Wireless communication, especially that relying on 5G technology, plays a crucial role in modern networks. The use of massive multiple-input, multiple-output (MIMO) systems is one of the key advancements in this area, as it improves energy efficiency (EE) and spectral efficiency (SE), making such a technique critical for future communication networks. This article focuses on optimizing EE and SE using a new metaheuristic multiverse optimization algorithm (MVO), and compares the results obtained with those achieved with the use of the Pachycondyla Apicalis algorithm (API) and other methods. Furthermore, the study explores the best values for factors such as coherence time, power amplifier efficiency, and hardware power in each user, with all of them playing a critical role in maximizing EE. The authors also examine the correlation between EE and SE in the downlink direction. The results show that the MVO approach achieves better performance in fewer iterations compared to API and other methods, demonstrating its potential for improving wireless communication systems.

This paper investigates the potential improvements in Free Space Optics (FSO) communication systems using Particle Swarm Optimization (PSO) and the Pachycondyla Apicalis Algorithm (API). FSO technology transmits data using laser beams, offering benefits like high bandwidth and enhanced security, with the capability to achieve data rates of up to 10 Gbps over distances of up to 2 km under favorable weather conditions. However, this technology faces challenges due to environmental factors such as rain, fog, and atmospheric turbulence, which can impact its performance. This study specifically addresses link margin degradation caused by these impairments and applies PSO as an efficient baseline metaheuristic, selected for its computational simplicity, rapid convergence, and robustness, while benchmarking its performance against the API algorithm. Simulation results indicate that PSO optimization significantly increases the link margin for various divergence angles compared to the API algorithm. For divergence angles of 1, 1.5, 2.4, and 3 mrad, the link margin improved by 6.4, 11.1, 9.8, and 7.6 dB, respectively, at a fixed transmitted power of 10 dBm. This demonstrates that PSO maintains a higher link margin at divergence angles above 2 mrad compared to both the API algorithm and the conventional scenario. The main contributions of this study are: the development of a bio-inspired optimization framework for FSO systems, enhancement of link robustness against turbulence, beam misalignment, and fading, and demonstration of the framework’s applicability to both current 5G backhaul scenarios and prospective 6G optical wireless networks. Beyond simulation, the framework has been verified for practical feasibility and shown to align with commercially available optical hardware. In addition, PSO can be integrated with real-time atmospheric sensing and predictive weather models to enable proactive parameter tuning, ensuring resilient and efficient 6G FSO deployment. Overall, the results confirm that misalignment-optimized PSO enhances resilience under severe conditions, supporting 6G availability requirements.

Internet of things (IoT) has made long range wide area network (LoRaWAN) a key component of low-power communication; nevertheless, its adoption in mission-critical domains is limited by its latency, throughput, and quality of service (QoS) restrictions. To bridge these gaps, this paper proposes a hybrid three-layer structure that combines LoRaWAN, fifth generation (5G), and artificial intelligence (AI) to achieve a dynamic trade-off between scalability, reliability, and energy efficiency. According to the findings, the proposed hybrid model significantly improves network performance. It is based on a random forest regressor that integrates LoRaWAN and 5G technologies. The model increases throughput to 40-80 Mbps while maintaining moderate energy consumption, and reduces latency from an average of over 300 ms to less than 150 ms. Additionally, the random forest algorithm improved the overall network performance stability and the packet delivery ratio to roughly 97%. This approach is more effective than earlier studies that relied on descriptive methods or a single technology. This work establishes the foundation for the applications of IoT in smart agriculture, healthcare, and fourth industrial revolution (Industry 4.0).