Research On Adaptive Beamforming Control Algorithm Of Smart Antenna

It is very limited spectrum resources in the rapid development of mobilecommunication technology, become more and more scarce and precious. In order toreduce the mobile communication signal attenuation in the channel complexenvironment, improve the reception of mobile communication system and emissionperformance, people put forward the concept of signal enhancement. Smart antennabelongs to this category. Smart antenna for the development of space resources,therefore, the filter of smart antenna technology can be attributed to a kind of spaceand time.Because of the smart antenna technology has very strong anti-jamming capability,and it also has anti multipath and fading ability, so the majority of scientific researchworkers of the smart antenna technology has paid a great deal of attention. Itsworking principle is that the each array element of antenna array is given the samplingdata, determine the number of signal sources, and then estimates the parameters of thesignal and the formation of beam, the key lies in the adaptive beam-forming. Antennabeam-forming to adaptive control system, its technical difficulty is how thebeam-forming algorithm to adaptively control the pattern of antenna, electromagneticwave of antenna can achieve directional receiving and transmitting. Because of thefast convergence of the system and the circuit complexity relies on beam-formingalgorithm, so the choice of what kind of algorithms to form a pattern, which is veryimportant to smart antenna system.In this paper, research on the adaptive beam control algorithm, beam algorithmincluding non-blind algorithms and blind algorithms. Non-blind algorithm requires abase station sends a local reference sequence, and the blind algorithm without.Firstly, comparative study the computation and performance of blind andnon-blind two kinds of adaptive beamforming algorithm, some details of thealgorithm, and the algorithm of figure and derivation, and simulated by usingMATLAB software. According to the comparative studies, the scope of application ofLMS algorithm based on steepest descent gradient estimation is relatively somemore widely, it is particularly suitable for use in an unknown signal statisticalcharacteristics of stable environment. In this paper, the LMS algorithm usesminimum error criterion.Secondly, This paper is based on the LMS algorithm, an improved scheme is putforward, and validates the use of the HFSS. Based on the original algorithm, the interference signal autocorrelation value e (n)e (n d)to control the size of stepfactor, the fixed step factor of LMS algorithm improvement as the variable stepfactor can improve the anti-interference performance of smart antenna system fornoise signal self-correlation is weak, so this improved LMS algorithm can havewider application occasions.Finally, research on adaptive beam control algorithm for smart antennas aresummarized and analyzed, and points out the research direction in the future.