• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.4244-4274
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• 2021

The utilization of UAVs in various fields has led to the development of flying ad hoc network (FANET) technology. In a network environment with highly dynamic topology and frequent link changes, the traditional routing technology of FANET cannot satisfy the new communication demands. Traditional routing algorithm, based on geographic location, can "fall" into a routing hole. In view of this problem, we propose a geolocation routing protocol based on multi-agent reinforcement learning, which decreases the packet loss rate and routing cost of the routing protocol. The protocol views each node as an intelligent agent and evaluates the value of its neighbor nodes through the local information. In the value function, nodes consider information such as link quality, residual energy and queue length, which reduces the possibility of a routing hole. The protocol uses global rewards to enable individual nodes to collaborate in transmitting data. The performance of the protocol is experimentally analyzed for UAVs under extreme conditions such as topology changes and energy constraints. Simulation results show that our proposed QLGR-S protocol has advantages in performance parameters such as throughput, end-to-end delay, and energy consumption compared with the traditional GPSR protocol. QLGR-S provides more reliable connectivity for UAV networking technology, safeguards the communication requirements between UAVs, and further promotes the development of UAV technology.

• 한국통신학회논문지
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• 제37권8C호
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• pp.655-662
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• 2012

본 연구에서는 다수 레이다신호의 간섭으로 인해 항공기가 데이터통신이 두절될 것을 대비하여 새로운 주파수(채널)을 탐색하기 위해 Cognitive Radio 기술을 활용한 항공인지무선시스템을 제안한다. 항공기의 데이터통신 채널을 확보하기 위해 비행환경하에 레이다의 주파수를 인지하여 지형정보를 통한 유효주파수를 산출하여 빠르게 스펙트럼을 센싱하는 방법을 제안하였다. 기지국은 항공기와 레이더의 위치를 기반으로 자유공간의 경로손실을 이용한 방식으로 유효 주파수를 계산하였고 이동체에 대한 변수를 병행하여 적용하였다. 분석 결과 기존 최대 주파수 탐색시간이 제안된 방법을 활용시 절반으로 단축됨을 입증하였다.