scholarly journals A Low-Complexity GA-WSF Algorithm for Narrow-Band DOA Estimation

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Haihua Chen ◽  
Jialiang Hu ◽  
Hui Tian ◽  
Shibao Li ◽  
Jianhang Liu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Computational Complexity ◽  
Population Size ◽  
Narrow Band ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Low Complexity ◽  
Estimation Accuracy ◽  
Improved Genetic Algorithm ◽  
Complexity Estimation

This paper proposes a low-complexity estimation algorithm for weighted subspace fitting (WSF) based on the Genetic Algorithm (GA) in the problem of narrow-band direction-of-arrival (DOA) finding. Among various solving techniques for DOA, WSF is one of the highest estimation accuracy algorithms. However, its criteria is a multimodal nonlinear multivariate optimization problem. As a result, the computational complexity of WSF is very high, which prevents its application to real systems. The Genetic Algorithm (GA) is considered as an effective algorithm for finding the global solution of WSF. However, conventional GA usually needs a big population size to cover the whole searching space and a large number of generations for convergence, which means that the computational complexity is still high. To reduce the computational complexity of WSF, this paper proposes an improved Genetic algorithm. Firstly a hypothesis technique is used for a rough DOA estimation for WSF. Then, a dynamic initialization space is formed around this value with an empirical function. Within this space, a smaller population size and smaller amount of generations are required. Consequently, the computational complexity is reduced. Simulation results show the efficiency of the proposed algorithm in comparison to many existing algorithms.

scholarly journals Application of Bee Evolutionary Genetic Algorithm to Maximum Likelihood Direction-of-Arrival Estimation

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Xinnan Fan ◽  
Linbin Pang ◽  
Pengfei Shi ◽  
Guangzhi Li ◽  
Xuewu Zhang
Keyword(s):  
Genetic Algorithm ◽  
Computational Complexity ◽  
Maximum Likelihood ◽  
Likelihood Function ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Initial Population ◽  
Crossover Operator ◽  
Excellent Performance ◽  
Evolutionary Genetic

The maximum likelihood (ML) method achieves an excellent performance for DOA estimation. However, its computational complexity is too high for a multidimensional nonlinear solution search. To address this issue, an improved bee evolutionary genetic algorithm (IBEGA) is applied to maximize the likelihood function for DOA estimation. First, an opposition-based reinforcement learning method is utilized to achieve a better initial population for the BEGA. Second, an improved arithmetic crossover operator is proposed to improve the global searching performance. The experimental results show that the proposed algorithm can reduce the computational complexity of ML DOA estimation significantly without sacrificing the estimation accuracy.

scholarly journals Enhanced 2D-DOA Estimation for Large Spacing Three-Parallel Uniform Linear Arrays

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Dong Zhang ◽  
Yongshun Zhang ◽  
Cunqian Feng
Keyword(s):  
Elevation Angle ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Low Complexity ◽  
Estimation Accuracy ◽  
Linear Arrays ◽  
Eigen Value ◽  
Directional Cosine ◽  
2D Doa Estimation ◽  
Value Decomposition

An enhanced two-dimensional direction of arrival (2D-DOA) estimation algorithm for large spacing three-parallel uniform linear arrays (ULAs) is proposed in this paper. Firstly, we use the propagator method (PM) to get the highly accurate but ambiguous estimation of directional cosine. Then, we use the relationship between the directional cosine to eliminate the ambiguity. This algorithm not only can make use of the elements of the three-parallel ULAs but also can utilize the connection between directional cosine to improve the estimation accuracy. Besides, it has satisfied estimation performance when the elevation angle is between 70° and 90° and it can automatically pair the estimated azimuth and elevation angles. Furthermore, it has low complexity without using any eigen value decomposition (EVD) or singular value decompostion (SVD) to the covariance matrix. Simulation results demonstrate the effectiveness of our proposed algorithm.

scholarly journals A Novel Iterative Discrete Estimation Algorithm for Low-Complexity Signal Detection in Uplink Massive MIMO Systems

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 980 ◽  
Author(s):  
Hui Feng ◽  
Xiaoqing Zhao ◽  
Zhengquan Li ◽  
Song Xing
Keyword(s):  
Computational Complexity ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Estimation Algorithm ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Base Station ◽  
Damping Factor ◽  
Mimo Detection ◽  
Discrete Estimation

In this paper, a novel iterative discrete estimation (IDE) algorithm, which is called the modified IDE (MIDE), is proposed to reduce the computational complexity in MIMO detection in uplink massive MIMO systems. MIDE is a revision of the alternating direction method of multipliers (ADMM)-based algorithm, in which a self-updating method is designed with the damping factor estimated and updated at each iteration based on the Euclidean distance between the iterative solutions of the IDE-based algorithm in order to accelerate the algorithm’s convergence. Compared to the existing ADMM-based detection algorithm, the overall computational complexity of the proposed MIDE algorithm is reduced from O N t 3 + O N r N t 2 to O N t 2 + O N r N t in terms of the number of complex-valued multiplications, where Ntand Nr are the number of users and the number of receiving antennas at the base station (BS), respectively. Simulation results show that the proposed MIDE algorithm performs better in terms of the bit error rate (BER) than some recently-proposed approximation algorithms in MIMO detection of uplink massive MIMO systems.

QoS Routing Optimization Based on Improved Genetic Algorithm

2014 ◽  
Vol 998-999 ◽  
pp. 1169-1173
Author(s):  
Chang Lin He ◽  
Yu Fen Li ◽  
Lei Zhang
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Computational Complexity ◽  
Fitness Function ◽  
Qos Routing ◽  
Experimental Results ◽  
Improved Genetic Algorithm ◽  
Coding Schemes ◽  
Routing Optimization

A improved genetic algorithm is proposed to QoS routing optimization. By improving coding schemes, fitness function designs, selection schemes, crossover schemes and variations, the proposed method can effectively reduce computational complexity and improve coding accuracy. Simulations are carried out to compare our algorithm with the traditional genetic algorithms. Experimental results show that our algorithm converges quickly and is reliable. Hence, our method vastly outperforms the traditional algorithms.

scholarly journals DOA Estimation for Sources with Large Power Differences

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Qingyuan Fang ◽  
Mengzhe Jin ◽  
Weidong Liu ◽  
Yong Han
Keyword(s):  
Computational Complexity ◽  
Doa Estimation ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Invariant Property ◽  
Large Power ◽  
Diagonal Loading ◽  
Weak Source ◽  
Strong Source ◽  
Cramer Rao Bound

Sources with large power differences are very common, especially in complex electromagnetic environments. Classical DOA estimation methods suffer from performance degradation in terms of resolution when dealing with sources that have large power differences. In this paper, we propose an improved DOA algorithm to increase the resolution performance in resolving such sources. The proposed method takes advantage of diagonal loading and demonstrates that the invariant property of noise subspace still holds after diagonal loading is performed. We also find that the Cramer–Rao bound of the weak source can be affected by the power of the strong source, and this has not been noted before. The Cramer–Rao bound of the weak source deteriorates as the power of the strong source increases. Numerical results indicate that the improved algorithm increases the probability of resolution while maintaining the estimation accuracy and computational complexity.

scholarly journals A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Faming Gong ◽  
Haihua Chen ◽  
Shibao Li ◽  
Jianhang Liu ◽  
Zhaozhi Gu ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Computational Complexity ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Search Method ◽  
Wireless Sensor ◽  
Initial Value ◽  
Effectiveness And Efficiency ◽  
Very High

We address the problem of DOA estimation in positioning of nodes in wireless sensor networks. The Stochastic Maximum Likelihood (SML) algorithm is adopted in this paper. The SML algorithm is well-known for its high resolution of DOA estimation. However, its computational complexity is very high because multidimensional nonlinear optimization problem is usually involved. To reduce the computational complexity of SML estimation, we do the following work. (1) We point out the problems of conventional SML criterion and explain why and how these problems happen. (2) A local AM search method is proposed which could be used to find the local solution near/around the initial value. (3) We propose an algorithm which uses the local AM search method together with the estimation of DML or MUSIC as initial value to find the solution of SML. Simulation results are shown to demonstrate the effectiveness and efficiency of the proposed algorithms. In particular, the algorithm which uses the local AM method and estimation of MUSIC as initial value has much higher resolution and comparable computational complexity to MUSIC.

scholarly journals Beam-Doppler Unitary ESPRIT for Multitarget DOA Estimation

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Cai Wen ◽  
Yan Zhou ◽  
Mingliang Tao ◽  
Jianxin Wu ◽  
Jinye Peng
Keyword(s):  
Fourier Transform ◽  
Computational Complexity ◽  
Doa Estimation ◽  
Critical Issue ◽  
Radar System ◽  
Estimation Accuracy ◽  
Invariance Property ◽  
Multitarget Tracking ◽  
Numerical Examples ◽  
System A

High-resolution direction of arrival (DOA) estimation is a critical issue for mainbeam multitarget tracking in ground-based or airborne early warning radar system. A beam-Doppler unitary ESPRIT (BD-UESPRIT) algorithm is proposed to deal with this problem. Firstly, multiple snapshots without spatial aperture loss are obtained by using the technique of time-smoothing. Then the conjugate centrosymmetric discrete Fourier transform (DFT) matrix is used to transform the extracted data into beam-Doppler domain. Finally, the rotational invariance property of the space-time beam is exploited to estimate DOA of the target. The DOA estimation accuracy is improved greatly because the proposed algorithm takes full advantage of temporal information of the signal. Furthermore, the computational complexity of the presented algorithm is reduced dramatically, because the degree of freedom after beam transformation is very small and most of the operations are implemented in real-number domain. Numerical examples are given to verify the effectiveness of the proposed algorithm.

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