1. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 4, July-August (2013), © IAEME
42
IMPLEMENTATION OF CHANNEL ESTIMATION ALGORITHMS IN
OFDM FOR 64 SUBCARRIERS
Navdeep Bansal1
, Sukhjeet Singh2
, Pardeep Kumar Jindal3
1
ECE Department, GTBKIET Chhapianwali
2
ECE Department, GTBKIET Chhapianwali
3
ECE Department, GGSCET Talwandi Sabo
ABSTRACT
Main objectives of this paper is to design the PSK and QAM system for Symbol Error Rate
(SER) performance analysis and to estimate the channels in OFDM. PSK & QAM syatems are
designed for 64 Sbcarriers. In this paper we will compare the SER for both techniques for same
modulation rate and same number of subcarrier. In this paper we will show how Symbol error rate is
reduced as modulation rate increases for PSK & QAM. We will use three algotihms LS, LMMSE &
Modified MMSE to compare the result parameters. Modified MMSE gives better results than LS &
LMSE but computational complexity will be increased that is its major drawback.
Keywords: OFDM, PSK, QAM, SER, LS, LMMSE, Modidied MMSE
1. INTRODUCTION
In this paper we will design the system for PSK & QAM modulation techniques for 64
subcarriers for the channel estimation in OFDM. We will implement the LS and LMMSE algorithms
to estimate the channels and compare the symbol error rate for the PSK & QAM Modulation
technique.
OFDM(Orthognal Frequency Division Modulation) is a multichannel modulation that divides a
given channel into many parallel sub-channels or subcarriers, so that multiple symbols are sent in
parallel. It is a block transmission technique.The transmitted OFDM signal multiplexes several low-
rate data streams-each data stream is associated with a given subcarrier. The main advantage of this
concept in a radio environment is that each of the data streams experiences an almost flat fading
channel. In slowly fading channels, the inter-symbol interference (ISI) and inter-carrier interference
(ICI) within an OFDM symbol can be avoided with a small loss of transmission energy using the
concept of a cyclic prefix [4].
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2. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
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The channel estimation can be performed by following pilot patterns.
• Block type Pilot arrangement.
• Comb type Pilot arrangement.
Block Pilot Type: In block type, pilot tones are inserted in all subcarriers of an OFDM symbols
periodically This type is suitable for slow-fading channels where channel characteristics are assumed
stationary during one OFDM data block. For block type arrangements, channel at pilot tones can be
estimated by using LS based or LMMSE based estimation, and assumes that channel remains the
same for the entire block. So in block type estimation, we first estimate the channel, and then use the
same estimates within the entire block [1].
Comb Type Pilot Type: The comb type pilot arrangement is generally based on inserting pilot tones
in each individual OFDM data block as shown in figure 3.5.The channel is estimated in all OFDM
symbols. The concept is to introduce some of the sub carriers as pilot carriers in each OFDM
symbol. Comb type pilot tone estimation, has been introduced to satisfy the need for equalizing when
the channel changes even in one OFDM block. The comb-type pilot channel ssestimation consists of
algorithms to estimate the channel at pilot frequencies and to interpolate the channel. In a fast fading
channel, the characteristics of a radio channel are changing within an OFDM block. Therefore,
channel transfer function should be estimated in each OFDM symbol of a data block. [1]
Channel Estimation Methods: Channel can be estimated at pilot frequencies by the following
methods:
1. Least Square based Channel Estimation Method
2. Linear Minimum Mean Square Error based Estimation Method
2. BLOCK DIAGRAM
Fig2.1: Channel Estimation using LS/MMSE algorithm
In Block type pilot based channel estimation , each subcarrier in OFDM symbol is used in
such a way that all subcarriers are used as pilots. The estimation of the channel is then done using
Least square estimator amd Minimum mean square error estimator. [9], [13],[14].

3. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 4, July-August (2013), © IAEME
44
3. SIMULATION PARAMETERS
Table No. 1
PARAMETER SPECIFICATION
Number of
Subcarriers
N=64
FFT size 64
Length of Guard
Interval
L=4, L= 32 & L= 64
samples
Modulation type Different types of
QAM/PSK
Pilot Type Block type arrangements
Channel Model Rayleigh fading
Channel Bandwidth 1 MHz
Maximum Delay
time
12 microseconds.
Doppler frequency
shift
100-250 Hz
For block-type pilot channel estimation, it is assumed that each block consists of a fixed
number of OFDM symbols. The each OFDM symbols consists of 64 subcarriers. Pilots are sent at
all subcarriers of the first symbol of each block and channel estimation is performed by using LS,
LMMSE. Channel estimated at the beginning of the block is used for all of the following symbols
of the block.
4. IMPLEMENTATION AND RESULT DISCUSSION
Figure 4.1: Performance comparison of Figure 4.2: Performance comparison of
QAM symbol error rate 4QAM symbol error rate
(N= 64, M=4, L=4, S1=32)
10 20 30 40 50 60 70 80 90 100
10
-1.6
10
-1.5
10
-1.4
10
-1.3
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)
10 20 30 40 50 60 70 80 90 100
10
-2
10
-1
10
0
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)

4. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 4, July-August (2013), © IAEME
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Figure 4.3: Performance comparison of Figure 4.4 Performance comparison of
8QAM symbol error rate 16QAM symbol error rate
(N= 64, M=8, L=4, S1=32) (N= 64, M=16, L=4, S1=32)
Figure 4.5: Performance comparison of Figure 4.6: Performance comparison of
32QAM symbol error rate 64QAM symbol error rate
(N= 64, M=32, L=4, S1=32) (N= 64, M=64, L=4, S1=32)
Figure 4.7: Performance comparison Figure 4.8: Performance comparison of
of BPSK symbol error rate QPSK symbol error rate
(N= 64, M=2, L=4, S1=25) (N= 64, M=4, L=4, S1=25)
10 20 30 40 50 60 70 80 90 100
10
-2
10
-1
10
0
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)
10 20 30 40 50 60 70 80 90 100
10
-2
10
-1
10
0
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)
10 20 30 40 50 60 70 80 90 100
10
-0.9
10
-0.8
10
-0.7
10
-0.6
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)
10 20 30 40 50 60 70 80 90 100
10
-0.9
10
-0.8
10
-0.7
10
-0.6
10
-0.5
10
-0.4
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)
10 20 30 40 50 60 70 80 90 100
10
-1.6
10
-1.5
10
-1.4
10
-1.3
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)
10 20 30 40 50 60 70 80 90 100
10
-2
10
-1
10
0
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)

5. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 4, July-August (2013), © IAEME
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Figure 4.9: Performance comparison of Figure 4.10: Performance comparison of
8QPSK symbol error rate 16QPSK symbol error rate
(N= 64, M=8, L=4, S1=25) (N= 64, M=16, L=4, S1=25)
Figures 4.1 to 4.6 and from Table-2, the results of computations of symbol error rates of
different methods of channel estimation for different types of Quadrature Amplitude Modulations
(QAM) have been calculated and compared under the conditions as per Table 2 parameters for 64
subcarriers. The channel correlation matrix RHH for LMMSE method consists of 64 coefficients and
the modified MMSE method considered 32 coefficients in the matrix have been
considered. It has been observed that the modified MMSE estimator has smaller MSE than that of
LMMSE estimator and much smaller LS estimator
Figure 4.11: Performance comparison of Figure 4.12: Performance comparison of
32 QPSK symbol error rate 64QPSK symbol error rate
(N= 64, M=32, L=4, S1=25) (N= 64, M=64, L=4, S1=25)
10 20 30 40 50 60 70 80 90 100
10
-2
10
-1
10
0
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)
10 20 30 40 50 60 70 80 90 100
10
-0.7
10
-0.6
10
-0.5
10
-0.4
10
-0.3
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)
10 20 30 40 50 60 70 80 90 100
10
-0.5
10
-0.4
10
-0.3
10
-0.2
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)
10 20 30 40 50 60 70 80 90 100
10
-0.2
10
-0.1
SNR in dB
SymbolErrorRate
SNR V/S Symbol Error Rate in OFDM SYSTEM
LSE
MMSE
Modified MMSE(M)

6. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 4, July-August (2013), © IAEME
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TABLE-2: Symbol error rate performance comparison of different QAM (N=64)
In Figures 4.7 to 4.12 and from Table-3, the results of computations of symbol error rates of
different methods of channel estimation for different types of Phase Shift Keying (PSK) have been
calculated and compared under the conditions as per Table 01 parameters for 64 subcarriers. The
channel correlation matrix RHH for LMMSE method consists of 64 coefficients and the modified
MMSE method considered 25 coefficients in the matrix have been considered. It has been
observed that the modified MMSE estimator has similar MSE than LMMSE estimator and much
smaller than LS estimator. Hence: On considering the optimal number of coefficients 25 out of 64,
the performance of modified MMSE method is better than LMMSE and much better than the LS
methods. Also it reduces the computational complexity of MMSE method by considering only the
significant coefficients 25 out of 64 for different types of PSK modulations.
Modulation
Type
Estimation
Method
SNR
(10 dB)
SNR
(20 dB)
SNR
(30 dB)
SNR
(40 dB)
SNR
(50 dB)
SNR
(60 dB)
SNR
(70 dB)
SNR
(80 dB)
QAM LS 0.0514 0.0376 0.0390 0.0394 0.0388 0.0391 0.0394 0.0386
LMMSE 0.0520 0.0309 0.0244 0.0234 0.0238 0.0233 0.0232 0.0239
Modified
MMSE
0.0425 0.0267 0.0231 0.0229 0.0238 0.0234 0.0232 0.0240
4QAM LS 0.1019 0.0989 0.0992 0.0924 0.0902 0.0899 0.0900 0.0897
LMMSE 0.0950 0.0770 0.0738 0.0743 0.0744 0.0744 0.0742 .0742
Mod
MMSE
0.0926 0.0783 0.0703 0.0639 0.0592 0.0589 0.0586 0.0586
8QAM LS 0.1106 0.0792 0.0729 0.0728 0.0714 0.0735 0.0713 0.0741
LMMSE 0.1335 0.1186 0.1224 0.1251 0.1258 0.1259 0.1250 0.1284
Mod
MMSE
0.0914 0.0599 0.0512 0.0495 0.0481 0.0480 0.0480 0.0502
16QAM LS 0.1257 0.1065 0.1033 0.1041 0.1037 0.1043 0.1049 0.1047
LMMSE 0.1874 0.1694 0.1674 0.1658 0.1635 0.1640 0.1632 0.1629
Mod
MMSE
0.1104 0.0893 0.0891 0.0884 0.0880 0.0888 0.0892 0.0891
32QAM LS 0.1321 0.1123 0.1139 0.1136 0.1151 0.1143 0.1155 0.1123
LMMSE 0.2733 0.2556 0.2602 0.2581 0.2598 0.2582 0.2580 0.2562
Mod
MMSE
0.1715 0.1294 0.1182 0.1126 0.1134 0.1143 0.1121 0.1147
64QAM LS 0.1732 0.1504 0.1471 0.1478 0.1447 0.1471 0.1451 0.1485
LMMSE 0.4210 0.4106 0.4093 0.4127 0.4125 0.4119 0.4101 0.4144
Mod
MMSE
0.1715 0.1294 0.1182 0.1126 0.1134 0.1143 0.1121 0.1147

7. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
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Table 3: Symbol error rate performance Comparision of Diff. PSK (N=64)
Result Comparision
TABLE- 4: Performance comparison of different QAM & PSK modulations
‘
Modulation
Type
Estimation
Method
SNR
(10 dB)
SNR
(20 dB)
SNR
(30 dB)
SNR
(40 dB)
SNR
(50 dB)
SNR
(60 dB)
SNR
(70 dB)
SNR
(80 dB)
BPSK LS 0.0535 0.0396 0.0409 0.0392 0.0398 0.0393 0.0383 0.0390
LMMSE 0.0554 0.0412 0.0409 0.0389 0.0388 0.0385 0.0396 0.0392
Modified
MMSE
0.0389 0.0257 0.0238 0.0236 0.0234 0.0228 0.0236 0.0235
QPSK LS 0.1476 0.1250 0.1134 0.1115 0.1100 0.1054 0.1053 0.1057
LMMSE 0.1023 0.0664 0.0490 0.0432 0.0428 0.0432 0.0430 0.0432
Mod MMSE 0.0944 0.0601 0.0460 0.0423 0.0424 0.0432 0.0434 0.0432
8PSK LS 0.2343 0.1797 0.1661 0.1601 0.1563 0.1543 0.1543 0.1542
LMMSE 0.2207 0.1433 0.1464 0.1537 0.1541 0.1542 0.1543 0.1545
Mod MMSE 0.1697 0.0760 0.0583 0.0589 0.0607 0.0608 0.0606 0.0605
16PSK LS 0.5085 0.4217 0.4123 0.3947 0.3894 0.3896 0.3900 0.3898
LMMSE 0.4348 0.3166 0.2939 0.2846 0.2819 0.2803 0.2806 0.2801
Mod MMSE 0.3718 0.1924 0.1720 0.1788 0.1863 0.1863 0.1864 0.1864
32PSK LS 0.7160 0.6603 0.6785 0.6753 0.6715 0.6713 0.6714 0.6715
LMMSE 0.6876 0.5290 0.4844 0.4737 0.4707 0.4683 0.4684 0.4683
Mod MMSE 0.6406 0.3989 0.3212 0.2943 0.2785 0.2683 0.2652 0.2652
64 PSK LS 0.8657 0.8496 0.8522 0.8546 0.8590 0.8590 0.8592 0.8591
LMMSE 0.8339 0.8107 0.8318 0.8357 0.8339 0.8295 0.8281 0.8277
Mod MMSE 0.8025 0.6484 0.6226 0.6115 0.6008 0.5953 0.5933 0.5934
Modulation Type
N=64 Subcarrier
LS LMMSE Modified MMSE
QAM 0.0514 0.0520 0.0425
4QAM 0.1019 0.0950 0.0926
8QAM 0.1106 0.1335 0.0914
16QAM 0.1257 0.1874 0.1104
32QAM 0.1321 0.2733 0.1266
64QAM 0.1732 0.4210 0.1715
BPSK 0.0535 0.0554 0.0389
QPSK 0.1476 0.1023 0.0944
8PSK 0.2343 0.2207 0.1697
16PSK 0.5085 0.4348 0.3718
32PSK 0.7160 0.6876 0.6406
64PSK 0.8657 0.8339 0.8025

8. International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
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The results obtained from simulations showed that the LMMSE method performs
significantly better than the LS estimator, but having drawback of more computational complexity.
The results of the modified MMSE channel estimator are better than LMMSE, which is based on the
rank-reduction of the correlation matrix with almost the same performance as the full-rank LMMSE
method, while significantly reducing the computational complexity. Further, the simulations results
showed that the symbol error rate increasing as the modulation type is increased for different QAMs
and PSKs
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