1. Pilot subcarrier based channel estimation in OFDM system
Advanced Computational and Communication Paradigms
(08 – 10 September, 2017 )
Technical Session :-Track-IV (LNEE) (08 September, 2017) Paper ID :- 128
Pilot subcarrier based channel estimation in OFDM system
Harjeet Singh*,Savina Bansal
Affiliations: Electronics Engg/ IKG Punjab Technical University, Jalandhar
Flat No. 12, Staff Colony, BHSBIET, Lehragaga, Distt. Snagrur (India)
address:

2. 1
Abstract
Channel estimation is essential at receiver for accurate channel state information in orthogonal frequency division multiplexing (OFDM) system. Pilot subcarriers are used in pilot assisted estimation for the channel. In this paper, we propose an algorithm for mapping 4 bit pilot bits into gray coded complex constellation and a technique to insert gray coded complex pilot symbols into OFDM stream before transmission for channel estimation. Gray coded pilot symbol constellation mapping and DFT based time-varying system is implemented in Matlab using LS estimation techniques. Our proposed algorithm illustrates superior performance over the cross-entropy optimization, stochastic sequential search (SSS) and stochastic parallel search (SPS) for time varying system.
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

3. Paper Outline Introduction Related Works Problem Definition2
Paper Outline
Introduction
Related Works
Problem Definition
Proposed  Methodology
Results & Discussions
Conclusion
Future Scope
References            
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

4. 3
Introduction
Channel estimation is first and foremost issue for today’s high data rate transmission for wireless communication system with multipath propagation
For high data rate transmission with minimum impairments, orthogonal frequency division multiplexing is a technique with long symbol duration, spectrally efficient and high bandwidth efficiency for frequency-selective multipath fading channels 
In OFDM system, pilot subcarriers are scattered with data symbols in time varying channel to track time and frequency selective channel characteristics.
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

5. 4
Allocation of fixed number of pilot subcarrier in data stream for OFDM system, where the channel impulse response varies rapidly degrades the system performance.
Design of pilot patterns and pilot density are taken by Shuichi ohno (2011), S. Coleri, et.al ( 2002) and W. Zhang et.al (2006) for time and frequency selective channel to minimize the mean square error (MSE) assuming equi-spaced pilot subcarrier and Pilot pattern for minimum delay spread and minimum doppler frequency design were proposed byM Dong et.al (2002) and Chenhao Qi et.al (2015).
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

6. 5
Related Works
Three pilot design schemes were proposed by Chenhao Qi et.al (2015) to obtain near-optimal pilot pattern for spare channel estimation. Techniques named stochastic sequential search (SSS) and stochastic parallel search (SPS), are based on the stochastic search and iterative group shrinkage (IGS) technique employs a tree-based searching structure . The SSS, SPS, and IGS schemes converge much faster than the cross-entropy optimization and the exhaustive search and are thus more efficient
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

7. 6
Problem Definition
Many a works are available in literature that is suggested to improve efficiency of estimating the channel characteristics for time varying channels under multipath environment. Generation of random pilot pattern is more challenging in time varying systems due to its high complexity. Inserting of pilot symbols before transmission for proper channel estimation is basically an overhead of the system, and it is desirable to keep the number of pilot symbols to a minimum. So, by choosing a suitable pilot pattern we can reduce the number of pilot symbols, and improve the system performance.
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

8. 7
Proposed  Methodology
In proposed algorithm, mapping of four bits pilot symbols is taken up based on Karnaugh maps equivalent to superimpose two ASK signals on quadrature carriers (I and Q components) using gray coded 16-QAM constellation. Let PQRS be the four bits pilot symbol, here first two bits (PQ) are considered as the two bits ASK modulated (also called Pulse Amplitude Modulation) on the in-phase arm and next two bits (RS) are considered as the two bits of ASK modulated on the quadrature arm. For 16 QAM constellation, each point represents a 4-bit pilot symbols named as ABCD, composed of two (AB) in-phase bits on I axis and two (CD) quadrature bits on Q axis. Here bits ABCD are mapped to the levels (±3, ±1) using Gray code.
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

9. 8
Proposed Algorithm
Mapping of pilot bit into respective gray coded constellations.
Set the sub-symbol number of OFDM (N) and symbol number of one simulation (NL) from mapping output of bit source as follows.
[N, NL] = size (Mapping output of bit source)
Here bit source is obtained from sub carriers index and OFDM symbols.
After setting [N,NL], mapping of the input pilot symbol bits into gray coded constellation using 16-ary QAM and to find best possible constellation from 4x4 matrixes as per input pilot symbol bit-
(-3,3) (-1,3) (1,3) (3,3)
(-3,1) (-1,1) (1,1) (3,1)
(-3,-1) (-1,-1) (1,-1) (3,-1)
(-3,-3) (-1,-3) (1,-3) (3,-3)
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

10. Sequence length = zeros (N, (NL+ceil(NL/pilot interval)))). 9
Set the sequence length based on sub-symbol number of OFDM (N), symbol number of one simulation (NL) and pilot interval.
Sequence length = zeros (N, (NL+ceil(NL/pilot interval)))).
Set the pilot sequence length based on the input pilot bit taken into consideration.
Pilot sequence length = complex symbol of the pilot symbol*ones (N,1)
Insertion of gray coded pilot constellation into OFDM data stream after every pilot interval as per the following algorithm.
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

11. 10
Count = 0; i=1; While Count < (symbol number of one simulation (NL)/pilot interval); Output sequence series = pilot sequence length; Count=Count+1; if Count * pilot interval <= symbol number of one simulation (NL) Output sequence series =mapping (:, (( count-1)* pilot interval+1): count* pilot interval); else Output sequence series = mapping (:,(( count-1)* pilot interval+1): NL); end i=i +pilot interval+1;
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

12. 11
Results
Performance evaluations of the proposed OFDM system with multipath delay channel for Gray coded pilot symbol bits is carried out using simulations.
Channel bandwidth of OFDM system and the sampling rate were chosen as 1MHz. Total number of subcarriers was set to 128, which yielded
Sub-carrier spacing of kHz and
OFDM symbol time was kept as 128 µsec.
Guard interval of 32 µsec, OFDM block time 160 µsec.
For OFDM multipath channel estimation over Rayleigh fading channel, channel coefficients and Doppler frequency are kept constant for lowering the system complexity.
Transmission, delay is kept at [0 µsec, 2µsec, 4µsec, 8µsec, 12µsec]
RMS delay spread of the channel is 4 µsec.
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

13. Fig. 1. Variation of SER V/s pilot symbol complex constellations12
It is seen that with input gray coded complex constellation changed by one bit, the system performance changes at each constellation point due to variation of minimum distance among them.
SER
Complex Constellations
Fig. 1. Variation of SER V/s pilot symbol complex constellations
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

14. 13
The simulation is extended further over the time varying channel having Doppler shift of 50Hz, 100Hz, and 200Hz. Here, we consider gray coded constellation training symbol 0010 (-3+3j) and 0111 (-1+j). It is seen that proposed system using gray coded symbol (0010 (-3+3j)) performed better at 100Hz Doppler shift for LS and feedback LS estimation technique as proposed in [20].
Fig. 2. :- Comparison of LS and feedback LS techniques for Gray coded complex pilot constellation (-3+3j)
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

15. Fig. 3. :- Comparison of pilot patterns performance14
Fig. 3. :- Comparison of pilot patterns performance
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16. 15
In Fig.3, performance of different pilot patterns for cross-entropy optimization, stochastic sequential search (SSS) and stochastic parallel search (SPS) taken up in [19] are compared with the pattern scheme proposed in this work. Results show that proposed pilot pattern 0111(-1+j) resulted in lowest SER beyond 14dB among all the compared techniques. Similarly proposed pilot pattern 0010 (-3-3j) also performed better though beyond 21dB.
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

17. 16
Conclusion
In this paper, we propose an algorithm for inserting a gray coded pilot symbol into OFDM data stream. Simulation is carried out for all pilot symbols constellation to find the best possible constellation for DFT based time-varying OFDM system. Our simulations results show that among all gray coded pilot constellation for 16-QAM, the constellation (0111 (-1+j)) performs much better as compared to other constellations. The proposed pilot patterns improved the system performance compared to cross-entropy optimization, stochastic sequential search (SSS) and stochastic parallel search (SPS) pilot patterns.
        
First International Conference on Advanced Computational and Communication Paradigms (ICACCP-2017)

18. 17
Future Scope
The work is further extended to overcome Pilot overhead, and Complexity problems associated with OFDM system for compressed sensing.
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19. 18
References            
Shuichi Ohno et.al (2011), “Preamble and pilot symbol design for channel estimation in OFDM system with null subcarriers”, EURASIP Journal on wireless Communications and Networking, pp.1-17.
Ming Liu (2012), “A Novel Data-Aided Channel Estimation with Reduced Complexity for TDS-OFDM Systems”, IEEE Transactions On broardcasting, volume- 58 , issue-2, p.p 247 – 260.
Senol, H et.al (2012) , “Non data-Aided Joint Channel Estimation and Equalization for OFDM Systems in Very Rapidly Varying Mobile Channels”, IEEE Transactions On Signal processing, Volume-60 , Issue 8, p.p 4236 – 4253.
Xiaoyi Tang et.al (1999), “Effect of Channel Estimation Error On M-Qam BER Performance In Rayleigh Fading”, IEEE Transactions On Communications,volume- 47, no. 12, pp
Jae Kyoung Moon and Song Inchol (2000), “Performance of Channel Estimation Methods for OFDM systems in a Multipath fading channels”, IEEE Transactions on Consumer Electronics,volume-46, No.1, pp
S.Ohno, and G.B Giannakis (2002), “Optimal training and redundant precoding for block transmissions with applications to wireless OFDM,” IEEE transactions on communications, volume- 50,no.12,pp
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20. 19
Lin D and Lim T J (2007), “The variation inference approach to joint data detection and phase noise estimation in OFDM,” IEEE Trans. Signal Process., volume 55, issue 5, pp. 1862–1874.
Xiaoding Cai et.al (2004), “Error probability minimizing pilots for OFDM with M-PSK Modulation over Rayleigh-fading channels”, IEEE transactions on vehicular technology, volume-53, issue 1, pp
Design Schemes for Sparse Channel Estimation in OFDM Systems”, IEEE transactions on vehicular technology, volume 64, issue 4,pp
Harjeet Singh and Savina Bansal (2017), “Improvement in time varying multipath channel estimation”, 5th International Conference on Advancements in Engineering and Technology (ICAET-2017) (ISBN No ), p.p .
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