Today's electricity grid is rapidly evolving, with increased penetration of renewable energy sources (RES). Conventional Optimal Power Flow (OPF) has non-linear constraints that make it a highly non-linear, non-convex optimisation problem. This complex problem escalates further with the integration of RES, which are generally intermittent in nature. In this article, an optimal power flow model combines three types of energy resources, including conventional thermal power generators, solar photovoltaic generators (SPGs) and wind power generators (WPGs). Uncertain power outputs from SPGs and WPGs are forecasted with the help of lognormal and Weibull probability distribution functions, respectively. The over and underestimation output power of RES are considered in the objective function i.e. as a reserve and penalty cost, respectively. Furthermore, to reduce carbon emissions, a carbon tax is imposed while formulating the objective function. A grey wolf optimisation technique (GWO) is employed to achieve optimisation in modified IEEE-30 and IEEE-57 bus test systems to demonstrate its feasibility. Hence, novel contributions of this work include the new objective functions and associated framework for optimising generation cost while considering RES; and, secondly, computational efficiency is improved by the use of GWO to address the non-convex OPF problem. To investigate the effectiveness of the proposed GWO-based approach, it is compared in simulation to five other nature-inspired global optimisation algorithms and two well-established hybrid algorithms. For the simulation scenarios considered in this article, the GWO outperforms the other algorithms in terms of total cost minimisation and convergence time reduction.

With the fifth generation communication system in the phase of deployment, the research community has focused its attention toward a higher frequency spectrum, data rate in terabits per second, latency lower than 1 ms, and ultrahigh reliability. Communication systems having such characteristics are expected to be rolled out in the sixth generation. This article presents key technology enablers for deployment in ultra-reliable and low-latency communications for 6G networks. In addition, the potential issues related to system security and spectrum management in 6G networks are also discussed. The significant technological enablers include machine learning, channel estimation, intelligent reflecting surfaces, terahertz communication, spectrum sharing, and system security, which possess the potential to revolutionaize the future of wireless communication networks.

The non-orthogonal multiple access (NOMA) technique is a strong candidate for 5G cellular networks that enable greater multiuser capacity and user fairness through multiplexing in the power domain. The user data are pulse-shaped using the orthogonal frequency-division multiplexing (OFDM) technique based on the fast Fourier transform (FFT) for conventional NOMA. We propose a discrete wavelet transform-based pulse shaping technique for NOMA. We present a closed-form expression of the bit error rate (BER) for FFT-NOMA as well as wavelet-based NOMA (WNOMA) systems. The theoretical and simulation BER results show that WNOMA outperforms FFT-NOMA in additive white Gaussian noise.

The hybrid power line communication (PLC) and visible light communication (VLC) systems can be effectively utilized for the efficient design of 5G communication setup. However, each of these integrated communication media is not primarily meant for the specific purpose of data communication, as PLC and VLC have historically served to transfer electrical energy transfer and light, respectively. With the advent of high flickering rate light emitting diodes and efficient multiplexing/modulation schemes, both technologies are observed as potential data communication carriers. Therefore, this paper presents a novel approach for modifying the modulation technique in accordance with the channel requirements of a hybrid PLC-VLC-based 5G communication systems. We provide a thorough analysis of the research work done to co-use these two technologies for data communication, suggest some exciting applications of integrated PLC-VLC systems and propose discrete wavelet transform (DWT)-based orthogonal frequency division multiplexing (OFDM) to tune the physical parameters as per the hybrid channel characteristics. Theoretical and simulation bit-error-rate results exhibit that DWT-OFDM outperforms an OFDM-based PLC-VLC system. The proposed hybrid system can be used to design smart buildings where indoor/intra-building connectivity is maintained by VLC whereas inter-building networking based on PLC communication.

Limited energy resources of sensor nodes in Wireless Sensor Networks (WSNs) make energy consumption the most significant problem in practice. This paper proposes a novel, dynamic, self-organizing Hesitant Fuzzy Entropy-based Opportunistic Clustering and data fusion Scheme (HFECS) in order to overcome the energy consumption and network lifetime bottlenecks. The asynchronous working-sleeping cycle of sensor nodes could be exploited to make an opportunistic connection between sensor nodes in heterogeneous clustering. HFECS incorporates two levels of hierarchy in the network and energy heterogeneity is characterized using three levels of energy in sensor nodes. HFECS gathers local sensory data from sensor nodes and utilizes multi-attribute decision modeling and the entropy weight coefficient method for cluster formation and the cluster head election procedure. After cluster formation, HFECS uses the same techniques for performing data fusion at the first hierarchical level to reduce the redundant information flow from the first-second hierarchical levels, which can lead to an improvement in energy consumption, better utilization of bandwidth and extension of network lifetime. Our simulation results reveal that HFECS outperforms the existing benchmark schemes of heterogeneous clustering for larger network sizes in terms of half-life period, stability period, average residual energy, network lifetime, and packet delivery ratio.