We present the simulation of the adaptive blind beam formation using the normalized constant modulus algorithm (NCMA) for the application of intelligent antenna systems. The importance and basic design of the intelligent antenna in terms of mathematical model is discussed. In this paper we consider 16-point Quadrature Amplitude Modulation (QAM) data, which is one of the preferred modulation formats in the design of modems and other wireless fixed location applications in the industry. The simulation results are presented in terms of matrix factor and antenna matrix response, in which a significant improvement is observed in comparison with other related works.
Modeling and simulation of a uniform linear matrix using adaptive beam formation with minimum bit error rate (BER) for the application of intelligent antennas by means of matrix adaptation - Normalised Meat Mean Square (MI-NLMS). We have modeled a linear array of antennas for a power beam width of 20 ° (HPBW) and obtained beam-forming with digital modulation of 16-point quadrature amplitude modulation (QAM). This modulation technique is used for systems such as CDMA, Wi-Fi (IEEE 802.11) and WiMAX (IEEE 802.16). The algorithm has the advantage of both block and sample adaptation by sample techniques, which demonstrates that block adaptation performance and LMS normalization minimize system capacity and minimize bit error rate (BER) Up to 10-4 for the signal-to-noise ratio of 13 dB. Quadrature amplitude modulation (QAM) allows us to send more bits per symbol to achieve higher throughput and to overcome fading and other interference. The simulation is done in MATLAB.