New blind adaptive interference suppression algorithms for DS/CDMA communication systems are presented, A generalized projection algorithm is presented to update a multiple access interference (MAI) suppression filter...
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New blind adaptive interference suppression algorithms for DS/CDMA communication systems are presented, A generalized projection algorithm is presented to update a multiple access interference (MAI) suppression filter in a static communication environment, The algorithm adaptively adjusts the filter coefficients by iteratively projecting them onto constraint sets, The constraint sets consist of data sets and property sets, which are obtained from the received signal and prior knowledge of the desired signal, respectively, A space alternating generalized projection algorithm with approximate EM mapping is also presented to suppress the MAI in a dynamic communication environment, This algorithm jointly estimates the filter and desired signal amplitude using a stochastic approximation of the EM algorithm, The performance characteristics of the proposed algorithms are shown by output signal-to-interference ratio and bit-error-rate simulation results. The results show that the proposed algorithms significantly outperform the existing adaptive algorithms in steady state.
A major problem with blind equalization algorithms based on the distribution matching principle is that they need a long time to accomplish their convergence. What affects convergence has not been discovered to date. ...
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A major problem with blind equalization algorithms based on the distribution matching principle is that they need a long time to accomplish their convergence. What affects convergence has not been discovered to date. The similarity between the least mean-square (LMS) algorithm (widely used for adaptive equalization) and the blind algorithms is considered here. It is expected that the convergence of the blind algorithms is dependent on the condition number of the correlation matrix of the input sequence. Prefiltering methods, including coefficient-fixed type and coefficient-adaptive type, are derived for blind equalization. In these methods, the prefilters are realized by a prediction error filter, which has the ability to compensate for amplitude distortion induced by a channel. Since the prefilters have such ability, the blind equalizers to be cascaded with them are required only to compensate for phase distortion. As a result, the burden imposed on the blind equalizers is reduced. The prefilters output a near-white sequence and lead to an improvement in the convergence of the blind algorithms, being degraded as the condition number is increased. The effectiveness of the proposed methods is validated by computer simulations.
This paper proposes a new adaptive Interference Cancelling Equalizer (ICE) with a blind algorithm. From a received signal, ICE not only eliminates inter-symbol interference, but also cancels co-channel interference. B...
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This paper proposes a new adaptive Interference Cancelling Equalizer (ICE) with a blind algorithm. From a received signal, ICE not only eliminates inter-symbol interference, but also cancels co-channel interference. blind ICE can operate well even if training signals for the interference are unknown. First, training signal conditions for applying blind ICE are considered. Next, a theoretical derivation for blind ICE is developed in detail by applying the maximum likelihood estimation theory. It is shown that RLS-MLSE with diversity, which is derived for mobile radio equalizers, is also effective for blind ICE. Computer simulations demonstrate the 40 kb/s QDPSK transmission performance of blind ICE as a blind canceller with two branch diversity reception under Rayleigh fading in a single interference environment. The simulations assume synchronous training;the canceller is trained for the desired signal but not for the interference signals. blind ICE can be successfully achieved at more than - 10 dB CIR values when average Eb/No is 15 dB and a maximum Doppler frequency is 40 Hz.
This paper reviews recent progress in adaptive signal processing techniques for digital mobile radio communications. In Radio Signal Processing (RSP), digital signal processing is becoming more important because it ma...
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This paper reviews recent progress in adaptive signal processing techniques for digital mobile radio communications. In Radio Signal Processing (RSP), digital signal processing is becoming more important because it makes it relatively easy to develop sophisticated adaptive processing techniques. Adaptive signal processing is especially important for carrier signal processing in RSP. Its main objective is to realize optimal or near-optimal radio signal transmission. Application environments of adaptive signal processing in mobile radio are clarified. Adaptive equalization is discussed in detail with the focus on adaptive MLSE based on the blind algorithm. Demodulation performance examples obtained by simulations and experiments are introduced, which demonstrates the recent advances in this field. Next, new trends in adaptive array processing, interference cancelling, and orthogonalization processing are reviewed. Finally, the three automatic calibration techniques that are based on adaptive signal processing are described for realizing high precision transmission devices.
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