MIMO-OFDM

This is the project detail of my project " MIMO-OFDM channel estimation ". I hope it useful for those working in wireless technology.

1. Perunthalaivar Kamarajar Institute of Engineering and Technology (PKIET) Department of Electronics & Communication Engineering PROJECT REVIEW (18.04.2017) 1

2. OPTIMIZATION OF PDPR FOR SIMULATING CHANNEL CAPACITY TO MIMO-OFDM SYSTEMS by ARUN PRASANTH.R Reg. No 13TC1306 DURGA SRINIVAS . V Reg . No 13TC1312 KEERTHI.P Reg . No 13TC1321 PARAMESWARI . N Reg. No 13TC1338 Under the Guidance of Dr. A. SUNDHAR Assistant Professor 2

3. CONTENT Broad Area of Project Current Scenario of Project Proposed Area of project MIMO OFDM Literature Survey Challenges Ahead Project Objective System Architecture Module Pilot Patterns Simulation Results And Discussion References 3

4. S ervices anywhere and anytime. S tay reachable all over the globe. I ntegrating various wireless access technologies to satisfies the user needs. H igher data rates, variety of services, applications and global roaming of multiple access networks . BROAD AREA OF PROJECT ( Wireless Communication ) 4

5. Optimization of Spectrum Use Various Multiplexing and different Coding Techniques Multiple Access Techniques Internetworking and Convergence Mechanism Mobility Management and Handover Issues Network Security Routing Traffic allocation and Load balancing Mechanism Interference Cancellation CURRENT SCENARIO OF PROJECT ( Project Areas in Wireless Communication ) 5

6. MIMO-OFDM SYSTEMS MIMO , a multi user concept where multiple antennas are used both at the transmitter and receiver. Accelerate the channel capacity OFDM is a modulation technique which encodes digital data on multiple carrier frequencies High speed, high data rate, high spectral efficiency PROPOSED AREA OF PROJECT 6

7. MULTIPLE INPUT MULTIPLE OUTPUT Multiple antenna array are used both at transmitter and receiver MIMO accelerate the channel capacity better than SISO This technology boosts data rates in rich scattering environment , diversity gain , . 7

8. MIMO FEATURES Increased Data rate Increase System Capacity by 20% to 40% It gives Reliable communication High Diversity Gain 8

9. ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING 9

10. OFDM FEATURES Widely used in 4G Technologies Serve in Channel Interferences Avoid Fading Most resistance to frequency selective fading Sufficient use of spectrum by overlap Channel Equalization becomes simpler Eliminates ISI and IFI—Cycle prefix 10

11. OFDM DIAGRAM 11

12. S.No Author / Title of the Paper Extract Limitations 1 Gabor Fador and Miklos Telek ,” On the Pilot Data Power Trade Off In Single Input Multiple Output Systems” May 2014. Mean square equalization Finds path loss between mobile station to base station Number of antenna grows large Investigate multicell system Signal cell analyses re-examined 2 K.Siva Nagamma , K. Udaya Kiran ,”A Novel Approach for Channel Estimation In MIMO-OFDM System Using The Efficient Pilot Patterns”,IEEE Journals October 2014. Unitary matrix based on scattered pilot Estimate pilot patterns Channel impulse response estimation Depends on frequency response and impulse response 3 K.Vidhya , K.R. Shankakumar ,”Channel Estimation and Otimization For Pilot Design In MIMO OFDM Systems”,IEEE Journals February 2013. Estimated by BER and mean square error Compared with random and orthogonal placement of pilot . Estimation done with BER and mean square root LITERATURE SURVEY 12

13. S.No Author / Title of the Paper Extract Limitations 4 Dipika Agnihotri , Mandeep Singh Saina ,”Channel Capacity Enhancement of Diffferent Fading Channel Using Hybrid Algorith In MIMO OFDM Systems”,IEEE journals December 2015. Enhance channel capacity for different faing channels Hybrid algorithm MIMO-OFDM Expensive 5 Hlaing Minn , Daniel Munoz, “Pilot Design for Channel Estimation OF MIMO OFDM Systems with Frequency –Dependent I/Q Imbalances”, IEEE Transactions August 2010. I/Q imbalance Efficient pilot design Estimate mean square error optimally Depends upon resources , users and channels 6 Chao Zhang, Yichen Wang , “Optimal Relay Power Allocation for Amplify and Forward Relay Network With Non-Linear Power Amplifiers”, April 2011. Optimal relay power allocation Frame work of non-linear distorted aware receiver Not proposed to symmetric networks 13

14. S.No Author / Title of the Paper Extract Limitations 7 V. K. Varma Gottumukkala , Hlaing Minn , “ Capacity Analysis and Pilot Data Power Allocation For MIMO-OFDM With Transitter and Receiver IQ Imbalances and Residual Carrier Frequency Offset”, IEEE Transactions February 2012. Residual carrier frequencies offset IQ imbalance Pilot data power allocation Channel capacity is more sensitive to CFO 8 H. Chamkhia , A. Omri , R. Bouallegue , “Improvement Of LTE System Performance By Using A New Pilot Structure “ , IEEE Journals February 2012. LTE downlink system 2. LTE pilot structure Used less number of pilot Based only DVB structure 9 Samir Kapoor, Daniel J. Marchok ,” Pilot Assisted Synchronization For Wireless OFDM Systems Over Fast Time Varying Fading Channels “ , May 1998. Frequency synchronization technique Frequency offsets are estimated Real time complementation Approximately algorith m used Only for frequency selective fading 14

15. Using pilot patterns with optimized PDPR M ore power required for pilot than data Increasing the SNR not the bandwidth Channel capacity similar to optimum capacity, but its capacity is improved by power to pilot and data sub carriers. CHALLENGES AHEAD 15

16. To simulate the channel capacity in order to accelerate the high speed, high data rate to improve the existing cellular mobile communications IEEE 802.11 and LTE (4G) technologies using MIMO OFDM systems by optimizing PDPR with the pilot patterns. PROJECT OBJECTIVE 16

17. 4G TECHNOLOGIES HIGH SPEED, HIGH DATA RATE INCREASE BANDWIDTH INCREASE SNR LEADS TO MULTIPLEXING COMPLEXITY CHANNEL CAPACITY PILOT SYMBOLS OFDM TECHNOLOGY OPTIMIZE PDPR MIMO TECHNOLOGY PILOT PATTERNS (3 TYPES) SYSTEM ARCHITECTURE 17

18. MODULE OPTIMIZATION OF PDPR FOR SIMULATINGCHANNEL CAPACITY TO MIMO-OFDM SYSTEMS 18

19. MIMO-OFDM AND CHANNEL ESTIMATION OFDM used in conjunction with MIMO to provide high speed Wireless,4G and mobile communications. The above technology is highly advantageous only if the channel estimation is properly done. For proper channel estimation we send “ pilots ” along with data . 19

20. Time-Frequency representation of OFDM symbol and OFDM Frame 20

21. CONCEPT OF PILOT SYMBOLS Just symbols transmitted along with data symbols Pilot symbols doesn’t carry any data It estimates the Unknown channel Pilot symbols infused in to each OFDM frame Channel estimation with three pilot pattern's for capacity 21

22. CONCEPT OF PDPR Pilot to data power ratio Optimize the ratio--  Channel capacity Large impact on spectral and energy efficiency It depends on the number of Antenna’s 22

23. PILOT PATTERNS There are three principal pilot patterns under our consideration : 1. Independent Pilot pattern (Time division Multiplexed ) 2. Scattered Pilot Pattern(Frequency Division Multiplexed ) 3. Orthogonal Pilot Pattern(Code Division Multiplexed) 23

24. INDEPENDENT PILOT PATTRENS E [ The channel estimation error covariance defined as Single antenna is used to broadcast pilot tones Other antennas for data symbols More amount of data sent than pilot 24

25. SCATTERING PILOT PATTRENS The channel estimation error covariance is given by Pilot tones transmitted at different antennas at different carriers In Same carriers, data also send It require greater power than data 25

26. ORTHOGONAL PILOT PATTERN The channel estimation error covariance is given by It follows code division multiplexing AWGN channel is constant for no. of OFDM symbols 26

27. CAPACITY LOWER BOUND Capacity Lower Bound is defined as the amount of mutual information between the known and unknown signals over the symbol period over which the data is to be transmitted . It is represented by Where H is the Hermitian matrix It has been observed that the is different for different pilot patterns C lb = E[ log 2 det(1+ρ eff HH) ]   27

28. for IPP for SPP for OPP OPTIMAL PDPR When an optimal PDPR is achieved is maximized and hence it maximizes the ergodic capacity lower bound = P r P t D – ( P r P t LD/ Gϒ p +L )   = P r P t D ac – ( P r P t LD/ Gϒ p +L )   = P r P t D - ( P r P t LD/P t σp 2 +L)   28

29. we get the optimal PDPR to maximize the capacity as Independent/Orthogonal design: Scattered pilot design: The results portray that that the capacity of the independent and orthogonal pilot patterns is identical 29

30. PILOT AND DATA SYMBOL INSERTION IN LTE 30

31. SIMULATION RESULTS AND DISCUSSION USING MATLAB 31

32. The channel capacity increases along with the decrease of the pilot power Three different pilot patterns were compared with the perfect channel Shannon’s capacity rule CHANNEL CAPACITY AND PERCENTAGE OF PILOT POWER 32

33. The effective capacity of the signal varies with the QoS . Compared 2x2 , 3x3 , 4x4 At low effective capacity The MIMO 4x4 shows high Q oS EFFECTIVE CAPACITY 33

34. ENERGY EFFICIENCY OF PDPR AND MIMO It shows different config .,for both PDPR and MIMO The Average Power constraint were calculated w.r.t effective capacity It shows the PDPR and MIMO For different config . of antennas. 34

35. CHANNELCAPACITY AND SNR The SNR simulated with the channel capacity It shows Increasing of the SNR along with the increasing Effective capacity . 35

36. REFERENCES Ye Zhang ; Wei-Ping Zhu, “Energy – efficient pilot and data allocation in massive MIMO communication systems based on MMSE channel estimation” , IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.3571,3575, March 2016 . Minn , H.; Munoz, D., " Pilot Designs for Channel Estimation of MIMO OFDM Systems with Frequency-Dependent I/Q Imbalances, " Communications, IEEE Transactions on , vol.58, no.8, pp.2252,2264, August 2010GJ. Gottumukkala , V.K.V.; Minn , H., "Capacity Analysis and Pilot-Data Power Allocation for MIMO-OFDM With Transmitter and Receiver IQ Imbalances and Residual Carrier Frequency Offset," Vehicular Technology, IEEE Transactions on , vol.61, no.2, pp.553,565, Feb. 2012 Moshavi , S.; Yellin , D.; Sadowsky , J.S.; Perets , Y.; Pick, K., "Pilot interference cancellation technology for CDMA cellular networks," Vehicular Technology, IEEE Transactions on , vol.54, no.5, pp.1781,1792, Sept. 2005 Qinfei Huang; Ghogho , M.; Freear , S., "Pilot Design for MIMO OFDM Systems With Virtual Carriers," Signal Processing, IEEE Transactions on , vol.57, no.5, pp.2024,2029, May 2009 doi : 10.1109/TSP.2008.2011824 36

37. Kezhi Wang; Yunfei Chen; Alouini , M.-S.; Feng Xu, "BER and Optimal Power Allocation for Amplify-and-Forward Relaying Using Pilot-Aided Maximum Likelihood Estimation," Communications, IEEE Transactions on , vol.62, no.10, pp.3462,3475, Oct. 2014 Cicerone, M.; Simeone , O.; Spagnolini , U., "Channel Estimation for MIMO-OFDM Systems by Modal Analysis/Filtering," Communications, IEEE Transactions on , vol.54, no.10, pp.1896,1896, Oct. 2006 doi : 10.1109/TCOMM.2006.881401 A . Dowler and A. Nix, “Performance evaluation of channel estimation techniques in a multiple antenna OFDM system,” in Proc., IEEE Veh . Technology Conf. , vol. 2, Oct. 2003, pp. 1214–1218 Fodor , Gabor; Fodor, Gabor; Telek , Miklos; Telek , Miklos, "On the Pilot-Data Power Trade Off in Single Input Multiple Output Systems," European Wireless 2014; 20th European Wireless Conference; Proceedings of , vol., no., pp.1,8, 14-16 May 2014 Young- Keum Song; Dongwoo Kim; Zander, J., "Pilot power adjustment for saving transmit power in pilot channel assisted DS-CDMA mobile systems," Wireless Communications, IEEE Transactions on , vol.9, no.2, pp.488,493, February 2010 37

38. THANK YOU 38