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ISSN: 2277 –
9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 6, August 2012 Channel Estimation using OFDM for 4G 1. Sumit Kumar Gupta 2. Ajay kumar Vishwakarma Abstract— Research and development are taking place all over The higher data rate of 3G systems will be able to support a the world to define next generation of wireless broadband widerange of applications including Internet access, voice multimedia communication systems.Wireless Broadband communications and mobile videophones. In addition to this, Technologies allow simultaneous delivery of voice, data and a large number of new applications will emerge to utilize the video over fixed or mobile platforms. WiFi, WiMAX, 3G, UWB are some of the emerging broadband technologies. WiMAX is permanent network connectivity, such as wireless appliances, standards-based (IEEE 802.16) wireless technology that provides notebooks with built in mobile phones, remote logging, high-throughput broadband connections over long distances. The wireless web cameras, car navigation systems, and so forth. In paper is divided into two parts channel estimation and channel fact most of these applications will not be limited by the data tracking. In the channel estimation part, estimation of the rate provided by 3G systems, but by the cost of the channel transfer function in the preamble using MLS method is serviceeasier or more enjoyable. Applications are virtually down. The various effect of varying channel length and Doppler unlimited as long as the devices have the capabilities to frequency on different modulation technique is seen. Study of the provide such type of services. Research has just recently effects of channel. At high SN, both methods reach an error floor begun on the development of 4th generation (4G) mobile due to the residual error produced by the ICI. This paper develop robust and low complexity channel estimation communication systems.Ultimately 4G networks should algorithms and compare different modulation technique for encompass broadband wireless services, such as High OFDMA reuse1 systems, which are in compatible with the IEEE Definition Television (HDTV) (4 - 20 Mbps) and computer 802.16e standard. network applications (1 - 100 Mbps). This will allow 4G networks to replace many of the functions of WLAN systems. However, to cover this application, cost of service must be Keywords—Wireless, OFDM, 4G, Modulation, channel reduced significantly from 3G networks. The spectral estimation, channel width, Doppler frequency. efficiency of 3G networks is too low to support high data rate services at low cost. As a consequence one of the main I. INTRODUCTION focuses of 4G systems will be to significantly improve the spectral efficiency Supporting the high data rates with Now-a 3rd generation mobile systems such as the Universal sufficient robustness to radio channel impairments, require Mobile Telecommunications System (UMTS) are introduced. careful choosing of modulation technique. OFDM is a robust These systems are striving to provide higher data rates than efficient modulation scheme for broadband communications. current 2G systems such as the Global System for Mobile It combats multipath fading and narrow band interference communications (GSM) and IS-95. Second generation efficiently. OFDMA, multiple access scheme based on systems are mainly targeted at providing voice services, while OFDM, has lots of flexibility and when coupled with feedback 3rd generation systems will shift to more data oriented information it can achieve high data rates efficiently. The services such as Internet access. Third generation systems use wireless MAN-OFDMA is one of the air interface standard for Wide-band Code Division Multiple Access (WCDMA) as the NLOS communication. carrier modulation scheme.[1] This modulation scheme has a high multipath tolerance, flexible data rate, and allows a greater cellular spectral efficiency than 2G systems. Third II. CHANNEL ESTIMATION: PRINCIPLES generation systems will provide a significantly higher data rate (64 kbps – 2 Mbps) than second generation systems (9.6 – The channel is the medium through which the signal travels 14.4kbps). from the transmitter to the receiver. Unlike wired channels that are stationary and deterministic, wireless channels are extremely random in nature. Some of the features of wireless Sumit Kumar Gupta, Asst .Professor ,Dept. Of Electronics communication like mobility, place fundamental limitations & communication, Bansal institute of engineering & on the performance in a wireless system. The transmission technology (BIET),Lucknow, India, 9452052155) path between the transmitter and receiver can vary from line- of-sight (LoS) to one that is severely obstructed by buildings, Ajay kumar Vishwakarma,Sr.Lecturer Dept. Of terrain and foliage. Efficient channel estimation strategies are Electronics & communication, Bansal institute of engineering required for coherent detection and decoding. Channel & technology BIET,Lucknow, India,9839039699 estimates are used in diversity techniques like Maximal Ratio combining. In opportunistic communication systems, the channel estimate is feedback to the transmitter. The transmitter uses the channel knowledge to exploit Multi User 41 All Rights Reserved © 2012 IJARCSEE
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ISSN: 2277 –
9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 6, August 2012 Diversity (MUD). Therefore, the channel estimator is IV. ORTHOGONAL FREQUENCY DIVISION inevitable in any wireless communication system.[4] MULTIPLEXING (OFDM) A channel model on the other hand can be thought of as a mathematical representation of the transfer characteristics of In the scenario of high bit rate digital communications over this physical medium. This model could be based on some wireless channels, one often has to deal with transmission known underlying physical phenomenon or it could be formed channels that exhibit a phenomenon known as fading or a by fitting the best mathematical / statistical model on the highly time-varying frequency response over the signal observed channel behavior. Most channel models are bandwidth. This fading occurs over wireless transmission formulated by observing the characteristics of the received media primarily because the signal in such media is signals for each specific environment. Different mathematical transmitted across multiple paths of varying attenuation and models that explain the received signal are then fit over the delay spread. In such a system, with the use of single carrier accumulated data. Usually the one that best explains the modulation systems, channel equalization turns out to be a behavior of the received signal is used to model the given very difficult task, especially in the presence of time-varying physical channel. channels, and the discrepancies in the SNR at different Channel estimation is simply defined as the process of frequencies lead to a low spectral efficiency, or even to a characterizing the effect of the physical channel on the input reduction in the useful bandwidth. The idea underlying the sequence. If the channel is assumed to be linear, the channel adoption of multicarrier modulation systems is that of dividing estimate is simply the estimate of the impulse response of the the available channel band into a very high number of sub- system. It must be stressed once more that channel estimation bands (sub channels) , each one so small that the channel is only a mathematical representation of what is truly frequency response can be assumed to be constant within a happening. single sub-band . The overall information stream is thereby partitioned into corresponding sub streams, each one of them being transmitted over a different sub-channel. By dividing III. NEED FOR CHANNEL ESTIMATION the available bandwidth into several narrowband sub-channels each of which undergoes frequency flat fading, high-rate data Channel estimation algorithms allow the receiver to is sent through low-rate sub channels in parallel. Also, a cyclic approximate the impulse response of the channel and explain prefix is used to make sub-channels orthogonal to one another the behavior of the channel. This knowledge of the channel's so that inter carrier interference (ICI) and inter symbol behavior is well-utilized in modern radio communications. interference (ISI) are avoided. With these advantages OFDM Adaptive channel equalizers utilize channel estimates to has been adopted as the standard transmission technology for overcome the effects of inter symbol interference. Diversity digital audio broadcasting (DAB) and terrestrial digital video techniques (for e.g. the IS-95 Rake receiver) utilize the broadcasting (DVB-T) in Europe, and recently for wireless channel estimate to implement a matched filter such that the local area networks (WLAN) such as HIPERLAN/2 IEEE receiver is optimally matched to the received signal instead of 802.11a and IEEE 802.16. It is also one of the promising the transmitted one. Maximum likelihood detectors utilize techniques for the fourth generation (4G) cellular system. channel estimates to minimize the error probability. One of Although the theoretical basis for development of OFDM is the most important benefits of channel estimation is that it over 40 years old, it has not been implemented successfully allows the implementation of coherent demodulation.Coherent until recently owing to high amount of computational demodulation requires the knowledge the phase of the signal. complexity and memory requirements of the receiver for such This can be accomplished by using channel estimation a system. techniques. The channel estimation in OFDMA can be widely classified into two categories.[7] 1. Pilot Based channel Estimation: known symbol called pilots are transmitted. 2. Blind Channel Estimation Methods: No pilots are required. It uses some underlying mathematical properties of data sent. The Blind channel estimation methods are computationally complex and (a) Time domain, The number of cycles hard to implement. The Pilot based channel estimation methods are easy to implement, but they reduce bandwidth (b) Frequency domain, the peak of thein Symbol differ by one efficiency. The Pilot based methods are more popular for adjacent sinc comes at the null of other sincsub nowadays. IEEE802.16e standards supports the Pilot based carriers waveforms. channel estimation Fig 1. Orthogonality of subcarriers 42 All Rights Reserved © 2012 IJARCSEE
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9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 6, August 2012 V. SYSTEM MODEL higher.Variation in QPSK amplitude is not much. Hence carrier power almost remains constant. We derive a linear system model which relates the transmitted iv) QAM:- OFDM symbol (in frequency domain), [ ] 1 2 1 , ,... ,........ − = For same bit error the BW required by QAM is reduced k N x x x x x and the received OFDM symbol [ ] 1 2 1 , ,.... to half as compared to BPSK. Less bit error probability. ,......... − = k N y y y y y . Assuming that most of the energy in the impulse response is concentrated in L taps, the channel VI. SIMULATIONS PARAMETERS vector is given by [ ] 1 2 , 1 , ,..... 0,..0 L NX h = h h h . Assume that channel remains constant over one OFDM A system level simulator, developed in MATLAB, for single symbol and L is less than the cyclic prefix.[4] cellular, single user environment has been used. The Simulation parameters are shown in the table below Fig 2. OFDM System Model VI. MODULATON SCHEMES It is defined as the process by which some characteristic of a signal called carrier is varied in accordance with modulating signal.Used modulation technique are i). Binary Phase Shift Keying (BPSK) ii).Differential Phase Shift Keying (DPSK) iii).Quadrature Phase Shift Keying (QPSK) iv).Quadrature Amplitude Modulation (QAM) i) BPSK:- Table 1. Less Probability of error.It need a complicated synchronizing ckt at the receiver for generation of local carrier. Ambiguity in The fading channel is implemented with the Jakes Method the output signal because use square law device in receiver (Sum of Sinusoids method). The fading channel model, with side. power delay profile corresponding to PED B, 1 is used. The channel parameters are listed below. Only sample spaced ii) DPSK:- channels are considered. The non-integer samples of the PDP DPSK does not need carrier at it receiver. This means that the are mapped to the nearest sample position. The pilots are complicated circuitry for generation of local carrier is QPSK modulated and they have unit energy. avoided. The BW requirement of DPSK is reduced compared to that of BPSK.The probability or error rate of DPSK is higher than that of BPSK. Noise interference in DPSK has more. iii). QPSK:- For the same bit error rate, the BW required by QPSK is reduced to half as compared to BPSK. Because of reduced BW, the information transmission rate of QPSK is 43 All Rights Reserved © 2012 IJARCSEE
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9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 6, August 2012 10 PSK QPSK 0 QAM Normalized MeanSquareError -10 -20 -30 -40 -50 -60 5 10 15 20 25 30 35 40 Table 2. Symbol Index VII. RESULTS:- Fig-4 Channel Length=6 and Doppler Frequency 40 Hz Parameter Modulation Technique 10 PSK Doppler PSK QPSK QAM 0 QPSK QAM frequency NMSE NMSE NMSE Normalized MeanSquareError Hz -10 in dB in dB in dB -20 20 -40 -42 -42 -30 40 -46 -41 -47 -40 60 -41 -38 -49 -50 70 -45 -38 -49 -60 5 10 15 20 25 30 35 40 Symbol Index Table 3. For fixed channel length and varying Doppler frequency 10 PSK 10 PSK QPSK 0 QPSK QAM 0 QAM Normalized MeanSquareError -10 Normalized MeanSquareError -10 -20 -20 -30 -30 -40 -40 -50 -50 -60 -60 5 10 15 20 25 30 35 40 5 10 15 20 25 30 35 40 Symbol Index Symbol Index Fig -5 Fig-3 Channel Length=6 and Doppler Frequency 60 Hz Channel length=6 and Doppler Frequency=20 Hz Fig-6 Channel length=6 and Doppler Frequency=70 Hz 44 All Rights Reserved © 2012 IJARCSEE
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9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 6, August 2012 VIII. CONCLUSION The pilot based channel estimation and tracking algorithms are investigated for reuse1 OFDMA system, which is in compatible with IEEE 802.16e standard. We studied and simulated MSL method for sample spaced channels. The FFT based method is affected by the ―smearing effect‖ due to the pulse shaping in the OFDMA symbol because of this it’s performance curve reaches an error floor at high SNR. MLS method is always superior to the other. We studied the performance of MLS method under the channel varying inside an OFDMA symbol. This introduces ICI and causes the MLS method to reach an error floor at high SNR. I have seen the effect of varying Doppler frequency on different modulation technique. We get that QAM is better Sumit Kumar Gupta, B.Tech, M.Tech (Digital Communication) from MANIT Bhopal(M.P). I have five year teaching experience. than other modulation technique for varying Doppler frequency. REFERENCES:- [1] Panayiotis Kolios, Vasilis Friderikos, Katerina Papadaki, ‖Future Wireless Mobile Networks: Energy Consumption and Resource Utilization in Mechnical Relaying‖, IEEE Vehicular Technology Magazine, March 2011. [2] S.M. Riazul Islam and Kyung Sup Kwak,―Winner-Hopf Interpolation Aided Kalman Filter-Based Channel Estimation for MB-OFDM UWB Systems in Time Varying Dispersive Fading Channel‖, ICACT, Feb.7- 10,2011 [3] Hussain Hijazi, Eric Pierre Simon, Martine Lienard, Laurent Ros, ―Channel Estimation for MIMO-OFDM Systems in Fast Time-Varying Environments‖, 4th ISCCSP 2010, Limassol, Cyprus, 3-5 March 2010 [4] Darryn Lowe and Xiaojing Huang ―Complementary Channel Estimation and Synchronization for OFDM‖ The 2nd International Conference on Wireless.IEEE 2007 [5] Yoshida Honmachi Sakyo-ku, ― Uplink Channel Estimation for OFDMA System‖ Kazunori Hayashi and Hideaki Sakai Graduate School of Informatics, Kyoto University JAPAN IEEE ICASSP 2007 [6] IEEE Std. 802.16e, ―Air interface for fixed and mobile broadband wireless access systems amendment for physicaland medium access control layers for combined fixedand mobile operation in licensed bands,‖ IEEE, 2006. [7] A. Mobasher and A. K. Khandani "Integer-Based Constellation Shaping Method for PAPR Reduction in OFDM Systems," IEEE Transactions on Communications, vol. 54, Issue 1, Jan. 2006, pp. 119-127. . [8] A. Aassie-Ali, 0. Aly and A.S. Omar, "High resolution WLAN indoor channel parameter estimation and measurements for communication and positioning applications at 2.4, 5.2 and 5.8 GHz," in Proc. IEEE Radio and Wireless Symposium, RWS-2006 (San Diego) 2006. 45 All Rights Reserved © 2012 IJARCSEE
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