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Cascading overload failures occurred in power systems due to higher penetration of renewable energy resources (RERs), which causes uncertainty in a grid. To overcome these cascading overload failures, proper assessment in the form of load flow balancing and transients stability is required in renewable integrated power grids (RIPGs). This problem becomes more critical in the occurrence of multiple intervals faults in multiple interconnected RIPGs, which causes the tripping of several RERs. Due to which outages occurred in various transmission lines, which lead the power system to cascading overload failures. To tackle this problem, hybrid probabilistic modeling is proposed in this paper for balancing load flow and an assessment of transients stability in multiple interconnected RIPGs. For balancing of load flow, a smart node transmission network topology is utilized along with integrating a unified power flow controller (UPFC), while transients instabilities are assessed through a UPFC alone. Contrary to the previously proposed algorithms, which are only suitable to compensate network instabilities in case of only a single interval fault, this work is supported by probabilistic modeling to compensate network instabilities under the occurrence of not only a single interval fault but also in case of more severe multiple intervals faults in multiple interconnected RIPGs that will lead the network to cascading failure outages. Simulation results verify that our proposed probabilistic algorithm achieved near an optimal performance by outperforming the existing proposed methodologies, which are only confined to mitigate the effect of network instabilities only in case of single interval fault and fails to address these network instabilities under the occurrence of severe multiple interval faults, which leads the network to cascading failure outages. These simulation results are also validated through an industrial case study performed on a western Denmark transmission network to show the superiority of our proposed algorithm.

Faster-than-Nyquist signaling (FTNS) has already been shown to increase the communication capacity on certain channels such as additive white Gaussian noise and block flat multiple-input multiple-output (MIMO) Rayleigh fading channels. The following issues, however, remain unresolved: 1) whether FTNS enables a capacity increase in generalized MIMO Rayleigh fading channels that are selective in time, frequency, and space; and 2) how channel selectivities affect the capacity and if present, the FTN capacity gain. To address the issues, this paper firstly investigates the ergodic capacity of MIMO-FTN transmission over triply-selective fading channels. We derive a low-complexity approximate capacity formula and also show how it degenerates in other channel models, such as doubly-selective single-input single-output fading channels, which can be considered as the special cases of triply-selective fading channels. The capacity evaluation results obtained under different channel conditions show that: 1) MIMO-FTN outperforms MIMO-Nyquist in terms of capacity; 2) the FTN gains are nearly consistent, while the FTN gains obtained in the frequency-selective fading channels are slightly higher than those obtained in the flat fading channels. [ABSTRACT FROM AUTHOR]

In this letter, we present a digital transmitter for dual-band narrowband-Internet-of-Things (NB-IoT) applications achieving a large dynamic range with high-speed cartesian RF-DACs requiring less area and consuming low power consumption. The proposed transmitter incorporates integrated output baluns, a reconfigurable digital interpolater-based oversampling for DAC image suppression, or avoidance of coexistence channel. A true SAW-less design is realized by external low-cost low-pass filtering of the spurious emission satisfying NB-IoT requirements. Implemented in standard 40-nm CMOS technology with a core area of $2.1\times1.5$ mm2 and packaged with QFN-68, the transmitter achieves a dynamic range from −47.5 to 24.8 dBm with error vector magnitude (EVM) <−25 dB. The peak efficiency is 44.1% at 28.7-dBm output power, with a 2.4-V power supply. [ABSTRACT FROM AUTHOR]

Faster-than-Nyquist signaling (FTNS) has emerged as a promising technique to increase communication capacity in bandwidth-limited channels. However, the presence of FTN-induced inter-symbol interference (FTN-ISI) in the received observations, is detrimental to channel estimation (CE) and data detection in terms of computational complexity and performance. This paper copes with these problems by incorporating linear pre-equalization (LPE) and composite precoding formed by linear spectral precoding and Tomlinson-Harashima precoding (THP), into the FTNS. Specifically, LPE completely pre-equalizes the FTN-ISI, while spectral precoding resolves the LPE-caused signal spectral broadening by introducing proper artificial ISI, which is pre-equalized by THP. Channel-induced ISI, as the only ISI component in the observations, is estimated and equalized using the classical frequency-domain low-complexity schemes. We show that there are four advantages of the LPE-aided CE over the CE designed for the FTN transmissions without FTN-ISI pre-equalization, namely lower pilot overhead, simpler yet optimal pilot sequence design, lower mean-squared error of CE, and more robust against the FTN-ISI. Simulation results show that our scheme improves the performance of CE and detection, compared to existing FTN frequency-domain CE and equalization schemes. [ABSTRACT FROM AUTHOR]

The state-of-the-art radio-frequency (RF) devices limit the deployment of extremely high-order quadrature amplitude modulation (QAM) formats (e.g., 16384-QAM) to meet the high-capacity demand on microwave backhaul links. This paper turns to faster-than-Nyquist (FTN) transmission using lower-order constellations and lower-cost RF devices as a solution to the demand. To realize low-complexity interference cancellation, we pre-equalize the FTN-induced inter-symbol interference at the transmitter by using Tomlinson-Harashima precoding (THP), while at the receiver suppressing the phase noise (PHN) generated by the RF local oscillators with pilot symbol assisted approaches. However, the THP may distort the pilots, which degrades the performance of PHN compensation. To resolve this problem, we propose two pilot designs that are distortion-free to precisely estimate the PHN samples. Moreover, we derive a closed-form expression of the symbol detection signal-to-noise ratio (SNR), in terms of the THP-FTN waveform parameters. With the SNR expression, a waveform optimization procedure is developed to maximize the SNR and enhance the achievable FTN capacity. The proposed scheme is validated in the simulated platform of 4096-QAM microwave link. The results demonstrate that the FTN signaling achieves the system capacity equivalent to that of the 16384-QAM Nyquist signaling with an SNR gain of 5.8 dB. [ABSTRACT FROM AUTHOR]

We report on the methodology of developing a hybrid model and utilizing it as a template to initiate running behavior in a legged robot. The hybrid model is comprised of a physics-based, rolling, spring-loaded, inverted pendulum (R-SLIP) model, and a data-driven model that compensates for unmodeled dynamics using Gaussian process (GP) regression. The hybrid R-SLIP-GP model retains the R-SLIP's intrinsic running dynamics, as well as improves the template's accuracy without intensive data training and iteration efforts. The proposed hybrid model was evaluated via simulation and in empirical robot running experiments. The results confirm that the added GP-based model greatly improved the model's accuracy, especially discrepancies resulting from the originally difficult-to-model complex leg-ground interactions. In addition, the R-SLIP-GP model was utilized as a complete motion template to design and control the robot's running motion. The experimental results demonstrate that the hybrid template can initiate more stable and power-efficient running motion in the robot than using the R-SLIP template. [ABSTRACT FROM AUTHOR]