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11th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2015)

作者： Hongliang Fu Chao Li Tiejun Yang Institute of Information Science and Engineering Henan University of Technology Zhengzhou China

ISBN: (纸本)9781510821279

In this paper, considering the problem of performance loss due to limited feedback in multiuser MIMO downlink systems, a novel limited feedback precoding for multiuser MIMO systems based on array preprocessing is proposed. The maximum SINR criteria is used for selecting optimal codeword from the Grassmannian codebook and perturbation codeword at the receiving, and feedback the Grassmannian precoding codeword index and perturbation codeword index to the transmitter, then the array preprocessing is used at the transmitter and receiver to get optimal capacity, and compensate for the performance loss due to the limited feedback. Simulation results show that the proposed method to ensure the cost of the feedback link, the system throughput and BER performance are improved effectively.

关键词： array preprocessing Limited Feedback Multiuser MIMO Precoding prediction coding multiple input multiple output systems Feedback codeword

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array interpolation and DOA MSE reduction

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2005年第12期53卷 4464-4471页

作者： Hyberg, P Jansson, M Ottersten, B FOI Swedish Def Res Agcy SE-17290 Stockholm Sweden KTH Royal Inst Technol Dept Signals Sensors & Syst SE-10044 Stockholm Sweden

Interpolation or mapping of data from a given real array to data from a virtual array of more suitable geometry is well known in array signal processing. This operation allows arrays of any geometry to be used with fast direction-of-arrival (DOA) estimators designed for linear arrays. In an earlier companion paper [21], a first-order condition for zero DOA bias under such mapping was derived and was also used to construct a design algorithm for the mapping matrix that minimized the DOA estimate bias. This bias-minimizing theory is now extended to minimize not only bias, but also to consider finite sample effects due to noise and reduce the DOA mean-square error (MSE). An analytical first-order expression for mapped DOA MSE is derived, and a design algorithm for the transformation matrix that minimizes this MSE is proposed. Generally, DOA MSE is not reduced by minimizing the size of the mapping errors but instead by rotating these errors and the associated noise subspace into optimal directions relative to a certain gradient of the DOA estimator criterion function. The analytical MSE expression and the design algorithm are supported by simulations that show not only conspicuous MSE,improvements in relevant scenarios, but also a more robust preprocessing for low signal-to-noise ratios (SNRs) as compared with the pure bias-minimizing design developed in the previous paper.

关键词： array interpolation array mapping array preprocessing bias reduction direction-of-arrival (DOA) mean-square-error (MSE) reduction

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array interpolation and bias reduction

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2004年第10期52卷 2711-2720页

作者： Hyberg, P Jansson, M Ottersten, B Swedish Def Res Agcy FOI Stockholm Sweden Royal Inst Technol KTH Dept Signals Sensors & Syst Stockholm Sweden

Interpolation (mapping) of data from a given antenna array onto the output of a virtual array of more suitable configuration is well known in array signal processing. This operation allows arrays of any geometry to be used with fast direction-of-arrival (DOA) estimators designed for linear arrays. Conditions for preserving DOA error variance under such mappings have been derived by several authors. However, in many cases, such as omnidirectional signal surveillance over multiple octaves, systematic mapping errors will dominate over noise effects and cause significant bias in the DOA estimates. To prevent mapping errors from unduly affecting the DOA estimates, this paper uses a geometrical interpretation of a Taylor series expansion of the DOA estimator criterion function to derive an alternative design of the mapping matrix. Verifying simulations show significant bias reduction in the DOA estimates compared with previous designs. The key feature of the proposed design is that it takes into account the orthogonality between the manifold mapping errors and certain gradients of the estimator criterion function. With the new design, mapping of narrowband signals between dissimilar array geometries over wide sectors and large frequency ranges becomes feasible.

关键词： array interpolation array mapping array preprocessing bias reduction

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