mimo ofdm
Post on 09-Jun-2015
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MIMO-OFDM
OVERVIEW OF MIMO AND USE OF DIFFERENT TECHNIQUES TO IMPROVE WIRELESS COMMUNICATION
USING MIMO
By:
Darshan Patil, B.E Electronics and Telecommunications, LTCOE
Significance & Introduction of MIMO-OFDM
Ever-increasing demands in communication industry towards wireless
Challenges: - to improve spectral efficiency
- efficient bandwidth utilization
- economical Signal Processing algorithms - high speed processing h/w
Solution: MIMO-OFDMLaptop mimo antenna prototype
Problem statement:
To build a prototype of Next genx wireless WAN’s with MIMO-OFDM system using set of algorithms and techniques to analyze the performance and replicate it as a practical implementation through simulations.
Scope of the project
Coupling MIMO and OFDM concepts to improve data rates in downlink of wireless communication networks.
Analyzing the performance and building a prototype of Wireless WAN’S using MIMO-OFDM
Use of adaptive loading algorithms such as Chows and Compello’s.
Employing SVD (singular value decomposition) method to increase the performance incase of MIMO
Literature survey and R&D
1)MIMO concept overview
- Multiple i/p multiple o/p antenna array
- Used to increase data rates,
improve capacity and BER (bit error rate) of the system
- Typically used with ofdm so as to suit best needs in next genx comm. i.e. “4G”
Diagram of a MIMO wireless transmissionsystem.
2) OFDM concept overview
- Converts a frequency selective channel into a parallel collection of frequency flat sub channels
- Orthogonal frequency division multiplexing uses bandwidth efficiently
- Improves multipath fading issues
- Reduces the effect of ISI (inter-sub carrier interference)
OFDM System block Diagram
3) Adaptive algorithms and SVD method
good sub carriers with high channel power gain are made to carry more bits and/or be allocated with less transmission power, and vice versa for the weak sub carriers.
Two algorithms :-
1. Chows :
2. Campellos optimum discrete loading algorithm :
SVD: method used to overcome sub channel interference, to allocate transmitted Bit/Power through sub channels in an optimum manner.
Technologies needed
STTD (space time transmit diversity)
SM (spatial multiplexing)
AMC (adaptive modulation & coding) with modulation techniques such as QPSK, 16-QAM, 64-QAM
H-ARQ (Hybrid automatic repeat request)
Shared access and MAC (medium access control) used for scheduling packet access with Qos
Comparison of technologies
Antenna & types
Multibeam MIMO antenna with 3 beams/ sector and 3 sectors/cell
Full frequency Reuse concept across cells
Equipments
Modem TMS 320c6x digital signal processor
Power PCTM processor
MAC and controller kit
High end D/A converters
RF and power amplifiers
Turbo decoder IC
Implementation and simulation
Architectures1. Node B prototype hardware
architecture
2. UE prototype hardware architecture
Simulation results
Prototype is helpful in Indoor/indoor application rather than outdoor/indoor
RF channel replicators are used to create the correlation between outdoor/indoor and indoor/indoor
Project Activities
Survey, Implementation and performance analysis of existing MIMO
Learning s/w and h/w
Developing efficient algorithms
Software synchronization development
Various candidate coding and receiver strategies
Identification of Equipment
Implementation of prototype
Project Schedule
Conclusion
The results obtained from these tests indicate very good performance for the MIMO-OFDM prototype.
Concept is proving to be very robust in highly dispersive channels
Cost reduction is being investigated through various methods
Simulation results show that at any given BER the adaptive SISO system will be outperformed by the adaptive MIMO system
Other future work areas involve the improvement of MIMO processing complexity and practical implementation issues.
THANK YOU!!
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