Effect of channel estimation error on M-QAM BER performance in Rayleigh fading

1999 ◽  
Vol 47 (12) ◽  
pp. 1856-1864 ◽  
Author(s):  
Xiaoyi Tang ◽  
M.-S. Alouini ◽  
A.J. Goldsmith
Keyword(s):  
Channel Estimation ◽  
Rayleigh Fading ◽  
Estimation Error ◽  
Channel Estimation Error ◽  
Ber Performance

scholarly journals Iterative Mean Removal Superimposed Training for SISO and MIMO Channel Estimation

2008 ◽  
Vol 2008 ◽  
pp. 1-9 ◽  
Author(s):  
O. Longoria-Gandara ◽  
R. Parra-Michel ◽  
M. Bazdresch ◽  
A. G. Orozco-Lugo
Keyword(s):  
Channel Estimation ◽  
Radio Channel ◽  
Estimation Error ◽  
Mimo Channel ◽  
Channel Estimation Error ◽  
Superimposed Training ◽  
Iterative Techniques ◽  
Alamouti Coding ◽  
The Impact ◽  
Ber Performance

This contribution describes a novel iterative radio channel estimation algorithm based on superimposed training (ST) estimation technique. The proposed algorithm draws an analogy with the data dependent ST (DDST) algorithm, that is, extracts the cycling mean of the data, but in this case at the receiver's end. We first demonstrate that this mean removal ST (MRST) applied to estimate a single-input single-output (SISO) wideband channel results in similar bit error rate (BER) performance in comparison with other iterative techniques, but with less complexity. Subsequently, we jointly use the MRST and Alamouti coding to obtain an estimate of the multiple-input multiple-output (MIMO) narrowband radio channel. The impact of imperfect channel on the BER performance is evidenced by a comparison between the MRST method and the best iterative techniques found in the literature. The proposed algorithm shows a good tradeoff performance between complexity, channel estimation error, and noise immunity.

On the Performance of the Golden Code in the Presence of Channel Estimation Error in Correlated MIMO Rayleigh Fading Channels

Frequenz ◽  
2014 ◽  
Vol 68 (9-10) ◽  
Author(s):  
Mohamed Lassaad Ammari ◽  
Wahiba Abid
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Channel Estimation ◽  
Fading Channels ◽  
Rayleigh Fading ◽  
Estimation Error ◽  
Channel Estimation Error ◽  
Rayleigh Fading Channels ◽  
Detection Techniques ◽  
Golden Code

AbstractThe Golden Code (GC) is a full-rate and full-diversity, space-time code for 2 × 2 multiple-input multiple-output (MIMO) systems with non-vanishing minimum determinant. Thanks to its algebraic construction, the GC achieves diversity-multiplexing gain trade-off and preserves the mutual information. The zero-forcing (ZF) detection is one of the simplest detection techniques that has a low computational complexity and provides a suboptimal performance. The purpose of this work is to investigate the effect of channel estimation error on the performance of the MIMO-ZF receiver for golden coded systems in spatio-temporally correlated Rayleigh fading channels. An upper and a lower bounds of the error probability are delivered and compared to the Monte Carlo simulation results. We quantify the capacity reduction due to the channel estimation error and to the spatio-temporally correlation. A tight lower bound of the ergodic capacity is provided. Numerical results show an excellent agreement between analytic bounds and Monte Carlo simulation curves. Moreover, the performances of the GC, in terms of bit error rate (BER) and channel capacity, are compared with those of the Alamouti coding.

Physical layer security of MIMO STBC over Rayleigh fading channels in the presence of channel estimation error

Optik ◽  
2016 ◽  
Vol 127 (19) ◽  
pp. 7625-7630 ◽  
Author(s):  
Sudakar Singh Chauhan ◽  
Pankaj Verma ◽  
Mukesh Mathur ◽  
Mansi Agarwal ◽  
Tushar Gupta
Keyword(s):  
Channel Estimation ◽  
Fading Channels ◽  
Physical Layer Security ◽  
Rayleigh Fading ◽  
Estimation Error ◽  
Physical Layer ◽  
Channel Estimation Error ◽  
Rayleigh Fading Channels

scholarly journals Visible Light Communication with Input-Dependent Noise: Channel Estimation, Optimal Receiver Design and Performance Analysis

2021 ◽  
Author(s):  
MAYSA YASEEN ◽  
Malek Alsmadi ◽  
Ayse E. Canbilen ◽  
salama Ikki
Keyword(s):  
Channel Estimation ◽  
Visible Light ◽  
Data Transmission ◽  
Estimation Error ◽  
Visible Light Communication ◽  
Least Square ◽  
Channel Estimation Error ◽  
Closed Form Expression ◽  
Optimal Receiver ◽  
Ber Performance

<div>In this paper, single-input single-output (SISO) visible light communication (VLC) subject to signal-dependent shot noise (SDSN) is investigated. We discuss both channel estimation and data transmission. In the former, we introduce least square (LS) and maximum likelihood (ML) estimators. Moreover, we derive the Cram´er–Rao lower bound (CRLB) of the channel estimation error. With regard to data transmission, we present optimal and sub-optimal receiver designs and discuss their bit error rate (BER) performance. In particular, a closed-form expression of the BER is derived for a sub-optimal receiver using the on-off-keying (OOK) modulation technique. An approximated expression is then derived for the optimal receiver. Our analysis shows that the CRLB performance does not have a linear relation with the SDSN, thermal noise, or the fading channel. On the other hand, the SDSN has a dramatic effect on the channel estimation error bound, and it can degrade the BER performance. Increased performance degradation can also be noticed due to the joint effects of the channel estimation error and SDSN.</div>

scholarly journals Visible Light Communication with Input-Dependent Noise: Channel Estimation, Optimal Receiver Design and Performance Analysis

2021 ◽  
Author(s):  
MAYSA YASEEN ◽  
Malek Alsmadi ◽  
Ayse E. Canbilen ◽  
salama Ikki
Keyword(s):  
Channel Estimation ◽  
Visible Light ◽  
Data Transmission ◽  
Estimation Error ◽  
Visible Light Communication ◽  
Least Square ◽  
Channel Estimation Error ◽  
Closed Form Expression ◽  
Optimal Receiver ◽  
Ber Performance

<div>In this paper, single-input single-output (SISO) visible light communication (VLC) subject to signal-dependent shot noise (SDSN) is investigated. We discuss both channel estimation and data transmission. In the former, we introduce least square (LS) and maximum likelihood (ML) estimators. Moreover, we derive the Cram´er–Rao lower bound (CRLB) of the channel estimation error. With regard to data transmission, we present optimal and sub-optimal receiver designs and discuss their bit error rate (BER) performance. In particular, a closed-form expression of the BER is derived for a sub-optimal receiver using the on-off-keying (OOK) modulation technique. An approximated expression is then derived for the optimal receiver. Our analysis shows that the CRLB performance does not have a linear relation with the SDSN, thermal noise, or the fading channel. On the other hand, the SDSN has a dramatic effect on the channel estimation error bound, and it can degrade the BER performance. Increased performance degradation can also be noticed due to the joint effects of the channel estimation error and SDSN.</div>

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