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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]

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]

There are differences between routing in traditional and in Cognitive Radio Networks (CRNs). The availability of channels, periodic spectrum sensing, jammers activity, are some of these differences, etc. CRNs may contain a large number of Internet of Things (IoT) devices, hence, modeling such networks with a flat graph model generates a huge graph size. Thus, the motivation behind this work is clear bearing in mind that modeling such networks with a Multi-layer Hyper-Graph (MLHG) is the idea presented in this paper, in which each hyper-edge represents a group of CR devices, and each layer represents a licensed channel. In this paper, the main aim is to consider four key factors to maximize end-to-end network throughput, which are, transmission rate, licensed users activity, jammers activity, and needed number of time sharing. In literature, considering both jamming activity and time sharing for routing exists in few papers till now. This work proposes and develops three cutting-edge routing protocols that are aware of the four aforementioned factors, namely, Jamming-Activity-Sharing-Rate-Aware protocol, Jamming-Activity-Rate-Aware protocol, and Jamming-Activity-Sharing-Aware protocol. We compare these protocols with three recent proposed protocols in CRNs. Simulation results indicate that when jammers activity and time sharing are considered, network throughput is significantly enhanced. Specifically, our proposed jamming-aware protocols significantly outperform the existing three jamming-unaware protocols by up to 127 %. [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]

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 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]