Search

Recent advances in unmanned aerial vehicle (UAV) technology have revolutionized various industries, finding applications in embedded systems, autonomy, control, security, and communication. Autonomous UAVs are distinguished by their ability to make informed decisions, anticipate potential scenarios, and learn from past experiences with the help of AI algorithms. This paper examines a practical monitoring system with an autonomous UAV, a charging station, and multiple targets that move randomly within a defined mission area. The mission area is divided into zones, and the UAV navigates through these zones efficiently. The primary objective is to maximize the probability of detecting targets, considering constraints such as limited battery life and charging station location. This challenge is initially framed as a search benefit maximization problem and subsequently reformulated as a Markov Decision Process (MDP) problem. To address the MDP formulation, we introduce a reinforcement learning (RL)-based approach that enables the UAV to comprehend unpredictable multi-target movements autonomously. The placement of the charging station in the proposed system is determined using the optimal median approach. The simulation results demonstrate that the proposed RL-based detection system significantly outperforms the reference systems in terms of detection rate and convergence. [ABSTRACT FROM AUTHOR]

The expansion of smart home devices has revolutionized residential living by offering convenience and improved energy efficiency. However, this also increases potential vulnerabilities. Traditional centralized intrusion detection systems (IDS) are unsuitable for smart homes due to privacy, scalability, and distribution concerns. Consequently, Machine Learning (ML)-based IDSs have emerged as efficient solutions. Nevertheless, conventional ML approaches are centralized, which poses privacy risks and increases communication overhead. To address these issues, this paper proposes a novel fog-federated learning (2FIDS)-based IDS for the smart home ecosystem. The 2FIDS adopts a decentralized architecture, allowing devices to train a detection model while preserving local data privacy collaboratively. Furthermore, it is deployed at the fog layer, enabling efficient and localized anomaly detection. Extensive evaluations using three datasets, the Bot-IoT, TON-IoT, and MQTTset datasets, demonstrate that the 2FIDS model achieves high detection accuracy, consistently exceeding 96% across various attack types in the Bot-IoT and TON-IoT datasets and 86% for MQTTset dataset. It exhibits robust scalability, maintaining performance as fog nodes increase from 5 to 15. The federated learning approach effectively preserves data privacy while improving upon traditional centralized methods in terms of communication efficiency and latency reduction. [ABSTRACT FROM AUTHOR]

Flying Ad‐Hoc Network (FANET) is a promising ad hoc networking paradigm that can offer new added value services in military and civilian applications. Typically, it incorporates a group of Unmanned Aerial Vehicles (UAVs), known as drones that collaborate and cooperate to accomplish several missions without human intervention. However, UAV communications are prone to various attacks and detecting malicious nodes is essential for efficient FANET operation. Trust management is an effective method that plays a significant role in the prediction and recognition of intrusions in FANETs. Specifically, evaluating node behaviour remains an important issue in this domain. For this purpose, the authors suggest using fuzzy logic, one of the most commonly used methods for trust computation, which classifies nodes based on multiple criteria to handle complex environments. In addition, the Received Signal Strength Indication (RSSI) is an important parameter that can be used in fuzzy logic to evaluate a drone's behaviour. However, in outdoor flying networks, the RSSI can be seriously influenced by the humidity of the air, which can dramatically impact the accuracy of the trust results. FUBA, a fuzzy‐based UAV behaviour analytics is presented for trust management in FANETs. By considering humidity as a new parameter, FUBA can identify insider threats and increase the overall network's trustworthiness under bad weather conditions. It is capable of performing well in outdoor flying networks. The simulation results indicate that the proposed model significantly outperforms FNDN and UNION in terms of the average end‐to‐end delay and the false positive ratio. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) technology is crucial for enabling dynamic spectrum management. CR allows opportunistic spectrum sharing with licensed primary radio (PR) users by allowing the so-called secondary users to dynamically access the under-utilized parts of the frequency bands that are allocated/licensed to the PR networks (PRNs). The CR system pays a utilization-dependent price to PRNs for utilizing the unused spectrum. An essential challenge in this domain is how to characterize the economic implications of spectrum sharing between the CR system and PRNs. Specifically, we consider a CR system with two competing CR service providers. This market model is known as the "duopoly model," a market structure premise that consists of two companies providing the same type of service. For such a model, we investigate the problem of maximizing the overall achieved profit in the CR system. Specifically, we mathematically formulate the profit-maximization spectrum assignment problem for the two CR providers subject to spectrum sharing, power distribution, spectrum pricing, and quality of service constraints. We demonstrate that this optimization problem is an NP-hard binary nonlinear programming problem. Therefore, we adopt a meta-heuristic optimization method based on Antlion Optimization to solve the problem suboptimally. Simulation results revealed that our proposed profit-aware optimization significantly outperforms traditional CR-based spectrum access mechanisms. [ABSTRACT FROM AUTHOR]

The recent developments in unmanned aerial vehicles (UAVs) and indoor hybrid LiFi–WiFi networks (HLWNs) present a significant opportunity for creating low-cost, power-efficient, reliable, flexible, and ad-hoc HLWN-enabled indoor flying networks (IFNs). However, to efficiently operate and practically realize indoor HLWN, a unified physical layer (UniPHY) is indispensable for joint communication (control and data transfer) and sensing (e.g., localization). A UniPHY structure reduces costs and increases overall flexibility for HLWN-based IFNs. While conventional block-based wireless transceivers independently designed for LiFi and WiFi offer mediocre performance for a composite UniPHY waveform, a machine learning-based end-to-end learning framework for UniPHY can improve overall error performance and reduce the complexity of UAV transceiver hardware. Therefore, this paper proposes a novel generic end-to-end learning framework for a UniPHY system that can efficiently enable HLWN. The performance of the proposed learning framework based on deep neural networks (DNNs) and convolutional neural networks (CNNs) is investigated. Additionally, we assess the computational complexity of the proposed DNN and CNN learning frameworks. The results demonstrate that the performance of DNNs and CNNs varies depending on the considered channel model. Specifically, the analysis reveals that CNNs outperform traditional DNNs in WiFi (Rayleigh fading-based) channels. In contrast, traditional DNNs perform better than CNNs in LiFi (additive white Gaussian noise (AWGN)-based) channels. [ABSTRACT FROM AUTHOR]

In this paper, we develop a novel demultiplexer design for Coarse Wavelength Division Multiplexer (CWDM). The device consists of multi-layer inhomogeneous semi-conductor material, where the refractive index of each layer is graded according to a predefined profile. The proposed design exploits the ray's spatial shift that results from the material dispersion as different wavelengths propagate through the different layers of the device. Our design forces the multiplexed light to refract after propagation for short distance within the device leading to smaller device size while providing the needed spatial shift between the ray's of the adjacent multiplexed wavelengths. The proposed structure can be easily implemented using the well-established technology utilized in fabricating existing graded-index fibers. The impacts of the various design parameters (such as the incident angle, number of layers, the layer thickness, the spacing between adjacent wavelengths, the refractive index difference) on the amount of achieved spatial shift between the adjacent wavelengths and the size of the device are investigated. Compared to previous proposed techniques, our device can be easily fabricated to provide higher spatial shift while reducing the device size with by controlling the different design parameters. [ABSTRACT FROM AUTHOR]

Wireless communication demands rapidly increase due to the increase of Internet of Things applications, which leads researchers to build secondary networks that exploit the spectrum holes of primary networks. Cognitive radio (CR) technology is adopted in ad-hoc networks (AHNs) rather than infrastructure-based networks because AHNs have lower cost, higher coverage, and easier maintenance compared to infrastructure-based networks. Moreover, in-band-full-duplex (IBFD) in CR networks (CRNs) is gaining the interest of researchers. This mix between IBFD and CRNs brings a great enhancement in the network's performance due to efficient dynamic spectrum access. Therefore, we propose an adaptive FD-CRNs routing protocol that uses a common control channel. Adaptive FD communication is conducted in our protocol where the secondary users adapt their communication mode based on the primary users' activity on the spectrum. Communication modes used in our work are FD transmit and sense, FD transmit and receive, and sensing only. The performance of our protocol was evaluated using a java language simulator for IBFD-CRNs introduced previously in the literature. Also, we compare the performance of our protocol with three previous protocols, probabilistic and deterministic path selection in cognitive radio network, and multi-cast half-duplex routing protocol and broadcast full-duplex routing protocol. The performance metrics used are throughput and total execution time. [ABSTRACT FROM AUTHOR]

The integration of cognitive radio (CR) into power domain non-orthogonal multiple access (NOMA) wireless systems has been envisioned as a promising paradigm for supporting massive energy-efficient beyond fifth-generation (B5G)-based IoT connectivity. This paper presents a novel two-dimensional orthogonal multiple access (OMA)-NOMA CR-based power minimization approach for battery-constrained B5G-based IoT networks. According to the proposed approach, the time and frequency domains are integrated together with NOMA for the purpose of serving a larger number of CR users. Our approach divides the available time of each idle frequency channel into a set of time slots, each can serve a group of CR users through power-domain multiplexing. Our approach consists of two phases: user-pairing with channel assignment and power-allocation. The user-pairing associated channel-assignment problem is mathematically presented as a binary linear-programming problem, which is shown to be a uni-modular optimization with polynomial-time complexity. Given the paired users and assigned channels, the power-minimization problem under a set of quality-of-service constraints is formulated as a non-convex optimization. Then, we implement an iterative method that transfers the problem into a convex optimization. Simulation results reveal that our two-dimensional OMA-NOMA CR-based approach provides significant performance gain over the conventional CR-based OMA-NOMA power-minimization in terms of the total consumed transmission power. [ABSTRACT FROM AUTHOR]

Designing an efficient wireless sensor network (WSN) system is considered a challenging problem due to the limited energy supply per sensor node. In this paper, the performance of several bi-objective optimization algorithms in providing energy-efficient clustering solutions that can extend the lifetime of sensor nodes were investigated. Specifically, we considered the use of the Moth–Flame Optimization (MFO) algorithm and the Salp Swarm Algorithm (SSA), as well as the Whale Optimization Algorithm (WOA), in providing efficient cluster-head selection decisions. Compared to a reference scheme using the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol, the simulation results showed that integrating the MFO, SSA or WOA algorithms into WSN clustering protocols could significantly extend the WSN lifetime, which improved the nodes' residual energy, the number of alive nodes, the fitness function and the network throughput. The results also revealed that the MFO algorithm outperformed the other algorithms in terms of energy efficiency. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) along with cognitive radio (CR) have been recently configured as potential solutions to fulfill the extraordinary demands of the fifth generation (5G) and beyond (B5G) networks and support the Internet of Thing (IoT) applications. Multiple users can be served within the same orthogonal domains in NOMA via power-domain multiplexing, whilst CR allows secondary users (SUs) to access the licensed spectrum frequency. This work investigates the possibility of combining orthogonal frequency division multiple access (OFDMA), NOMA, and CR, referred to as hybrid OFDMA-NOMA CR network. With this hybrid technology, the licensed frequency is divided into several channels, such as a group SUs is served in each channel based on NOMA technology. In particular, a rate-maximization framework is developed, at which user pairing at each channel, power allocations for each user, and secondary users activities are jointly considered to maximize the sum-rate of the hybrid OFDMA-NOMA CR network, while maintaining a set of relevant NOMA and CR constraints. The developed sum-rate maximization framework is NP-hard problem, and cannot be solved through classical approaches. Accordingly, we propose a two-stage approach; in the first stage, we propose a novel user pairing algorithm. With this, an iterative algorithm based on the sequential convex approximation is proposed to evaluate the solution of the non-convex rate-maximization problem, in the second stage. Results show that our proposed algorithm outperforms the existing schemes, and CR network features play a major role in deciding the overall network's performance. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) technology is proposed to provide huge spectrum opportunities to enable a large-scale deployment of Internet-of-Things (IoT) sensing-based applications. An important challenge in this domain is how to design efficient channel assignment algorithms for delay-sensitive CRIoT-based sensor networks while being resilient to jamming attacks (the most common threat to IoT network reliability). Such channel assignment algorithms must enable parallel multi-channel transmissions in order to satisfy the imposed quality-of-service and delay requirements of the CRIoT devices while being spectrum efficient. This article introduces a multi-channel batch-based security-aware medium access control (MAC) design proposed for time-critical CRIoT deployments, referred to as BMRJA-MAC. The proposed design aims at improving the overall network performance by serving the largest possible number of CRIoT nodes by utilizing their multi-channel transmission capabilities while being reactive jamming-aware. The performance of the proposed MAC design is validated via simulations and experimentally using the Future Internet-of-Things (FIT) IoT-LAB testbed. Compared with reference protocols, the results show that BMRJA-MAC significantly improves network performance and spectrum efficiency. [ABSTRACT FROM AUTHOR]

The IEEE 802.11 MAC protocols have been implemented in many wireless ad hoc and infrastructure networks. Most of the IEEE 802.11-based networks adopt a one-hop transmission mechanism (the source and destination communicate using a direct link). While this strategy is simple, it degrades network performance as it limits the number of data transmissions that can concurrently take place. The performance of IEEE 802.11 MAC in terms of delay and overall achieved throughput can be improved when the overall transmission time for each data transmission from the access point (AP) to any node in the network is minimized. Occupying the time-frequency resources for a shorter time period results in more available resources for other potential downlink transmissions to take place. In this work, we present a modified MAC protocol for IEEE 802.11 infrastructure-based networks with device-to-device transmission strategy. The main goal of our proposed protocol is to minimize the transmission time for individual downlink transmissions while maximizing the utilization of network resources by using D2D multi-hop transmissions, thereby improving the overall achieved throughput. In our proposed mechanism, the AP selects the multi-hop path that requires the minimum transmission time to deliver the data packets to destination. This path is selected even though the direct path exists. Compared to the IEEE 802.11 standard, simulation results show significant performance improvements in terms of throughput and fairness. [ABSTRACT FROM AUTHOR]

Existing liquefied petroleum gas (LPG) detection systems are ad hoc and designed as stand-alone nodes. This article, however, presents an integrated end-to-end wireless sensor network (WSN) system that integrates hardware and software for early warning gas leakage detection and monitoring applications, fully utilizing the Internet of Things (IoT) functionalities and capabilities in WSNs at the network level such that network performance is improved. The proposed system can operate in single- and multihop modes depending on the surrounding radio frequency environment and network topology. Specifically, we design a per-deployed WSN system for LPG detection/monitoring in residential areas and factories that collects, analyzes, and forwards the collected information over a wireless channel to the monitoring center to take the appropriate action. To achieve a reliable communication and data delivery, we implement an efficient communication protocol that organizes the data exchange between different nodes in the network. The proposed WSN system is deployed and experimentally tested. The data acquired from the various experiments are used to examine the reliable operation of the implemented system in terms of robustness and data delivery reliability. Robust and reliable performance is demonstrated with packet loss rate as low as 5%. The experimental results also indicate that the proposed system can promptly detect gas leakage within 50 ms and provide accurate gas concentration measurements with 97% accuracy. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensors are considered the key elements in enabling efficient Internet of Things (IoT) networking and services. One of the key objectives in designing a WSN is increasing network lifetime by reducing the overall network energy consumption. To achieve this, several techniques have been proposed to extend the network lifetime, such as clustering. Clustering divides the network into several clusters, each with its own member nodes and a cluster‐head (CH) node. In this paper, a novel clustering mechanism is developed with the objective of extending network lifetime through load balancing in wireless sensor networks (WSNs). This is achieved by electing a new node to a provides specific tasks in the WSN to decrease energy consumption and enhance network lifetime. This node is called a relay node that is responsible of delivering the received data packets from the CHs, and then forwards them to the central node (sink). Unlike previous clustering schemes, the proposed algorithm consists of three main processes: CH selection, relay node selection, and medium access control processes. These processes depend on energy level and user's distributions. The performance of the proposed algorithm is investigated through simulation experiments in terms of network lifetime under various network parameters. The results reveal that the proposed mechanism significantly enhances network lifetime compared to previously proposed algorithms. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is a new intelligent wireless technology that aims at improving spectrum utilization by allowing opportunistic access to the underutilized licensed spectrum. Wireless CR operating environment is typically characterized by its unreliable and unpredictable channel conditions and time availability due to fading and the randomness of primary radio (PR) activities. In such environment, packet fragmentation is needed to enhance the probability of success/packet delivery and reduce the needed number of packet re-transmission attempts. Specifically, the quality and availability of the PR channels along with the data packet size should be considered when designing communication protocols for CR networks (CRNs) such that the packet success probability is improved. Based on the quality and availability of the PR channels, an optimal-packet size metric is derived, which is defined as the packet size that can be transmitted over a selected channel while guarantying a predefined probability of success. In this paper, we propose three fragmentation-based channel assignment algorithms: fixed-fragment size algorithm, first-fit algorithm and near-exact fit algorithm. The first algorithm divides the packet equally over the selected channels while the other algorithms use variable fragment size. The main objectives of the algorithms are to enhance network throughput, decrease the number of dropped packets and reduce the average number of retransmission attempts. This preserves more channels for potential future CR transmissions, resulting in higher network throughput with less energy consumption. Simulation results show that the proposed algorithms significantly outperform existing CRN channel assignment algorithms with no fragmentation. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) technology has been demonstrated as one of the key technologies that can provide the needed spectrum bands for supporting the emerging spectrum-hungry multimedia applications and services in next-generation wireless networks. Multicast routing technique plays a significant role in most of wireless networks that require multimedia data dissemination to a group of destinations through single-hop or multi-hop communication. Performing multimedia multicasting over CR networks can significantly improve the quality of multimedia transmissions by effectively exploiting the available spectrum, reducing network traffic and minimizing communication cost. An important challenge in this domain is how to perform a multi-cast transmissions over multiple hops in a dynamically varying CR environment while maintaining high-quality received video streaming to all multi-case CR receivers without affecting the performance of legacy primary radio networks (PRNs). In this paper, we investigate the problem of multicast multimedia streaming in multi-hop CR networks (CRNs). Specifically, we propose an intelligent multicast routing protocol for multi-hop ad hoc CRNs that can effectively support multimedia streaming. The proposed protocol consists of path selection and channel assignment phases for the different multi-cast receivers. It is based on the shortest path tree (SPT) that implements the expected transmission count metric (ETX). The channel selection is based on the ETX, which is a function of the probability of success (POS) over the different channels that depends on the channel-quality and availability. Simulation results verify the significant improvement achieved by the proposed protocol compared to other existing multicast routing protocols under different network conditions. [ABSTRACT FROM AUTHOR]

Recent developments in self-interference cancellation (SIC) techniques have made in-band full-duplex (IBFD) transmission systems possible. IBFD technology can enhance, or theoretically speaking double, spectrum utilization by allowing simultaneous transmission and reception using the same radio-frequency channel. Integrating the IBFD technology in cognitive radio (CR) systems can further enhance spectrum utilization and provide huge spectrum opportunities for efficient deployment of next-generation multi-hop wireless systems. Routing protocols for typical CR networks (CRNs) assume that CR users are equipped with half-duplex receivers. Limited number of protocols have been designed for FD-based CRNs. However, these protocols do not account for security threats in wireless environment, which could significantly affect system performance. In this paper, we develop a security-aware intelligent routing scheme that aims at mitigating the effects of jamming attacks on IBFD CRNs. This scheme considers the unique characteristics of the CRN environment while being IBFD-aware. Specifically, it considers the primary user’s channel-availability time, channel quality and jamming strategy. For a source-destination pair, our protocol collects a set of loop-free paths. Then, it attempts to assign channels for the hops along each path with the goal of achieving the highest Probability of Success (PoS) of each path. The per-hop channel selection for each path is derived as an optimization problem, for which sub-optimal solutions are found using a polynomial-time approximate method. Based on the computed channel assignment and PoS over each path, the path with the highest PoS between the source and destination is selected. Simulation results show that our secure-aware IBFD-based routing can significantly mitigate the jamming effects on CRN performance by improving the packet-delivery ratio, and consequently network throughput compared with existing FD-based routing protocols. [ABSTRACT FROM AUTHOR]

Recent advances in full-duplex (FD) communications along with the introduction of the concept of device-to-device communications have challenged the applicability of traditional routing and scheduling schemes in multi-hop cognitive radio networks (CRNs). In this letter, we derived a close-form expression to quantify the impact of time-sharing of a given channel assignment along a given path on network performance. Based on the derived expression, we mathematically model the channel-assignment problem that minimizes the number of time-shared hops along a given path as a binary-quadratic optimization problem (BQP). Then, we transfer the BQP into a binary linear programming problem (BLP), which is sub-optimally solvable using a polynomial-time sequential fixing method. Simulation results indicate that routing with assignment that minimizes the needed number of time-shared transmissions along a path can provide significant improvement in network throughput. [ABSTRACT FROM AUTHOR]

In this paper, we develop a joint channel assignment and adaptive Multi-Input–Multi-Output (MIMO) mode selection protocol for MIMO-based multi-channel cognitive radio networks. The proposed protocol utilizes the dynamic access capabilities of cognitive radio devices along with the multiplexing and/or diversity gains offered by MIMO systems in order to improve network throughput and communication reliability. The proposed protocol attempts at enhancing system performance by selecting the best MIMO operating modes (multiplexing, diversity, or hybrid multiplexing-diversity mode) for each idle channel according to the surrounding RF environment, and then selects the channel that provides the highest throughput. The network performance of our protocol (the overall network throughput and MIMO efficiency) is investigated under various traffic and network conditions through simulations. Compared to diversity-mode channel assignment, multiplexing-mode channel assignment, and adaptive mode selection with random channel selection protocols, our proposed protocol reveals significant performance improvement in network throughput under different traffic and network conditions. [ABSTRACT FROM AUTHOR]

Summary: Spectrum sharing protocols for cognitive radio networks (CRNs) are often designed based on an exclusive channel occupancy policy. This policy does not allow concurrent cognitive radio (CR) transmissions to take place over the same channel. Unfortunately, this can significantly affect spectrum utilization and network performance. Allowing several secondary users to simultaneously share the same channel naturally improves spectrum utilization and avoids unnecessary blocking of CR transmissions. The key challenge in enabling efficient operation of multichannel CRNs is how to perform efficient power‐controlled media‐access‐control (MAC) protocols. These protocols include both power control and channel assignment. In this paper, we propose a power‐controlled MAC protocol for CRNs based on interference‐channel occupancy model with the objective of maximizing the number of served CR transmissions. It uses a novel power‐controlled channel assignment mechanism that allows several concurrent interference‐limited transmissions to simultaneously proceed over each idle channel in the same neighborhood. We present two variants of the power‐controlled channel assignment mechanism. The first proposed variant is suitable for CRNs with fixed data packet size, whereas the other is suitable for dynamic CRNs with variable packet size. The second variant of our protocol employs a users' scheduling procedure that attempts to fully utilize the available time‐frequency blocks. Simulation results indicate that employing transmission power control along with appropriate channel assignment and users' scheduling in CRNs can significantly improve the spectrum utilization and the overall network performance. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is a promising technology that allows devices to effectively utilize the underutilized or unutilized portions of the licensed spectrum. In literature, several channel assignment and spectrum sharing algorithms for CR Networks (CRNs) have been developed to improve spectrum efficiency without considering the problem of Adjacent Channel Interference (ACI). Guard-Band (GB)-aware mechanisms have been proposed in CRNs to prevent ACI and improve spectrum efficiency. However, most of the existing GB-aware algorithms assume having channels with fixed-rate and employ a sequential channel assignment paradigm. Unfortunately, this assumption is not realistic, because channel's conditions may vary over time. In this work, we propose a GB-aware channel assignment that considers the channel-dependent achieved transmission rates (due to Rayleigh fading time-varying conditions) at different time slots while simultaneously assigning channels to several CR transmissions. This batch based proposal aims at increasing network capacity and minimizing the number of assigned channels per user subject to rate demand and interference constraints. Simulation experiments demonstrate the effectiveness of our proposed scheme, which show a significant improvement in network performance in terms of the number of served CR users. [ABSTRACT FROM AUTHOR]

This paper introduces a new fuzzy advanced harmony search algorithm for solving single-objective buffer allocation problems (BAPs). The proposed algorithm represents the first attempt at solving BAPs using a fuzzy logic system, by tuning the advanced harmony search control parameters. The main steps of the proposed algorithm included parameter initialisation, harmony memory initialisation and evaluation, improvisation, harmony memory update, AHS parameter update, and termination criterion check. The aim of this approach is to achieve a better convergence rate and avoid the stacking of local optima. The performance of the proposed algorithm was compared with other methods used in solving BAPs. The proposed approach has shown a higher capability in finding optimal solutions compared to previous methods used for two benchmark problems. Improvement of up to 94.75% in the overall throughput is reported for the 3-stage problem, while for the 12-stage problem, a slight improvement (up to 7.58%) is also reported in the overall throughput. The results achieved indicate that the proposed algorithm is an efficient and promising tool in solving BAPs. [ABSTRACT FROM AUTHOR]

Recent developments of self-interference suppression techniques have enabled practical implementations of full-duplex (FD) cognitive-radio (CR) communication systems. Such systems can significantly enhance spectrum utilization by allowing a CR user to simultaneously transmit and receive over the same frequency channel. However, the CR FD-capabilities challenge the effectiveness of existing CR-based routing protocols as joint FD-aware channel-assignment and routing are essential to enhance network performance. In this letter, we propose a joint FD-aware channel-assignment and route selection protocol in FD-based CR networks (CRNs) under time-varying channel conditions and transmission rates. Specifically, for a given set of paths between a CR source-destination pair, our protocol computes the channel-assignment over each path that maximizes the end-to-end network throughput subject to interference constraints. This assignment problem is shown to be an NP-hard binary linear programming (BLP) that can be sub-optimally solved in polynomial-time using the sequential-fixing procedure. Then, our protocol determines the path with the highest end-to-end network throughput. Simulation results reveal that our proposed routing protocol significantly improves the end-to-end throughput compared to previous FD-aware routing protocols. [ABSTRACT FROM AUTHOR]

In this paper, a new design for a demultiplexer device for Wavelength Division Multiplexing (WDM) communication system is proposed. The proposed device consists of an inhomogeneous layer of a semiconductor material with refractive index that is graded according to a given profile. To minimize the size of the proposed device and achieve better spatial shift between the multiplexed wavelengths, several mirrors are placed at different locations inside the device. These mirrors will force the multiplexed light to be reflected before reaching the total internal reflection point. By controlling the different design parameters such as incident angle, the refractive index profile, etc., a small size, low cost and less complexity WDM device can be realized. In the design process, we exploits the ray’s spatial shift that results from the introduced mirrors and the material dispersion. In addition, the effect of the aforementioned design parameters on the amount of spatial shift between the adjacent wavelengths and the size of the device has been investigated. Results show that the proposed design achieves higher spatial shift as well as smaller device size in comparison with precedent WDM device designs. [ABSTRACT FROM AUTHOR]

Several new attacks have been identified in CRNs such as primary user emulation, dynamic spectrum access (DSA), and jamming attacks. Such types of attacks can severely impact network performance, specially in terms of the over all achieved network throughput. In response to that, intrusion detection system (IDS) based on anomaly and signature detection is recognized as an effective candidate solution to handle and mitigate these types of attacks. In this paper, we present an intrusion detection system for CRNs (CR-IDS) using the anomaly-based detection (ABD) approach. The proposed ABD algorithm provides the ability to effectively detect the different types of CRNs security attacks. CR-IDS contains different cooperative components to accomplish its desired functionalities which are monitoring, feature generation and selection, rule generation, rule based system, detection module, action module, impact analysis and learning module. Our simulation results show that CR-IDS can detect DSA attacks with high detection rate and very low false negative and false positive probabilities. [ABSTRACT FROM AUTHOR]

The adjacent channel interference (ACI) resulting from imperfect filtering can severely degrade the performance of any wireless communication system. Despite this fact, most of previously proposed medium access control (MAC) protocols for cognitive radio networks (CRNs) were designed while ignoring the effects of ACI (assuming ideal filtering). The effect of ACI can be reduced by introducing guard bands (GBs). However, this solution comes at the expense of degrading spectrum efficiency. In this paper, we develop an efficient GB-aware MAC protocol that attempts at maximizing network throughput while improving fairness in CRNs. Unlike most of previously proposed GB-aware MAC protocols that perform channel assignment sequentially, our MAC performs the channel assignment for multiple CR links simultaneously (the so-called batch method). Batching enables concurrent channel assignment for multiple CR links, which consequently allows for concurrent data transmissions. Batching can be realized by introducing an admission control phase for CR users to share their control information. The batch method can effectively provide distributed decisions that achieve better throughput while reducing the number of GBs. Our MAC also allows the CR users to utilize the reserved GBs of primary networks under predefined FCC power constraints. Simulation results indicate that our protocol achieves significant performance improvement compared to previous GB-aware protocols. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) networks are expected to offer a huge bandwidth to wireless users through dynamic spectrum access techniques. To realize this new network paradigm, effective distributed coordination schemes to exchange control information without assuming the availability of a prespecified common control channel (CCC) are needed. In this paper, we propose a distributed group-based spectrum-aware coordination scheme for carrier-sense multiple access with collision avoidance (CSMA/CA)-based CR networks, which is called virtual clustering distributed coordination (VCDC). By using a CSMA/CA access mechanism, VCDC allows neighboring CR users with a similar view to spectrum opportunities to asynchronously organize themselves into virtual clusters and coordinate their communications using locally available CCCs. VCDC differs from previous cluster-based schemes in that it exploits the discrete orthogonal frequency-division multiplexing (D-OFDM) technology to reduce neighbor-discovery time and facilitate intercluster communication and broadcasting. Three variants of the VCDC scheme are proposed, which are one-hop, two-hop, and constrained VCDC. These variants provide different cluster size based on the number of adopted local CCCs. We compare the performance of the VCDC scheme with existing clustering schemes. Simulation results show that VCDC constructs fewer larger size clusters with an appropriate number of common idle channels and introduces a lower percentage of clusters with no shared idle channels. Thus, VCDC performs better without imposing synchronization. [ABSTRACT FROM PUBLISHER]

This paper presents a curriculum design approach for a Masters Programme in Telecommunications Management based on demand data obtained from surveying the needs of potential students of the proposed programme. Through online surveys disseminated at telecom companies in Jordan, it was possible to measure the demand for such a programme and to determine the required programme contents and specifications. The curriculum design is based on definition of programme outcomes and on using a house of quality approach (HOQ) to determine the list of courses required in the programme. Surveyed competencies are mapped to a long list of proposed courses in a HOQ in order to determine the importance of each of these courses. A final list of core and elective courses is then developed considering the contribution to programme outcomes and the academic standards. [ABSTRACT FROM PUBLISHER]

This article presents the methodology and results of the curriculum review of the Masters of Science programme in Wireless Communications offered by the Telecommunications Engineering Department at Yarmouk University in Jordan. The review is based on expert opinion collected through questionnaires and meetings about the programme and focuses on two main aspects: the first is relevance of the programme to the needs of local and regional telecommunications industry and the second is comparability to similar programmes in the EU. Through an extensive analysis of the collected data, a set of recommendations for improvement of the existing curriculum was developed. These recommendations were then used to redesign the curriculum with regard to contents, teaching methodology and assessment. [ABSTRACT FROM AUTHOR]

The cognitive radio (CR) paradigm calls for open spectrum access according to a predetermined etiquette. Under this paradigm, CR nodes access the spectrum opportunistically by continuously monitoring the operating channels. A key challenge in this domain is how the nodes in a CR network (CRN) cooperate to access the medium in order to maximize the CRN throughput. Typical multichannel MAC protocols assume that frequency channels are adjacent and that there are no constraints on the transmission power. However, a CRN may operate over a wide range of frequencies, and a power mask is often enforced on the transmission of a CR user to avoid corrupting the transmissions of spectrum-licensed primary-radio (PR) users. To avoid unnecessary blocking of CR transmissions, we propose a novel distance-dependent MAC protocol for CRNs. Our protocol, called DDMAC, attempts to maximize the CRN throughput. It uses a novel probabilistic channel assignment mechanism that exploits the dependence between the signal's attenuation model and the transmission distance while considering the traffic profile. DDMAC allows a pair of CR users to communicate on a channel that may not be optimal from one user's perspective, but that allows more concurrent transmissions to take place, especially under moderate and high traffic loads. Simulation results indicate that, compared to typical multichannel CSMA-based protocols, DDMAC reduces the blocking rate of CR requests by up to 30%, which consequently improves the network throughput. [ABSTRACT FROM AUTHOR]

The article presents a survey which examines the challenges and developments of channel access protocols proposed for multihop cognitive radio networks. It discusses key design issues in development of medium access control (MAC) protocols for such networks. It also explores the development in MAC protocol design for CRNs. It outlines several challenges including the provision of an effective distributed coordination among CR users and computation of neighborhood-dependent power mask.

Algorithms for spectrum sharing over resource‐limited cognitive radio networks are often designed to solve specific problems. This means that a certain algorithm deals specifically with a certain limited resource, and is not suitable for other resources. This limitation violates the software‐defined networking philosophy, where a scheme has to be reprogrammable to cope with different limited resources that can dynamically arise depending on network conditions. In this work, we investigate the problem of spectrum sharing in resource‐limited cognitive radio networks. Specifically, we introduce a novel spectrum sharing algorithm that is compatible with software‐defined networks, in the sense that it can be reprogrammed to support multiple constraints on resources of different types. A main feature of the proposed scheme is that computations could be distributed across multiple processing units to reduce computational complexity on each unit. In addition, the proposed algorithm is equipped with a fairness scheme. Simulation results demonstrate the efficacy of the proposed scheme. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is considered as a key enabling communication technology that offers efficient wireless connectivity to Internet of Things (IoT) devices. Its integration with the future 5G architecture is expected to advance the IoT paradigm. Security attacks can severely degrade the performance of such CR‐based IoT (CRIoT) networks. The effect of security attacks can be reduced by implementing defensive approaches. However, such solutions come at the expense of degrading spectrum efficiency and consuming more network resources. In this paper, we investigate the spectrum sharing and access problem in a multidevice single‐transceiver CRIoT network with time‐critical applications under jamming attacks. Our main goal is to maximize the number of simultaneously served IoT devices over all available idle channels while ensuring delay requirement, hardware, link quality, security attacks, and spectrum utilization constraints. This problem is formulated as a total unimodular binary linear programming, which is shown to be solvable in polynomial time. Unlike most of previous security‐aware channel assignment solutions that conduct the channel assignment sequentially, our solution simultaneously provides secured distributed channel‐assignment decisions for multiple CRIoT links (batching method). Batching can be realized through an admission control stage for CR IoT devices to announce their control packets. Simulation results reveal that our solution significantly improves network performance compared to previous security‐aware schemes. Cognitive radio (CR) is considered as a key enabling communication technology that offers efficient wireless connectivity to Internet of Things (IoT) devices. Security attacks can severely degrade the performance of CR‐based IoT (CRIoT). Unlike most of previous security‐aware channel assignment solutions that conduct the channel assignment sequentially, our solution simultaneously provides secured distributed channel‐ assignment decisions for multiple CRIoT link (batching method). Simulation results reveal that our solution significantly improves network performance compared to previous security‐aware schemes. [ABSTRACT FROM AUTHOR]