SEQAR is a MATLAB-based software tool for the design and analysis of conformal antenna arrays of any type. It uses complex single-element radiation patterns, simulated in commercial electronic design automation (EDA) ...
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SEQAR is a MATLAB-based software tool for the design and analysis of conformal antenna arrays of any type. It uses complex single-element radiation patterns, simulated in commercial electronic design automation (EDA) programs or taken from measurements, to construct arbitrary antenna arrays. beamforming capabilities, as well as the influences of tolerances and element failures for these arrays, can be investigated. As an example, the pattern synthesis of a conformal antenna array employed in a receiver for precise safety-of-life satellite navigation is presented.
In this paper, we propose a framework for optimizing power consumption in Smart Antenna. A Smart Antenna (SA) consists of an antenna array and a smart processor at the back end. We have considered the power expended i...
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ISBN:
(纸本)9781479923618
In this paper, we propose a framework for optimizing power consumption in Smart Antenna. A Smart Antenna (SA) consists of an antenna array and a smart processor at the back end. We have considered the power expended in the radio unit and the computation unit of the smart antenna system. We have established that in power limited applications, operating at 'small' distances, both computation power and radio power influence the battery life. The proposed framework explores the SA design space for the beamforming application, taking into account the related parameters like distance, bit error rate, path loss exponent and the modulation scheme. Specifically, we have evaluated beamforming algorithms, Least Mean Square, Recursive Least Square, Constant Modulus algorithms. The power consumed by each of the algorithms is estimated and the total power in each case for SA is compared. It is found that the gain provided by a specific algorithm is counteracted by the power required to run the algorithm. We have analytically derived the 'cross-over distance' where one algorithm becomes more power efficient with respect to another. Simulations have been carried out for a StrongARM SA-1100 processor platform. Simulations suggest that Least Mean Square algorithm is the most power efficient algorithm for distances below 600m.
Adaptive beamforming procedures based on linear least-squares estimation of a wanted signal, such as the sample matrix inverse (SMI) algorithm, have been shown to successfully excise unwanted interference from the bea...
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Adaptive beamforming procedures based on linear least-squares estimation of a wanted signal, such as the sample matrix inverse (SMI) algorithm, have been shown to successfully excise unwanted interference from the beamformer output. It is usually assumed that the signal environment is stationary, however under nonstationary conditions, such as those experienced by an array mounted on a rapidly moving platform, performance may be significantly degraded. The paper examines the effects of array motion on the structure of the sample covariance matrix and derives expressions for the resulting eigenvalues. These results are used to show that even when the same data is used both to compute the adaptive weights and to form the beamformer output, performance can be sensitive to extremely small movements of the array. In particular, simple closed-form expressions are derived for the limiting angular displacements of linear arrays which can be tolerated without significant performance degradation during the time taken to acquire sufficient data to update the weights.
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