MIMO-UFMC Transceiver Schemes for Millimeter Wave Wireless Communications

The UFMC modulation is among the most considered solutions for the realization of beyond-OFDM air interfaces for future wireless networks. This paper focuses on the design and analysis of an UFMC transceiver equipped with multiple antennas and operating at millimeter wave carrier frequencies. The paper provides the full mathematical model of a MIMO-UFMC transceiver, taking into account the presence of hybrid analog/digital beamformers at both ends of the communication links. Then, several detection structures are proposed, both for the case of single-packet isolated transmission, and for the case of multiple-packet continuous transmission. In the latter situation, the paper also considers the case in which no guard time among adjacent packets is inserted, trading off an increased level of interference with higher values of spectral efficiency. At the analysis stage, the several considered detection structures and transmission schemes are compared in terms of bit-error-rate, root-mean-square-error, and system throughput. The numerical results show that the proposed transceiver algorithms are effective and that the linear MMSE data detector is capable of well managing the increased interference brought by the removal of guard times among consecutive packets, thus yielding throughput gains of about 10 - 13 $\%$. The effect of phase noise at the receiver is also numerically assessed, and it is shown that the recursive implementation of the linear MMSE exhibits some degree of robustness against this disturbance

Robust optimized certainty equivalents and quantiles for loss positions with distribution uncertainty

The paper investigates the robust optimized certainty equivalents and analyzes the relevant properties of them as risk measures for loss positions with distribution uncertainty. On this basis, the robust generalized quantiles are proposed and discussed. The robust expectiles with two specific penalization functions $\varphi_{1}$ and $\varphi_{2}$ are further considered respectively. The robust expectiles with $\varphi_{1}$ are proved to be coherent risk measures, and the dual representation theorems are established. In addition, the effect of penalization functions on the robust expectiles and its comparison with expectiles are examined and simulated numerically.Comment: 5 figures, 24 page

FERI: A Multitask-based Fairness Achieving Algorithm with Applications to Fair Organ Transplantation

Liver transplantation often faces fairness challenges across subgroups defined by sensitive attributes like age group, gender, and race/ethnicity. Machine learning models for outcome prediction can introduce additional biases. To address these, we introduce Fairness through the Equitable Rate of Improvement in Multitask Learning (FERI) algorithm for fair predictions of graft failure risk in liver transplant patients. FERI constrains subgroup loss by balancing learning rates and preventing subgroup dominance in the training process. Our experiments show that FERI maintains high predictive accuracy with AUROC and AUPRC comparable to baseline models. More importantly, FERI demonstrates an ability to improve fairness without sacrificing accuracy. Specifically, for gender, FERI reduces the demographic parity disparity by 71.74%, and for the age group, it decreases the equalized odds disparity by 40.46%. Therefore, the FERI algorithm advances fairness-aware predictive modeling in healthcare and provides an invaluable tool for equitable healthcare systems

Optimal Waveforms Design for Ultra-Wideband Impulse Radio Sensors

Ultra-wideband impulse radio (UWB-IR) sensors should comply entirely with the regulatory spectral limits for elegant coexistence. Under this premise, it is desirable for UWB pulses to improve frequency utilization to guarantee the transmission reliability. Meanwhile, orthogonal waveform division multiple-access (WDMA) is significant to mitigate mutual interferences in UWB sensor networks. Motivated by the considerations, we suggest in this paper a low complexity pulse forming technique, and its efficient implementation on DSP is investigated. The UWB pulse is derived preliminarily with the objective of minimizing the mean square error (MSE) between designed power spectrum density (PSD) and the emission mask. Subsequently, this pulse is iteratively modified until its PSD completely conforms to spectral constraints. The orthogonal restriction is then analyzed and different algorithms have been presented. Simulation demonstrates that our technique can produce UWB waveforms with frequency utilization far surpassing the other existing signals under arbitrary spectral mask conditions. Compared to other orthogonality design schemes, the designed pulses can maintain mutual orthogonality without any penalty on frequency utilization, and hence, are much superior in a WDMA network, especially with synchronization deviations

A Combination of Extended Fuzzy AHP and Fuzzy GRA for Government E-Tendering in Hybrid Fuzzy Environment

The recent government tendering process being conducted in an electronic way is becoming an inevitable affair for numerous governmental agencies to further exploit the superiorities of conventional tendering. Thus, developing an effective web-based bid evaluation methodology so as to realize an efficient and effective government E-tendering (GeT) system is imperative. This paper firstly investigates the potentiality of employing fuzzy analytic hierarchy process (AHP) along with fuzzy gray relational analysis (GRA) for optimal selection of candidate tenderers in GeT process with consideration of a hybrid fuzzy environment with incomplete weight information. We proposed a novel hybrid fuzzy AHP-GRA (HFAHP-GRA) method that combines an extended fuzzy AHP with a modified fuzzy GRA. The extended fuzzy AHP which combines typical AHP with interval AHP is proposed to obtain the exact weight information, and the modified fuzzy GRA is applied to aggregate different types of evaluation information so as to identify the optimal candidate tenderers. Finally, a prototype system is built and validated with an illustrative example for GeT to confirm the feasibility of our approach

Accounting for aerosol scattering in the CLARS retrieval of column averaged CO_2 mixing ratios

The California Laboratory for Atmospheric Remote Sensing Fourier transform spectrometer (CLARS‐FTS) deployed at Mount Wilson, California, has been measuring column abundances of greenhouse gases in the Los Angeles (LA) basin in the near‐infrared spectral region since August 2011. CLARS‐FTS measures reflected sunlight and has high sensitivity to absorption and scattering in the boundary layer. In this study, we estimate the retrieval biases caused by aerosol scattering and present a fast and accurate approach to correct for the bias in the CLARS column averaged CO2 mixing ratio product, X_(CO2). The high spectral resolution of 0.06 cm^(−1) is exploited to reveal the physical mechanism for the bias. We employ a numerical radiative transfer model to simulate the impact of neglecting aerosol scattering on the CO_2 and O_2 slant column densities operationally retrieved from CLARS‐FTS measurements. These simulations show that the CLARS‐FTS operational retrieval algorithm likely underestimates CO_2 and O_2 abundances over the LA basin in scenes with moderate aerosol loading. The bias in the CO_2 and O_2 abundances due to neglecting aerosol scattering cannot be canceled by ratioing each other in the derivation of the operational product of X_(CO2). We propose a new method for approximately correcting the aerosol‐induced bias. Results for CLARS X_(CO2) are compared to direct‐Sun X_(CO2) retrievals from a nearby Total Carbon Column Observing Network (TCCON) station. The bias‐correction approach significantly improves the correlation between the X_(CO2) retrieved from CLARS and TCCON, demonstrating that this approach can increase the yield of useful data from CLARS‐FTS in the presence of moderate aerosol loading