<p>Wireless Mesh Networks (WMNs) are emerging as an increasingly attractive area of research which offering cost-effective, easily deployable, and high-performance solutions for broadband network access. Among the advancements in this field, Multiple Input Multiple Output (MIMO) technology stands out as a significant breakthrough, greatly enhancing network capacity and performance. This research investigates the crucial aspects of WMNs, including network routing, channel assignment, and the capacity of MIMO channels, with a specific focus on the impact of varying numbers of transmit and receive antennas. An intelligent Teaching–Learning-Based Optimization (TLO) algorithm was applied to determine the optimal routing paths between source and destination nodes in Wireless Sensor Networks (WSNs) to optimize network efficiency and significantly improves overall network performance. The proposed method is evaluated through number of simulations and demonstrated that the algorithm's ability to converge rapidly and achieving optimal solutions in minimal time. The attained results highlight the effectiveness of the Alamouti scheme, particularly the 2 × 2 antenna configuration, which achieves a remarkably low Bit Error Rate (BER) of 1.1e-005 units. Even with a 2 × 1 configuration, the BER is reduced to 0.001606 units, showcasing superior performance compared to the traditional Maximum Ratio Combining (MRC) technique. These results underscore the potential of the proposed approach to significantly enhance the performance and reliability of WMNs, making it a promising solution for future wireless communication networks.</p>