Iterative channel estimation and decoding for convolutionally coded anti-jam FH signals

Electr. Eng. Dept., Maryland Univ., College Park, MD
IEEE Transactions on Communications (Impact Factor: 1.98). 03/2002; DOI: 10.1109/26.983327
Source: IEEE Xplore

ABSTRACT An iterative algorithm for joint decoding and channel estimation
in frequency-hopping (FH) networks is proposed. In the proposed
algorithm, soft decoder outputs are used in the iterative estimation of
the time-varying variance of the additive interference resulting from
the sum of the thermal noise, partial-band noise jamming, and other-user
interference. The soft outputs are also used in the estimation of the
independent random carrier phases and multiplicative Rayleigh fading
coefficients in different frequency dwells. The estimation process is
further enhanced through the insertion of known symbols in the
transmitted data stream. The proposed iterative symbol-aided
demodulation scheme is compared with the coherent scenario, where the
channel state information is assumed to be known a priori at the
receiver, for both convolutionally coded and turbo coded FH systems. The
proposed iterative channel estimation approach is suited for slow FH
systems where the channel dynamics are much slower than the hopping
rate. This observation motivates the consideration of another robust
approach for generating the log-likelihood ratios for fast hopping
systems in additive white Gaussian noise channels. Simulation results
that demonstrate the excellent performance of the proposed algorithms in
various scenarios are also presented

Download full-text


Available from: Hesham El Gamal, Mar 26, 2015
1 Follower
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Orthogonal frequency division multiplexing (OFDM) systems are vulnerable to narrow-band jamming signals. We jointly tackle two problems: channel estimation in the presence of unknown interference, and decoding with imperfect channel knowledge. In this paper, we propose robust, yet simple, receiver algorithms consisting of both channel estimation and information decoding. The receiver conducts threshold tests to detect interference followed by pilot erasure and channel estimation. Then, channel estimation error and unknown interference statistics are dealt with by the robust log-likelihood ratio (LLR) calculations for soft iterative decoding. The proposed receiver algorithm does not require any statistical knowledge of interference and its complexity is linear against the length of codewords. Simulation results show that the bit-error-rate (BER) performance of the proposed system is only 2~3 dB away from a genie system where channel information and interference parameters are perfectly known. We also demonstrate that soft decision feedback from a decoder to enhance channel estimation achieves additional 0.5 ~ 1dB improvement.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We propose a new method for practical non-Gaussian and nonstationary underwater noise modeling. This model is very useful for passive sonar in shallow waters. In this application, measurement of additive noise in natural environment and exhibits shows that noise can sometimes be significantly non-Gaussian and a time-varying feature especially in the variance. Therefore, signal processing algorithms such as direction-finding that is optimized for Gaussian noise may degrade significantly in this environment. Generalized autoregressive conditional heteroscedasticity (GARCH) models are suitable for heavy tailed PDFs and time-varying variances of stochastic process. We use a more realistic GARCH-based noise model in the maximum-likelihood approach for the estimation of direction-of-arrivals (DOAs) of impinging sources onto a linear array, and demonstrate using measured noise that this approach is feasible for the additive noise and direction finding in an underwater environment.
    Journal on Advances in Signal Processing 01/2007; DOI:10.1155/2007/71528 · 0.81 Impact Factor
  • Source