In this paper, we design a 5 G -compliant semipersistent scheduling algorithm that guarantees determinism (i.e., bounded delay and zero jitter) over the wireless link for delayconstrained traffic. This is especially important for industrial remote control applications handling time-sensitive traffic. To this end, we adapt the window reservation mechanism for wired networks introduced in IEEE 802.1Qbv to also ensure determinism over 5G wireless links. Based on the statistical characterization of the radio channel, we develop a rigorous method to determine the number of time-frequency resources that must be reserved in each 5 G subframe to accommodate all time-sensitive traffic traversing the wireless link. Numerical simulations are conducted in representative industrial scenarios, showing that neighboring base stations have to coordinate their transmissions to avoid interference and mitigate channel fading. Numerical results demonstrate that window design for timesensitive traffic benefits from coordination in two key ways: by extending coverage and significantly increasing the number of time-critical flows that a 5G network can support in industrial deployments.

This paper presents a novel radio frame design for wireless links that allows efficient scheduling of multiple time-sensitive flows with bounded delay and arbitrarily small packet jitter requirements. The proposed design is compatible with the IEEE 802.1 standards for Time Sensitive Networks (TSN) and permits the efficient integration of wireless links into newly arrived wired TSN infrastructure. With this aim, we have reformulated the window reservation mechanism introduced in standard 802.1Qbv to deal with the variable transmission rate of wireless links. The new radio frame is organized in a sequence of partially-overlapped windows. If the intended flow does not use its window completely, the unconsumed time can be scheduled to other flows in overlapped windows. The benefits of this approach are evaluated numerically in an illustrative industrial scenario showing substantial gain in terms of both reduced control cycle (flows’ periodicity) and enhanced transmission throughput (number of admitted flows).

Reducing the large sidelobes of multicarrier signals is crucial to prevent adjacent channel interference. Spectral precoding is an effective approach toward this goal, at the expense of throughput loss due to precoder redundancy; thus, it is of interest to explore alternative precoder designs with improved performance at lower redundancies. We present a novel precoder which minimizes radiated power within a user-selectable frequency region. The structure of the precoding matrix is chosen to allow efficient mitigation of in-band distortion at the receiver by means of iterative and successive interference cancellation, while completely avoiding distortion to protected and pilot subcarriers. By exploiting the low-rank properties of constituent blocks, computational complexity can be significantly reduced with little impact on sidelobe reduction. Simulation results show the benefits of the proposed design, which is particularly effective in redundancy-limited settings targeting high spectral efficiency.

This study presents a wind retrieval simulator of a floating Doppler Wind Lidar (DWL) with 6 Degrees of Freedom (DoF) motion. The simulator considers a continuous-wave conical-scanning floating DWL which retrieves the wind vector from 50 radial velocities per scan. The 6 DoF motion framework as well as the most important buoy motion equations are summarized. Rotational and translational motion effects over HWS measurements are studied parametrically.

A multiple access (MA) optimization technique for massive low-rate direct-sequence spread spectrum communications is analyzed in this work. A dense network of users transmitting at the same rate to a common central node under channel-aware energy allocation is evaluated. At reception, successive interference cancellation (SIC) aided by channel decoding is adopted. Our contribution focuses on wireless scenarios involving a vast number of users for which the provided user-asymptotic model holds. Variational calculus (VC) is employed to derive the energy allocation function that, via user-power imbalance, maximizes the network spectral efficiency (SE) when perfect channel state information at transmission (CSIT) is available and both average and maximum per-user energy constraints are set. Monte Carlo simulations at chip-level of a SIC receiver using a real decoder assess the proposed optimization method.

This paper studies the throughput maximization of a dense multiple access network of low-rate subscribers that share the same practical Forward Error Correction (FEC) code and modulation scheme, and transmit to a central node that implements a Successive Soft Interference Cancellation (soft SIC) strategy in order to mitigate Multiple Access Interference (MAI). In the user-asymptotic case, we make use of Variational Calculus (VC) tools to derive, in terms of the Packet Error Rate (PER) of the shared encoder and the Residual Energy (RE) from imperfect cancellation, the optimum energy profile that maximizes the network spectral efficiency, when a sum power constraint at the SIC input is enforced. Comparative performance analyses using a representative encoder are carried out. Simulation results show the benefit of the adopted soft SIC scheme in front of other SIC strategies, obtaining relevant throughput gains under high traffic loads.

The frequency diversity exhibited by cyclostationary signals is exploited in this paper. A novel rank-1 frequency-domain representation of a digital waveform is proposed to address the generalized likelihood ratio (GLR) detection of a cyclo-stationary signal with unknown white noise. With the aim of avoiding the well-known sensitivity of cyclostationary-based detectors to frequency-selective fading channels, a parametric channel model based on the coherence bandwidth is adopted and incorporated in the GLR test. The proposed detector outperforms the classical spectral correlation magnitude detectors by exploiting the rank-1 structure of small spectral co-variance matrices.

A two-scale ad hoc wireless network is envisaged in which the interference power generated in long-range connections is recycled by the surrounding wireless nodes in order to support their own short-range communications. We prove that the network energy efficiency is independent of the transmitters range and, therefore, that long-range transmitters can supply the power required for short-range connectivity without degrading the overall network energy efficiency. As an example, we have studied the feasibility of a short-range multiple-access return-link powered by the interference harvested from neighboring long-range connections.

This paper addresses the problem of blind detection of a wide-sense stationary (WSS) signal over fading channels. We propose a test statistic which is optimal from a correlation-matching perspective that shows invariance with respect to the noise power and the channel gain. In the blind scenario, we derive the quadratic sphericity test (QST) which exploits the structure of the fading channel as a squared mean to arithmetic mean ratio of the eigenvalues of the autocorrelation matrix of the observations. We provide numerical results to assess the performance of the QST in several fading scenarios, as well as the benchmarking to other blind and non-blind detectors.

We propose a scheme for Compressed Sensing in the noiseless setting that reconstructs the original signal operating on a binary graph where the samples are obtained sequentially. The proposed scheme has an affordable computational complexity and a large performance enhancement with respect to similar schemes in the literature, thanks to the proposed measurement matrix structure and enhanced decoding based on a message passing algorithm.

This paper proves that second-order symbol-rate blind channel identification is feasible if the transmitted bit stream is encoded and the channel estimator conveniently exploits the code redundancy. This result is surprising because most error correcting codes do not alter the symbols correlation. Despite this, it can be shown that second-order methods can exploit the symbols fourth-order statistical information, which contains part of the code redundant structure. Analytical and numerical results are presented for the BPSK (binary phase shift keying) modulation and simple error-correcting block codes. The extension to more sophisticated coding and modulation schemes seems straightforward although computationally intensive.

In this paper we study from a theoretical and practical perspective the problem of nondata-aided (NDA) carrier phase recovery with MSK-type modulations. As suggested in previous works, the optimal ML estimator for low SNRs is quadratic on the received data. However, self-noise limits its performance in the medium-to-high SNR interval. To overcome this limitation, we have deduced optimal second-order schemes for the whole SNR range. The proposed estimator is asymptotically efficient when the SNR is low and cancels out the self-noise at high SNRs. Closed-form expressions are obtained for the high-SNR asymptotic case and a complete discussion is provided on its applicability in closed-loop and feed-forward schemes.

The paper presents a novel approach to parameter estimation based on sample covariance matrix linear processing. The originality of this framework relies upon two facts: (1) the Gaussian assumption about the nuisance parameters is avoided; (2) quadratic feed-forward schemes are designed saving the complexity and delay of conventional ML-based algorithms that carry out an exhaustive search throughout the whole parameter range. This second aim is achieved by adopting a Bayesian perspective in which the parameter of interest is modeled as a random variable of known a priori distribution. The Bayesian approach allows us to establish certain optimality criteria (mean squared error, bias and variance) yielding to estimation schemes with the best performance on the average, that is, with respect to the assumed prior of the parameter. In order to illustrate the proposed theory, we address the problem of frequency estimation in digital communications. This example has been chosen because its formulation encompasses several problems of special interest such as non-data-aided open-loop carrier synchronization, direction-of-arrival estimation in narrow-band uniform linear arrays and, if the signal is processed in the frequency domain, timing recovery and time-of-arrival estimation in positioning systems, as well.

In this paper we develop a new, versatile framework for the design of optimal non-data-aided (NDA) parameter estimators based on the exploitation of the received signal sample covariance matrix. The estimator coefficients are optimized in. order to yield minimum mean squared error (MSE) estimates of the parameter. Some linear constraints are introduced into the optimization process allowing the designer to have control over the estimator characteristic response. For those scenarios where bias is forbidden, as it happens in ranging applications, we provide the optimal solution minimizing the estimates bias within the range of the received parameter. The adopted approach is Bayesian as we treat the wanted parameter as a random variable with a known a priori probability distribution (prior). This modeling allows us to unify the design of both open- and closed-loop estimators. The proposed formulation encompasses all the linear modulations as well as the binary continuous phase modulation (CPM). The new approach supplies optimal estimation schemes without the need of assuming a given statistics for the unknown symbols, that is, avoiding the common adoption of the Gaussian assumption, which does not apply in digital communications. Special attention is paid to those low-complexity implementations for which the maximum likelihood efficiency is not guaranteed.

The study of parameter estimation under additive and multiplicative noise terms constitutes an interesting signal processing research topic with important consequences in the development of high-performance digital communication receivers. In this sense, the paper addresses the analysis of non-assisted digital synchronizers based on up to fourth-order moments and it shows how this alternative outperforms the conventional second-order techniques. The study is performed for MSK (minimum shift keying) as a particular case of the binary CPM modulations. This transmission scheme is adopted because it allows a simple extension to any linear digital modulation and to any multiple access modulation, as well. Simulation results show that the higher-order techniques exhibit a parameter estimation variance closer to the so-called modified Cramer-Rao bound for moderate-to-high SNR if compared to second-order techniques.