TY - GEN
T1 - Interference reduction and capacity improvement in collaborative beamforming networks via directivity optimization
AU - Jayaprakasam, Suhanya
AU - Rahim, Sharul Kamal Abdul
AU - Leow, Chee Yen
AU - Ting, Tiew On
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/8/24
Y1 - 2015/8/24
N2 - Collaborative beamforming with finite number of collaborating nodes produces sidelobes that depend on the nodes' arrangement. Sidelobes cause interference when they occur at the directions of unintended receivers and thus reduce the transmission rate at these receivers. Peak sidelobe minimization does not effectively minimize the overall sidelobe of a beampattern formed by collaborative beamforming. Two main contributions are highlighted in this paper. First, we proposed a new fitness function based on directivity instead of the conventional peak sidelobe. Second, we applied the genetic algorithm (GA) to reduce the sidelobe in collaborative beamforming. This proposed solution is implemented without any feedback from the unintended receiver(s). In the light of reduced sidelobe, we recorded the resultant capacity and calculated its improvement. Results showing up to 14% of capacity improvement, proving the efficacy of the proposed methodologies: the GA and the new fitness function.
AB - Collaborative beamforming with finite number of collaborating nodes produces sidelobes that depend on the nodes' arrangement. Sidelobes cause interference when they occur at the directions of unintended receivers and thus reduce the transmission rate at these receivers. Peak sidelobe minimization does not effectively minimize the overall sidelobe of a beampattern formed by collaborative beamforming. Two main contributions are highlighted in this paper. First, we proposed a new fitness function based on directivity instead of the conventional peak sidelobe. Second, we applied the genetic algorithm (GA) to reduce the sidelobe in collaborative beamforming. This proposed solution is implemented without any feedback from the unintended receiver(s). In the light of reduced sidelobe, we recorded the resultant capacity and calculated its improvement. Results showing up to 14% of capacity improvement, proving the efficacy of the proposed methodologies: the GA and the new fitness function.
KW - beampattern optimization
KW - capacity analysis
KW - collaborative beamforming
KW - genetic algorithm
UR - https://www.scopus.com/pages/publications/84944389264
U2 - 10.1109/I4CT.2015.7219592
DO - 10.1109/I4CT.2015.7219592
M3 - Conference Proceeding
AN - SCOPUS:84944389264
T3 - I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding
SP - 332
EP - 336
BT - I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Computer, Communications, and Control Technology, I4CT 2015
Y2 - 21 April 2015 through 23 April 2015
ER -