  Malicious jamming launched by smart jammer, which attacks legitimate
transmissions has been regarded as one of the critical security challenges in
wireless communications. Thus, this paper exploits intelligent reflecting
surface (IRS) to enhance anti-jamming communication performance and mitigate
jamming interference by adjusting the surface reflecting elements at the IRS.
Aiming to enhance the communication performance against smart jammer, an
optimization problem for jointly optimizing power allocation at the base
station (BS) and reflecting beamforming at the IRS is formulated. As the
jamming model and jamming behavior are dynamic and unknown, a win or learn fast
policy hill-climbing (WoLF-PHC) learning approach is proposed to jointly
optimize the anti-jamming power allocation and reflecting beamforming strategy
without the knowledge of the jamming model. Simulation results demonstrate that
the proposed anti-jamming based-learning approach can efficiently improve both
the IRS-assisted system rate and transmission protection level compared with
existing solutions.
