Research And Implementation Of Efficient Routing Algorithm For Flying Ad-Hoc Network

With the development of airborne communication technology,Flying ad-hoc Network(FANET),which is highly dynamic and intelligent,can enhance the ability of UAV cluster to cooperatively complete complex tasks.As a mobile sensor,UAV cluster can collet information in areas beyond the coverage of base stations and send the perceived data back to the command center for analysis,thus realizing remote control of the physical world.However,the available spectrum resources of UAV cluster are scarce compared with that required to transmit vast amount of sensing data.In addition,it is necessary to transmit perceived data back through multi-hop networking of multiple UAVs,which is due to the limited transmission range of a single UAV.The airborne communication network is characterized by multi-link coexistence and topological dynamics.Therefore,how to adapt the links according to transmission requirements to realize the complementarity between heterogeneous links,and improve the networking efficiency by designing intelligent adaptive routing algorithm is worth studying.To solve the above problem,this paper firstly builds a heterogeneous self-organizing airborne communication network model to simulate the UAV cluster networking and communication behavior,and then proposes an adaptive clustering algorithm and intelligent routing strategy for heterogeneous links.By implementing the algorithm on the platform,the practical value of the proposed algorithm is analyzed.The main contributions of this paper are as follows:Firstly,this paper designs and builds a heterogeneous self-organizing airborne communication network model platform.Primarily,the network topology layer,node layer and process layer models for CSMA,FDMA and TDMA communication links is built based on three-layer modeling mechanism.Furthermore,the state machine jump logic of distributed weighted clustering and heterogeneous link adaptation is designed and realized according to the fast networking requirements of UAV groups.In addition,this paper proposes a multi-hop routing algorithm based on direction angle,and then implements the simulation test function based on the network performance indicator of end-to-end delay,throughput,network stability for this algorithm.Secondly,this paper proposes an adaptive clustering algorithm and intelligent routing strategy for heterogeneous links.In order to improve the data transmission efficiency,the data of multiple UAVs are gathered and transmitted back to the command center by means of multi-hop relay between different UAV clusters.To further improve data transmission efficiency,UAVs can flexibly choose heterogeneous data link according to the difference of transmission requirements.In order to increase the driving force of multi-hop back,a multi-hop routing algorithm based on Q-learning is designed.Then,the proposed algorithm simulation is implemented on the platform of the heterogeneous self-organizing airborne communication network.The simulation results indicate that compared with the traditional routing algorithm,the average delay was reduced by 6.7%and the average queue length was reduced by 33%,the proposed algorithm can reduce the delay of multi-hop transmission on the premise of ensuring system stability.