Abstract-Starting from the definition of mutual information, one promptly realizes that the probabilities inferred by Bayesian tracking can be used to compute the Shannon information between the state and the measurement of a dynamic system. In the Gaussian and linear case, the information rate can be evaluated from the probabilities computed by the Kalman filter. When the probability distributions inferred by Bayesian tracking are non tractable, one is forced to resort to approximated inference, which gives only an approximation to the wanted probabilities. We propose upper and lower bounds to the information rate between the hidden state and the measurement based on approximated inference. Application of these bounds to multiplicative communication channels is discussed, and experimental results for the discrete-time phase noise channel and for the GaussMarkov fading channel are presented.

Abstract-The iterative demodulation and decoding algorithm introduced in 2005 by Colavolpe, Barbieri, and Caire to cope with channels affected by phase noise needs pilot symbols to bootstrap. However, pilot symbols reduce the spectral efficiency of the system and, consequently, system's throughput. The aim of the paper is to show that trellis-based demodulation can be used to bootstrap the iterative process without the need of pilot symbols. Also, the complexity issue of trellis-based demodulation is addressed in the paper. The result is that the performance of iterative demodulation and decoding after the iterations is virtually unaffected by complexity reduction, provided that the reduced-complexity demodulator guarantees cycle-slip-free operation. From the numerical results presented in the paper we show that cycle-slip-free operation can be achieved with substantial complexity reduction also for phase noise associated with linewidths of practical interest.

The impact of large phase noise, typical of cost-effective energy-efficient sources such as VCSELs, on the transmission of a single side-band optical OFDM signal in case of direct detection over uncompensated fiber tracks is investigated thanks to Monte Carlo simulations. Comparison with the results achieved by a semi-analytical approach is reported, in particular when the laser linewidth is comparable to the OFDM subcarrier spacing

This paper investigates the differences between the symbol-spaced discrete-time Wiener phase noise channel model, commonly assumed in the literature to represent the effect of phase noise, and that obtained by symbol-rate sampling the filtered continuous-time received signal affected by continuous-time Wiener phase-noise. In particular, for comparison, we consider some statistical tests to check temporal and distributional properties of the two models. We show that the fit between the two models is very good even for quite strong values of phase noise. The main result is that when the standard deviation of the discrete-time Wiener phase noise increment σ P N is below a threshold of approximatelyσ P N ≃ 0.1 rad, the discrete-time Wiener model provides a good approximation to the actual symbol-spaced sampled filtered signal affected by continuous-time Wiener phase noise. We show that when σ P N is below σ P N the ratio between the power of the signal and the power of the model mismatch is greater than 20 dB. Simulation results are also presented to compare bit error rates of the two models in case of QPSK and 16-QAM transmission and to compare the power spectral densities of their associated complex exponential phase noises. Our results suggest that the discrete-time Wiener phase noise model can be adopted for many real-world systems, where, according to experimental results available in the literature, σ P N in the order of 0.1 rad is rarely found even when the nonlinearity of the optical channel is deeply stressed.

The complexity and the power consumption of digital signal processing are crucial issues in optical transmission systems based on mode division multiplexing and coherent multiple-input multiple-output (MIMO) processing at the receiver. In this paper the inherent characteristic of spatial separation between fiber modes is exploited, getting a MIMO system where joint demultiplexing and detection is based on spatially separated photodetectors. After photodetection, one has a MIMO system with nonlinear crosstalk between modes. The paper shows that the nonlinear crosstalk can be dealt with by a low-complexity and non-adaptive detection scheme, at least in the cases presented in the paper.