Study Of Adaptive Beamforming Algorithm Of Smart Antenna

In recent years, with time division multiplexing, frequency division multiplexing, code division multiplexing continue to develop, the increase in channel capacity is already very difficult. At this time, smart antenna, a special type of time-division multiple access system which employs the adaptive modulation technique has been known for its high efficiency in use of the system resource. Beamforming is the very core technology of smart antenna. Beamformer, by adjusting the weight vector of antenna array, can get optimal output for some convergent criterion.The principle of smart antenna and its structure are introduced in this paper firstly, and then some convergent rules are described. Finally, some beamforming algorithms are illuminated at length. In the last chapter, several improved beamforming algorithms are proposed. Firstly, a semi-blind algorithm is presented by integrating RLS algorithm with DDA algorithm. It not only can shorter training sequence, but also can overcome the problem of catch-interference. At the same time it can conduct real-time tracking, than the recursive least squares algorithm with better performance. Secondly, adopting an improved maximum signal-to-(interference plus noise) ratio (MSINR) criterion, capon algorithm, based on estimating DOA of signal, can find the beamforming vector without having to separate the desired and interfering signals. Consequently, the performance of the beamfomer does not degrade substantially due to the estimation error of the array response vector. Then, by combining this beamformer with RAKE receiver, this algorithm can utilize space diversity and time diversity, so it gains better anti-multipath performance. Lastly, DRMTA combined with RLS algorithm after receiving signals despreaded, has a rapid convergence .When more noise in the circumstances, it has a better performance.Matlab simulations proved that the improved algorithms have better performances.