- Open Access
- Total Downloads : 10
- Authors : Swathi Balakrishnan
- Paper ID : IJERTCONV3IS32011
- Volume & Issue : NACTET – 2015 (Volume 3 – Issue 32)
- Published (First Online): 24-04-2018
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License: This work is licensed under a Creative Commons Attribution 4.0 International License
A Novel Superimposed Sequence based Channel Estimation on Two-Way MIMO Relay System
Department of Electronics and Communication Engineering Mount Zion College of Engineering, Kadammanitta, Pathanamthitta, Kerala, India
Abstract: In recent years the MIMO relay systems are more attracted. The MIMO relay system can maximize the mutual information between the source and destination. For all MIMO relay system the individual channel state information to be estimated. In this paper apply the method of superimposed training and pilot sequence to estimate the individual channel state information (CSI) of the first-hop and second-hop links for two-way MIMO relay systems. In this algorithm, a relay training sequence and pilot sequence is superimposed on the received signals at the relay node to assist the estimation of the second-hop channel matrices. The convolution coding is used for the effective transmission. And the relay uses the DAF protocol. The optimal structure of the source and relay training sequences is derived to minimize the mean-squared error (MSE) of channel estimation. Moreover, the optimal power allocation between the source and relay training sequences is derived to improve the performance of channel estimation.
Index terms: MIMO relay, training sequence, MMSE,DFE
The MIMO relay systems are widely used in communication system. The nodes exchange their information through relay node and can increase the spectral
efficiency. In one way MIMO communication the signal is transmitted from one source node to the destination node. In the two-way relay system two nodes exchanges and can provide high spectral efficiency. The MIMO relay system needs the instantaneous channel state information knowledge for extracting the source signals at the destination node.
The training sequences and pilot sequences can be used to estimate the individual CSI of first and second hop links for two way MIMO relay system. The training sequences are some random sequences and pilot sequences have some fixed value. The combined estimation can avoid the false estimation and power should be optimally allocated.
The optimal power allocation is done by minimizing the MSE. This paper introduce the method for the estimation by the sequences. The decision feedback equalizers are used to avoid the ISI. The convolution codes to minimize the MSE. Since the convolution codes can detect and correct errors.
High rate and reliable wireless communication uses the multiple input and multiple output system. The optimal relay pre-coding matrix for a three node two hop MIMO relay
communication system has been developed. The MIMO relay communication is extensively used. The relay pre-coding design problems are investigated.
The MIMO relay communication uses the amplify and forward protocol. So that it will first amplify and then forward the received signal. This AF protocol can be used for optimal power allocation. This will give high signal to noise ratio. But this study focus only on the one-way MIMO and the instantaneous CSI is unknown. To extract the signal from the received one, the instantaneous CSI should be essential. For the instantaneous CSI estimation the least-square algorithm proposed.
For obtaining the individual CSI, ML criteria is developed. It is not a better method since designed for single antenna system. Superimposed channel training algorithm can proposed for orthogonal frequency division multiplexing modulated one-way systems.
The existing system investigate the channel estimation problem for the two-way MIMO relay system by superimposing the training sequence. It is developed on the frequency-selective fading environment and achieved a better performance through optima power allocation by minimizing the MSE. But there is no any other technique implemented for the ISI reduction and error free transmission. The random training sequence can generate the false estimation.
In the MIMO communication the source node and the destination node exchange their information through multiple input multiple output relays. So the same information can be transmitted through different path. Then the loss of signal through one path will not affect the correct reception. The superimposed training sequence can estimate the individual CSI. The Rayleigh fading environment based algorithm can provide more better solutions.
The proposed system mainly uses super imposed sequence method. The data transmitted along with the training sequences. The convolution codes used to encode for reducing errors. It will give better power performances. The training and pilot sequences gives the correct estimation and avoid the false estimations. The convolution encoder can detect and correct the errors.
The relay uses the DAF protocol. Pilot sequences then imposed at the relay.
The impulse response of the channel can be expressed
. l s
,0 l L 1
Figure1: Block diagram of the system model
The block diagram shows the overview of the proposed system. The input data is some sample sequences. The power assigned in the transmission from source to relay and relay to destination. Then for reducing the errors the data to be encoded using the convolution encoder. The effective BPSK modulation scheme is used for the transmission. Then for the estimation the training and pilot sequence are superimposed. Training sequence added with the first and last portions. So it can reduce the ISI. The data inserted within the fixed valued pilot sequence. So it will not change the value of data. By using the training sequence find the delay of the faded signal. Then forward it to the destination.
At the destination, after eliminating the sequences estimation is performed. The decision feedback equalizer is efficient in eliminating the ISI. So it is used in the equalization. After decoding the transmitted signal can be received and performances are analyzed.
At the receiver after decoding the performance is analyzed. This is mainly from the MSE performances. The MSE is minimum for large value of power levels. Generally for the input x the output ,y will be
Here the path gain is . Path delay and sampled path delay are and s .
MIMO relays transmit the signal in different ways.
So that the multiple path will reduce the MSE. More multipath will give better performance.
Develop a MMSE based algorithm to retrieve the first hop channel matrices, which takes into account the estimation error inherited from the estimation of the second- hop channel matrices.
Different MIMO uses different number of antennas. The antenna will be introduce errors, since here more parameters should be estimated. Strong signals having high power and MSE is reduced.
The simulation results are used to study the performance of two-way MIMO relay system obtained from the analytical results. All nodes are equipped with same number of antennas, that is, NS Nr N . For simplicity, we assume that all channel taps have unit variances. We use the shortest length of training sequence with L (5Q 2)N . For all cases the
MSE for nodes 1 and 2 are computed.
All the simulation results are compared with the existing system. The proposed system gives the better. Each plots will give the effect of NMSE. To get the correct signa, the power level should be high and error should be reduced.
The figure 2 shows the performance comparison for different number of antennas. The graph is plotted with the power in y axis and NMSE in the x axis. The error free transmission gives high SNR. So that the MSE is less. As the power increases the NMSE decreases. But for large number of antennas the NMSE increases as more unknowns to be estimated. The proposed system gives better performance.
The figure 3 shows the comparison for different alpha values. The MIMO relay uses the amplify and forward
y hx n
protocol. The alpha is the amplifying factor. Low NMSE with
The received signal may contain the noise and is multiplied with the channel matrix. This may modified and is represented as
high power gives better performance. So that here highest amplifying factor leads to get the better performance. The optimal alpha curve is obtained by applying the GSS technique
y .h p W
in the proposed algorithm. The optimal alpha curve
consistently has the lowest MSE level for all P. This proves that
Here be the input sequences. The channel has some impulse responses. It will affected to the transmitted signal. The encoded date is added with training and pilot sequences. The relay uses the amplify and forward protocol.
The again the pilot sequence superimposed and transmit
through the channel.
the GSS technique is able to obtain the optimal alpha at different P efficiently.
Figure 2:Performance comparison of existing and proposed for different values of Q and N
Figure 3: Performance comparison of existing and proposed system for different values of alpha
Figure 4 : NMSE versus Q for different P
The figure 4 investigate effect of the number of multipath Q on the performance of the proposed algorithm. For more number of multipath the signal can be received efficiently. So the performance of channel estimation improves when Q increases, as all channel taps are set to have unit variance.
We have applied the convolution codes and equalization for the error free transmission. The superimposed training and pilot sequences are applied on the two way MIMO relay system in frequency selective fading environment. For using the multipath the NMSE is minimized. The power allocation between the source and destination is optimized. Then the simulation results shows the better performance from the existing system.
I would like to express my profound gratitude to our Head of the Department Prof. Rangit Varghese, for his encouragement and for providing all his facilities for my work. I express my highest regards and sincere thanks to my guide Asst.Prof. Amit Elizebeth Oommen, who provided necessary guidance and serious advice for my work.
L. Sanguinetti, A. A. DAmico, and Y. Rong, A tutorial on transceiver design for amplify-and- forward MIMO relay systems, IEEE J. Sel. Areas Commun., vol. 30, no. 8, pp. 13311346, Sep 2012.
F. Gao, R. Zhang, and Y.-C. Liang, Optimal channel estimation and training design for two-way relay networks, IEEE Trans. Commun., vol. 57, no. 10, pp. 30243033, Oct. 2009.
I. HammerstrÃ¶m and A. Wittneben, Power allocation schemes for amplify-and-forward MIMO-OFDM relay links, IEEE Trans. Wireless Commun., vol.6, no. 8, pp. 27982802, Aug. 2007
C. W. R. Chiong, Y. Rong, and Y. Xiang, Channel training algorithms for two-way MIMO relay systems, IEEE Trans. Signal Process., vol. 61, no.16, pp. 39883998, Aug. 2013.
Y. Fan and J. Thompson, MIMO configurations for relay channels:Theory and practice, IEEE Trans. Wireless Commun., vol. 6, no. 5, pp. 17741786, May 2007.
X. Tang and Y. Hua, Optimal design of non-regenerative MIMO wireless relays, IEEE Trans.Wireless Commun., vol. 6, no. 4, pp. 1398 1407, Apr. 2007
M. R. A. Kandaker and Y. Rong, Precoding design for MIMO relay multicasting, IEEE Trans. Wireless Commun., vol. 12, no. 7, pp. 3544 3555, Jul. 2013.
C. E. Shannon, Two-way communication channels, in Proc. 4th Berkeley Symp. Probability Statist., Berkeley, CA, USA, 1961, vol. 1, pp.611644
S. Xu and Y. Hua, Optimal design of spatial source-and-relay matrices for a non-regenerative two-way MIMO relay system, IEEE Trans.Wireless Commun., vol. 10, no. 5, pp. 16451655,May 2011
Y. Rong, M. R. A. Khandaker, and Y. Xiang, Channel estimation of dual-hop MIMO relay systems via parallel factor analysis, IEEE Trans.Wireless Commun., vol. 11, no. 6, pp. 22242233, Jun. 2012.
Swathi Balakrishnan received the B.Tech degree in Electronics and Communication Engineering from M.G University, Kerala at Musaliar College of Engineering and Technology in 2013 and now she is pursuing her M.Tech degree in Electronics and Communication Engineering under the same university in Mount Zion College of Engineering.