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.

The cognitive radio-based sensor network (CRSN) is envisioned as a strong driver in the development of modern power system smart grids (SGs). This can address the spectrum limitation in the sensor nodes due to interference cause by other wireless devices operating on the same unlicensed frequency in the Industrial, Scientific and Medical band. These sensor nodes are used for monitoring and control purposes in various components of a SG, ranging from generation, transmission, and distribution, and down to the consumer, including monitoring of utility network assets. A reliable SG communication network architecture is required for transferring information which needed by the SG applications, alongside the monitoring and control by CRSN. Hence, this paper investigates and explores the CRSN conceptual framework, and SG communication architecture with its applications; vis-à-vis the communication access technologies, including implementation design with quality of service support. Consequently, this paper highlights various research gaps, such as implementation design model, utilization of LPWAN for CRSN based SG deployment, and so on. This includes discussion on the future direction for various aspects of the CRSN in SG. To address these research gaps, we introduced a smart unified communication solution to improve the efficiency of the SG and mitigate various associated challenges.

Recently, cognitive radio based sensor network (CRSN) has been introduced into Smart Grids (SG) in order to address the problems of spectrum inefficiency and interferences. CRSN has the capability of opportunistic spectrum access (OSA) to dynamically allocate radio resources to the sensor nodes. However, one of the CRSN challenges is the problem of dual/multi correlation fading channels due to dual/multi antenna channels of the sensor nodes as well as very close spacing of sensor nodes deployment in a SG environment. This correlation can lead to degradation of the signals as well as co-channels interference. In addition, the signal-interference-noise-ratio (SINR), multipath fading, and shadowing peculiar to SG harsh environmental condition including interference from SG equipment also pose great challenges to CRSN based SG. All these problems have attracted research attentions; however, research regarding the problem of correlated signals in SG has not been considered. Hence, this paper aims to address the problem of correlation in multi fading channels. Consequently, an MGF based performance analysis of M-QAM error probability over Nakagami-q dual correlated fading channels with maximum ratio combiner (MRC) receiver technique has been derived using analytical method of trapezoidal numerical integration. An algorithmic approach which is based on a proposed transformation technique has been introduced. The error probability performance analysis is then carried out in MATLAB simulation, the simulations result agrees with the analytical/theoretical result with overlapping curves. Finally, the produced results show that dual correlated channels degrade the signal performance.

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.

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.