With the faster growth of fifth-generation (5G) and sixth-generation (6G) wireless communication systems, there are unprecedented requirements for ultra-low energy consumption wireless and microwave networks facing an increasing demand for enabling extreme-bandwidth data rates, massive connectivity, and low-latency communications. For optimization problems such as network routing, microwave resource allocation and antenna parameters adaptation, even though the general optimality of the solutions can be proven or demonstrated while optimizing directly with traditional algorithms, they often converge slowly and get trapped in local optima. In response to these issues, this paper presents an Energy Efficient Wireless and Microwave Network Framework using Advanced Hybrid Salp Swarm–Whale Optimization (HSSWO) algorithm. It provides a hybrid method that uses SSA with its good exploration ability and WOA for adaptively exploiting the routing paths, transmission power, microwave antenna parameters, and spectrum assignment. It further adds an AI-assisted network evaluation module for intelligent decision-making. The experimental results show that the proposed HSSWO framework attains 95.82% energy efficiency, a 41.6% improvement in network lifetime, throughput of 12.47 Gbps, packet delivery ratio of 99.21%, end–to–end latency of only 0.58 ms and a packet loss of only 0.69%. Moreover, the utilization of the proposed method leads to a reduction of optimization time for an average of 31.8% as well as improving convergence speed by an average of 36.4% over state-of-the-art optimization methods. The proposed HSSWO framework is an efficient energy-aware architecture for next-generation wireless and microwave communication systems as these results confirm.