16,198 research outputs found

    MAI Cancellation with Commutation Signaling

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    This paper deals with PIC-parallel interference cancellation with and without the ISI cancellation system-commutation signaling (CS), in a deep Rayleigh fading environment, time and frequency selective, assuming the spreading sequences and the features of the channels of the several interfering users is known. It is proved that PIC lead to good profits especially when the CS technique is used together, because these systems subtract the MAI estimated for each user. These estimates improve when the ISI is cancelled, since the MAI estimated depends upon the estimate of the transmitted symbols by each interfering user. Additionally, it considers the blind detection (without knowledge of spreading sequences nor the features of the channels of the interfering users) with a noise whitening matched filter (NWMF) that combats the MAI through the whitening of the interfering power spectrum (following the single-user philosophy

    A novel interference rejection scheme for DS-CDMA using adaptive noise cancellation

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    ISI Cancellation Using Blind Equalizer Based on DBC Model for MIMO-RFID Reader Reception

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    Under the dyadic backscatter channel (DBC) model, a conventional zero forcing (ZF) and minimum mean square error (MMSE) method for MIMO-RFID reader reception are not able to be rapidly cancelled inter-symbol interference (ISI) because of the error of postpreamble transmission. In order to achieve the ISI cancellation, the conventional method of ZF and MMSE are proposed to resolve a convergence rate without postpreamble by using a constant modulus algorithm (CMA). Depending on the cost function, the CMA is used which based on second order statistics to estimate the channel statement of channel transfer function. Furthermore, the multiple-tag detection is also considered under the assumption of the maximum likelihood estimation. The comparison of the conventional method and the proposed method is analyzed by using computer simulation and experimental data. We can see that the proposed method is better than the conventional method with a faster ISI cancelling and a lower bit error rate (BER) improving as up to 12 tags

    Multiple-input multiple-output least-squares constant modulus algorithms

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