Communication Algorithms Research Articles

RETRACTED ARTICLE: Intelligent fuzzy rule-based approach with outlier detection for secured routing in WSN

In wireless sensor networks (WSNs), energy optimization and the provision of security are the major design challenges. Since the wireless sensor devices are energy constrained, the issue of high energy consumption by the malicious nodes must be addressed well in order to enhance the network performance by making increased network lifetime, reduced energy consumption and delay. In the past, many researchers worked in the provision of new techniques for providing improved security to WSN in order to enhance the reliability in the routing process. However, most of the existing routing techniques are not able to achieve the required security through the use of intelligent techniques for safeguarding the sensor nodes from malicious attacks. In order to address these problems, a new fuzzy temporal clustering-based secured communication model with trust analysis and outlier detection has been developed in this research work. For this purpose, a new fuzzy temporal rule-based cluster-based routing algorithm with trust modelling and outlier detection for monitoring the nodes participating in the communication has been proposed. In addition, a fuzzy temporal rule- and distance-based outlier detection algorithm is also proposed in this paper for distinguishing the malicious nodes from other nodes within each cluster of the network and has been used in the secured routing algorithm. The proposed secure routing algorithm uses the temporal reasoning tasks of explanation-based learning and prediction as well as spatial constraints for making efficient routing decisions through the application of trust and key management techniques for performing effective authentication of nodes and thereby isolating the malicious nodes from communication through outlier detection. By applying these two proposed algorithms for communication in the proposed work, it is proved through experiments that the proposed secure routing algorithm and the outlier detection algorithm are able to perform secured and reliable routing through genuine cluster head nodes more effectively. Moreover, these two algorithms provide improved quality of service with respect to the reliability of communication, packet delivery ratio, reduction in end-to-end delay and reduced energy consumption.

FedOpt: Towards Communication Efficiency and Privacy Preservation in Federated Learning

Artificial Intelligence (AI) has been applied to solve various challenges of real-world problems in recent years. However, the emergence of new AI technologies has brought several problems, especially with regard to communication efficiency, security threats and privacy violations. Towards this end, Federated Learning (FL) has received widespread attention due to its ability to facilitate the collaborative training of local learning models without compromising the privacy of data. However, recent studies have shown that FL still consumes considerable amounts of communication resources. These communication resources are vital for updating the learning models. In addition, the privacy of data could still be compromised once sharing the parameters of the local learning models in order to update the global model. Towards this end, we propose a new approach, namely, Federated Optimisation (FedOpt) in order to promote communication efficiency and privacy preservation in FL. In order to implement FedOpt, we design a novel compression algorithm, namely, Sparse Compression Algorithm (SCA) for efficient communication, and then integrate the additively homomorphic encryption with differential privacy to prevent data from being leaked. Thus, the proposed FedOpt smoothly trade-offs communication efficiency and privacy preservation in order to adopt the learning task. The experimental results demonstrate that FedOpt outperforms the state-of-the-art FL approaches. In particular, we consider three different evaluation criteria; model accuracy, communication efficiency and computation overhead. Then, we compare the proposed FedOpt with the baseline configurations and the state-of-the-art approaches, i.e., Federated Averaging (FedAvg) and the paillier-encryption based privacy-preserving deep learning (PPDL) on all these three evaluation criteria. The experimental results show that FedOpt is able to converge within fewer training epochs and a smaller privacy budget.

Heterogeneous V2V Communications in Multi-Link and Multi-RAT Vehicular Networks

Connected and automated vehicles will enable advanced traffic safety and efficiency applications thanks to the dynamic exchange of information between vehicles, and between vehicles and infrastructure nodes. Connected vehicles can utilize IEEE 802.11p for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. However, a widespread deployment of connected vehicles and the introduction of connected automated driving applications will notably increase the bandwidth and scalability requirements of vehicular networks. This paper proposes to address these challenges through the adoption of heterogeneous V2V communications in multi-link and multi-RAT vehicular networks. In particular, the paper proposes the first distributed (and decentralized) context-aware heterogeneous V2V communications algorithm that is technology and application agnostic, and that allows each vehicle to autonomously and dynamically select its communications technology taking into account its application requirements and the communication context conditions. This study demonstrates the potential of heterogeneous V2V communications, and the capability of the proposed algorithm to satisfy the vehicles' application requirements while approaching the estimated upper bound network capacity.

V2VR: Reliable Hybrid-Network-Oriented V2V Data Transmission and Routing Considering RSUs and Connectivity Probability

Vehicular ad hoc networks (VANETs) have been widely used in intelligent transportation systems (ITSs) for purposes such as the control of unmanned aerial vehicles (UAVs) and trajectory prediction. However, an efficient and reliable data routing decision scheme is critical for VANETs due to the feature of self-organizing wireless multi-hop communication. Compared with wireless networks, which are unstable and have limited bandwidth, wired networks normally provide longer transmission distances, higher network speeds and greater reliability. To address this problem, this paper proposes a reliable VANET routing decision scheme based on the Manhattan mobility model, which considers the integration of roadside units (RSUs) into wireless and wired modes for data transmission and routing optimization. First, the problems of frequently moving vehicles and network connectivity are analyzed based on road networks and the motion information of vehicle nodes. Second, an improved greedy algorithm for vehicle wireless communication is used for network optimization, and a wired RSU network is also applied. In addition, routing decision analysis is carried out in accordance with the probabilistic model for various transmission ranges by checking the connectivity among vehicles and RSUs. Finally, comprehensive experiments show that our proposed method can support real-time planning and improve network transmission performance compared with other baseline protocol approaches in terms of several metrics, including package delivery ratio, time delay and wireless hops.

Data Fusion Algorithm of Power Line Carrier Communication Based on Minimum Spanning Tree Theory

With the expansion of the clean energy photovoltaic power generation systems, the requirements of communication and data exchange capacity become higher and higher. The status information of each photovoltaic unit should be collected. However, when the number of PV units is too large or the collection frequency is too high, it will generate huge amount of data to the communication system. If each monitoring terminals transmits the data to the master station independently, the huge traffic flows occupy bandwidth and reduce the communication efficiency, which also affect the real-time monitoring of the photovoltaic system. To solve this problem, this paper proposed a novel data fusion algorithm for power line carrier communication based on minimum spanning tree transmission path. The data fusion packet format is also presented. Finally, the effectiveness of the proposed algorithm is proved by comparing the amount of data brought by the fusion algorithm and the non-fusion algorithm.

Anti-interference Algorithm for Broadband Wireless Communication based on Embedded Microcontroller

In order to improve the reliability of broadband wireless communication, the anti-interference design of broadband wireless communication in embedded environment is carried out, and an anti-interference algorithm of broadband wireless communication based on embedded microcontroller is proposed. The hardware of the anti-interference device is mainly composed of the communication modulating module, ARM main control system module and the single chip microcomputer main control module. The anti-interference algorithm is designed by using inter-symbol interference suppression algorithm, and the data transmission channel distribution model of broadband wireless communication is constructed. The interference filtering of broadband wireless communication is based on the decision feedback equalization method. The simulation results show that the anti-interference design of broadband wireless communication using this method has strong anti-interference ability, the output SNR is higher than that of the traditional method, and the communication quality is improved.

Design and evaluation of a high-sensitivity digital receiver with the finite impulse response filter algorithm for free-space laser communication

We discuss the design of a digital laser communication receiver and its sensitivity test process. Laser communication is especially suitable for long-distance low-power micro–nano satellite links due to its narrow beam width, but the electro-optical noise situation of the micro–nano satellite platform is complicated and bad. Hence, it is necessary to introduce a digital laser communication receiver to flexibly suppress interference and noise to improve communication sensitivity. A digital laser communication receiver based on the avalanche photodiode (APD) is designed. Based on the principle of digital communication error probability, a high-sensitivity APD device is selected, and a digital receiving channel based on field programmable gate array is designed. The finite impulse response, the dynamic threshold, the baseband median, and other filtering algorithms are used to optimize the signal-to-noise ratio and enhance the detection sensitivity. At the same time, an 800-nm laser communication receiver sensitivity test experimental architecture is designed and the detection sensitivity experiment is carried out. The experiment indicates that the APD receiver achieves detection sensitivity at an Mbps rate better than −60 dBm. The digital filtering algorithm provides a filtering signal-to-noise ratio improvement of about 15 dB, which supplies a reference for the receiver design of micro–nano satellite laser communication.

A Novel Area-Power Efficient Design for Approximated Small-Point FFT Architecture

Fast Fourier transform (FFT) is an essential algorithm in digital signal processing and advanced mobile communications. With the continuous development of modern technology, the area-power efficient hardware implementation of FFT has attracted a lot of attention. In this article, a novel design for FFT implementation is proposed. The number of resource-expensive multiplications in our design is decreased by a twiddle factor merging technique that reduces the hardware area. Subsequently, a common subexpression sharing scheme is applied to reuse the hardware resources to further save the hardware area. In addition, a magnitude-response aware approximation algorithm is proposed for applications where the transformation accuracy can be compromised a little bit for lesser hardware area and power dissipation. Logic synthesis shows that the proposed 16-point FFT architecture can save hardware area and power dissipation on application-specific integrated circuit (ASIC) by up to 65.7% and 53.1% compared with recently published designs. Similarly, the proposed 32-point FFT architecture achieves up to 58.8% reduction on hardware area and 60.0% reduction on power dissipation on ASIC.

Particle Swarm Optimization based Power Control Algorithms for SWIPT-Assisted D2D Communications Underlaying Cellular Networks

We studied power control algorithms for SWIPT-assisted D2D communications underlaying cellular networks in this paper. The particle swarm optimization (PSO) based power control algorithm is put forward to mitigate the interference and enhance the sum throughput of D2D networks. In order to avoid falling into the local optimum, we combined simulated annealing with particle swarm optimization(SA-PSO) to improve performance of the algorithm. The main idea is to allocate proper transmitting powers to D2D links while maximizing the total throughput. Unlike other related works, the transmitting power and the power splitting ratio are both optimized in this paper. Simulation results demonstrate our algorithms are conductive to boosting the total throughput of D2D networks. The PSO and SA-PSO based algorithms outperform the game-theory based algorithm in terms of the sum throughput of D2D networks.

Energy and Time Efficient Route Discovery in Manet using Modified Aodv Routing Protocol

In MANET usually nodes interact with each other either directly or by relaying nodes depending on whether nodes present are in vicinity of each other or not respectively. There are different routing protocols which work on the principle either of demand or not. AODV is a reactive routing protocol which performs on the strategy of shortest hop in its vicinity. Sometimes there is a route failure in network then some message is sent to the node if reply is not received with in time frame then for sure path is broken. So it is wastage of time and energy of all the participating nodes. Main reason behind the node failure is the sustaining energy of the participating nodes in the communication. Since nodes which have very less energy gets consumed when these try to send either data or reply to and from the nodes. Sometimes a node has minimum energy to send data. As soon as it sends data it is switched off and does not send delivery successful reply to the originating network. So in this case network thinks path is broken so message is again sent to another path. So here it again there is loss of energy of other communicating node and also wastage of time to send data to nodes. In this research work, an energy and time efficient approach will be proposed which will save time as well as energy of remaining nodes which further utilizes all the known linked paths simultaneously for transmitting data with the help of AODV routing protocol. Different simulation parameters are used to check the accuracy of approach. Simulation is performed on NS-3. There will be 50 to 100 nodes in the topology. Performance metrics like throughput, energy deviation, packet lost, packet delivery ratio and other will be used for performance checking with respect to standard AODV routing protocol. This research work provides the improvements to the existing algorithms of communication among network nodes in mobile ad-hoc networks (MANET) to obtain better results.

A Lifetime-Enhancing Method for Directional Sensor Networks with a New Hybrid Energy-Consumption Pattern in Q-coverage Scenarios

An important issue in directional sensor networks (DSNs) is how to prolong the network lifetime in Q-coverage scenarios where each target point may have different coverage requirements. When the Q-coverage requirement is met, it is an effective way to maximize the network lifetime by controlling energy consumptions. Unlike the existing results where only the sensing energy consumption is considered, this paper proposes a new hybrid energy consumption pattern, which reflects the reality of energy consumptions more closely. In such a pattern, both sensing and communication energy consumptions are considered. By combining scheduling and clustering technologies to control these two kinds of energy consumptions in each round, a new lifetime-enhancing method (NLEM) is devised to prolong the network lifetime. First, a sensing direction scheduling algorithm for Q-coverage is proposed to make different sensing direction sets meet the coverage requirement of each target point. Then, a new cluster head selection algorithm and an inter-cluster communication algorithm are developed to select an optimal cluster head set and achieve multi-hop communication, respectively. Simulation results demonstrate the effectiveness of the NLEM in prolonging the network lifetime for DSNs in Q-coverage scenarios.

Development and pilot of a prescription drug monitoring program and communication intervention for pharmacists.

Pharmacists' role in addressing the opioid crisis continues to expand, but lack of training specifically related to standardized prescription drug monitoring program (PDMP) use and communication strategies for provider and patient interactions remains a significant issue. We developed the Resources Encouraging Safe Prescription Opioid and Naloxone Dispensing (RESPOND) Toolkit to enhance community pharmacists' understanding of their role in addressing opioid safety; improve integration of PDMP into daily workflow; and enhance communication between pharmacists, prescribers, and patients. To describe the development of RESPOND Toolkit and summarize findings from initial pilot testing. RESPOND development was informed by focus groups with patients, prescribers, and pharmacists and an external advisory committee. Materials developed include a patient screening & communication algorithm, a provider communication checklist and an online continuing education course with three distinct modules. The RESPOND Toolkit was pilot tested in six community pharmacies in Oregon across two 6-month intervention phases. Pilot data collection included a pre-post intervention survey, pre-post knowledge assessment quizzes within the online course, and post-intervention semi-structured interviews. Interview feedback informed revisions after each phase to shape the final content, flow, and delivery of RESPOND. Sixteen of 21 pharmacists completed the online training, revealing a large, significant effect on knowledge gain across the three training modules (pre-score 57, post-score 84; p<0.001; Cohen's d=1.85). Of these participants, 10 also completed the baseline and post intervention survey and showed non-significant moderate improvements in knowledge, perceived behavioral control, and self-efficacy to address opioid safety issues. The RESPOND Toolkit has promise as an effective and scalable approach to providing community pharmacist-tailored training, especially in the areas of effective communication and workflow integration, to promote behavioral shifts supporting opioid safety for patients. Further development and testing in a larger sample is warranted.

Priority Based Time-Division Multiple Access Algorithm for Medium Range Data Communication in Very High Frequency Radios

In this paper, A novel and efficient time division multiple access (TDMA) algorithm for military last-mile data communication is designed. A dynamic slot assignment method coupled with an out-of-band control mechanism is used for the proposed design. In out-of-band, there is a well-defined control segment along with the data segment. So, if a new node specifically a high priority node arrives at the network, it can signal its arrival by a response in the designated mini-slots and can also check the slot in the network, if no idle slots are available. Assigning priority to the nodes would also ensure the delivery of the important messages first. Query messages are broadcasted by the Central node in order to detect new nodes. This reduces nodes working time and also ensures that the nodes don’t interrupt any existing communication. Furthermore, we describe the feasibility and the reliability of this algorithm for military’s last-mile (end user) data communication.

Revisiting Lightweight Encryption for IoT Applications: Error Performance and Throughput in Wireless Fading Channels With and Without Coding

Employing heavy conventional encryption algorithms in communications suffers from added overhead and processing time delay; and in wireless communications, in particular, suffers from severe performance deterioration (avalanche effect) due to fading. Consequently, a tremendous reduction in data throughput and increase in complexity and time delay may occur especially when information traverse resource-limited devices as in Internet-of-Things (IoT) applications. To overcome these drawbacks, efficient lightweight encryption algorithms have been recently proposed in literature. One of those, that is of particular interest, requires using conventional encryption only for the first block of data in a given frame being transmitted. All the information in the remaining blocks is transmitted securely without the need for using heavy conventional encryption. Unlike the conventional encryption algorithms, this particular algorithm achieves lower overhead/complexity and higher data throughput. Assuming the additive white Gaussian noise (AWGN) channel, the performance of the lightweight encryption algorithm under study had been evaluated in literature in terms of throughput under the assumption that the first block, that undergoes conventional encryption, is free of error, which is practically unfeasible. In this paper, we consider the AWGN channel with Rayleigh fading and assume that the signal experiences a certain channel bit error probability and investigate the performance of the lightweight encryption algorithm under study in terms of bit error probability and throughput. We derive analytical expressions for these performance metrics considering modulated signals with and without coding. In addition, we propose an extension to the lightweight encryption algorithm under study by further enhancing its security level without significantly affecting the overhead size and processing time. Via numerical results we show the superiority of the lightweight encryption algorithm under study over the conventional encryption algorithms (like the AES) and the lightweight encryption algorithms proposed in literature in terms of error and throughput performance.

Intelligent Resource Allocation for Train-to-Train Communication: A Multi-Agent Deep Reinforcement Learning Approach

The application of train-to-train (T2T) communication in urban rail transit is expected to simplify system structure, reduce maintenance costs, and improve operational efficiency. In particular, train-to-wayside (T2W) communication coexist with T2T communication in the train control system based on T2T communication. To make full use of limited spectrum resources, frequency reuse is adopted as an efficient technique, but it brings the co-channel interference unfortunately, which affects the quality of service (QoS) for T2T and T2W users. In this paper, we propose a multi-agent deep reinforcement learning (MADRL) based autonomous channel selection and transmission power selection algorithm for T2T communication to reduce the co-channel interference. Specifically, each agent interacts with the environment and selects actions to implement a distributed resource allocation mechanism independently, adopting asynchronous updates to avoid different agents choosing the same sub-band. Simulation results show the superiority of our proposed algorithm: compared with the existing resource allocation schemes for T2T communication, the system throughput and the successful transmission probability of T2T links are greatly improved.

Intelligent modulation recognition algorithm for optical communication

In order to improve the modulation recognition algorithm effect of an optical communication system, an improved modulation recognition algorithm technology based on wavelet transform on the time-varying optical communication system is designed. Firstly, considering the time-varying effect of noise on the communication system, wavelet transform is introduced to pre-process the signal of the optical communication system, extracting the characteristic number of modulation recognition of optical communication system, and a classifier of modulation recognition is established by data mining technology to realize modulation recognition technology of optical communication system. Finally, several typical modulation modes of the optical communication system are tested by simulated experiments. In this paper, several typical modulation modes are identified accurately, and real-time on-line analysis of modulation recognition is realized. In the optical communication system, the recognition accuracy of the modulation pattern is higher than other modulation recognition technologies, which has high practical application value.

Martingales-Based ALOHA-Type Grant-Free Access Algorithms for Multi-Channel Networks With mMTC/URLLC Terminals Co-Existence

As a simple single-phase transmission strategy, grant-free access is believed to be an effective way to guarantee the stringent quality of service (QoS) requirements for ultra-reliable low-latency communications (URLLCs). However, unless a theory-based fine evaluation on dynamic delay, we cannot hope to overcome the natural defects of random access and so effectively utilize the time-frequency resources. In this paper, we propose a novel multi-channel ALOHA-type (M-ALOHA) grant-free access algorithm for heterogeneous machine type communication (MTC) networks with URLLC-type terminals and delay-tolerant massive MTC (mMTC)-type terminals co-existence. Firstly, we construct a statistical service model characterizing the transmission rate of each terminal with joint consideration of the features of M-ALOHA access scheme, short packet transmissions and frequency-selective fading channel. Then, taking the great advantages of service-martingales theory in random queuing analysis, we present an ingenious delay analysis and obtain the martingales-based formulation of delay-bound violation probability, where the sporadic feature of MTC traffic arrival is carefully addressed. Finally, the M-ALOHA algorithm is formulated as a system throughput maximization problem subject to martingales-based statistical delay-QoS and the total bandwidth of system. The problem is solved by the proposed bi-objective multi-variable-grey wolf optimizer (BOMV-GWO) algorithm. As a result, we obtain the access probability for each terminal and the optimal parameters for the system design, including the number of sub-channels, the bandwidth for each sub-channel and the packets transmission rate. Simulation results demonstrate that the performance of our M-ALOHA algorithm is favorable.

Scheduling Algorithm supporting V2X Communications based on NOMA access

5G promises very high throughput and low latency. It will be able to support the exchange of large amounts of data with a wide variety of communications, including Vehicle-to-Everything (V2X) services. Conventional resource allocation techniques based on orthogonal multiple access (OMA) appear to be unsuitable for a dense network due to limited resources available. This work presents a new planning algorithm called SAVCN (Scheduling Algorithm for V2X Communication based on NOMA), for the 5G network. The main feature of NOMA is the same resource can be shared by multiple users. The purpose of our algorithm is to improve network performance in terms of throughput, equity, the number of V2X users served and error rates. In fact, SAVCN efficiently allocates available resource blocks (Rbs) to maximize system throughput by taking into account a well-defined criterion on the minimum distance between transmitters and receivers. The simulation results indicate promising performance for SAVCN.

Energy Efficiency Optimization and Dynamic Mode Selection Algorithms for D2D Communication Under HetNet in Downlink Reuse

Device-to-Device communication (D2D) is a promising technique for improving fifth-generation cellular network (5G) spectrum and energy efficiency. However, limited user power and co-channel interference make designing an energy efficient D2D communication a difficult task. In this paper, a novel framework is proposed to optimize the energy efficiency of D2D communication coexisting with a heterogeneous network (HetNet) in downlink transmission. This optimization problem is mathematically formulated in terms of mode selection, power control, and resources allocation (i.e., NP-hard problem). The optimization fraction problem is simplified based on network load and is solved using different optimization methods. An innovative dynamic mode selection based on Fuzzy clustering is introduced. Proposed scheme performance is evaluated and compared to the standard algorithm. Simulation demonstrated the advantage of the proposed framework in terms of gain performance in both energy efficiency and number of successfully connected D2D users. Moreover, D2D communication improves energy efficiency of the heterogeneous network of Downlink transmission.

СКЛАДНІСТЬ АЛГОРИТМУ ОЦІНЮВАННЯ ФУНКЦІОНАЛЬНОЇ БЕЗПЕКИ ІНФОРМАЦІЙНИХ ТЕХНОЛОГІЙ ДЛЯ СТВОРЕННЯ ГАРАНТОЗДАТНИХ АВТОМАТИЗОВАНИХ СИСТЕМ

The complexity of the algorithm of communication of the system of linear levels with open regular parts by means of list decoding of "shortened" codes of reed painters which are intended for use in methods of an estimation of functional safety of cryptographic algorithms of cryptographic subsystems of the guaranteed automated systems creating on objects of critical infrastructure and socially important objects. This paper proposes solving problems to assess the complexity of the proposed algorithm. As a result, the upper estimates of the average labor productivity for the general case and the maximum complexity of the proposed algorithm for many special reviews related to the restoration of the formed linear results of the maximum period over a field of two elements. The achievable upper part of the list, which is formed using the proposed algorithm, is also indicated. The obtained results indicate that with certain collaborations between the parameters of the previously proposed algorithm, the time complexity was changed in comparison with the previously known deterministic algorithm for a similar purpose, which is based on the fast Hadamara transformation. This means that a more effective tool can be used to assess the impact of cryptographic subsystems on powerful cyberattacks to obtain a more accurate assessment of their functional security.