MVDR Algorithm Based Linear Antenna Array Performance Assessment For Adaptive Beamforming Application (original) (raw)
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Wireless data traffic is in a continuous growth, and there are increasing demands for wireless systems that provide deep interference suppression and noise mitigation. In this paper, adaptive beamforming (ABF) technique for Smart Antenna System (SAS) based on Minimum Variance Distortionless Response (MVDR) algorithm connected toCircular Antenna Array (CAA) is discussed and analyzed. The MVDR performance is evaluated by varying various parameters; namely the number of antenna elements, space separation between the elements, the number of interference sources, noise power label, and a number of snapshots. LTE networks allocate a spectrum band of 2.6 GHz is used for evaluating the MVDR performance. The MVDR performance is evaluated with two important metrics; beampattern and SINR. Simulation results demonstrate that as the antenna elements increase, the performance of the MVDR improves dramatically. This means the performance of MVDR greatly relies upon the number of the elements. Half...
Beamforming Algorithms Technique by Using MVDR and LCMV
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In this paper, minimum variance distortionless response (MVDR) algorithm for adaptive Beamforming is applied to a linear array under known mutual coupling among half wavelength dipole (HWD) antennas. This algorithm will minimize the signals from all interference directions while keeping the desired signal undistorted. The problem of calculating mutual coupling coefficient of the array HWD antennas formed into a matrix has been considered. The obtained results show the effectiveness of the proposed method, in which the optimum weighting of adaptive antenna arrays is accomplished by computing the weight vector that achieves maximum towards the desired signal and nulls towards interferers. Also, performance evaluation of this algorithm in terms of complexity, convergence speed, and amplitude response will be present. It is shown from the simulation results that the performance of the beamforming algorithm considering the mutual coupling effect can be improved by the proposed compensation method. We also simulate the signal-to-interference-plus-noise ratio (SINR) with different input signal-to-interference ratio (SIR). The different results obtained are in good agreement with those of the literature.
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The minimum variance distortionless response (MVDR) beamforming algorithm is used in smart antenna design for wireless communication. The operation of MVDR is based on finding the optimum weight to direct the main lobe beam to the desired user location with a unity gain. MVDR is very sensitive to signature vector mismatch. This mismatch occurs due to waveform deformation, local scattering, imperfect array element calibration and element shape distortion, which leads to errors in finding the direction of arrival (DOA) of the signal. In this paper, a new technique to modify the MVDR is presented, modelled and evaluated. The proposed algorithm is named modified MVDR (MMVDR) and is dependent on reconstructing the signature vector (steering vector) and the covariance matrix to introduce accurate beamformer weight by re-localization the reference element to be in the middle of ULA, rather than at one end side. The new reference position partitions the array's elements into two groups around this reference, which leads to treat received signals with identical phase along the array's elements, as well as increasing the degree of freedom to deals with different types of uniform arrays. The evaluation results show that MMVDR outperforms MVDR with respect to beamformer accuracy, system cost, processing time and signal classification to overcome the errors in DOA estimation which occur due to fabrication and calibration errors.
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A sensitivity analysis of two distortionless beamformers is presented in this paper 1 . Specifically, two well-known variants, namely the minimum power distortionless response (MPDR) and minimum variance distortionless response (MVDR) beamformers, are considered. In our scenario, which is typical to many modern communications systems, waves emitted by multiple point sources are received by an antenna array. An analytical expression for the signal to interference and noise ratio (SINR) improvement obtained by both beamformers under steering errors is derived. These expression are experimentally evaluated and compared with the robust Capon beamformer (RCB), a robust variant of the MPDR beamformer. We show that the MVDR beamformer, which uses the noise correlation matrix in its minimization criterion, is more robust to steering errors than its counterparts, that use the received signal correlation matrix. Furthermore, even if the noise correlation matrix is erroneously estimated due to steering errors in the interference direction, the MVDR advantage is still maintained for reasonable range of steering errors. These conclusions conform with Cox [1] findings. Only line of sight propagation regime is considered in the current contribution. Ongoing research extends this work to fading channels.
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We present an analysis of the signal-to-interferenceplus-noise ratio (SINR) at the output of the minimum variance beamformer. The analysis is based on the assumption that the signals and noise are Gaussian and that the number of samples is large compared to the array size, and it yields an explicit expression for the SINR in terms of the different parameters affecting the performance, including signal-to-noise ratio (SNR), interference-to-noise ratio (INR), signal-to-interference ratio (SIR), angular separation between the desired signal and the interference, array size and shape, correlation between the desired signal and the interference, and finite sample size.
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This paper introduces an 8-element linear array designed for adaptive array applications, using least mean square (LMS) algorithm to enhance the directivity of the array. Microstrip antenna has been optimized at 2.3 GHz, a pivotal frequency ranges relevant to 4G and 5G applications. This design is thoughtfully extended to encompass 8-elements, achieved through the art of parameterization using computer simulation technology (CST) microwave studio. This geometry of 8-element exhibits considerable promise, significantly elevating the gain from 6.13 dBi for a single element to an impressive 15.5 dBi for all eight-element array. To further empower the array's adaptability and beam-steering capabilities, the LMS algorithm is simulated. This intelligent algorithm computes complex weights, thoughtfully with various angles, including those for the interested user at 60° and 30°, as well as potential interferers at 10° and 15°, as simulated in MATLAB. These meticulously calculated weights are effectively applied to antenna elements using CST, facilitating beam steering in various directions. During CST simulations, notable peaks in performance emerge at 54° and 28°, strategically aligned with nulls at 10° and 15°. Remarkably, these results exhibit a remarkable degree of concurrence with those obtained through MATLAB simulations, affirming effectiveness of the proposed adaptive array design.