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Accurate precipitation measurement is critical for managing flood and drought risks. Traditional meteorological tools, such as rain gauges and remote sensors, have limitations in resolution, coverage, and cost-effectiveness. Recently, the opportunistic use of microwave communication signals has been explored to improve precipitation estimation. While there is growing interest in using satellite-to-earth microwave links (SMLs) for machine learning-based precipitation estimation, direct rainfall estimation from raw signal-to-noise ratio (SNR) data via deep learning remains underexplored. This study investigates a range of machine learning (ML) approaches, including deep learning (DL) models and traditional methods like gradient boosting machine (GBM), for estimating rainfall rates from SNR data collected by interactive satellite receivers. We develop real-time models for rainfall detection and estimation using downlink SNR signals from satellites to user terminals. By leveraging a year-long dataset from multiple locations—including SNR measurements paired with disdrometer and rain-gauge data—we explore and evaluate various ML models. Our final models include ensemble approaches for both rainfall detection and cumulative rainfall estimation. The proposed models provide a reliable solution for estimating precipitation using Earth–satellite microwave links, potentially improving precipitation monitoring. Compared to the state-of-the-art power-law-based models applied to similar datasets reported in the literature, our ML models achieve a  46 %  reduction in the root mean squared error (RMSE) for event-based cumulative precipitation predictions. [ABSTRACT FROM AUTHOR]

Coastal climate services play a crucial role in developing customised climate information for diverse end-users and stakeholders. To build climate-resilient societies, decision-makers should be empowered through easy access to powerful tools that enable timely adaptation to future and ongoing hazards. For this reason, fit-for-purpose climate services are needed to conduct accurate historical characterisation and projections for interpretative studies on climate- and water-related risks at the local coastal scale. The EU-funded SCORE project (Smart Control of Climate Resilience in European Coastal Cities) utilises climate and marine services for the development of smart technologies that support nature-based solutions to address specific concerns, including rising sea levels, coastal erosion, and coastal flooding due to extreme weather events. As part of the SCORE project, decision-makers will be able to address climate change-related coastal effects in their own cities through novel participatory approaches (Coastal City Living Labs—CCLLs). As part of this framework, this work (i) discusses the main requirements for the identification of fit-for-purpose coastal climate services for local-scale impact studies in European coastal cities based on CCLL requests and prior knowledge and (ii) provides relevant parameters and features that fulfil the users' needs. [ABSTRACT FROM AUTHOR]

In multicarrier (MC) broadband wireless networks, nonlinear power amplification is one of the main performance limiting factor, and therefore its effects have to be properly quantified during the design phase of the radio links. This letter outlines an analytical framework for the forward-link of a bandlimited MC code division multiple access that intends to fulfill this need while improving the scarce efficiency of conventional simulation-based-only design procedures. Through the extended Bussgang theorem, the approach presented herein yields a theoretical description of several time- and frequency-domain system features, such as transmitted signal power spectrum, constellation warping, nonlinear distortion noise and BER metric. Extensive simulation results verify the accuracy of the proposed analysis under typical multiple-access operating conditions. Index Terms--Multicarrier Code Division Multiple Access communications, nonlinear channel, Bussgang theorem, constellation warping, nonlinear distortion noise.

Positioning algorithms in cellular networks has become increasingly important as a means of supporting emerging services that require a sufficiently precise estimation of the position of the mobile terminal (MT) associated with a given base station (BS). Currently, even the most sophisticated positioning algorithms require at least three BSs to achieve satisfactory precision. This paper presents a novel algorithm that makes use of a single-BS antenna array to locate MTs in cellular networks. A triangulation technique is utilized and supported by some minimal information about the environment in the BS neighborhood. This algorithm is shown to perform well when operating in a microcellular environment with perfect channel-parameter estimation. The effect of finite resolution of the input parameters is also investigated. The performance is analyzed for a universal mobile telecommunications system microcellular scenario through a three-dimensional deterministic channel model. Finally, the performance of the proposed positioning technique is compared to the well-known location method based on the time-of-arrival measurements at three different BSs. Index Terms--Deterministic propagation model, location techniques, microcellular wireless networks, radiolocation, ray tracing, wide-band code-division multiple-access (W-CDMA).

This paper is concerned with the estimation of the rate-of-change of the instantaneous frequency of an unmodulated carrier. Such an issue arises, for instance, in satellite communication systems based on a low-earth-orbit constellation, wherein the speed of each satellite relative to earth is rapidly time-varying, and consequently, the received carrier is affected by nonnegligible Doppler shift and Doppler rate. First, we present simple yet efficient estimators of the Doppler rate derived from maximum-likelihood estimation theory. Next, we investigate their performance in terms of bias and estimation error variance. Finally, we compare our variance results with the relevant modified Cramer-Rao hound. Index Terms - Doppler effect, frequency estimation, satellite communication.

The satellite-to-mobile link of a mobile personal satellite communication system employing power-controlled direct-sequence code-division multiple access (DS-CDMA) and exploiting satellite diversity is analyzed and its performance compared with a more traditional communication system utilizing single-satellite reception. The semianalytical model developed has been thoroughly validated by means of extensive Monte Carlo computer simulations. System capacity and performance have been numerically evaluated in the presence of a realistic operating scenario, including antenna radiation pattern, imperfect power control, shadowing, and cross-polarization effects. It is shown how the capacity gain provided by diversity reception considerably shrinks in the presence of increasing traffic or in the case of mild shadowing conditions. Moreover, the quantitative results tend to indicate that to combat system capacity reduction due to the intrasystem interference, no more than two satellites sharing the same frequency slot must be active over the same region. Index Terms - Code-division multiaccess, diversity methods, satellite mobile communications.

Fast and reliable signal sense and signature code synchronization for direct-sequence spread-spectrum (DS-SS) signals are key issues in the design of the receiver for modern packet code-division multiple-access (CDMA) radio networks for mobile communications - this motivates the study of the signal-recognition and code-acquisition (SR/CA) scheme we describe in this paper. Specifically, starting from elementary estimation and detection theory criteria, we work out a noncoherent parallel SR/CA algorithm that is suited to a full-digital implementation in a single application-specific integrated circuit (ASIC). The results of a theoretical analysis of such a scheme, encompassing additive white Gaussian noise (AWGN) and multiple-access interference (MAI), are integrated and validated by an overall time-domain system simulation. We also evaluate through a simplified approach the impact of some degradation factors on the overall circuit performance, namely, sampling epoch and carrier frequency offset and 1-b signal quantization, to allow optimization of the design parameters as a function of the characteristics of the received signal. Index Terms - Code-division multiaccess, synchronization, parallel algorithms.

Code-division multiple-access (CDMA) with direct-sequence/spread-spectrum (DS/SS) modulated signals has emerged as a strong candidate for the air interface of the universal wireless personal communication network planned for the end of the century. In this paper, we take into consideration a recently proposed low-complexity blind adaptive interference-mitigating detector (BALD) scheme that minimizes the detrimental effect of the multiple-access interference (MAI) on the bit-error-rate (BER) performance of a CDMA data demodulator. We describe a few modifications to the original algorithm that make it more suitable to a practical implementation with dual-binary phase-shift keying (D-BPSK)-modulated DS/SS signals. Specifically, we show how to make the BAID invariant to a possible carrier phase offset introduced in the front-end of the data demodulator, and we also suggest how to increase the robustness of such detector to asynchronous MAI. The uncoded BER performance of the resulting "extended" detector is then evaluated theoretically and by computer simulation in the case of coherent and differential signal detection. Index Terms - Adaptive signal detection, code-division multi-access, interference suppression.