TY - GEN

T1 - Joint Channel Parameter Estimation Using Evolutionary Algorithm

AU - Li, Wei

AU - Ni, Qiang

PY - 2010

Y1 - 2010

N2 - This paper proposes to utilise Evolutionary Algorithm (EA) to jointly estimate the Time of Arrival, Direction of Arrival, and amplitude of impinging waves in a mobile radio environment. The problem is presented as the joint Maximum Likelihood (ML) estimation of the channel parameters where typically, the high dimensional non-linear cost function is deemed to be too computationally expensive to be solved directly. Simulation results show that the proposed method is extremely robust to initialisation errors and low SNR environments, while at the same time it is also computationally more efficient than popular iterative ML methods i.e. the Space-Alternating Generalised Expectation-maximisation (SAGE) algorithm.

AB - This paper proposes to utilise Evolutionary Algorithm (EA) to jointly estimate the Time of Arrival, Direction of Arrival, and amplitude of impinging waves in a mobile radio environment. The problem is presented as the joint Maximum Likelihood (ML) estimation of the channel parameters where typically, the high dimensional non-linear cost function is deemed to be too computationally expensive to be solved directly. Simulation results show that the proposed method is extremely robust to initialisation errors and low SNR environments, while at the same time it is also computationally more efficient than popular iterative ML methods i.e. the Space-Alternating Generalised Expectation-maximisation (SAGE) algorithm.

U2 - 10.1109/ICC.2010.5502478

DO - 10.1109/ICC.2010.5502478

M3 - Conference contribution/Paper

SN - 978-1-4244-6404-3

BT - Communications (ICC), 2010 IEEE International Conference on

PB - IEEE

CY - New York

T2 - 2010 IEEE International Conference on Communications

Y2 - 23 May 2010 through 27 May 2010

ER -