Comparison of Kernel Methods Applied to Smart Antenna Array Processing

Author(s):  
Christos Christodoulou ◽  
Manel Martínez-Ramón

Support vector machines (SVMs) are a good candidate for the solution of antenna array processing problems such as beamforming, detection of the angle of arrival, or sidelobe suppression, due to the fact that these algorithms exhibit superior performance in generalization ability and reduction of computational burden. Here, we introduce three new approaches for antenna array beamforming based on SVMs. The first one relies on the use of a linear support vector regressor to construct a linear beamformer. This algorithm outperforms the minimum variance distortionless method (MVDM) when the sample set used for training is small. It is also an advantageous approach when there is non-Gaussian noise present in the data. The second algorithm uses a nonlinear multiregressor to find the parameters of a linear beamformer. A multiregressor is trained off line to find the optimal parameters using a set of array snapshots. During the beamforming operation, the regressor works in the test mode, thus finding a set of parameters by interpolating among the solutions provided in the training phase. The motivation of this second algorithm is that the number of floating point operations needed is smaller than the number of operations needed by the MVDM since there is no need for matrix inversions. Only a vector-matrix product is needed to find the solution. Also, knowledge of the direction of arrival of the desired signal is not required during the beamforming operation, which leads to simpler and more flexible beamforming realizations. The third one is an implementation of a nonlinear beamformer using a non-linear SVM regressor. The operation of such a regressor is a generalization of the linear SVM one, and it yields better performance in terms of bit error rate (BER) than its linear counterparts. Simulations and comparisons with conventional beamforming strategies are provided, demonstrating the advantages of the SVM approach over the least-squares-based approach.

2018 ◽  
Vol 7 (4.7) ◽  
pp. 136
Author(s):  
T. S. Jyothi Lakshmi ◽  
S. Sandeep ◽  
Dr. V. Rajya Lakshmi

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.  


Author(s):  
M. Martinez-Ramon ◽  
A. Navia-Vazquez ◽  
C.G. Christodoulou ◽  
A.R. Figueiras-Vidal

Author(s):  
Maria Trigka ◽  
Christos Mavrokefalidis ◽  
Kostas Berberidis

AbstractIn the context of this research work, we study the so-called problem of full snapshot reconstruction in hybrid antenna array structures that are utilized in mmWave communication systems. It enables the recovery of the snapshots that would have been obtained if a conventional (non-hybrid) uniform linear antenna array was employed. The problem is considered at the receiver side where the hybrid architecture exploits in a novel way the antenna elements of a uniform linear array. To this end, the recommended scheme is properly designed so as to be applicable to overlapping and non-overlapping architectures. Moreover, the full snapshot recoverability is addressed for two cases, namely for time-varying and constant signal sources. Simulation results are also presented to illustrate the consistency between the theoretically predicted behaviors and the simulated results, and the performance of the proposed scheme in terms angle-of-arrival estimation, when compared to the conventional MUSIC algorithm and a recently proposed hybrid version of MUSIC (H-MUSIC).


Author(s):  
Sangita Lalchand ◽  
Muhammad Mazhar Manzoor ◽  
Amir Ijaz ◽  
Imran Ahmed Awan ◽  
Asad Ali Siddique

Author(s):  
Haoyu Zhang ◽  
Ahmed O. El-Rayis ◽  
Nakul Haridas ◽  
Nurul H. Noordin ◽  
Ahmet T. Erdogan ◽  
...  

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