TY  - CONF
TI  - A Time-Domain Channel Impulse Response Estimation Method for an OFDM Sounding System
ID  - scholars11408
KW  - Frequency domain analysis; Frequency estimation; Impulse response; Mean square error; Orthogonal frequency division multiplexing
KW  -  Channel characterization; Channel impulse response; Cyclic correlation; Estimation methods; Estimation techniques; Frequency domain pilots; Mean squared error; Reliable communication
KW  -  Time domain analysis
N2  - Channel characterization is essential to develop a reliable communication system. In this article, a time-domain cyclic correlation-based channel impulse response (CIR) estimation technique is proposed for frequency-domain pilot aided orthogonal frequency division multiplexing (OFDM) sounding systems. The proposed system provides an improved mean squared error (MSE) as compared to least square (LS) and minimum least square (MMSE) techniques. In this paper, periodic comb-type pilots are considered. The time-domain cyclic correlation results of the up-sampled frequency-domain pilot sequence contain multiple copies of CIR with a length equal to the sequence length. The aggregated response from various copies of CIR in one symbol results in a better CIR estimation. The proposed system provides better performance with very less computational complexity. The performance of the system is evaluated in the Rayleigh channel. The results show that the proposed method can be a better alternative to LS and MMSE technique for OFDM sounding systems. © 2019 IEEE.
N1  - cited By 4; Conference of 6th IEEE International Conference on Smart Instrumentation, Measurement and Application, ICSIMA 2019 ; Conference Date: 27 August 2019 Through 29 August 2019; Conference Code:159025
AV  - none
A1  - Iqbal, A.
A1  - Jeoti, V.
A1  - Drieberg, M.
A1  - Wen, W.P.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083916943&doi=10.1109%2fICSIMA47653.2019.9057303&partnerID=40&md5=f33350f0d24fbf10768a9c38c26a8d63
PB  - Institute of Electrical and Electronics Engineers Inc.
SN  - 9781728139524
Y1  - 2019///
ER  -