Analyzing block type channel estimation for OFDM based digital communication system

. Orthogonal frequency division multiplexing (OFDM) is a promising technique in the current broadband wireless communication system due to the high data rate transmission capability and the ability to combat frequency selective fading of the channel. Channel estimation is mainly implemented by sending pilot symbols in the transmitted bit streams. In this paper, channel estimation based on block type pilot arrangements is analyzed using Least Square (LS) and Minimum Mean Square Error (MMSE) channel estimators. Performance is analyzed in terms of Bit Error Rate and Mean Square Error by varying pilot energy levels and by varying channel length. It is gathered that performance gets affected considerably with change in pilot energy levels implying there exist an optimum value for pilot energy for getting better performance.


Introduction
In OFDM system many sub-channels are used in parallel.The channels are overlapping in frequency, but the distance between them is chosen so that the different channels anyhow are orthogonal.OFDM is a promising technique in the current broadband wireless communication system due to the high data rate transmission capability and the ability to combat frequency selective fading of the channel.OFDM, which is the recent trend in wireless technology, is a multicarrier modulation scheme having high data stream splitting into low data stream that are transmitted simultaneously over a number of subcarriers.OFDM is widely used in the wireless systems such as wireless LAN, terrestrial digital television broadcasting, cell-phone and Wi-MAX.Wireless channels used for transmitting the high data rate digital signals usually suffers from various impairments due to multipath propagation of the signals owing to different types of obstacles present, and frequency dependent channel characteristics.As a result the received signal gets corrupted leading to misjudgment of the signal transmitted and hence reducing the system fidelity and utility for high data rate transmissions.To recover the signal correctly at the receiving end it becomes crucial to apply the inverse channel characteristics at the receiver to nullify the non-linear channel effects.So, channel estimation is an important aspect of high speed data transmission systems before applying demodulation at the receiving end.Channel estimation is mainly implemented by sending pilot symbols in the transmitted bit streams.The channel estimation has been performed by inserting pilot tones into each OFDM symbol.In this paper, channel estimation based on block type pilot arrangements using LS and MMSE channel estimators is studied.This paper is organized as follows.In this section 2, simulated system description is described.Section 3 discusses channel estimation.Performance analysis and conclusion are given in section 4 and section 5.

Simulated system description
In figure 1, the information data in binary form are first grouped and mapped into mutiamplitude multi-phase signals according to the type of modulation used in the signal modulator.After inserting pilots uniformly between the information data sequence, IFFT block is used to transform and multiplex the complex data sequence into time domain signal.Following the IFFT block, a guard interval (larger than the expected delay spread), is inserted in order to prevent possible intersymbol interference (ISI) in OFDM systems.The transmitted signal is then sent to a frequency selective multi-path time varying slow fading channel.At the receiver, the guard insertion is removed first and the received samples are then sent to the FFT block for de-multiplexing the multi-carrier signal.Following FFT block, the pilot signals are extracted from the demultiplexed samples.The transmitted data samples can then be recovered from the knowledge of the channel responses by simply dividing the received signal by the channel response.After signal demodulation at the demodulator, the binary data could be reconstructed at the receiver output.ICAET 2016 -

Channel estimation
In block type pilot arrangement, OFDM symbols with pilots at all subcarriers are transmitted periodically for channel estimation.Block type pilot arrangement is especially suitable for slow fading radio channels.This type of pilot arrangement is relatively insensitive to the frequency selectivity.The FFT matrix F is given by: Where Assume (thus ) and are known at the receiver in advance, the MMSE estimator of h is given by: Note that if h is not Gaussian, is not necessary a MMSE estimator.
(7) MMSE tries to minimize the MSE error rate.It has better rate than LS estimator having high SNR ratio.

Performance analysis
Channel estimation based on block based pilot arrangement using LS and MMSE channel estimators has been implemented for OFDM system using MATLAB platform.The figure 3 shows the BER for BPSK modulation in which the channel estimation is done using LS algorithm at different pilot energy levels.It is seen that performance gets affected considerably with change in pilot energy levels.For very low energy level (=0.5) the BER deteriorates.It improves with increasing pilot energy (=2).However, further increase in energy results in increasing the bit error rate.This implies that there exist an optimum value for pilot energy for getting better performance.The figure 4 shows the BER rate for BPSK modulation in which the channel estimation is done using LS algorithm at different pilot energy levels and at channel length L=32.It is seen that performance gets affected considerably with change in pilot energy levels.For very low energy level(=0.5)the BER deteriorates.With increase in pilot energy level beyond E=0.5, the performance tends to improve with increase in energy level upto E=2.However, further increase in energy level does with help rather BER starts deteriorates as shown for pilot energy E=4, 6.Though the BER remains slighty better then that at E=0.5.So, E=2 pilot energy level seem to be the optimum one.Futher, it is seen that with increase in channel length, for given energy per bit to noise power spectral density ratio, BER is slight higher as compared to lower channel length.

Figure 5. MSE at different pilot energy levels using LS algorithm, L=16
The figure 5 shows the MSE for OFDM using LS algorithm at different pilot energy levels (=0.In comparison to similar results for LS algorithm, it is seen that BER is much lower in MMSE algorithm.Although, this improvement is at the cost of increase in complexity.

Conclusion
In this paper, channel estimation based on block type pilot arrangements is studied and analyzed using Least Square (LS) and Minimum Mean Square Error (MMSE) channel estimators.The channel estimation has been performed by inserting pilot tones into each OFDM symbol.Based on the results obtained, it is gathered that ICAET 2016 performance gets affected considerably with change in pilot energy levels.For very low energy level(=0.5)the BER and MSE deteriorates.It improves with increasing pilot energy (=2), though further increase is not helpful and performance degrades.With increasing channel length, the BER and MSE tends to increase slightly.

Figure 3 .Figure 4 .
Figure 3. Performance at different pilot energy levels using LS algorithm, L=16

Figure 9 .
Figure 9. MSE at different pilot energy levels using MMSE algorithm, L=16 The figure 9 shows the MSE for OFDM using MMSE estimator at different pilot energy levels.It is seen that the MSE considerably increases by increasing pilot energy levels (0.5, 2, 4, 6) but MSE tends to reduce with increase in E b /N o =4,6,8.With further increase in E b /N o , the MSE at pilot energy levels (0.5, 2, 4,6) is almost same.

Figure 10 .
Figure 10.MSE at different pilot energy levels using MMSE algorithm, L=32 The figure 10 shows the MSE for OFDM using MMSE estimator at different pilot energy levels.It is seen that at pilot energy levels (0.5,2, 4, 6) the MSE tends to reduce with increase in E b /N o .Further increase in Eb/No (=12, 14,16), the MSE is almost same at all energy levels.In comparison to similar results for LS algorithm, it is seen that BER is much lower in MMSE algorithm.Although, this improvement is at the cost of increase in complexity.
for MMSE at pilot energy=0.5Mean Square Error for MMSE at pilot energy=2 Mean Square Error for MMSE at pilot energy=4 Mean Square Error for MMSE at pilot energy=6

Table 1 .
Performance parameters analysis