In this paper, we process channel Signal-to-Noise-Ratio time series gathered in the proximity of the Pianosa island, Italy, in Summer 2009. These traces are used to model the performance of capacityachieving code ensembles as employed in an Incremental Redundancy (IR) Hybrid Automatic Repeat reQuest (HARQ) error control scheme. We apply a code-matched channel state quantization technique aimed at representing channel evolution over time with low quantization error; the evolution of the channel among the quantized states is then represented using a Markov model, over which we base the analytical evaluation of IR-HARQ performance.Results confirm that IR-HARQ consistently improves link performance with respect to Type I HARQ. In addition, we observe that the different channel statistics due to different transmitter and receiver placements, as well as to the acoustic propagation conditions considered in our scenario, have an impact on HARQ performance. This impact is correctly captured by our Markov model, suggesting good adherence of the model to actual channel behaviors. The validation of the models (by simulating over different traces than those used to train the models) suggests that they are robust to moderate non-stationarity, making them good candidates to give a compact representation of the channel behavior, e.g., in network simulators.

In this paper, we present an analysis of the space-time correlation and power-delay profile (PDP) properties of the underwater acoustic channel in the nearabouts of the Pianosa Island, off the north-western coast of Italy. Our data has been collected during sea trials which took place from May to September 2009. Using the results from this evaluation, we compare the measured bit error rates affecting the transmission of Frequency-Hopping Binary Frequency Shift Keying (FH-BFSK) against those obtained by simulating the same digital modulation scheme over synthesized channels whose spread in time has the same statistical properties as those found in the trials, and whose channel taps are Rayleigh-distributed. The results show a generally good accordance of the simulated performance with the outcomes of the experiments. Moreover, given the absence of a widely agreed upon underwater channel model, and the recent interest in incorporating more accurate propagation simulators into network simulators, we compare the measured channel impulse responses against those obtained through the ray tracing tool Bellhop, and give some observations about the suitability of the tool for the purpose of reproducing realistic channel traces

We address the design of pilot sequences for channel estimation in the context of multiple-user Massive MIMO; considering the presence of channel correlation, and assuming that the statistics are known, we seek to exploit the spatial correlation of the channels to minimize the length of the pilot sequences, and specifically the fact that the users can be separated either through their spatial signature (low-rank channel covariance matrices), or through the use of different training sequences. We introduce an algorithm to design short training sequences for a given set of user covariance matrices. The obtained pilot sequences are in general non-orthogonal, however they ensure that the channel estimation error variance is uniformly upper-bounded by a chosen constant over all channel dimensions. We show through simulations using a realistic scenario based on the one-ring channel model that the proposed technique can yield pilot sequences of length significantly smaller than the number of users in the system.

In this paper, we developed transmission strategies able to deliver a prescribed number of packets by a deadline T while minimizing transmission attempts. All the packets have a single common transmission deadline. The three systems analyzed here differ from each other on the way Channel State Information (CSI) is provided by the receiver. In the first system, the receiver sends back CSI only when packets fail; in the second system, the receiver provides CSI only if this minimizes a given cost function; and in the third system, feedback is sent whenever a given threshold condition is verified. The communication channel is modeled as a time-varying correlated fading channel, represented by a Markov chain. For the first two systems, the optimal schedules are obtained through Dynamic Programing (DP). The third scheduler is based on a heuristic strategy, whose performance is evaluated through numerical simulations, and compared with that of the two optimal schedulers obtained through DP. Results showed that the heuristic scheduler can reach performance similar to that of DP schedulers.Index Terms-Energy-efficient scheduling, stochastic optimal control, efficient wireless communications.