Smart Antenna Array Patterns Synthesis: Null Steering and Multi-User Beamforming by Phase Control

Mouhamadou, Moctar; Vaudon, Patrick; Rammal, M.

doi:10.2528/pier05112801

Cited by 159 publications

(120 citation statements)

References 15 publications

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“…It is the expansion and extension of the existing MIMO techniques of the 4G network [3][4][5][6][7][8][9][10][11][12][13][14][15]. Nowadays, the 4G cellular network supports simultaneous wireless transfer of maximum 8-ports [16], which is not enough to meet the requirements of future wireless data services.…”

Section: Introductionmentioning

confidence: 99%

A Method for Analyzing Broadcast Beamforming of Massive Mimo Antenna Array

Yuan¹,

Cui²,

Fan³

2017

PIER Letters

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Abstract-In this paper, a new analysis method of broadcast beamforming for a massive MIMO antenna array, targeting at the fifth generation mobile communication, is introduced. In order to solve the problem of narrow broadcast beam coverage, the element phase of massive MIMO antenna array is optimized using a method, which combines both numerical electromagnetic analysis method and global optimization algorithm. The analysis results show that the optimal value of 3 dB broadcast beam width for 64 antenna elements in the horizontal plane is 36 degree, which is 0.55 times of that of the 4G base station. In addition, the optimal value of gain loss increases to about 13 dB compared with the gain of the antenna fed with equal amplitude and in phase. So it is also necessary to take the system link budget of the broadcast channel into consideration. The proposed analysis method and design solution can provide reference for the research of the next generation mobile communication.

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Section: Introductionmentioning

confidence: 99%

A Method for Analyzing Broadcast Beamforming of Massive Mimo Antenna Array

Yuan¹,

Cui²,

Fan³

2017

PIER Letters

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show abstract

“…[1][2][3][4][5][6][7][8][9][10][11][12]. The directionsof-arrival (DOA) estimation [13][14][15][16][17][18] of signals impinging on an array of sensors is a fundamental problem in array processing, and many methods have been proposed for its solution.…”

Section: Introductionmentioning

confidence: 99%

Blind Direction of Arrival Estimation of Coherent Sources Using Multi-Invariance Property

Zhang¹,

Yu²,

Feng³

et al. 2008

PIER

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Abstract-Blind direction of arrival (DOA) estimation algorithms of coherent sources using multi-invariance property is presented in this paper. ESPRIT-like algorithm in [23] can estimate DOA of coherent signal, but its performance is without satisfaction. We reconstruct the received signal to form data model with multi-invariance property, and then multi-invariance ESPRIT and multi-invariance MUSIC algorithms for coherent DOA estimation are proposed in this paper. Our proposed algorithms can resolve the DOAs of coherent signals. They have much better DOA estimation performance than ESPRITlike algorithm. Meanwhile they identify more DOAs than ESPRIT-like algorithm. The simulation results demonstrate their validity.

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“…The causes of steering vectors mismatches in the practical applications include direction-of-arrival (DOA) errors [3], imperfect array calibration and/or distorted antenna shape [4], array manifold mismodeling due to source wavefront distortions resulting from environmental inhomogeneities [5], near-far problem [6], source spreading and local scattering [7] as well as other effects [8]. Therefore, the robustness against the steering vector uncertainties in adaptive beamformers is highly required [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Beamforming for Steering Vector Uncertainties Based on Equivalent Doas Method

Gu¹,

Shi²,

Chen³

et al. 2008

PIER

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Abstract-The adaptive beamformers often suffer severe performance degradation when there exist uncertainties in the steering vector of interest. In this paper, we develop a new approach to robust adaptive beamforming in the presence of an unknown signal steering vector. Based on the observed data, we try to estimate an equivalent directionof-arrival (DOA) for each sensor, in which all factors causing the steering vector uncertainties are ascribed to the DOA uncertainty only. The equivalent DOA of each sensor can be estimated one by one with the assumption that the elements of the steering vector are uncorrelated with each other. Using a Bayesian approach, the equivalent DOA estimator of each sensor is a weighted sum of a set of candidate DOA's, which are combined according to the value of the a posteriori probability for each pointing direction. In this way, the signal steering vector and the diagonal loading sample matrix inversion (DL-SMI) version adaptive beamformer can be obtained. Numerical simulations illustrate the robustness of the proposed beamforming algorithm. 278Gu et al.

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Smart Antenna Array Patterns Synthesis: Null Steering and Multi-User Beamforming by Phase Control

Cited by 159 publications

References 15 publications

A Method for Analyzing Broadcast Beamforming of Massive Mimo Antenna Array

A Method for Analyzing Broadcast Beamforming of Massive Mimo Antenna Array

Blind Direction of Arrival Estimation of Coherent Sources Using Multi-Invariance Property

Robust Adaptive Beamforming for Steering Vector Uncertainties Based on Equivalent Doas Method

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