JournalTOCs

Wireless Networks
Journal Prestige (SJR): 0.336

Citation Impact (citeScore): 2
Number of Followers: 6

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1572-8196 - ISSN (Online) 1022-0038
Published by Springer-Verlag

[2467 journals]

Sustainable remote patient monitoring in wireless body area network with
Multi-hop routing and scheduling: a four-fold objective based
optimization approach
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  Abstract: Abstract Wireless body area networks (WBAN) are essential for patient monitoring and reducing lengths of stay in hospitals. Our research's objective was to create a scheduling strategy and energy-efficient routing for WBANs that was energy-efficient while also enhancing network life. The projected model includes four major phases: (a) Network setup and clustering, (b) Next-hop-node selection (c) Multi-hop routing, and (d) Scheduling. The nodes (sensors embedded in the patient) are clustered during the network creation phase, and the Cluster Head (CH) for data transmission to sink is chosen using the new Modernized Stackelberg Game Theory. Then, the optimal next-hop node for data transmission (from CH to sink) is accomplished via a new optimized four-fold-objectives model, to reduce the network's overall energy usage by balancing the energy use among the sensor nodes. The four-fold objectives like energy, Link quality, Mobility, and Trust Value are taken into consideration during the selection of the optimal path. Moreover, a new Enhanced Glow Worm Swarm Optimization (En-GWSO) model is designed to find the optimal path among the available paths. This En-GWSO model is an extended version of the standard GWSO model. The data reaches the sink via the optimal path, and hence the data transmission delay is reduced. From the sink, the data is transmitted via the routers in a multi-hop fashion. Further, at the receiver end, the scheduling takes place. In the scheduling phase, the data from the sink node is sent in their time slots i.e., Time Division Multiple Access (TDMA) to the concerned receiver (doctor/emergency/hospital). Finally, a comparative evaluation is made to validate the efficiency of the projected model.
  PubDate: 2023-03-21
Anchor-based sparse subspace incomplete multi-view clustering
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  Abstract: Abstract In recent decades, multi-view clustering has received a lot of attention. The majority of previous research has assumed that all instances have complete views or at least one view that includes all instances. However, the incomplete multi-view clustering issue arises because real-world data frequently lack instances in each view. We propose a novel anchor-based sparse subspace incomplete multi-view clustering solution to this issue. Through a unified sparse subspace learning framework, the proposed method learns inter-view anchor-to-anchor and intra-view anchor-to-incomplete affinities and fuses them into a consensus sparse anchor graph, which yields a unified clustering result. Our method outperforms other incomplete multi-view clustering methods in three important ways: (1) it uses a small number of hyperparameters to learn a sparse consensus graph from the data; (2) Because of the anchor-based graph construction, it can process large datasets; (3) It is naturally capable of handling both negative entries and multiple views. Last but not least, extensive experiments show that the proposed method is effective, supporting the claim that it consistently outperforms current clustering methods.
  PubDate: 2023-03-20
Performance analysis of a Queueing system based on vacation with fault
repairable and spare servers in the MP2P network
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  Abstract: Abstract Peer-to-Peer (P2P) network is a logical layer distributed network built on the physical network, and nowadays the communication of mobile P2P (MP2P) network in various wireless environments is also developing rapidly. However, the peer in the MP2P network needs to take on both server and client roles, resulting in poor network performance and high energy consumption. Combining this feature, improving network performance and reducing system energy consumption becomes a hot issue. In order to address the problem of wasted energy consumption caused by unnecessary online behavior of partially idle peers on the server side when there are few peers on the requesting side of the network, the mechanism of spare service peers online and standard service peers sleep is applied. In the meantime, considering physical damage, peer feedback and peer impatience, impatient customers and feedback strategies are introduced. Then an M/M/c+d queueing model based on synchronous multiple vacation with fault repairable and spare servers, and variable service rates is built, which is subsequently used to simulate the performance of an MP2P network in various wireless environments, such as Wireless Mesh network (WMNs), wireless Local Area Network (WLAN), wireless Metropolitan Area network (WMAN), etc. The expressions for system performance indicators are obtained by employing quasi-birth-and-death process (QBD), matrix-geometric solution method and Gauss-Seidel iteration method. Through numerical experiments, the effects of system parameters on performance indicators of the MP2P system, such as online energy consumption, are studied. Moreover, through using Nash equilibrium and social optimal strategy, the value of the social maximum benefit under the social optimization is obtained, which provides a decision framework for the MP2P system to improve its network performance and reduce the online energy consumption.
  PubDate: 2023-03-20
Correction to: Range free localization in WSN against wormhole attack
using Farkas’ Lemma
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  PubDate: 2023-03-16
Inter-satellite link scheduling and power allocation method for satellite
networks
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  Abstract: Abstract Satellite networks have attracted a lot of attention due to their unique advantages such as wide coverage and high data rate. In particular, the use of inter-satellite links (ISLs) allows multiple satellites to collaborate to provide a wider range of services. However, it is more difficult for the design of ISLs and resource allocation with the increasing number of satellites, which further leads to high network cost. Therefore, this paper aims to design an efficient ISLs establishment scheme and power allocation method to reduce the network cost. First, the network cost optimization problem is formulated as a mixed integer linear programming. Then, with equal power allocation scheme, a Lagrange relaxation method is used to decompose the optimization problem into two subproblems, i.e., routing problem and ISLs establishment problem. Specifically, the optimal routing scheme is equivalent to solving a min-cost max-flow problem of time expanded graph. The ISLs design problem can be directly solved by using branch and bound method in parallel. Moreover, with given routing and ISL scheme, the optimal power allocation is given based on convex optimization theory. Finally, the simulation results have be provided for verifying the effectiveness of proposed algorithm.
  PubDate: 2023-03-16
Optimization of energy and delay on interval data based graph model of
wireless sensor networks
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  Abstract: Abstract Emerging applications of wireless sensor networks (WSNs) in various domain of real-life require establishment of such routing topology for wireless sensors which can balance energy consumption with delay minimization. Despite a plethora research on energy and delay optimization in this field, work on developing delay minimum and energy efficient connected routing topology on heterogenous bi-directional WSNs where each node is assigned with a power interval, remain untouched. Considering this problem, we have introduced ‘Interval data based graph model (IDGM)’ and ‘Sorted-interval data based graph model (S-IDGM)’ of WSNs to explicitly deal with nodes’ power interval and proposed ‘Energy and Delay Optimization (EDO)’ algorithm to optimize S-IDGM such that the maximum topology delay, total topology delay and maximum node’s power interval become minimum in polynomial time complexity. A new function is formulated to estimate topology delay based on link distance and link interference after showing dependency analysis between link distance and link interference on large number of WSNs towards achieving optimal solutions. Extensive simulation work, graphical and statistical t-test analysis have been carried out to show the performance of EDO algorithm in minimizing topology delay and nodes’ power consumption, better than the existing algorithms from similar grounds. t-test analysis shows that the proposed EDO algorithm achieves optimal energy saving of nodes at 5% level of significance along with optimal minimization of max and total topology delay at 2% level of significance on S-IDGMs.
  PubDate: 2023-03-16
Deep unfolding based optimization framework of fractional programming for
wireless communication systems
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  Abstract: Abstract Multiple-ratio fractional programming (FP) has been applied to the optimization of wireless communication networks, because of the signal-to-interference-plus-noise ratio terms. However, in order to find solutions, FP requires iterative processes and may include complex operations, such as binary search, eigen-decomposition, and matrix inversion. Thus, the computational complexity and delay may violate the real-time requirements of delay-sensitive applications. To tackle this challenge, we propose a deep unfolding FP (DUFP) optimization framework naturally incorporating expert knowledge and deep neural networks. By unfolding the iterative process to neural network layers, the proposed DUFP framework trains a neural network with a little number of trainable parameters offline and then finds solutions online with reduced computational complexity. In addition, the proposed DUFP approach is applied to downlink beamforming problems to validate its efficiency. Finally, simulation results show that the proposed DUFP approach can achieve a balance between performance and computational complexity.
  PubDate: 2023-03-16
A hybrid C-GSA optimization routing algorithm for energy-efficient
wireless sensor network
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  Abstract: Abstract Power saving is the fundamental concern in designing of the routing algorithms for wireless sensor networks (WSNs). In the present optimized energy-efficient routing protocol (OEERP), some sensor nodes (residual nodes) are discarded without being part of any cluster in the cluster formation process, called generation of residual nodes. Such discarded nodes transfer the inadequate information, either directly to the next best hop or to base station. In transmission of the useless control messages, energy is wasted, causes the reduction of sensor network’s life period. The key objective of this proposed scheme is to enhance the surviving period of WSN with the help of assistant cluster nodes. Energy optimization is achieved by developing an Improved-Optimized Energy-Efficient Routing Protocol (I-OEERP) which eliminates such residual nodes creation and enhances the network lifetime. The nature of the given scheme C-GSA is based on a hybrid of both Crow Search Algorithm (CSA) and Gravitational Search Algorithm (GSA). By utilizing the concepts of CSA cluster formation, residual node formation can be controlled. After that, GSA is used for routing.
  PubDate: 2023-03-16
Synchronization for dynamic complex networks combining degree distribution
and eigenvector criteria
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  Abstract: Abstract A complex network is composed of nodes and connecting edges, which can be applied to describe the structure of many real systems. Synchronization is an important behavior of dynamic complex networks. The traditional methods, such as changing network coupling mode and external control strategies, etc., cannot achieve complete network synchronization. In order to solve the network synchronization problem, in the paper, we propose a method of constructing an improved small-world network that combines degree distribution and eigenvector criteria from the viewpoint of the topology of complex networks and analyze the effects of network topology on synchronization capability. Aiming at the problem that synchronization capability is suppressed due to the uneven degree distribution during the construction of network model, we present a method of degree distribution connection to select the nodes with a smaller degree preferentially when reconnecting edges. Combining eigenvector Criteria, we also present a method of building Enhanced Synchronization Small-World, which deletes connecting edges by selecting the nodes with a larger degree and reconnects edges according to the eigenvector criterion. On this basis, we further analyze the impacts of differences in different network topologies on synchronization capability. The experimental results show that our solution is effective to construct network through the combination of degree distribution and eigenvector criterion, which can solve the network synchronization problem well by improving network topology.
  PubDate: 2023-03-15
A stochastic geometric programming approach for power allocation in
wireless networks
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  Abstract: Abstract In this paper, we consider the power allocation problem for 5 G wireless networks using massive multiple input multiple output technologies. Two non-linear optimization models are considered to maximize the worst user signal-to-interference noise ratio and the total capacity of the network subject to power constraints. In particular, we transform the first one into a geometric programming (GP) problem. Whereas the second one leads to a signomial programming formulation. The main contributions of the paper are first to propose novel formulations for power allocation in wireless networks while using stochastic, geometric, and signomial programming frameworks altogether. We derive stochastic formulations for each GP model to deal with the uncertainty of wireless channels. Secondly, since solving optimally the stochastic models represents a challenging task, we obtain tight bounds using approximation solution methods. In particular, the piece-wise linear programming and the sequential approximation methods allow us to obtain tight intervals for the objective function values of the stochastic models. Notice that these intervals contain the optimal solutions. In particular, we propose an approximated GP model that allows obtaining lower bounds for the signomial problem. This is achieved by using the arithmetic–geometric mean inequality. Finally, we compare the deterministic and stochastic models and prove the robustness of the stochastic models. Notice that we solve all the instances and obtain near-optimal solutions for most of them.
  PubDate: 2023-03-14
Increasing quality of service in wireless local area networks through
fuzzy logic based feedback control method
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  Abstract: Abstract In many studies aimed at improving the quality of service (QoS) in wireless local area networks (WLAN), the performance was improved by applying non-ACK model, physical interference model, analytical models etc. with using optimization algorithms with stable simulations. For efficient QoS in WLANs, performance is generally increased using 802.11n medium access control protocol through request to send threshold value (RSTV), fragmentation threshold value (FTV) and buffer size (BS) parameters. While the RSTV activates the request to send/clear to send (RTS/CTS) mechanism in carrier sense multiple access with collision avoidance (CSMA/CA) protocol, FTV fragments the larger packets during CSMA/CA transmission, reducing the packet loss in WLANs. BS, however, is the memory used in the CSMA/CA model to reduce cost. In previous studies, most of the new model applied in process layers by using Riverbed Modeler simulation tool and ideal input values had been obtained for RSTV, FTV and BS during the simulation stable. In this study, a new model proposed for CSMA/CA protocol on the process layers which used feedback controlled method with fuzzy logic to improve QoS during the simulation. Values obtained with nearly six million different test results, has been revealed that throughput was increased by 26.48%, the channel utilization by 2.30%, the data traffic received by 14.59% and the data traffic sent by 17.06% respectively. While RSTV, FTV and BS input parameters are optimized with the help of the feedback controlled algorithm used in these studies, the effects of external parameters such as number of nodes, inter-arrival time, transmitting power etc. on the performance improvements in the model are demonstrated in graphics. All these test results have shown that the new model provides a high rate of performance improvement for WLANs.
  PubDate: 2023-03-14
Design of an adaptive framework with compressive sensing for spatial data
in wireless sensor networks
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  Abstract: Abstract Wireless Sensor Networks (WSNs) gather active sensor data within a specified period to the sink node. The data transmission in restricted resource utilization in wireless surroundings is a primary issue. Compressive sensing enables resource utilization based on spatial data by exploiting the transfer of limited measurements according to the original signals. In this paper, an Adaptive Adjacent based Compressive Sensing (AACS) methodology is proposed for effective data construction in spatial-related wireless sensor networks. A sparse Matrix is constructed with the coordinates of location and position for data transmission. The fuzzy logic is used to find the best forwarder among the sensor nodes in the network using the parameters of Mobility, Energy, and Fuzzy cost. Within a sensing time, the sensor node forwards the data around the time to the adjacent node according to a correlation. The communication time provides proficient enhancement with compressed data with AACS and sparse index. Therefore, AACS gives a reduced amount of communication and maximizes accuracy. AACS is compared with the related techniques and the results prove that the proposed methodology performed well in the performance metrics. The performance analysis shows that the proposed technique has produced 54.7% of network throughput than the relevant technique, 76.9% lesser routing overhead, and 44% of minimized relative error.
  PubDate: 2023-03-14
High gain substrate integrated waveguide antenna with enhanced bandwidth
for millimeter-wave wireless network applications
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  Abstract: Abstract A high-gain slotted waveguide antenna in substrate-integrated waveguide (SIW) configuration with enhanced bandwidth is proposed. Two different cases fabricated using Rogers RO 4003 substrate over a small area of 16 × 4.5 × 0.508 mm3 are discussed. SIW-based antenna having four longitudinally placed slots is studied with the help of simulation and experimental studies. Experimental results revealed that the proposed hourglass-shaped slot effectively enhanced the operation bandwidth without using additional complicated mechanisms. Improvement in bandwidth was achieved from the low-Q characteristics of the hourglass-shaped slots evidenced through the Z11 impedance analysis. The proposed hourglass-shaped slotted waveguide antenna exhibited 3.18% (37.09–38.29 GHz) impedance bandwidth with 5.8 dBi antenna gain at 38 GHz, where 1.08% bandwidth improvement was observed. Such low-profile planar structure resonating at mm-wave frequency band having high gain and improved bandwidth can be a suitable choice for integration with devices working in wireless network applications.
  PubDate: 2023-03-14
Applying machine learning enabled myriad fragment empirical modes in 5G
communications to detect profile injection attacks
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  Abstract: Abstract In order to facilitate communication, wireless networks are built from a collection of nodes that may be either static or dynamic. They are acquiring a lot of popularity in the area of research due to the fact that they are ad hoc in nature, and the number of users of mobile devices is rising day by day. Because of the ease with which these networks may be deployed in challenging and unsupervised rural places, the exchange of information has been a reality since the invention of these networks. Mobile ad hoc networks are simple to set up because of the properties that allow for self-organization and the fact that the medium is wireless. A lack of centralized fixed infrastructure, flexibility to frequent change in topologies, and other features like these are some of the other things that draw people's attention to wireless networks. Wireless networks are vulnerable to a wide range of assaults since their nodes are able to move around and their topologies are constantly changing. In addition, MANET operates in an environment that is both open and dynamic, which leaves it subject to a variety of threats from other types of network assaults. Routing protocols are almost always the target of one form or another of the same general category of attacks. Eavesdropping, causing damage, changing routing information, deleting routing information, manipulating information, advertising phoney routes, and misrouting information are all potential components of these assaults. The circumstances may make it difficult to maintain confidentiality in any communications. There are many different kinds of assaults, and each one may damage wireless networks on a different tier of the communication stack and bring the performance of the network down. Eavesdropping, jamming, traffic analysis and monitoring, denial of service attacks, grey hole attacks, black hole attacks, and wormhole assaults are a few examples of the many sorts of attacks that fall under this category. Ad-hoc networks are more susceptible to security breaches than traditional wired and wireless networks due to the usage of open wireless medium, dynamic topology, and dispersed and cooperative channel sharing. The wormhole attack on dispersed wireless networks is being described here by the person who conducted this study. Because this assault is so potent, it is very difficult to identify it before it has ever been launched. The invader may simply initiate it without having knowledge of the network or compromising any authorized nodes, which is a need for launching it. During a wormhole attack, a malicious node in one part of the network takes control of the packets and tunnels them to another hostile node in a different part of the network, which then repeats the packets locally. The thesis aims to do two things at the same time: (a) To simulate a variety of possible wormhole assaults on the MANET network (b) To investigate the functionality and efficiency of the proposed secure routing protocol within the context of these simulated attacks on the network.
  PubDate: 2023-03-14
Dependency-aware task offloading based on deep reinforcement learning in
mobile edge computing networks
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  Abstract: Abstract With the rapid development of innovative applications, lots of computation-intensive and delay-sensitive tasks are emerging. Task offloading, which is regarded as a key technology in the emerging mobile edge computing paradigm, aims at offloading the tasks from mobile devices (MDs) to edge servers or the remote cloud to reduce system delay and energy consumption of MDs. However, most existing task offloading studies either didn’t consider the dependencies among tasks or simply designed heuristic schemes to solve dependent task offloading problems. Different from these studies, we propose a deep reinforcement learning (DRL) based task offloading scheme to jointly offload tasks with dependencies. Specifically, we model the dependencies among tasks by directed acyclic graphs and formulate the task offloading problem as minimizing the average cost of energy and time (CET) of users. To solve this NP-hard problem, we propose a deep Q-network learning-based framework that creatively utilizes deep neural networks to extract system features. Simulation results show that our proposed scheme outperforms the existing DRL scheme and heuristic scheme in reducing the average CET of all users and can obtain near-optimal solutions.
  PubDate: 2023-03-14
Interference mitigation for non-orthogonal multiple access in
heterogeneous networks
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  Abstract: Abstract Non-orthogonal multiple access (NOMA) technique is a promising alternative for enhancing network sum-rate while increasing the interference experienced by the users. In heterogeneous networks, the signal of a NOMA user is affected by three types of interference; intra-cell, inter-cell, and inter-tier. In an environment with high interference, using orthogonal multiple access (OMA) along with NOMA is beneficial to improve the edge user performance. This work proposes a hybrid model, where NOMA and OMA are deployed together in the same spectrum band. The performance of hybrid model is compared to NOMA and OMA for heterogeneous networks by stochastic geometry analysis. The analysis includes pico- and femto-cell alternatives to elaborate varying interference conditions. Using the capacity analysis formulation of NOMA, a power level optimization framework is presented for maximum sum-rate and fairness objectives. Besides, two pairing methods, near-to-near and near-to-far pairing, are included from the literature to reveal pairing effect on user-specific and system-level performance. The numerical results indicate NOMA trade-offs for increasing edge user capacity by power optimization and resistance of hybrid model to interference under different conditions.
  PubDate: 2023-03-13
Improved 3D localization algorithm for large scale wireless sensor
networks
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  Abstract: Abstract As localization represents the main core of various wireless sensor network applications, several localization algorithms have been suggested in wireless sensor network research. In this article, we put forward an iterative bounding box algorithm enhanced by a Kalman filter to refine the unknown node’s estimated position. In fact, several research efforts are currently in progress to extend the 2D positioning algorithm in WSNs to 3D that reflects reality and the most practical applications. Subsequently, we replace a large number of GPS-equipped anchors with a single mobile anchor. In our studies, we consider the type of range-free sensor network exploiting the wireless sensors connectivity. We assess the performance of our algorithm using exhaustive experiments on several isotropic and anisotropic topologies. Our proposed algorithm can fulfill the joint goals of algorithm transparency and accuracy for various scenarios by evaluating parameters such as localization accuracy whilst changing other simulation parameters such as the effect of communication range, mobile anchor node position and sensor node deployment topology. It has been proven by the results of the experiments that the proposed algorithm effectively reduces the location error without requiring more equipment or increasing the communication cost.
  PubDate: 2023-03-13
A new localization mechanism in IoT using grasshopper optimization
algorithm and DVHOP algorithm
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  Abstract: Abstract Nowadays, different types of computer networks such as Wireless sensor networks (WSNs), the Internet of things (IoT), and wireless body area networks (WBANs) transfer information, share resources, and process information. The IoT is a novel network which interconnects various smart devices and can consist of heterogeneous components such as WSNs for monitoring and collecting information. Characterized by specific advantages, the IoT contains different types of nodes, each with few sensors to collect environmental information on agriculture, ecosystem, search and rescue, conflagrations, etc. Despite extensive applications and high flexibility in the modern world, the IoT faces specific challenges, the most important of which include routing, energy consumption and localization. Localization leads to other network challenges and thus can be considered the most important challenge in the IoT. Localization refers to a process aiming at determining the positions and locations of objects lacking global positioning system (GPS) and needing to use the information of network sensors and topology to estimate their own positions and locations. The distance vector hop (DV-Hop) algorithm is a range-free localization technique, in which the major challenge is that the number of hops between two nodes is multiplied by a number that is the same for all nodes leading to a significant reduction in the localization accuracy. In the method proposed in this paper, a network node with no GPS determines the hops from three anchor nodes with GPS. The location of smart objects can be then estimated according to distances from those anchor nodes. Thereafter, a few positions can be created nearby to mitigate the error. Then each position can be regarded as a member of the grasshopper optimization algorithm (GOA) to minimize the localization error. According to the results obtained from implementation of the proposed algorithm, it is characterized by a lower localization error than grasshopper optimization, butterfly optimization, firefly and swarm optimization algorithms.
  PubDate: 2023-03-13
Downlink AP coordination based OFDMA and NOMA protocols for the
next-generation WLANs
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  Abstract: Abstract In recent years, with the increasing number of terminal connections, high-density deployment scenarios have become important scenarios for future wireless networks. Ultra-high throughput (EHT) in high density deployment scenarios is the technical goal of IEEE 802.11be, the next-generation wireless local area network (WLAN) standard. However, in a high-density deployment scenario, interference suppression between BSSs is serious, which seriously affects the throughput of a WLAN. And the resources available are limited. Therefore, for the next generation WLAN standard, this paper proposes a downlink transmission scheme based on AP coordination and the orthogonal frequency division multiple access (OFDMA) protocol and the non-orthogonal multiple access (NOMA) protocol, named Co-OFDMA–NOMA scheme. The core idea is to transform the interference and suppression relationship between neighboring BSSs into the relationship of mutual coordination and assistance through the Co-OFDMA–NOMA protocol proposed in this paper. Firstly, a downlink transmission scheme named the Co-OFDMA–NOMA protocol is designed. In addition, the protocol and its framework structure have good backward compatibility. Theoretical analysis shows that the proposed Co-OFDMA–NOMA protocol has significant performance gain, and simulation results prove the effectiveness of the scheme.
  PubDate: 2023-03-13
Securing FPGAs in IoT: a new run-time monitoring technique against
hardware Trojan
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  Abstract: Abstract In this paper, we propose a new run-time monitoring technique to detect hardware Trojan (HT) on working field-programmable gate array (FPGA), which is helpful for reinforcing the hardware security of IoT devices. First, we place multiple temperature sensors on FPGA and collect their value at each time interval. Then, we construct a predictive model which can estimate the distribution of sensor frequency in real-time. If the difference between the predicted value and the real one surpasses a dynamically updated threshold, an HT activation is reported. The experiment results reveal that our technique has high detection accuracy (≥ 98%), low false negative ratio (≤ 1.5%) and zero false positive ratio under various FPGA HT benchmarks.
  PubDate: 2023-03-11