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With unprecedented increases in traffic load in today's wireless networks, design challenges shift from the wireless network itself to the computational support behind the wireless network. In this vein, there is new interest in quantum-compute approaches because of their potential to substantially speed up processing, and so improve network throughput. However, quantum hardware that actually exists today is much more susceptible to computational errors than silicon-based hardware, due to the physical phenomena of decoherence and noise. This paper explores the boundary between the two types of computation---classical-quantum hybrid processing for optimization problems in wireless systems---envisioning how wireless can simultaneously leverage the benefit of both approaches. We explore the feasibility of a hybrid system with a real hardware prototype using one of the most advanced experimentally available techniques today, reverse quantum annealing. Preliminary results on a low-latency, large MIMO system envisioned in the 5G New Radio roadmap are encouraging, showing approximately 2--10\times× better performance in terms of processing time than prior published results.