In this paper, we focus on orthogonal time frequency space (OTFS) modulated transmissions over doubly-selective channels. Specifically, we investigate the state-of-the-art techniques for effective detection in high-mobility scenarios and introduce innovative strategies aimed at achieving an optimal trade-off between complexity and performance. The proposed solutions are based on the Ungerboeck observation model and exploit the structure of the resulting channel matrix in the Doppler-delay domain. In particular, the first proposed method, denoted as HBCJRG, belongs to the family of message-passing algorithms, whose strength lies in a scheduling scheme that prioritizes the strongest interferers during the detection process. In contrast, the second proposed approach, denoted as ICG, is based on interference cancellation. Differently from the HBCJRGapproach, whose required computational load grows quadratically with the constellation cardinality, the ICGalgorithm is characterized by extremely low complexity. Simulation results demonstrate that the latter strategy allows to achieve an optimal trade-off between complexity and performance when compared to existing state-of-the-art solutions.

In the context of signal detection in the presence of an unknown time-varying channel parameter, receivers based on the Expectation Propagation (EP) framework appear to be very promising. EP is a message-passing algorithm based on factor graphs with an inherent ability to combine prior knowledge of system variables with channel observations. This suggests that an effective estimation of random channel parameters can be achieved even with a very limited number of pilot symbols, thus increasing the payload efficiency. However, achieving satisfactory performance often requires ad-hoc adjustments in the way the probability distributions of latent variables - both data and channel parameters - are combined and projected. Here, we provide, for the first time, an analysis of EP-based algorithms for the classical problem of coded transmission on a strong Wiener phase noise channel, employing soft-input soft-output decoding. The analysis includes possible improvements over the native application of EP, in order to identify its limitations and propose new strategies which reach the performance benchmark while maintaining low complexity, with a primary focus on challenging scenarios where the state-of-the-art algorithms fail.

Expectation Propagation (EP) is a promising framework in message-passing algorithms based on factor-graphs. The inherent ability to combine prior (partial) knowledge of system variables with channel observations suggests that an effective estimation of random channel parameters can be achieved even with a very limited number of pilot symbols, thus increasing the payload efficiency. Yet, the way in which the probability distributions of latent variables (both data and parameters) are combined and projected often requires ad-hoc adjustments to reach satisfactory performance. Here, we apply EP to a classical problem of LDPC-coded transmission on a strong Wiener phase noise channel and discuss how and why, even in the simple case of binary modulation, EP can fail or succeed.

We consider the phase noise affecting communication systems, where local oscillators are employed to obtain a reference signal for frequency and phase synchronizations. We try to fill the gap between measurements and analytical models, in case of free-running and phase-locked oscillators. In particular, we propose a closed form expression for the power spectral density of the phase noise described by few parameters that are explicitly linked to the oscillator measurements. We also propose an analytical model for the oscillator power spectral density.

We consider time-frequency-packed systems in an additive white Gaussian noise scenario. With respect to systems employing time packing, thus introducing intentional intersymbol interference only, a further improvement of the spectral efficiency is obtained by packing the adjacent carriers closer in frequency. The adoption of a multiuser detector can allow coping with the resulting intentional intercarrier interference. The optimal detector for time-frequency-packed systems has a complexity that increases exponentially with the number of interferers in both time and frequency dimensions and thus becomes unmanageable. We propose a suboptimal receiver, which is derived by using the framework based on factor graphs and the sum-product algorithm, with a complexity that is linear in the number of adjacent carriers and takes also advantage of a multi-user channel shortener to further reduce the complexity. We assess the performance by means of computer simulations and show that, when compared with other suboptimal receivers available in the literature and with the optimal detector, the proposed receiver results very promising in terms of trade-off between performance and computational complexity.

We propose a novel discrete-time model for the phase noise signal, in case of free-running and phase-locked oscillators. In particular, we show how the PN can be described by an autoregressive process. The strength of the proposed model is that it can be easily expressed in terms of measurement parameters of practical oscillators. We then analyse the most common discrete-time phase noise channel model with reference to the measurement parameters and to the system bandwidth. The derived analytical models for the discrete-time phase noise signal can be used for the design of estimation/detection algorithms, for performance evaluation, or simply for fast simulations.

In this paper, we consider the design of spiral constellations for channels affected by phase noise. The strength of the proposed constellations resides both on the performance and on the extreme simplicity of the design. The symbols can in fact be expressed in analytical form, and are uniquely defined through a single parameter that accounts for the phase and thermal noise variances. The performance of the proposed constellations are assessed in terms of information rate and error rate. Despite their simplicity, the new spiral constellations have excellent performance, especially when the constellation size grows large.

We investigate the use of maximum distance separable (MDS) codes to cache popular content to reduce the download delay of wireless content delivery. In particular, we consider a cellular system, where popular files are cached in a distributed fashion in a limited number of the mobile devices using an MDS code and can be downloaded from them using device-to-device (D2D) communication. The base station controls the D2D communication and assists the requests that cannot be fully satisfied by the distributed caching (DC) network by providing the missing data. We consider a network model, where the cell is divided into clusters, where D2D links can be activated. We derive an analytical expression for the delay incurred in downloading content from the wireless network assuming that devices roam in and out of clusters according to a Poisson random process. Our analysis allows to identify the parameters of the wireless network that mostly affect the performance and to compare different caching strategies in terms of delay. We show that DC using MDS codes can dramatically reduce the download delay with respect to the scenario where content is always downloaded from the base station and to the case of uncoded DC.

In this paper, we consider the design of spiral constellations for channels affected by phase noise. The strength of the proposed constellations resides both on the performance and on the extreme simplicity of the design. The symbols can in fact be expressed in analytical form, and are uniquely defined through a single parameter that accounts for the phase and thermal noise variances. The structure of the proposed constellations allows to easily determine the points that are closest to any point in the complex plane, therefore we also propose a low complexity detector that is suitable for phase noise channels in medium-high signal-to-noise ratio conditions. The performance of the proposed constellations are assessed in terms of information rate and error rate. Despite their simplicity, the new spiral constellations have excellent performance, especially when the constellation size grows large.

We consider the rates achievable by a user in a multibeam satellite system for unicast applications and propose alternatives to the conventional single-user symbol-by-symbol detection applied at user terminals. Single-user detection is known to suffer from strong degradation when the terminal is located near the edge of the coverage area of a beam and when aggressive frequency reuse is adopted. For this reason, we consider multiuser detection and take into account the strongest interfering signal. We also analyze two additional transmission strategies requiring modifications at medium access control layer. We describe an information-theoretic framework to compare the different strategies by computing the information rate of the user in the reference beam. Furthermore, we analyze the performance of coded schemes that could approach the information-theoretic limits. We show that classical codes from the DVB-S2(X) standard are not suitable when multiuser detection is adopted and we propose two ways to improve the performance based on the redesign of the code and of the bit mapping.

We study the achievable rates by a single user in multibeam satellite scenarios. We show alternatives to the conventional symbol-by-symbol detection applied at user terminals. Single user detection is known to suffer from strong degradation when the terminal is located near the edge of the coverage area, and when aggressive frequency reuse is adopted. For this reason, we consider multiuser detection, and take into account the strongest interfering signal. Moreover, we analyze a different transmission strategy, where the signals from two adjacent beams jointly serve two users in a time division multiplexing fashion. We describe an information-theoretic framework to compare different transmission/detection strategies by computing the information rate of the user in the reference beam.

We analyze the asymptotic performance of non-binary spatially-coupled low-density parity-check (SC-LDPC) codes built on the general linear group, when the transmission takes place over the binary erasure channel. We propose an efficient method to derive an upper bound to the maximum a posteriori probability (MAP) threshold for nonbinary LDPC codes, and observe that the MAP performance of regular LDPC codes improves with the alphabet size. We then consider nonbinary SC-LDPC codes. We show that the same threshold saturation effect experienced by binary SC-LDPC codes occurs for the nonbinary codes, hence we conjecture that the BP threshold for large termination length approaches the MAP threshold of the underlying regular ensemble.

We consider realistic satellite communications systems for broadband and broadcasting applications, based on frequency-division-multiplexed linear modulations, where spectral efficiency is one of the main figures of merit. For these systems, we investigate their ultimate performance limits by using a framework to compute the spectral efficiency when suboptimal receivers are adopted and evaluating the performance improvements that can be obtained through the adoption of the time-frequency packing technique. Our analysis reveals that introducing controlled interference can significantly increase the efficiency of these systems. Moreover, if a receiver which is able to account for the interference and the nonlinear impairments is adopted, rather than a classical predistorter at the transmitter coupled with a simpler receiver, the benefits in terms of spectral efficiency can be even larger. Finally, we consider practical coded schemes and show the potential advantages of the optimized signaling formats when combined with iterative detection/decoding.

This papers addresses the design of new energy-efficient Continuous Phase Modulation (CPM) waveforms suitable for being adopted in satellite mesh networks that are characterized by the absence of the Hub, and by small antennas and power amplifiers with moderate to low output saturated power at the user terminal. In particular, a CPM modulation format concatenated with a proper convolutional code for low spectral efficiency values has been selected to implement an efficient waveform for power-limited scenarios. Performance results show the gain obtained with respect to the DVB-RCS2 CPM waveforms at higher spectral efficiency also when transmission techniques, such as Burst Repetition, are considered, and confirm the suitability of the new designed CPM waveforms for satellite hub-less scenarios.

We consider a frequency-division-multiplexed satellite system where nonlinear distortions may originate from the presence of high power nonlinear devices and can cause significant performance degradations. The spectral efficiency is used as a performance measure to compare, from an information-theoretic point of view, different transmission strategies and modulation formats. More precisely, we will consider transmission schemes employing continuous phase modulations, which are robust to nonlinearities, and schemes based on linear modulations and employing a detector taking into account the nonlinear effects or more traditional techniques, such those based on predistortion of the nonlinear device.

We propose novel detection algorithms for linear modulations transmitted over nonlinear satellite channels, also impaired by additive white Gaussian noise. These algorithms are derived by using a Volterra-series expansion of the useful signal and by applying the sum-product algorithm to a suitably-designed factor graph. Being soft-input soft-output (SISO) in nature, the proposed detectors can be adopted in turbo processing without additional modifications. Typical linear modulations employed in satellite transmissions are considered in the numerical results. When compared with the optimal detection algorithm for these channels, whose complexity is exponential in the channel memory, the proposed schemes result very appealing in terms of tradeoff between performance and computational complexity. Particularly, the proposed schemes can approach the optimal performance with a complexity only linear in the channel memory.

We consider a frequency division multiplexed (FDM) system where each user employs a continuous phase modulation (CPM), serially concatenated with an outer code through an interleaver, and iterative detection/decoding. In such a system, the spectral efficiency can be increased by reducing the spacing between two adjacent channels, thus increasing the relevant interference. Hence, we address the design of low-complexity suboptimal multiuser detectors able to effectively cope with such an interference. We extend some well known multiuser detection algorithms proposed for code division multiple access (CDMA) systems. Moreover, we introduce a new detection scheme using the framework based on factor graphs (FGs) and the sum-product algorithm (SPA). The simulation results show that the described algorithms allow to effectively reduce the spacing, thus increasing the spectral efficiency, and in particular, the proposed detection scheme results to be the most effective one in terms of performance and computational complexity.

We consider a frequency division multiplexed (FDM) satellite system where each user employs a continuous phase modulation (CPM), serially concatenated with an outer code through an interleaver, and iterative detection/decoding. In such a system, the spectral efficiency can be increased by reducing the spacing between two adjacent channels, thus increasing the relevant interference. Hence, we address the design of low-complexity suboptimal multiuser detectors able to effectively cope with such an interference. We extend some well known multiuser detection algorithms proposed for code division multiple access (CDMA) systems. Moreover, we introduce a new detection scheme using the framework based on factor graphs (FGs) and the sum-product algorithm (SPA). The simulation results show that the described algorithms allow to effectively reduce the spacing, thus increasing the spectral efficiency, and in particular, the proposed detection scheme results to be the most effective one in terms of performance and computational complexity.

We consider a terrestrial wireless channel, whose statistical model under flat-fading conditions is due to Clarke. A lot of papers in the literature deal with receivers for this scenario, aiming at estimating and tracking the time-varying channel, possibly with the aid of known (pilot) symbols. A common approach to derive receivers of reasonable complexity is to resort to a Kalman filter which is based on an approximation of the actual fading process as autoregressive moving-average (ARMA) of a given order. The aim of this paper is to show that the approximation of the actual fading process, usually exploited in the literature, is far from effective. Thus, we present a novel technique, based on an off-line minimization of the mean square error of the channel estimate, which ensures a considerable gain in terms of bit-error rate for Kalman-based receivers without increasing the receiver complexity. Moreover, we also propose a novel approximation, to be employed in Kalman smoothers proposed for iterative detection schemes, which allows further performance improvements without a significant increase of the computational complexity.

We propose a novel iterative method, similar to the generalized Blahut-Arimoto algorithm recently proposed by Kavcic, to evaluate the Markov capacity of a continuous phase modulated signal over an additive white Gaussian noise channel. One of the novelty of our approach is that we maximize, with respect to the input distribution, the spectral efficiency in bps/Hz rather than the mutual information in bits per channel use. We address this problem by taking into account the bandwidth occupancy of the CPM signal by means of the Carson's rule bandwidth definition, and solving a linearly constrained nonlinear optimization problem. The results show that Markov capacity obtained with the proposed input optimization algorithm strongly outperforms the capacity for independent and uniformly distributed input.

We consider a terrestrial wireless channel, whose statistical model under flat-fading conditions is due to Clarke. A lot of papers in the literature deal with receivers for this scenario, aiming at estimating and tracking the time-varying channel, possibly with the aid of known (pilot) symbols. A common approach to derive receivers of reasonable complexity is to resort to a Kalman filter which is based on an approximation of the actual fading process as autoregressive moving-average (ARMA) of a given order. The aim of this paper is to show that the approximation of the actual fading process, usually exploited in the literature, is far from optimal. Thus, we present a novel technique, based on an off-line minimization of the mean square error of the channel estimate, which ensures a considerable gain in terms of bit-error rate for Kalman-based receivers without increasing the receiver complexity. Moreover, we also propose a novel approximation, to be employed in Kalman smoothers proposed for iterative detection schemes, which allows to further improve the performance without a significant increase of the computational complexity.