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Spatiotemporal signal reconstruction from samples randomly gathered in a multidimensional space with uncertainty is a crucial problem for a variety of applications. Such a problem generalizes the reconstruction of a deterministic signal and that of a stationary random process in one dimension, which was first addressed by Whittaker, Kotelnikov, and Shannon. In this work we analyze multidimensional random sampling with uncertainties jointly accounting for signal properties (signal spectrum and spatial correlation) and for sampling properties (inhomogeneous sample spatial distribution, sample availability, and non-ideal knowledge of sample positions). The reconstructed signal spectrum and the signal reconstruction accuracy are derived as a function of signal and sampling properties. It is shown that some of these properties expand the signal spectrum while others modify the spectrum without expansion. The signal reconstruction accuracy is first determined in a general case and then specialized for cases of practical interests. The optimal interpolator function is derived and asymptotic results are obtained to show the impact of sampling non-idealities. The analysis is corroborated by verifying that previously known results can be obtained as special cases of the general one and by means of a case study accounting for various settings of signal and sample properties.

Different design issues and performance aspects of a low-complexity echo canceller for digital on-channel repeaters are described in this paper. Locally generated pulse trains are injected in the repeated signal to estimate the coupling channel between the transmitting and the receiving antennas. In particular, we analyze a low-complexity channel cancellation technique based on the reconstruction of the coupling channel pulse response via digital FIR filtering. After developing a proper theoretical model, the analytical expressions of some important performance figures are determined, e.g. the Mean Rejection Ratio and the Echo Suppression at Nominal Position. Then, the description of our implementation of the echo canceller on a FPGA board is reported. Finally, the performance values derived by the theoretical model are compared to measurements results.

Different design issues and performance aspects of a lowcomplexity echo canceller for digital On-Channel Repeaters (OCRs) are described in this paper. Locally generated lowpower PN sequences are injected in the repeated signal to facilitate the estimation process of the coupling channel between the transmitting and the receiving antennas. In particular, we analyse a low-complexity channel estimation technique based on the autocorrelation properties of the training sequence. An expression for the cancelling performance is found analytically, in terms of Mean Rejection Ratio (MRR), and the impact of the filtering stages within the repeater is also addressed.

In this paper we analytically evaluate the downlink performance of a multi-carrier code division multiple access (MC-CDMA) system by employing partial combining when multiple antennas at the transmitter or at the receiver are considered. It is known that for single reception/transmission, the partial combining technique depends on a parameter which can be optimized as a function of the number of subcarrier, the number of active users and the SNR improving the performance with respect to other classical techniques (such as maximal ratio combining, equal gain combining, or orthogonality restoring combining). In this paper we extend the analysis considering also multiple antennas aiming at showing how the spatial diversity affects the performance as a function of the partial combining parameter.

Crowdsensing is an effective method to map physical spatial fields by exploiting sensors embedded in smartphones. Enclosing humans in the loop increases the amount of data available for the mapping process, with benefits in terms of accuracy and cost. On the other hand, the huge amount of data generated and the irregular spatial distribution of measurements are serious issues to be addressed. In this paper we propose a combined Gaussian process (GP)-State space method for crowd mapping whose complexity and memory requirements for field representation do not depend on the number of data measured. The method is validated through an experimental campaign and simulations.

This letter studies large-scale molecular communication systems by using point processes theory. A swarm of point transmitters randomly placed in a bounded space are considered in conjunction with a single fully absorbing receiver. The transmitters' positions are modeled by a spatial point process, but the global clock assumption, adopted by prior works, is here removed. More precisely, the emission times for each point transmitter are considered as random and are modeled by a non-stationary time-domain point process. We show that, if the intensity function is the same for all time point processes (thus taking the meaning of a distributed input), the average number of received molecules per time unit (receiving rate) can be computed through a convolution: the collective response to a one-molecule emission can be properly interpreted as the impulse response. This models unifies all the widely known transmitter models (exact concentration, Poisson concentration, and timing transmitter), which result as special cases. Analytical expressions for the receiving rate are provided and validated by Monte-Carlo simulations.

The most relevant impairment experienced by on-channel repeaters (OCRs) in single frequency networks scenarios is the presence of a coupling-channel between the transmitting and receiving antennas, that generates unwanted echoes. This phenomenon causes a degradation of the repeated signal and, above all, could lead to the instability of OCRs, owing to the positive feedback that could result. For this reason, OCRs are usually equipped with echo canceller units, aimed at removing the coupling contributions. In this paper, we consider a realistic OCR setup and we analytically derive proper design criteria for echo-cancellers, showing the role of system parameters and implementation aspects on their performance. Here, in particular, we investigate the joint effect of the estimation noise and the finite precision arithmetic of digital systems, the system sensitivity to different design parameters and the relation between the echo-cancelling performance and the probability of instability.

Spatial field reconstruction is important for a variety of applications based on environmental monitoring via Internet-of-Things and vehicular communications. This work develops a framework for the analysis of multidimensional stochastic sampling in vehicular crowdsensing, where samples are gathered from sensors on vehicles. Vehicular crowdsensing performance in terms of reconstruction mean-square error is compared to that obtainable with fixed installation. In the first case, sensors are assumed to be randomly distributed over the monitored area, while, in the latter, they are considered as regularly placed in a lattice. In addition, the positions of the mobile nodes are assumed non perfectly known at the interpolator. By extending recent results on multidimensional stochastic sampling, it is shown that a high field reconstruction accuracy can be obtained by vehicular crowdsensing even in cases where fixed infrastructure would lead to insufficient sampling.

This paper presents a smart city pilot project that will be developed in the city of Bologna. Different sensor devices will be deployed in several buildings to measure environmental quantities, such as temperature, humidity, luminosity and CO2. The pilot will use the LoRa low-rate, long-range communication technology to transmit sensed data to the control center. Results of a measurement campaign to characterize the propagation in the Bologna scenario are reported. Such results are then used as input to a simulator that provides both coverage and networklevel performance of the LoRa technology in the considered scenario. The paper shows that a proper parameter setting is needed to cover large urban areas while maintaining the timeon- air sufficiently low to keep packet losses at satisfactory levels.

This paper analyzes distributed molecular communications with multiple transmitters and multiple receivers randomly placed in a 3D space. Receivers, whose positions are modeled by a homogeneous Poisson point process, are assumed to be passive and spherical. Since they are not dimensionless, their presence affects the statistics of transmitter points, resulting in a Poisson hole process, instead of the Poisson process usually adopted in previous works on multiple transmitters. Moreover, molecules emissions from different transmitters are considered asynchronous, according to a recently proposed stochastic model. Here, the intensity function of the time point processes modeling molecules emissions is given a further meaning; in particular, it is considered as the propensity function of a chemical reaction. The average amount of received molecules per time unit (receiving rate) is evaluated accordingly for each receiver. When the swarm of receivers is considered as an equivalent, single, spatially distributed receiver, the average amount of received molecules per time and volume units (receiving rate density) is introduced and analytically evaluated.

Resource allocation is a challenging issue in multiuser wireless systems. Since users are not all in the same conditions and do not achieve the same performance given the same amount of resources, resource allocation must typically deal with the following two conflicting objectives: on the one hand, the overall performance should be maximized, tending to prioritize few users in better conditions, and on the other hand, fairness among users should be maximized, consequently reducing the overall performance. Identifying the compromise that is somehow optimum is all but simple and this aspect is normally worsened by the absence of a curve describing how the maximum performance varies changing the accepted level of fairness. To cover this gap, in this paper, we propose a unified and general mathematical formulation of the optimal performance versus fairness tradeoff in multiuser wireless communication systems. Differently from the existing literature, our approach is based on the generalized Lagrange method and adopts general definitions for both performance and fairness. Besides the exact solving equations describing how the maximum performance varies with fairness, we also derive a simpler lower bound with reduced computational cost. Example results are provided for two case studies, respectively, concerning linear and logarithmic dependence of performance on resources.