TY - GEN
T1 - Adaptive LMS-type filter for cyclostationary signals
AU - Shlezinger, Nir
AU - Todros, Koby
AU - Dabora, Ron
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/10/19
Y1 - 2016/10/19
N2 - Adaptive filters are employed in many signal pro- cessing and communications systems. Commonly, the design and analysis of adaptive algorithms, such as the least mean-squares (LMS) algorithm, is based on the assumptions that the signals are wide-sense stationary (WSS). However, in many cases, including, for example, interference-limited wireless communications and power line communications, the considered signals are jointly cyclostationary. In this paper we propose a new LMS-type algorithm for adaptive filtering of jointly cyclostationary signals using the time-averaged mean-squared error objective. When the considered signals are jointly WSS, the proposed algorithm specializes to the standard LMS algorithm. We characterize the performance of the algorithm without assuming specific distributions on the considered signals, and derive conditions for convergence. We then evaluate the performance of the proposed algorithm, called time-averaged LMS, in a simulation study of practical channel estimation scenarios. The results show a very good agreement between the theoretical and empirical performance measures.
AB - Adaptive filters are employed in many signal pro- cessing and communications systems. Commonly, the design and analysis of adaptive algorithms, such as the least mean-squares (LMS) algorithm, is based on the assumptions that the signals are wide-sense stationary (WSS). However, in many cases, including, for example, interference-limited wireless communications and power line communications, the considered signals are jointly cyclostationary. In this paper we propose a new LMS-type algorithm for adaptive filtering of jointly cyclostationary signals using the time-averaged mean-squared error objective. When the considered signals are jointly WSS, the proposed algorithm specializes to the standard LMS algorithm. We characterize the performance of the algorithm without assuming specific distributions on the considered signals, and derive conditions for convergence. We then evaluate the performance of the proposed algorithm, called time-averaged LMS, in a simulation study of practical channel estimation scenarios. The results show a very good agreement between the theoretical and empirical performance measures.
UR - http://www.scopus.com/inward/record.url?scp=84994217956&partnerID=8YFLogxK
U2 - 10.1109/ISWCS.2016.7600851
DO - 10.1109/ISWCS.2016.7600851
M3 - Conference contribution
AN - SCOPUS:84994217956
T3 - Proceedings of the International Symposium on Wireless Communication Systems
SP - 37
EP - 41
BT - ISWCS 2016 - 13th International Symposium on Wireless Communication Systems, Proceedings
PB - VDE Verlag GmbH
T2 - 13th International Symposium on Wireless Communication Systems, ISWCS 2016
Y2 - 20 September 2016 through 23 September 2016
ER -