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Proceedings ArticleDOI

Joint demodulation of cochannel signals using MLSE and MAPSD algorithms

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TLDR
In this paper, sequence estimation and symbol detection algorithms for the demodulation of co-channel narrowband signals in additive noise are proposed based on the maximum likelihood (ML) and maximum a posteriori (MAP) criteria for the joint recovery of both cochannel signals.
Abstract
Sequence estimation and symbol detection algorithms for the demodulation of cochannel narrowband signals in additive noise are proposed. These algorithms are based on the maximum likelihood (ML) and maximum a posteriori (MAP) criteria for the joint recovery of both cochannel signals. The error rate performance characteristics of these nonlinear algorithms were investigated through computer simulations. The results are presented. >

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Proceedings ArticleDOI

A new artificial neural network based adaptive non-linear equalizer for overcoming co-channel interference

TL;DR: It is shown through simulation results for a severe amplitude distorted co-channel system, that the DFFLE provides significantly superior BER performance characteristics compared to the conventional linear transversal equalizer (LTE) and the non-linear radial-basis function neural network and feedforward functional linkequalizer (FFLE) based structures.
Proceedings ArticleDOI

A single antenna interference cancellation algorithm based on fictitious channels filtering

TL;DR: A SAIC CCI canceling method by treating the real and imaginary parts of the received signal as independent diversity branches is introduced, and the simulation results are presented to illustrate the effectiveness of this algorithm.
Proceedings ArticleDOI

Blind identification algorithms for co-channel systems using higher-order statistics

TL;DR: The algorithm described in this work uses second- and fourth-order cumulants of the received signal to solve the blind identification of co-channel systems in communication systems which employ frequency reusage.
Proceedings ArticleDOI

A new linear co-channel interference mitigation algorithm

TL;DR: A new co-channel interference mitigation algorithm which estimate the SOI and the interfering signal from their superposition in the presence of additive noise and demonstrates a low complexity while maintaining a superior performance.
Proceedings ArticleDOI

A new method for the design of high performance receivers in the presence of co-channel interference

TL;DR: The co-channel interference mitigation in the time-scale domain (CIMTS) algorithm which estimates the signal of interest (SOI) and the interfering signal from their superposition in the presence of additive noise is presented.
References
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Digital Communications

Journal ArticleDOI

Reduced-state sequence estimation with set partitioning and decision feedback

TL;DR: A simple technique for quadrature partial-response signaling (QPRS) is described that eliminates the quasicatastrophic nature of the ML trellis and shows that a good performance/complexity tradeoff can be obtained.
Journal ArticleDOI

Statistical detection for communication channels with intersymbol interference

TL;DR: Simulation results show the optimum detector under a fixed delay constraint D to outperform a transversal equalizer even for relatively small values of D.
Journal ArticleDOI

Bayesian/decision-feedback algorithm for blind adaptive equalization

TL;DR: A new blind equalization algorithm is presented that incorporates a Bayesian channel estimator and a decision-feedback (DF) adaptive filter that is more robust to catastrophic error propagation and only a modest increase in the computational complexity.
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