Free-space optical communication delivers fiber-like bandwidth and inherent security, making it critical for 6G networks, military tactical communications and post-disaster emergency response. However, its strict line-of-sight requirement leaves it extremely vulnerable to malicious laser jamming from battery-powered drones, which operate in intermittent “attack-idle” cycles rather than continuously as most studies assume. Existing solutions also fail to balance performance and deployment cost, limiting real-world adoption.
Led by Professor Dingshan Gao, the Wuhan National Laboratory for Optoelectronics team addressed these gaps with a drone-mounted IRS system that creates virtual bounce paths to bypass blockages and jamming. Their three core innovations include a realistic Bernoulli jamming model, a comprehensive low-altitude composite channel model, and a customized alternating optimization algorithm with a convergence speed 2.7 times faster than genetic algorithms, reaching stable convergence in only 15 iterations.
The optimized system reduces outage probability by an order of magnitude while staying within budget. Researchers noted it provides both a real-time optimization engine for critical scenarios and a cost-effective path for civilian networks. The work entitled “Outage analysis and optimization for IRS-UAV-assisted FSO systems under malicious jamming” was published in Frontiers of Optoelectronics (published on May. 20, 2026).

DOI：10.2738/foe.2026.0023