Figure - available from: Applied Sciences
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Factor graph representation of Equation (8). The receiver contains two detection algorithms, each corresponding to a specific unknown channel parameter. The variable node PEik represents the i-th path existence at time k, while AEik represents the i-th attenuation existence at the same time.
Source publication
This paper addresses the problem of mitigating unknown partial path overlaps in communication systems. This study demonstrates that by utilizing the front-end insight of communication systems along with the sum–product algorithm applied to factor graphs, it is possible not only to track these overlapping components accurately, but also to detect al...
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Citations
... According to the Gaussian product rule, the product of re-scaled distributions provides a single Gaussian distribution which contains the memory of the channel coder in its mean. It should be mentioned that we employed the product of two re-scaled Gaussian distributions at every time epoch prior to bit LLR computations in our last work on multipath mitigation [6]. The corresponding factor graph is depicted in Fig. 1. ...
Thanks to the product rule of Gaussian distributions, the memory of channel coding schemes, such as low–density parity–check (LDPC) codes used in this paper, is reflected in the mean of a single Gaussian distribution, obtained through the product of re–scaled Gaussian observations in additive white Gaussian noise (AWGN) channels. Consequently, employing a novel bit log–likelihood ratio (LLR) updating algorithm, in conjunction with an appropriate scheduling procedure, increases the convergence speed of the decoder considerably. Bit LLR values close to zero are accumulated with those obtained in the current iteration of the receiver. Simulation results demonstrate a substantial improvement (close to 50%) in the convergence speed of the proposed algorithm compared to traditional ones. This approach can also be applied to conventional sequence and symbol detection strategies in the presence of memory. Although this approach only affects convergence in AWGN channels, it could play a vital role in scenarios involving nonlinear parameters, such as phase noise and multipath channels.
