Genetic algorithm-assisted joint quantised precoding and transmit antenna selection in multi-user multi-input multi-output systems

Genetic algorithm-assisted joint quantised precoding and transmit antenna selection in multi-user multi-input multi-output systems

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This study presents a simple and efficient genetic algorithm-assisted approach for joint quantised precoding and transmit antenna selection based on the criterion of maximum capacity. The objective is to alleviate the effect of multi-user interference and to reduce hardware costs, such as the cost of radio frequency chains associated with antennas in the downlink of multi-input multi-output systems with limited feedback. To avoid the enormous search effort required by existing approaches, the authors propose a novel variant of the conventional genetic algorithm, called the hybrid genetic algorithm, in which each chromosome is divided into a bit string for precoding vector selection and an integer string for transmit antenna selection. In addition, new crossover and mutation operations are employed to accommodate these new chromosomes. The results of simulations show that the performance of the proposed approach is close to that of the exhaustive search method, but its computational complexity is substantially lower.


    1. 1)
      • A.J. Paulraj , R. Nabar , D. Gore . (2003) Introduction to space-time wireless communications.
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
      • Santipach, W.: `Quantized transmit beamforming with antenna selection in a MIMO channel', Proc. Int. Wireless Communication Mobile Computing Conf., (IWCMC 2009), June 2009, p. 1238–1242.
    13. 13)
    14. 14)
    15. 15)
    16. 16)
    17. 17)
      • Syswerda, G., Palmucci, J.: `The application of genetic algorithms to resource scheduling', Proc. 4th Int. Conf. on Genetic Algorithm, 1991, p. 502–508.
    18. 18)
      • D.S. Watkins . (1991) Fundamentals of matrix compilations.
    19. 19)
      • D.J. Love . Grassmannian subspace packing.

Related content

This is a required field
Please enter a valid email address