civil fields. However, due to the broadcast nature of wireless communication and inherent air-to-ground line-of-sight channel, UAV wireless communication system is more vulnerable to security threats. On the basis of traditional encryption technology, the secrecy capacity of the UAV communication system can be improved by introducing physical layer security. This article aims to study the security of the physical layer in the UAV communication system, and summarizes the latest research results on the safety communication involving UAVs on the physical layer, such as trajectory optimization, power allocation, user scheduling and cooperative UAVs. Further, some potential research directions and challenges in physical layer security of UAV system are discussed.

Detection of Replica Node Attack Based on Exponential Moving Average Model in Wireless Sensor Networks

Due to the broadcast nature of wireless communication, wireless sensor networks (WSNs) are susceptible to several attacks. Amongst them, replica attack is one of the predominates as it facilitates the attackers to perform some other attacks. So, it is of immense significance to design a competent security method for WSNs. Introducing a trust method is the primary concern for assisting well-organized use of the available energy in each node in the energy restricted environment. In order to tradeoff between energy usage and attack detection, energy-based prediction approach is deemed to be a suitable one. A statistical method, exponential moving average (EMA) model based replica detection is proposed to detect replica node attack based on energy consumption threshold in WSNs. The difference between actual and predicted energy consumption exceeding the threshold level is considered as malicious. In this paper, future energy drop of a sensor node is forecasted using statistical measure instead of probabilistic method. In EMA model, the transition from higher power consuming state (active state) to lower power consuming states (sleep and sense states) is controlled by a fixed schedule. The accumulated average time of the node was in any state in the past is used to estimate the time duration of a node that spends in that state. Unlike Markov Model, the estimations of energy are made periodically. By this, computational overhead on the microcontroller of the sensor is greatly reduced in EMA approach. The simulation results taken using TRM simulator shows that choosing the threshold value which is neither too large nor too small results in optimum level of detection accuracy and lifetime of the network.

Power maximisation technique for generating secret keys by exploiting physical layer security in wireless communication

The intrinsic broadcast nature of wireless communication let the attackers to initiate several passive attacks such as eavesdropping. In this attack, the attackers do not disturb/stop or interrupt the communication channel, but it will silently steal the information between authentic users. For this purpose, physical layer security (PLS) is one of the promising methodologies to secure wireless transmissions from eavesdroppers. However, PLS is further divided into keyless security and secret key-based security. The keyless security is not practically implemented because it requires full/part of instantaneous/statistical channel state information (CSI) of the eavesdroppers. Alternatively, key-based security is exploiting the randomness and reciprocity of wireless channels that do not require any CSI from an eavesdropper. The secret key-based security is due to the unpredictability of wireless channels between two users. However, the secret key-based security mainly on two basic parameters, i.e. coherence time and transmission power. Nevertheless, the wireless channel between users has a short coherence time, and it will provide shorter keys' length due to which eavesdropper can easily extract keys between communicating parties. To overcome this limitation, we proposed the power allocation scheme to improve the secret key generation rate (SKGR) to strengthen the security between authentic users.

Secure Multiparty Device Pairing Using Random Peephole Generations

A secure device pairing mechanism is used to establish a trusted communication channel between unassociated wireless devices. The broadcast nature of wireless communication opens the door for man-in-the-middle (MITM) attacks, and even other subtle forms of masquerader and misfeasor attacks. This paper introduces a simple device pairing approach to tackle such attacks seamlessly. The algorithm is compatible with a multitude of devices, whereas a majority of existing algorithms are based on two devices exclusively. This approach utilizes a human visual channel as an Out-Of-Band (OOB) channel to authenticate the public keys exchanged between the devices. The interactive nature of this approach forces user attention, hence improving the reliability and consistency of the device pairing process. To do so, we introduce the concept of ‘peepholes,’ and mathematically define it before demonstrating the algorithm’s methodology. Subsequent sections also demonstrate its robustness against attacks via misfeasors, masqueraders, and men-in-the-middle.

Optimal Access Scheme for Security Provisioning of C-V2X Computation Offloading Network With Imperfect CSI

In a cellular vehicle-to-everything (C-V2X) enabled computation-offloading network, vehicular users may deliver computation tasks to a cellular base station (BS) through vehicle-to-infrastructure (V2I) transmission links in order to accommodate computation-intensive applications, where the BS is usually equipped with a mobile edge computing (MEC) server. However, due to the broadcast nature of wireless communications and high-mobility of vehicles, the computation-offloading information may suffer from an eavesdropping threat. In practice, the interference generated by device-to-device-based V2V (D2D-V) links can be utilized for protecting the offloading information against eavesdropping. This observation motivates a security provisioning for C-V2X computation-offloading network. Specifically, a dynamic threshold-based access scheme is required to maintain the interference under control for different channel conditions. Unfortunately, the previous studies that are based on the assumption of perfect channel state information (CSI) can not be applied for the dynamic vehicular networks. In this paper, we propose a dynamic threshold-based access scheme for security provisioning of C-V2X computation-offloading network by considering an imperfect CSI. In this scheme, an optimized access threshold is set to update adaptively in terms of channel estimation error for balancing both the security and reliability of the offloading link. Furthermore, the proposed scheme can maximize the secrecy throughput under a connection outage constraint of the D2D-V links, with the total area spectral efficiency optimized under the security performance criterion for the offloading link. Numerical results are provided for validating the proposed theoretical analysis. A useful design insight is provided for attaining an optimal configuration of C-V2X computation-offloading network.

A Analysis of Attack and Defense Mobile Ad Hoc Network Based on OPNET

Due to the broadcast nature of wireless communications, the damage to mobile ad hoc networks is becoming more and more common. We propose a network stability model that can effectively reflect the network performance when the network is damaged in real time. The Ad Hoc network model is built by using the node model supporting the IEEE802.11 standard provided by OPNET software to simulate the network performance of the network under different degrees of damage. This model provides an effective way for the simulation analysis of network performance under the condition of Ad Hoc network damage.

Joint Network Coding and ARQ Design Toward Secure Wireless Communications

The broadcast nature of wireless communications makes transmission susceptible to eavesdropping. Recently, physical-layer security has been extensively studied to secure the wireless transmissions, but the security is severely compromised when the eavesdropper has the superiority in the channel quality. Toward this issue, we in this paper propose a joint ARQ and network coding method exploiting the characteristics of both the physical layer and the link layer. Specifically, we relate the message to be transmitted in the current slot with the successfully decoded messages in previous slots, where the ARQ is employed at the legitimate side to guarantee the successful transmission and decoding. Once one or more received messages fail to be decoded at the eavesdropper, it further prevents the eavesdropper from decoding the transmissions in later slots and thus the message transmitted currently and later is secured at the legitimate side. Moreover, for the more disadvantageous case that the eavesdropper is geographically closer to the transmitter, we further propose a destination-aided network coding scheme, which secures private information no matter where the eavesdropper is. The closed-form expressions of intercept probability and loss probability of the private information are analytically presented. The simulation results are provided to confirm our theoretical findings.

An Efficient Content Delivery System for 5G CRAN Employing Realistic Human Mobility

Today’s modern communication technologies such as cloud radio access and software defined networks are key candidate technologies for enabling 5G networks as they incorporate intelligence for data-driven networks. Traditional content caching in the last mile access point has shown a reduction in the core network traffic. However, the radio access network still does not fully leverage such solution. Transmitting duplicate copies of contents to mobile users consumes valuable radio spectrum resources and unnecessary base station energy. To overcome these challenges, we propose huMan mObility-based cOntent Distribution (MOOD) system. MOOD exploits urban scale users’ mobility to allocate radio resources spatially and temporally for content delivery. Our approach uses the broadcast nature of wireless communication to reduce the number of duplicated transmissions of contents in the radio access network for conserving radio resources and energy. Furthermore, a human activity model is presented and statistically analyzed for simulating people daily routines. The proposed approach is evaluated via simulations and compared with a generic broadcast strategy in an actual existing deployment of base stations as well as a smaller cells environment, which is a trending deployment strategy in future 5G networks. MOOD achieves 15.2 and 25.4 percent of performance improvement in the actual and small-cell deployment, respectively.