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An enhanced minimum variance distortionless response beamformer techniques to reduce interference in array antenna system

机译:增强的最小方差无失真响应波束形成器技术,可减少阵列天线系统中的干扰

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摘要

Beamforming (BF) algorithm is one of the major smart antenna function that forming beams towards the direction of the desired user while simultaneously suppressing signals origination from other directions. Minimum Variance Distortionless Response (MVDR) is basically a unity gain adaptive beamformer which is suffering from performance degradation due to the presence of interference and noise. Also, MVDR is sensitive to the direction of arrival mismatch, and unsatisfactory null-forming level. This thesis presents two BF techniques to enhancing the MVDR null-forming level. First, the zero-null constraint adds to the MVDR beamformer based on uniform linear antenna arrays. The proposed MVDRZN is based on reconstructing the excitation weight vector coefficients to enforcing the undesired signal energy equal to zero (or near zero) and the desired signal energy equal to one (unity gain). Metaheuristic optimization algorithms are used widely to solve many engineering problems. Second, hybrid Particle Swarm Optimization/Gravitational Search Algorithm (PSOGSA) is used to obtain a desired radiation pattern by enhancing the MVDR nulling level. The proposed MVDRPSOGSA method combines the search methods of PSO and GSA, thus achieving the improved exploration ability needed to obtain high accuracy with deep null-forming in the directions of the interference sources. Whereas in the BF applications, Signal-to-Interference plus Noise Ratio (SINR) is a valid fitness function because it measures how well the array’s radiation pattern focuses energy on a Signal Of Interest (SOI) and steers nulls towards interference. In addition, to provide high accuracy beampattern and to enhance the null-forming level to suppress the interference and noise deeply. The performance of the proposed approaches is judged by the beampattern accuracy for azimuth and elevation scanning angles, SINR improvement through a deep null-forming level. The null width in the azimuth and elevation scanning angle also have been assessed. The result shows that the proposed MVDRZN method clearly introduce more than 300 dB negative power to serve the interference source with average SINR improvements approximately 250 dB and accurate azimuth and elevation angles. It is observed that the MVDRZN can provide a perfect radiation pattern with relatively few snapshots records. The obtained results confirm the complete agreement between MVDR technique and hybrid intelligent swarm PSOGSA algorithm. The proposed MVDRPSOGSA approach can successfully place very sharp nulls (-200 dB deep, on average) at the undesired angles. It is providing additional support to the smart antenna array system to combat the co-channel interference and array noise reduction. These approaches achieve significant SINR improvement by reducing the effects of multiple access interference in the wireless communication systems.
机译:波束成形(BF)算法是主要的智能天线功能之一,它可以朝着所需用户的方向形成波束,同时抑制来自其他方向的信号。最小方差无失真响应(MVDR)基本上是单位增益自适应波束形成器,由于存在干扰和噪声,其性能会下降。而且,MVDR对到达不匹配的方向和不令人满意的零形成水平很敏感。本文提出了两种提高MVDR空值形成水平的BF技术。首先,零空约束基于均匀线性天线阵列将其添加到MVDR波束形成器中。所提出的MVDRZN基于重构激励权重矢量系数以强制将不希望的信号能量等于零(或接近零)和期望信号能量等于1(统一增益)。元启发式优化算法被广泛用于解决许多工程问题。其次,使用混合粒子群优化/引力搜索算法(PSOGSA)通过增强MVDR无效水平来获得所需的辐射方向图。所提出的MVDRPSOGSA方法将PSO和GSA的搜索方法结合在一起,从而实现了获得更高的探查能力,从而获得了较高的探测能力,并在干扰源的方向上形成了深空洞。在高炉应用中,信号干扰加噪声比(SINR)是有效的适应度函数,因为它可以测量阵列的辐射方向图将能量集中在感兴趣的信号(SOI)上的程度,并使零点转向干扰。另外,提供高精度的波束图并增强零陷形成水平以深深地抑制干扰和噪声。所提出方法的性能是通过波束图形的方位角和仰角扫描角精度,通过深零位形成水平的SINR改善来判断的。还已经评估了方位角的零宽度和仰角扫描角。结果表明,所提出的MVDRZN方法明显引入了超过300 dB的负功率来为干扰源提供服务,平均SINR改善了约250 dB,并获得了精确的方位角和仰角。可以看出,MVDRZN可以提供快照记录相对较少的完美辐射图。获得的结果证实了MVDR技术与混合智能群PSOGSA算法之间的完全一致性。拟议的MVDRPSOGSA方法可以在不希望的角度成功放置非常尖锐的零点(平均深度为-200 dB)。它为智能天线阵列系统提供了额外的支持,以应对同频道干扰和降低阵列噪声。这些方法通过减少无线通信系统中的多址干扰的影响实现了显着的SINR改善。

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    Shahab Suhail Najm;

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  • 年度 2017
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