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Subject: search.filters.subject.ISI cancellation

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    Performance Comparison of OFDM-QAM and FBMC-QAM Filtered in Multi-User Massive MIMO Channel Characterization
    (2018-07-02)
    Teekapakvisit, Chakree
    ;
    Duangsuwan, Sarun
    The current 4G standard or long-term evolution (LTE) system is based on the use of orthogonal frequency division multiplexing-quadrature amplitude modulation (OFDM-QAM) for the downlink and uplink communications. OFDM is an orthogonal block transmission scheme which, in the presence of multi-path fading channels, plain orthogonal multicarrier modulation formats are not able to maintain orthogonality due to inter-symbol interference (ISI) among consecutive multicarrier symbols. A new modulation format is a filter bank multicarrier (FBMC). In this paper, we compare a performance of OFDM-QAM and FBMC-QAM to filter the ISI problem at the receiver. We evaluate the performance under the assumption of multiuser massive MIMO channel as a simplicity. The experimental results are depicted with eye-diagrams and the performance of bit error rates (BERs). As the result, the FBMC-QAM is a potential successor of the dominant OFDM-QAM where BER is acceptable with no ISI and it is definitely a promising modulation to use in 5G signal processing.
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    ISI cancellation using blind equalizer based on DBC model for MIMO-RFID reader reception
    (2015-01-01)
    Duangsuwan, Sarun
    ;
    Promwong, Sathaporn
    Considering a dyadic backscatter channel (DBC) model, the previous methods with zero forcing (ZF) and minimum mean squared error (MMSE) are not able to rapidly cancel inter-symbol interference (ISI) because of errors of post-preamble transmission in MIMO-RFID channel. In order to achieve the ISI cancellation, the proposed method is demonstrated to improve the convergence rate without postpreamble by using a constant modulus algorithm (CMA) in this paper. The CMA depends on the steepest descent algorithm function, which is based on the second order statistics (SOS) to estimate the channel characterization. We compare between the conventional method and the proposed method based on simulation and measured data. Furthermore, the multiple tag of post-processing is also considered under the assumption of the maximum likelihood detection. We can confirm that the proposed method is better than the conventional method with faster ISI cancelling and a lower bit error rate (BER) improving up to 12 tags.