TY - GEN
T1 - Low-sampling-rate ultra-wideband channel estimation using a bounded-data-uncertainty approach
AU - Ballal, Tarig
AU - Al-Naffouri, Tareq Y.
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2014/11/12
Y1 - 2014/11/12
N2 - This paper proposes a low-sampling-rate scheme for ultra-wideband channel estimation. In the proposed scheme, P pulses are transmitted to produce P observations. These observations are exploited to produce channel impulse response estimates at a desired sampling rate, while the ADC operates at a rate that is P times less. To avoid loss of fidelity, the interpulse interval, given in units of sampling periods of the desired rate, is restricted to be co-prime with P. This condition is affected when clock drift is present and the transmitted pulse locations change. To handle this situation and to achieve good performance without using prior information, we derive an improved estimator based on the bounded data uncertainty (BDU) model. This estimator is shown to be related to the Bayesian linear minimum mean squared error (LMMSE) estimator. The performance of the proposed sub-sampling scheme was tested in conjunction with the new estimator. It is shown that high reduction in sampling rate can be achieved. The proposed estimator outperforms the least squares estimator in most cases; while in the high SNR regime, it also outperforms the LMMSE estimator. © 2014 IEEE.
AB - This paper proposes a low-sampling-rate scheme for ultra-wideband channel estimation. In the proposed scheme, P pulses are transmitted to produce P observations. These observations are exploited to produce channel impulse response estimates at a desired sampling rate, while the ADC operates at a rate that is P times less. To avoid loss of fidelity, the interpulse interval, given in units of sampling periods of the desired rate, is restricted to be co-prime with P. This condition is affected when clock drift is present and the transmitted pulse locations change. To handle this situation and to achieve good performance without using prior information, we derive an improved estimator based on the bounded data uncertainty (BDU) model. This estimator is shown to be related to the Bayesian linear minimum mean squared error (LMMSE) estimator. The performance of the proposed sub-sampling scheme was tested in conjunction with the new estimator. It is shown that high reduction in sampling rate can be achieved. The proposed estimator outperforms the least squares estimator in most cases; while in the high SNR regime, it also outperforms the LMMSE estimator. © 2014 IEEE.
UR - http://hdl.handle.net/10754/565846
UR - http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6941904
UR - http://www.scopus.com/inward/record.url?scp=84932622643&partnerID=8YFLogxK
U2 - 10.1109/SPAWC.2014.6941904
DO - 10.1109/SPAWC.2014.6941904
M3 - Conference contribution
SN - 9781479949038
SP - 484
EP - 488
BT - 2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -