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Addressing the recent trend of the massive demand for resources and ubiquitous use for all citizens has led to the conceptualization of technologies such as the Internet of Things (IoT) and smart cities. Ubiquitous IoT connectivity can be achieved to serve both urban and underserved remote areas such as rural communities by deploying 5G mobile networks with Low Power Wide Area Network (LPWAN). The current architectures will not offer flexible connectivity to many IoT applications due to high service demand, data exchange, emerging technologies, and security challenges. Hence, this paper explores various architectures that consider a hybrid 5G-LPWAN-IoT and Smart Cities. This includes security challenges as well as endogenous security and solutions in 5G and LPWAN-IoT. The slicing of virtual networks using software-defined network (SDN)/network function virtualization (NFV) based on the different quality of service (QoS) to satisfy different services and quality of experience (QoE) is presented. Also, a strategy that considers the implementation of 5G jointly with Weightless-N (TVWS) technologies to reduce the cell edge interference is considered. Discussions on the need for ubiquity connectivity leveraging 5G and LPWAN-IoT are presented. In addition, future research directions are presented, including a unified 5G network and LPWAN-IoT architecture that will holistically support integration with emerging technologies and endogenous security for improved/secured smart cities and remote areas IoT applications. Finally, the use of LPWAN jointly with low earth orbit (LEO) satellites for ubiquitous IoT connectivity is advocated in this paper.

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Traditional power grids have unidirectional power flow and often information transfer, this limits their capacity for scalability, efficiency, and renewable energy integration. Smart grids (SGs) are being developed as more intelligent power grids with bidirectional power flow and information interchange. A reliable communication network is required in order to realize some important SG features, such as renewable energy integration, distributed energy resources, scalability, self‐healing and efficient holistic monitoring, and control capability. However, this communication network needs to comply with critical requirements. Cognitive radio (CR) has been projected as a possible solution to common problems in conventional wireless systems such as spectrum scarcity and interference. The CR accesses a greater range of spectra via dynamic spectrum access capability. This paper focuses on the evaluation of communication access technologies performance measurements and improved CR model for SG communications. This paper employs the National Institute of Standard framework for SG interoperability, the low power wide area network (LPWAN), multihoming, and a CR device such as TV white space band devices (TVBDs). The results from simulation analysis show that the performance of TVBDs outperforms the legacy Wi‐Fi in terms of latency; also, LPWA devices, such as LTE Cat1/LTE‐M devices, outperform the legacy cellular, such as CDMA 1x‐EVDO, in terms of latency and throughput. In addition, the improved CR model, which involves a proposed channel fragmentation strategy–based Alamouti scheme, outperforms legacy CR in terms of blocking probability and throughput in the harsh SG environment.

The development of a modern electric power grid has triggered the need for large-scale monitoring and communication in smart grids for efficient grid automation. This has led to the development of smart grids, which utilize cognitive radio sensor networks, which are combinations of cognitive radios and wireless sensor networks. Cognitive radio sensor networks can overcome spectrum limitations and interference challenges. The implementation of dense cognitive radio sensor networks, based on the specific topology of smart grids, is one of the critical issues for guaranteed quality of service through a communication network. In this article, various topologies of ZigBee cognitive radio sensor networks are investigated. Suitable topologies with energy-efficient spectrum-aware algorithms of ZigBee cognitive radio sensor networks in smart grids are proposed. The performance of the proposed ZigBee cognitive radio sensor network model with its control algorithms is analyzed and compared with existing ZigBee sensor network topologies within the smart grid environment. The quality of service metrics used for evaluating the performance are the end-to-end delay, bit error rate, and energy consumption. The simulation results confirm that the proposed topology model is preferable for sensor network deployment in smart grids based on reduced bit error rate, end-to-end delay (latency), and energy consumption. Smart grid applications require prompt, reliable, and efficient communication with low latency. Hence, the proposed topology model supports heterogeneous cognitive radio sensor networks and guarantees network connectivity with spectrum-awareness. Hence, it is suitable for efficient grid automation in cognitive radio sensor network–based smart grids. The traditional model lacks these capability features.

A cognitive radio sensor network (CRSN) based Smart Grid (SG) is a new paradigm for a modern SG. It is totally different from the traditional power grid and also different from the conventional SG that uses a static resource allocation technique to allocate resources to sensor nodes and communication devices in the SG network. Due to the challenges associated with competitive sensor nodes and communication devices in accessing and utilizing radio resources, the need for dynamic radio resource allocation (RRA) has been proposed as a solution for allocating radio resources to sensor nodes in a CRSN based smart grid ecosystem (network). These challenges include energy/power constraints, poor quality of service (QoS), interference, delay, spectrum efficiency issues, and excessive spectrum hand-offs. Hence, the optimization of resource allocation criteria, such as energy efficiency, throughput maximization, QoS guarantee, fairness, priority, interference mitigation/avoidance, etc., will go a long way in addressing the problems of RRA in a CRSN based SG. Consequently, this work explores RRA in CRSNs for SGs. Various resource allocation schemes, as well as its architecture in a CRSN for SG environment, are presented. The work reported in this paper introduces a model called the “guaranteed network connectivity channel allocation” for throughput maximization (GNC-TM) and optimal spectrum band determination in RRA for improved throughput criteria in CRSNs for SGs. The results show that the model outperforms the existing protocol in terms of throughput and error probability. Finally, the contribution to knowledge and future research direction, such as energy efficiency and hybrid energy harvesting schemes are highlighted.

Smart cities have been envisioned to provide smartness in managing internet of things (IoT) application domains, such as transport and mobility, health care, natural resources, electricity and energy, homes and buildings, commerce and retail, society and workplace, industry, agriculture, and the environment. The growth trajectory in usage of these IoT domains has led to a heterogeneous dense network in a smart city environment. The heterogeneous dense network in smart cities has led to challenges, such as difficulties in the management of LPWAN coexistence, interference, spectrum insufficiency, QoS, and scalability issues. The existing LPWAN technologies cannot support the heterogeneous dense network challenges in smart cities. Further, it cannot support diverse IoT, including medium- to high-bandwidth applications, due to the power, complexity, and resource constraints of the LPWAN devices. Hence, this paper addresses high data rate IoT applications and heterogeneous dense networks. This paper proposes a lightweight heterogenous multihomed network (LHM-N) model for diverse smart city applications that will address dense heterogeneity network challenges in a smart city. The work aims to advocate and integrate a manageable license-free LPWAN that will coexist with 5G private and public cellular networks in the LHM-N model. This will help to provide a cost-effective solution model in a heterogeneous dense smart city environment. Further, a secured lightweight energy-efficient packet-size forwarding engine (PSFE) algorithm is presented using the discrete event simulation (DES) methodological approach in MATLAB for complexity evaluation. In addition, a 5G reduced capability (RedCap) IoT device is integrated into the (LHM-N) model to support smart city. Finally, the results show that the LHM-N model outperforms the conventional quadrature amplitude modulation (QAM) protocol scheme in terms of error rate, latency, and data throughput with reduced energy costs for medium- to high-bandwidth industrial IoT applications. This validates the suitability of the LHM-N model for high data rate IoT applications.