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This study is aimed at using modern methods in beam forming in cognitive radio networks. The beam shaper has an important role in wireless communication by interferences reduction and system capacity improvement. Utilizing this method, the signal of every user is sent as much as feasible by base stations toward the receiver and interferences in the system are effectively reduced. It is worth mentioning that for implementing this method, it is needed to have enough information for forming sender antennas in the best way in order to reach the minimum interference and maximum cognitive radio link efficiency. This information is received in the sender in various ways. The goal of this survey is statingthe pattern forming methods and presenting modern approaches based on information simplification for performing this process while relatively maintaining the system quality. According to an adaptive structure in this study, whole of the channel information is simply sent from the receiver to the sender and it is not necessary to send all the channel information in the time of the channel change. Using this information in forming the pattern by the sender, the system quality would remain satisfactory and desirable. In another approach, quasi-optimal propagation pattern shaping vector is used by the purpose of simplification, convergence of the equations presented, and the elimination of limitations emerged.

Beam forming and modelling in cognitive radio wireless networks