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dc.contributor.authorRoziana, Mohammed Ariff
dc.contributorSchool of Computer and Communication Engineeringen_US
dc.date2022-12
dc.date.accessioned2023-02-22T08:00:19Z
dc.date.available2023-02-22T08:00:19Z
dc.date.issued2008-04
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/77912
dc.descriptionAccess is limited to UniMAP community.en_US
dc.description.abstractMultiple-antenna systems, also known as MIMO radio, can improve the capacity and reliability of radio communication. MIMO using OFDM modulation technique related to 802.11n is a new multi-streaming modulation technique that has recently been developed. When apply MIMO along with OFDM, they simply exploit the spatial dimension by increasing the number of unique spatial paths between the transmitter and receiver and modulated broadband channel into many parallel sub-channels. The approach taken for this project is to study and investigate the characteristic of MIMO-OFDM in term of BER performance, channel capacity and channel estimation for both sides, transmit and receive antenna. This project was done by simulation for MIMO-OFDM characteristic. In this thesis, we compare two type of channel estimation, Pilot Base and Data Aided. For BER performance, the selection on modulation type and coding rate play a significant role for throughput of the system. This will include Alamouti code and compare it base on SNR value to check its BER performance. Channel capacity also been simulated for various channel of transmit and receive antenna. Then relate channel capacity when channel was parallel after SVD technique and distributed as waterfilling algorithm. The performance for MIMO-OFDM system will be considered channel condition and multipath effect in scatter background.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subject.otherAntennasen_US
dc.subject.otherMultiple-antenna systemsen_US
dc.subject.otherMultiple Input Multiple Output (MIMO)en_US
dc.titleSimulation characteristic of MIMO-OFDM using Matlaben_US
dc.typeLearning Objecten_US
dc.contributor.advisorAmir Razif Ariff, Jamil Abdullah


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