MIMO OFDM
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The document provides an overview of MIMO-OFDM technology, addressing its significance in improving wireless communication efficiency through various techniques. It outlines the project's goals, such as building a prototype of a next-generation wireless WAN using adaptive loading algorithms and singular value decomposition for performance enhancement. Additionally, the document discusses the methodologies, necessary technologies, and promising simulation results indicating strong performance in highly dispersive channels.
MIMO OFDM
- 1. 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
- 2. 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-OFDM Laptop mimo antenna prototype
- 3. 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.
- 4. 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
- 5. Literature survey and R&D
- 6. 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 transmission system.
- 7. 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
- 8. 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 :- Chows : 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.
- 9. 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
- 11. Antenna & types Multibeam MIMO antenna with 3 beams/ sector and 3 sectors/cell Full frequency Reuse concept across cells
- 12. Equipments Modem TMS 320c6x digital signal processor Power PC TM processor MAC and controller kit High end D/A converters RF and power amplifiers Turbo decoder IC
- 13. Implementation and simulation Architectures Node B prototype hardware architecture UE prototype hardware architecture
- 14. 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
- 15. 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
- 16. Project Schedule
- 17. 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.
- 18. THANK YOU!!