TITLE:
PSO for CWSN Using Adaptive Channel Estimation
AUTHORS:
Jamal S. Rahhal
KEYWORDS:
CWSN; MIMO; CSI; LMS; Adaptive Channel Estimation; Particle Swarm
JOURNAL NAME:
International Journal of Communications, Network and System Sciences,
Vol.6 No.11,
November
19,
2013
ABSTRACT:
Wireless Sensor Network (WSN) is used in various applications. A
main performance factor for WSN is the battery life that depends on energy
consumption on the sensor. To reduce the energy consumption, an energy
efficient transmission technique is required. Cluster Wireless Sensor Network
(CWSN) groups the sensors that have the best channel condition and form a MIMO
system. This leads to enhancing the transmission and hence reducing energy consumed by the sensor. In CWSN systems multiple signals are
combined at the transmitter and transmitted by using multiple
antennas according to channel condition. CWSN requires a good estimation of the
Channel State Information (CSI) to implement a powerful and efficient system.
Channel Estimation technique should be used to better form the CWSN and make
use of the MIMO features. Adaptive Channel Estimation (ACE) is used to enhance
the BER performance of the CWSN by utilizing the retransmission feature devised
in this paper and feeding the CSI obtained to further enhance the clustering
algorithm. We use Particle Swarm Optimization (PSO) algorithm to find the
optimal cluster members according to a fitness function that derived from the
channel condition. Too many calculations and operations are required in exhaustive
search algorithms to form the optimal cluster arrangement. It shows that
optimal cluster formation can be implemented fast and efficiently by using
the PSO.