  In this paper, we propose a reinforcement learning-based flexible duplex
system for B5G with Sub-6 GHz. This system combines full-duplex radios and
dynamic spectrum access to maximize the spectral efficiency. We verify this
method's feasibility by implementing an FPGA-based real-time testbed. In
addition, we compare the proposed algorithm with the result derived from the
numerical analysis through system-level evaluations.
