Research On Key Techniques For Spatial Cognitive Anti-jamming

With the development of wireless communication technology, the spectrumresource shortage and the electromagnetic environment complexity is increasinglyapparent, So how to realize wireless communication with the capability ofanti-jamming in the complex electromagnetic environment has raised considerableattention in recent years. Traditional anti-jamming communication techniques aremainly designed based on the time domain, the spatial domain or the frequencydomain. Based on the project “a shortwave anti-jamming communication receivebeamforming” and combining with the spatial filtering and frequency domain cognitiveanti-jamming technology, this paper emphasized on the research and implementationfor:1.spatial beamforming algorithm2.beam-space algorithm3. frequency domaincognitive rendezvous algorithm.Firstly, the concept of spatial cognitive anti-jamming is introduced. Thesequence-based frequency rendezvous algorithm is focused, and a sequence-baseddesign for cognitive wireless network is proposed. Comparing with the previoussequence, simulation results show that the designed sequence has a large increase interms of the rendezvous expectation TTR and MaxTTR. It improves the rendezvousperformance of system.Secondly, We mainly focus on antenna pattern of an arbitrary array and explorethe feasibility of the array usage in spatial beamforming for anti-jamming. Then, themain principles and algorithms of adaptive beamforming are introduced. An improvedvariable step size LMS algorithm is proposed to solve the contradiction between theconvergence rate and the steady-state error in the traditional fixed step size LMSadaptive algorithm. Comparing with the traditional LMS algorithm, this new algorithmhas an apparently advantage in solving the contradiction above.Thirdly, this paper focuses on beam-space partially adaptive arrays ofreduced-demension partially adaptive arrays. The beam-space forming principle aswell as two beam-space forming algorithm (the DFT beam-space algorithm andadaptive-adaptive algorithm) are studied. The advantages as well as the disadvantagesof the two beam-space algorithms are put together, and the effectiveness of the twomethods are validated through simulation results.Finally, the LMS algorithm and the adaptive beam-space algorithm areimplemented in FPGA.