Adaptive Direction of Arrival Estimation Algorithms for 5G Network and Beyond (original) (raw)
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Fifth Generation (5G) wireless communication is an ecosystem of technological advancements involving a multitude of domains. These domains include Augmented Reality (AR), Internet of Things (IoT), Device-to-Device (D2D) Communication, Machine-to-Machine (M2M) Communication, Health IoT (H-IoT), Financial Technology (FinTech) etc. A multi-gigabit network architecture capable of offering data rates of the order of Gigabits per second (Gbps) is expected due to the enormous increase in the number of connected devices. 5G wireless communication systems are enough to accommodate the unavoidable explosion in user data traffic and area-wise connection densities. New and advanced signal processing techniques are used at both the transmitter and receiver sides to meet the growing data needs of the end-users without any outage. These techniques include precoding, zero forcing, Diversity, Beamforming, Relaying, Filtering, Combining, etc. In this paper, we studied and verified different beamformi...
An Overview of Direction-Of-Arrival Estimation Using an Antenna Array with Four Elements
American Journal of Applied Sciences, 2012
The Direction-of-Arrival (DOA) estimation techniques using antenna arrays are applied in large areas of research fields and have received great attention in literature. Mobile communication, Sonar and Radar are just some examples among a large number of possible applications. For example, in military application, it is very important to recognize the direction of any threat. Another example of commercial application is to identify the direction of an emergency cell phone call so that the rescue unit can act in time to the right location. Thereby, DOA estimation using a traditional fixed antenna has many limitations and becomes inappropriate in such applications. In this letter, we describe a DOA estimation system based on an antenna array and five port circuits for detecting arrival angles in azimuth plane of signals pitched by the antenna array. For this, we have based on Multiple Signal Classification (MUSIC) algorithm, which showed a certain limit of its performance in spite of its big reputation by the researchers. In our case, we only consider uncorrelated signals and assume the channel parameters corresponding to a real context. The purpose is to compare the quality of the detected angle in term of precision depending on the number of the samples depicted. ADS software and MATLAB are used to achieve this study. The simulation results on the proposed system designed to operate at 2.4 GHz frequency indicate that MUSIC algorithm is unable to automatically detect and localize the DOA of signals with high accuracy. Other algorithms exist and may provide more precision but require more computation time.
Performance Evaluation for Direction of Arrival Estimation Using 4-Element Linear Array
2019 13th European Conference on Antennas and Propagation (EuCAP), 2019
This paper presents the performance evaluation of Direction of Arrival (DOA) estimation techniques such as Root-MUSIC, Root-WSF and Beamspace-ESPRIT (BS-ESPRIT) algorithms under common Wi-Fi conditions such as operating in the IEEE radio frequency spectrum of 5 GHz band, the presence of noise and correlated, closely sourced signals. In addition, we will consider the computational time required for these algorithms to complete the estimation process. Results have shown that the 3 techniques provide a mean of 98.8% accuracy in detecting closely-sourced signals. Although Root-WSF has the longest average computational time of 36.7ms as opposed to BS-ESPRIT and Root-MUSIC at 29.4ms and 22.5ms respectively, Root-WSF technique performed best overall especially in detecting coherent signals with 99.78% accuracy as compared to BS-ESPRIT at 95.27% and Root-MUSIC at 64.77%.
Direction of Arrival Estimation using MUSIC Algorithm for Antenna Arrays
Direction of arrival (DOA) estimation has been a vital area of research since few decades due to its importance in applications like wireless communications, navigation, radar, sonar and soon. The resolution being one of the main challenges in the direction of arrival estimation can be enhanced by using an array antenna system with reliable signal processing. High resolution techniques make use of array antenna structures to efficiently process the incoming signals. This paper simulates a high resolution subspace based DOA algorithm namely; Multiple Signal Classification (MUSIC) on a uniform linear array in the presence of white Gaussian noise. The paper also provides an extensive discussion on importance of Adaptive beam forming algorithm used in mobile communication systems along with the DOA algorithm. The simulation results indicate that MUSIC which is a subspace based method provides high spatial resolution and the resolution improves as the number of array elements, number of snapshots and spacing between the array elements increase. It also showed that increase of separation angle between the two sources also gives better results.
Mobile communication networks face ever-increasing demands on their spectrum and infrastructure resources. Increased minutes of use, capacity-intensive data applications and the steady growth of worldwide mobile subscribers means that carriers will have to find effective ways to accommodate increased wireless traffic in their networks. Thus, the smart antennas system becomes capable to locate and track signals by the both: users and interferers and dynamically adapts the antenna pattern to enhance the reception in Signal-Of-Interest direction and minimizing interference in Signal-Of-Not-Interest direction. Hence, Space Division Multiple Access system, which uses smart antennas, is widely used in mobile communication systems, because it shows improvement in channel capacity and co-channel interference. But on the other hand the performance stability of smart antenna system greatly depends on efficiency of Direction of Arrival (DOA), which is used to estimate the angle of arrival of the number of incidents plane waves on the antenna array. This paper shows an effort on the study of performance analysis of DOA estimation Algorithms-MUSIC and ESPRIT for Adaptive Array Smart Antenna for Mobile Communication on different performance parameters such as number of elements, number of snap shots, noise mean, noise variance and spacing between elements.
MMOSPA-based direction-of-arrival estimation for planar antenna arrays
2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014
This work is concerned with direction-of-arrival (DOA) estimation of narrowband signals from multiple targets using a planar antenna array. We illustrate the shortcomings of Maximum Likelihood (ML), Maximum a Posteriori (MAP), and Minimum Mean Squared Error (MMSE) estimation, issues that can be attributed to the symmetry in the likelihood function that must exist when there is no information about labeling of targets. We proffer the recently introduced concept of Minimum Mean OSPA (MMOSPA) estimation that is based on the optimal subpattern assignment (OSPA) metric for sets and hence inherently incorporates symmetric likelihood functions.
Performance Analysis of Direction of Arrival ( DOA ) Estimation Techniques For LTE-R
2013
The third generation of Global System for Mobile Communications(GSM) have evolved to Long Term Evolution(LTE/SAE), similarly the GSM for Railway(GSM-R) is expected to evolve to LTE for Railway(LTE-R).Since LTE/SAE implements MIMO technologies it is also expected for LTE-R to adopt MIMO systems.In Array Processing it is possible to increase the capacity and throughput of the network by using Direction of Arrival(DOA) estimation techniques which may be stationary if the angle of arrival does not change with time or dynamic if the angles of arrival change with time.In this paper we study the performnace of DOA estimation algorithms that might be adopted for DOA estimations of High Speed Train LTE-R system.We will compare the performance of four algorithms namely: Multiple Signal Classification(MUSIC),Capon’s (MDVR),Min-Norm and Classical Beamformer applied on Uniforma Linear Array(ULA).
Perfomance Study of Direction of Arrival (DOA) Estimation Algorithms for Linear Array Antenna
2009 International Conference on Signal Processing Systems, 2009
This paper presents the performance analysis of five direction of arrival estimation algorithms namely Bartlett, Minimum Variance Distortionless Response (MVDR), Linear Prediction and MUSIC DOA Estimates. We present the description, comparison and the performance and resolution analyses of these algorithms. Sensitivity to various perturbations and the effect of parameters related to the design of the sensor array itself such as the number of array elements and their spacing are also investigated. The analysis is based on linear array antenna and the calculation of the pseudospectra function of the estimation algorithms. Matlab is used for simulating the algorithms.
The performance of the smart antennas greatly relies on the efficient estimation of direction of arrival. Therefore, the authors have addressed and analyzed high resolution subspace based algorithms to evaluate the performance for accurate estimation of direction-of-arrival (DOA) of signals impinging on uniform linear array (ULA). Simulation results showed that Matrix Pencil provides better performance in terms of root mean square error (RMSE) and probability of resolution; although its performance is not as good as Root-MUSIC algorithm for closely spaced signals. Profound analysis of these algorithms can be used to determine the direction of arrival of the signals at ULA.
Performance analysis of direction of arrival algorithms for Smart Antenna
International Journal of Electrical and Computer Engineering (IJECE)
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 ...