Tight Upper and Lower Bounds to the Information Rate of the Phase Noise Channel

Numerical upper and lower bounds to the information rate transferred through the additive white Gaussian noise channel affected by discrete-time multiplicative autoregressive moving-average (ARMA) phase noise are proposed in the paper. The state space of the ARMA model being multidimensional, the problem cannot be approached by the conventional trellis-based methods that assume a first-order model for phase noise and quantization of the phase space, because the number of state of the trellis would be enormous. The proposed lower and upper bounds are based on particle filtering and Kalman filtering. Simulation results show that the upper and lower bounds are so close to each other that we can claim of having numerically computed the actual information rate of the multiplicative ARMA phase noise channel, at least in the cases studied in the paper. Moreover, the lower bound, which is virtually capacity-achieving, is obtained by demodulation of the incoming signal based on a Kalman filter aided by past data. Thus we can claim of having found the virtually optimal demodulator for the multiplicative phase noise channel, at least for the cases considered in the paper.Comment: 5 pages, 2 figures. Accepted for presentation at ISIT 201

Reduced complexity sequence detection

The paper deals with the design of suboptimal receivers for data transmission over frequency selective channels. The complexity of the optimum detector, that is the maximum likelihood sequence detector (MLSD), turns out be exponential in the channel memory. Hence, when dealing with channels with long memory, suboptimal receiver structures must be considered. Among suboptimal methods, a technique that allows reduction of the complexity is the delayed decision feedback sequence detector (DDFSD). This receiver is based on a Viterbi processor where the channel memory is truncated. The memory truncation is compensated by a per-survivor decision feedback equalizer. In order to achieve good performance, it is crucial to operate an appropriate prefiltering of the received sequence before the DDFSD. Our contribution is to extend the principles of MLSD and DDFSD to the case where the prefilter is the feedforward filter of a minimum mean-square error decision feedback equalizer (MMSE-DFE). Moreover performance evaluation of the MMSE prefiltered DDFSD is addressed. The union upper bound is used to evaluate the probability of first-event error. Simulation results show that our proposed design of the MMSE-DDFSD gives substantial benefits when a severe frequency selective channel is considered

Improved Nyquist pulse shaping filters for generalized frequency division multiplexing

Generalized Frequency-Division Multiplexing (GFDM) is one of the multicarrier modulation schemes currently under study for next generation 5G cellular networks. One of the main characteristics of GFDM is the low out of band emission that is achieved by means of a flexible time-domain pulse shaping of individual subcarriers. In the paper, we propose to use improved Nyquist pulse shaping filters which have been originally introduced in the context of single-carrier modulation schemes for reducing the sensitivity to symbol timing error due to their higher eye opening and smaller maximum distortion. Here we consider their use in GFDM and evaluate their symbol error rate (SER) performance in case of 16-QAM transmission over an additive white Gaussian noise channel. Moreover, we also considered the concept of the wavelet for better time-frequency localization of the pulse shaping filters by using the Meyer auxiliary function. Numerical results are reported to demonstrate the superior SER performance achieved by the proposed improved Nyquist pulse shaping filters in comparison to that achieved with conventional Nyquist pulse shaping filters