Interference Mitigation using Adaptive Digital Beamforming for 5G Applications (original) (raw)
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Adaptive Beamforming approach have provided significant amount of contribution in mitigating interference in wireless communication. This paper presents an Adaptive Beamforming approach using MVDR (Minimum Variance Distortionless Response) for interference suppression and to form beam in the estimated direction. Non-Blind algorithm with MVDR beamforming approach have been proposed in this paper. Simulated results show that the proposed method provides better performance with narrower beamwidth and higher gain.
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Modeling and simulation of uniform linear array usi ng Matrix Inversion-Normalized Least Mean Square (MI-NLMS) adaptive beam forming with minimum Bit Er ror Rate (BER) is developed for smart antenna applications. We have modeled a linear array of ant ennas for 20°Half Power Beam Width (HPBW) and obtained the beam formation with digital modulation of 16 point Quadrature Amplitude Modulation (QAM).This modulation technique is used for the sys tems like CDMA,Wi-Fi (IEEE802.11) and WiMAX (IEEE 802.16).The algorithm have the advantage of both block adaptation and sample by sample techniques which shows that the performance of blo ck adaptation and normalization of Least Mean Square (LMS) improves the system capacity and minim ize bit error rate (BER) upto 10 -4 for the signal to noise ratio of 13 dB's. The Quadrature amplitude mo dulation (QAM) allows us to send more bits per symbol to achieve higher throughput and to overcome fading and other interferences. The simulation is done in...
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— Smart antenna attempt to enhance the received signal, suppress all interfering signals, and increase capacity. Beamforming is one of the mostly used antenna technique. It adjust the radiation beam in one specific direction also reduces multiple access interference. It also reduces common channel interference and multiple path fading, in result it increases capacity of mobile network. In this paper two antenna beam forming algorithms are analyzed. These two algorithms are Least Mean Square and Minimum Variance Distortionless Response. Outputs of these two algorithms are in weights. By using these outputs weights, two parameters i.e. Mean Square Error and Power Beam Width are calculated and two algorithm are compared by this parameters and respective results are discussed.