@InProceedings{8081651,
  author = {L. N. Ribeiro and S. Schwarz and M. Rupp and A. L. F. {de Almeida} and J. C. M. Mota},
  booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},
  title = {A low-complexity equalizer for massive MIMO systems based on array separability},
  year = {2017},
  pages = {2453-2457},
  abstract = {In this paper, we propose a low-complexity equalizer for multiple-input multiple-output systems with large receive antenna arrays. The computational complexity reduction is achieved by exploiting array separability on a geometric channel model. This property suggests a two-stage receive processing, consisting of (i) sub-array beamforming and (ii) low-dimension minimum mean square error (MMSE) equalization. Simulations indicate that the proposed method outperforms the classical MMSE filter in terms of complexity provided that the number of channel scatterers and the sub-arrays dimensions are not excessively large.},
  keywords = {antenna arrays;array signal processing;computational complexity;least mean squares methods;low-complexity equalizer;massive MIMO systems;array separability;antenna arrays;computational complexity reduction;geometric channel model;sub-array beamforming;square error equalization;sub-arrays dimensions;low-dimension minimum mean square error equalization;Tensile stress;Array signal processing;MIMO;Transmission line matrix methods;Equalizers;Receivers;Mathematical model},
  doi = {10.23919/EUSIPCO.2017.8081651},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570346687.pdf},
}

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