scholarly journals Angle of Arrival Estimation in Smart Antenna for Wireless Communication

2018 ◽  
Vol 7 (4.7) ◽  
pp. 136
Author(s):  
T. S. Jyothi Lakshmi ◽  
S. Sandeep ◽  
Dr. V. Rajya Lakshmi
Keyword(s):  
Smart Antenna ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Minimum Variance ◽  
Antenna System ◽  
Maximum Efficiency ◽  
Communication Link ◽  
Performance Study ◽  
Angle Of Arrival ◽  
Comparative Performance

Smart antenna technology has emerged as one of the most efficient techniques in supporting maximum communication link throughput. A smart antenna system with innovative signal processing can enhance the resolution of a signal’s direction of arrival estimation. Successful design of Smart antenna is dependent on the efficient performance of DOA estimation algorithm as well as beamforming algorithm. This paper presents a comparative performance study between Classical Beam forming method, MUSIC (Multiple Signal Classification), MVDR (Minimum Variance Distortion less Response) which are different direction of arrival algorithms used in linear antenna array. The objective is to analyse and compare these algorithms and determine which provides maximum efficiency.  

scholarly journals Performance analysis of direction of arrival algorithms for Smart Antenna

2019 ◽  
Vol 9 (6) ◽  
pp. 4873
Author(s):  
Btissam Boustani ◽  
Abdennaceur Baghdad ◽  
Aicha Sahel ◽  
Abdelmajid Badri
Keyword(s):  
Performance Analysis ◽  
Smart Antenna ◽  
Direction Of Arrival ◽  
Minimum Variance ◽  
Antenna System ◽  
Estimation Algorithms ◽  
Minimum Variance Distortionless Response ◽  
Subspace Fitting ◽  
Arrival Angles ◽  
Smart Antenna System

<p>This paper presents the performance analysis of the direction of arrival estimation algorithms such as Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Multiple Signal Classification (MUSIC), Weighted Subspace Fitting (WSF), The Minimum Variance Distortionless Response (MVDR or capon) and beamspace. These algorithms are necessary to overcome the problem of detecting the arrival angles of the received signals in wireless communication. Therefore, these algorithms are evaluated and compared according to several constraints required in smart antenna system parameters, as the number of array elements, number of samples (snapshots), and number of the received signals. The main purpose of this study is to obtain the best estimation of the direction of arrival, which can be perfectly implemented in a smart antenna system. In this context, the ROOT-Weighted Subspace Fitting algorithm provides the most accurate detection of arrival angles in each of the proposed scenarios.</p>

scholarly journals Evaluation of Minimum Variance Distortionless Response Beamforming Algorithm Based Circular Antenna Arrays

2016 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Suhail Najm Shahab ◽  
Ayib Rosdi Zainun ◽  
Balasim S. S. ◽  
Nurul Hazlina Noordin ◽  
Izzeldin Ibrahim Mohamed
Keyword(s):  
Antenna Arrays ◽  
Smart Antenna ◽  
Minimum Variance ◽  
Adaptive Beamforming ◽  
Antenna System ◽  
Noise Power ◽  
Noise Mitigation ◽  
Lte Networks ◽  
Continuous Growth ◽  
Minimum Variance Distortionless Response

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 of the wavelength is considered the best interelement spacing, the performance degraded as noise power increased, and more accurately resolution occurred when the number of snapshots increased. The proposed method was found to be performed better than some existing techniques. According to the result, the beampattern relies on the number of element and the separation between array elements. Also, the SINR strongly depends on noise power label and the number of snapshots.

scholarly journals An Inclusive Survey on Various Adaptive Beam Forming Algorithm for 5G Communications Systems

2020 ◽  
Author(s):  
Kaviya K R ◽  
Deepa S
Keyword(s):  
Smart Antenna ◽  
Minimum Variance ◽  
Antenna System ◽  
Least Square ◽  
Decision Feedback ◽  
Signal Interference ◽  
Beam Forming ◽  
Mean Square ◽  
Least Mean Square ◽  
Recursive Least Square

There are several existing wireless system in 5G technology, originating interference in same frequency band and degenerate the concert of received signal. Antenna System comprise of different Beam forming methods in which direction of required signal is generated by the beam and nulls and the voids are set in the direction of unwanted signal (Interference). The survey of different blind and non-blind beam forming algorithms are discussed using smart antenna and phased array. It involves Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Recursive Least Square (RLS), Sample Matrix Inversion(SMI), Linear Constrained Minimum Variance (LCMV), Constant Modulus (CMA), Decision feedback equalization based LMS (DFE-LMS) are considered. These algorithms are outlined to be claimed in 5G network to provide good quality, capacity and dealing with coincidence of signals and interference.

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