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

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

New normalized constant modulus algorithms with relaxation

Published versio

Blind adaptive equalizer for broadband MIMO time reversal STBC based on PDF fitting

In this paper, we propose a new blind adaptive technique used for the equalisation of space-time block coded (STBC) signals transmitted over a dispersive MIMO channel. The proposed approach is based on minimising the difference between the probability density function (PDF) of the equalizer output — estimated via the Parzen window method — and a desired PDF based on the source symbols. The cost function combines this PDF fitting with an orthogonality criterion derived from the STBC structure of the transmitted data in order to discourage the extraction of identical signals. This cost function motivates an effective and low-cost stochastic gradient descent algorithm for adapting the equaliser. The performance is demonstrated in a number of simulations and benchmarked against other blind schemes for the equalisation of STBC over broadband MIMO channels

New Concurrent Modulus Algorithm and Soft Decision Directed Scheme for Blind Equalization

AbstractThe Constant Modulus Algorithm (CMA) is recognized as the most widely used algorithm in blind channel equalization practice. However, the CMA cost function exhibits local minima, which often leads to ill-convergence. This paper proposes a concurrent equalizer, in which a Soft Decision Directed (SDD) equalizer operates cooperatively with a CMA equalizer, controlled through a non-linear link that depends on the system a priory state. The simulation results show that the proposed equalizer has faster convergence rate and lower steady-state mean square error than the CMA equalizer

Blind equalization based on pdf distance criteria and performance analysis

In this report, we address M-QAM blind equalization by fitting the probability density functions (pdf) of the equalizer output with the constellation symbols. We propose two new cost functions, based on kernel pdf approximation, which force the pdf at the equalizer output to match the known constellation pdf. The kernel bandwidth of a Parzen estimator is updated during iterations to improve the convergence speed and to decrease the residual error of the algorithms. Unlike related existing techniques, the new algorithms measure the distance error between observed and assumed pdfs for the real and imaginary parts of the equalizer output separately. The advantage of proceeding this way is that the distributions show less modes, which facilitates equalizer convergence, while as for multi-modulus methods phase recovery keeps being preserved. The proposed approaches outperform CMA and classical pdf fitting methods in terms of convergence speed and residual error. We also analyse the convergence properties of the most efficient proposed equalizer via the ordinary differential equation (ODE) method