Superimposed Training-Based Channel Estimation for MIMO Relay Networks

We introduce the superimposed training strategy into the multiple-input multiple-output (MIMO) amplify-and-forward (AF) one-way relay network (OWRN) to perform the individual channel estimation at the destination. Through the superposition of a group of additional training vectors at the relay subject to power allocation, the separated estimates of the source-relay and relay-destination channels can be obtained directly at the destination, and the accordance with the two-hop AF strategy can be guaranteed at the same time. The closed-form Bayesian Cramér-Rao lower bound (CRLB) is derived for the estimation of two sets of flat-fading MIMO channel under random channel parameters and further exploited to design the optimal training vectors. A specific suboptimal channel estimation algorithm is applied in the MIMO AF OWRN using the optimal training sequences, and the normalized mean square error performance for the estimation is provided to verify the Bayesian CRLB results.

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Research of Improved Algorithm for MIMO Channel Estimation

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.475-476.893 ◽

2013 ◽

Vol 475-476 ◽

pp. 893-899

Author(s):

Miao Miao Chang ◽

Jin He Zhou ◽

Ju Rong Wang

Keyword(s):

Singular Value Decomposition ◽

Channel Estimation ◽

Mean Square Error ◽

Minimum Mean Square Error ◽

Multiple Input Multiple Output ◽

Estimation Algorithm ◽

Singular Value ◽

Mimo Channel ◽

Mean Square ◽

Value Decomposition

We introduced an improved singular value decomposition (SVD) channel estimation algorithm for multiple-input multiple-output (MIMO) wireless communication system. The algorithm is supposed to solve the issue that the channel estimation result is not accurate when the training sequences have some 0 elements. The improvement is also applicable in the other channel estimation algorithms. We made some comparisons between the linear least squares (LS) and the linear minimum mean square error (LMMSE) channel estimation, the traditional singular value decomposition and the improved SVD algorithm to demonstrate the efficiency. Results show that the proposed improved SVD algorithm has better performance in mean square error (MSE) and bit error rate (BER) of channel estimation and the estimated values approach the actual channel state.

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Achievable rate and error performance of an amplify and forward multi-way relay network in the presence of imperfect channel estimation

IET Communications ◽

10.1049/iet-com.2015.0484 ◽

2016 ◽

Vol 10 (3) ◽

pp. 272-282 ◽

Cited By ~ 8

Author(s):

Shama Naz Islam

Keyword(s):

Channel Estimation ◽

Relay Network ◽

Achievable Rate ◽

Amplify And Forward ◽

Error Performance ◽

Imperfect Channel Estimation

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A Modified Superimposed Training Scheme for Individual Channel Estimation for Amplify-and-Forward Relay Network

Proceedings of the 2018 10th International Conference on Computer and Automation Engineering - ICCAE 2018 ◽

10.1145/3192975.3192997 ◽

2018 ◽

Author(s):

Xianwen He ◽

Gaoqi Dou ◽

Jun Gao

Keyword(s):

Channel Estimation ◽

Relay Network ◽

Amplify And Forward ◽

Superimposed Training ◽

Training Scheme

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SISO and MIMO Channel Estimation and Symbol Detection using Data-Dependent Superimposed Training

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005. ◽

10.1109/icassp.2005.1415746 ◽

2006 ◽

Cited By ~ 12

Author(s):

M. Ghogho ◽

D. McLernon ◽

E. Alameda-Hernandez ◽

A. Swami

Keyword(s):

Channel Estimation ◽

Mimo Channel ◽

Superimposed Training ◽

Symbol Detection ◽

Using Data

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A New Method for MIMO-OFDM Channel Estimation Based on Discrete Wavelet Transform

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.182-183.2066 ◽

2012 ◽

Vol 182-183 ◽

pp. 2066-2070

Author(s):

Hui Shi ◽

Ren Wang Song ◽

Gang Fei Wang

Keyword(s):

Wavelet Transform ◽

Channel Estimation ◽

Discrete Wavelet Transform ◽

Orthogonal Frequency Division Multiplexing ◽

Multiple Input Multiple Output ◽

Mimo Channel ◽

Discrete Wavelet ◽

Input Multiple Output ◽

Estimation Scheme ◽

Mimo Ofdm

This paper puts forward a suitable channel estimation scheme for multiple input multiple output and orthogonal frequency division multiplexing system (MIMO-OFDM) based on discrete wavelet transform. According to the least-squares standard (LS), this plan uses pilot to estimate the unit impulse response of MIMO channel firstly, then does wavelet denoising in changing domain, in order to reduce the frequency spectrum leakage and improve the estimation precision. At the same time, this method does not need to know channel information in advance, and can follow up the changes of channel on time with good error rate performance.

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An Improved Channel Estimation Algorithm Based on Superimposed Training Sequence

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.179-180.482 ◽

2011 ◽

Vol 179-180 ◽

pp. 482-489

Author(s):

Jie Yang ◽

Hua Min Zhang ◽

Wu Xie

Keyword(s):

Channel Estimation ◽

Simple Structure ◽

Estimation Algorithm ◽

Training Sequence ◽

Superimposed Training ◽

Direct Training ◽

Computational Requirement ◽

The Mean ◽

Allocation Of Time ◽

Cramer Rao Bound

A channel estimation algorithm based on superimposed training sequence is proposed in this paper. The algorithm does not need the allocation of time slot for superimposed training sequence, and it can estimate the channel coefficients without loss of bandwidth. The mean squared difference, Cramer-Rao bound and the lower bound of channel capacity are deduced based on the LS algorithm of channel estimation. It has simple structure, less computational requirement by using the LS algorithm. The result of simulation shows that the performance of system is improved to a large extent by using superimposed training sequence rather than direct training sequence, and the capacity of system is also increased.

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On Superimposed Training for MIMO Channel Estimation and Symbol Detection

IEEE Transactions on Signal Processing ◽

10.1109/tsp.2007.893941 ◽

2007 ◽

Vol 55 (6) ◽

pp. 3007-3021 ◽

Cited By ~ 48

Author(s):

Shuangchi He ◽

Jitendra K. Tugnait ◽

Xiaohong Meng

Keyword(s):

Channel Estimation ◽

Mimo Channel ◽

Superimposed Training ◽

Symbol Detection

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Individual Channel Estimation in a Diamond Relay Network Using Relay-Assisted Training

International Journal of Digital Multimedia Broadcasting ◽

10.1155/2017/1320689 ◽

2017 ◽

Vol 2017 ◽

pp. 1-8

Author(s):

Xianwen He ◽

Gaoqi Dou ◽

Jun Gao

Keyword(s):

Channel Estimation ◽

Relay Node ◽

Spatial Diversity ◽

Relay Network ◽

Destination Node ◽

Training Design ◽

Amplify And Forward ◽

Relay Nodes ◽

Training Scheme ◽

Data Signal

We consider the training design and channel estimation in the amplify-and-forward (AF) diamond relay network. Our strategy is to transmit the source training in time-multiplexing (TM) mode while each relay node superimposes its own relay training over the amplified received data signal without bandwidth expansion. The principal challenge is to obtain accurate channel state information (CSI) of second-hop link due to the multiaccess interference (MAI) and cooperative data interference (CDI). To maintain the orthogonality between data and training, a modified relay-assisted training scheme is proposed to migrate the CDI, where some of the cooperative data at the relay are discarded to accommodate relay training. Meanwhile, a couple of optimal zero-correlation zone (ZCZ) relay-assisted sequences are designed to avoid MAI. At the destination node, the received signals from the two relay nodes are combined to achieve spatial diversity and enhanced data reliability. The simulation results are presented to validate the performance of the proposed schemes.

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