Future wireless communication systems must be able to accommodate a large number of users and simultaneously to provide the high data rates at the required quality of service. In this paper a method is proposed to perform the N-Discrete Hartley Transform (N-DHT) mapper, which are equivalent to 4-Quadrature Amplitude Modulation (QAM), 16-QAM, 64-QAM, 256-QAM, … etc. in spectral efficiency. The N-DHT mapper is chosen in the Multi Carrier Code Division Multiple Access (MC-CDMA) structure to serve as a data mapper instead of the conventional data mapping techniques like QPSK and QAM schemes. The proposed system is simulated using MATLAB and compared with conventional MC-CDMA for Additive White Gaussian Noise, flat, and multi-path selective fa

While traditional energy sources such as oil, coal, and natural gas drive economic growth, they also seriously affect people’s health and the environment. Renewable energies (RE) are presently seen as an efficient choice for attaining long-term sustainability in development. They provide an adequate response to climate change and supply sufficient electricity. The current situation in Iraq results from a decades-long scarcity of reliable electricity, which has impacted various industries, including agriculture. There are diverse prospects for using renewable energy sources to address the present power crisis. The economic and environmental impacts of renewable energy systems were investigated in this study by using the solar pumpi

Community detection is one of the most fundamental applications in understanding the structure of complicated networks. Furthermore, it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships. Networking structures are highly sensitive in social networks, requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks. In addition, they miss out on accurately identifying clusters. Since single-objective optimization cannot always generate accurate and comprehensive results, as multi-objective optimization can.Therefore,we utilized two objective

The Combined Economic Emission Dispatch (CEED) problem is crucial for optimizing power system operation by minimizing costs and emissions while ensuring grid stability and meeting demand. This paper addresses the complex, nonlinear, and nonconvex nature of CEED, arising from factors like valve-point effects and transmission losses, which necessitates efficient metaheuristic algorithms. We introduce an Improved Zebra Optimization Algorithm (IMZOA), an enhanced bio-inspired technique integrating advanced adaptive foraging and dynamic defense mechanisms, along with a cubic function for CEED modeling, to improve search efficiency and convergence. IMZOA demonstrates significant numerical improvements, achieving up to a 0.80 % cost reduction for