Architecture Based on Array Processors for Data-Dependent Superimposed Training Channel Estimation

@article{RomeroAguirre2011ArchitectureBO,
  title={Architecture Based on Array Processors for Data-Dependent Superimposed Training Channel Estimation},
  author={Eduardo Romero-Aguirre and Ram{\'o}n Parra-Michel and Roberto Carrasco-Alvarez and Aldo G. Orozco-Lugo},
  journal={2011 International Conference on Reconfigurable Computing and FPGAs},
  year={2011},
  pages={303-308}
}
Channel estimation is a challenging problem in wireless communication systems because of users mobility and limited bandwidth. A plethora of methods based on pilot assisted transmissions (PAT) have been proposed in most practical systems to overcome this problem, but with the penalty of extra bandwidth consumption for training. Channel estimation based on superimposed training (ST) has emerged as an alternative in recent years because it saves valuable bandwidth by adding a training periodic… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 12 REFERENCES

Design and construction of a digital communications system based on implicit training

V. Najera-Bello
  • M.S. thesis, CINVESTAV-IPN, 2008.
  • 2008
VIEW 3 EXCERPTS

Improved channel estimation using superimposed training

  • IEEE 5th Workshop on Signal Processing Advances in Wireless Communications, 2004.
  • 2004
VIEW 2 EXCERPTS

Similar Papers

Loading similar papers…