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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Resource Allocation for Single Carrier Massive MIMO Systems

Resource allocation in orthogonal frequency division multiplexing (OFDM) systems is performed through allocating blocks of subcarriers to each user. Even though OFDM is the primary waveform for 5G NR systems, research reports have noted that single carrier modulation (SCM) offers several advantages over OFDM in massive multiple input multiple output (MIMO) systems, making it a preferred candidate for some future applications such as massive machine type communications (mMTC). This paper presents a method for SCM resource allocation and the relevant information recovery algorithms at the receiver. Our emphasis is on cyclic prefixed SCM, where highly flexible and efficient frequency domain detection algorithms enable the operation of many simultaneous users in a massive MIMO uplink scenario. The proposed resource allocation method allows the number of users to exceed the number of antennas at the base station (BS). Each single carrier transmission is partitioned into L interleaved streams, and each user is allocated a number of such streams. One major benefit of SCM is that each data symbol is spread over the entire bandwidth. As such, the receiver performance is dictated by the average channel gain across the transmission band rather than the channel gain at a given frequency bin or a small group of frequencies. In the proposed setup, each stream may be thought of as a resource block in SCM, analogous to resource blocks in OFDM. Hence, in the context of this paper, the terms resource blocks and streams may be used interchangeably.

5G and Beyond Communications↗
DOE OSTI2024

An Assessment of Receiver Algorithms for Distributed Massive MIMO Systems: Investigating Design Solutions and Performance

This study investigates receiver design solutions for distributed Massive Multiple Input Multiple Output (D-m MIMO) systems, taking into account parameters such as number of access points as well as concerns related to channel estimates that use single-carrier frequency-domain equalization (SC-FDE). A significant contribution of this research is the integration of Low-Density Parity-Check (LDPC) codes to simplify coding complexity and enhance communication efficiency. The research examines different receiver designs, such as spatial antenna correlation and sophisticated channel estimation methods. The authors propose integrating LDPC codes into the receiver architecture to simplify computations and enhance error correction and decoding. Moreover, the paper examines performance evaluation measures and approaches, highlighting the trade-offs among complexity, spectral efficiency, and error performance. The comparative analysis indicates the benefits, in terms of performance, of incorporating LDPC codes and improving system throughput and dependability. We examine four distinct receiver algorithms: zero-forcing (ZF), minimum mean square error (MMSE), maximum ratio combining (MRC), and equal gain combining (EGC). The study shows that MRC and EGC receivers work well in D-m MIMO because they make the receiver system less computationally demanding.

Gashtasbi, Ali↗
DOE OSTI2023

Physical Layer Security at a Point-to-Point MIMO System With 1-Bit DACs and ADCs

Low-resolution converters reduce the power consumption of wireless devices and help enable large energy-efficient arrays. In this letter, we evaluate the secrecy rate for the extreme case of 1-bit single-user multiple-input multiple-output systems following two signaling approaches. In the first method, the system uses discrete signaling. In the second, the system combines Gaussian signaling with artificial noise alongside power allocation. In the first case, we give a closed-form expression of the secrecy rate and propose an algorithm that provides near-optimal results for low signal-to-noise ratios (SNRs). Further, in the second scenario, depending on the channel state information, we suggest different precoding plans and derive a secrecy rate lower bound. At low SNR, power is allocated to the main signal. Only at high SNR is optimal power allocation effective. Moreover, knowing the eavesdropper channel greatly improves the system’s secrecy.

1-bit digital-to-analog (DAC) and analog-to-digita↗
DOE OSTI2023

Development of a dynamical model and energy analysis for wheel loader

The objective of this paper is to develop a fully integrated model for the wheel loader, including the subsystem dynamics of the engine, drivetrain, working circuit, steering circuit, and vehicle. It leads to a high-order strongly nonlinear system, and all state variables are coupled together to form a Multi-Input and Multi-Output (MIMO) system. A control architecture is proposed to decouple the MIMO system into several Single-Input and Single-Output (SISO) systems. Here, a tracking problem has been formulated to validate this fully integrated model with the field test data. The accuracy of the model is verified by the 2.3% difference between the measured and simulated fuel consumption. Meanwhile, an energy distribution analysis is conducted to reveal the energy consumption and energy loss of each portion of the wheel loader. Such a model can be used to plan the working pattern, guide the driving habits of human operators, or refine the underlying architecture, leading to the ultimate goal of reducing total fuel consumption and improving productivity.

42 ENGINEERING↗
DOE OSTI2022

Advances in Secure 5G Network for a Nationwide Drone Corridor

Recent research has validated the proposal to add a separate set of antennas for 5G coverage in the air, while the conventional set of antennas continues to provide coverage on the ground, for a nationwide drone corridor for 5G cellular drones. More importantly, this drone corridor can be made secure and reliable by adapting the drone trajectories to avoid interference and security attacks, and with advanced precoding and physical layer security. Energy efficiency can also be improved with low-resolution massive multiple-input multiple-output (MIMO) systems that utilize low resolution digital to analog converters. This paper describes additional research findings to further support the creation of this nationwide drone corridor. We design optimal drone trajectory within the drone corridor to improve safety for pedestrians and vehicles on the ground. We derive the optimum antenna uptilt angle to minimize outage probability for a given drone corridor. We also study the placement of intelligent reflector surfaces in an urban drone corridor in order to improve the multi-path scattering and hence the spatial multiplexing gains for serving drones. We calculate trajectories to maximize data rate in the presence of smart interference when drones are used as relays and each drone may be deployed in the paths of data flows from multiple BSs to multiple UEs. Next we demonstrate how the use of the additional set of antennas along with the 3GPP standard based subframe blanking method can minimize the interference from ground reflection of the radio frequency (RF) radiation from the downtilted antennas. The paper concludes with plans to continue with experimental studies to advance this work further.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

A Stability Analysis Tool for Bulk Power Systems Using Black-Box Models of Inverter-based Resources

This paper presents a small-signal stability analysis tool for large-scale power systems with high penetration of inverter-based resources (IBRs). Firstly, a network transfer function matrix (NTFM), which represents the information of the system topology, transmission lines, loads, IBRs locations, etc., is derived to model the entire power system network. Secondly, small-signal perturbation method is applied to obtain the sequence impedance/admittance responses of IBRs considering the frequency cross-coupling effects. With the obtained NTFM as well as IBRs' models, a multi-input, multi-output (MIMO) feedback system is constructed, and the generalized Nyquist criterion (GNC)-based stability method is employed to analyze the stability of the entire power system. Different testing cases based on a modified IEEE-14 bus system are leveraged to verify the proposed stability analysis tool.

Sun, Dongsen↗
DOE OSTI2023

A Stability Analysis Tool for Bulk Power Systems Using Black-Box Models of Inverter-Based Resources

This paper presents a small-signal stability analysis tool for large-scale power systems with high penetration of inverter-based resources (IBRs). Firstly, a network transfer function matrix (NTFM), which represents the information of the system topology, transmission lines, loads, IBRs locations, etc., is derived to model the entire power system network. Secondly, small-signal perturbation method is applied to obtain the sequence impedance/admittance models of the block-box IBRs considering the frequency cross-coupling effects. With the obtained NTFM as well as IBR models, a multi-input, multi-output (MIMO) feedback system is constructed, and the generalized Nyquist criterion (GNC)-based stability method is employed to analyze the stability of the entire power system. Furthermore, based on the developed stability analysis method, sensitivity analysis is conducted on an unstable case to identify which parameter has a high impact on the system stability. As a result, different test cases based on a modified IEEE 14- bus system as well as a reduced 240-bus WECC system are studied to verify the proposed stability analysis tool.

42 ENGINEERING↗
DOE OSTI2023

Network-Wide Traffic Signal Control Using Bilinear System Modeling and Adaptive Optimization

This study proposes a new multi-input multi-output optimal bilinear signal control method in which a bilinear dynamic model approximation is used to capture the nonlinear dynamics of the urban traffic networks. With signal green time splits as the control input and traffic delay changes as the output for each intersections in the network, a bilinear system model was developed, which, on the basis of linear system modeling, takes interactions among traffic delays and signal timing splits into consideration. Based on the bilinear system modeling framework, we conducted two steps in each time interval to derive traffic control strategies: (1) we used the normalized least-squared algorithm to estimate system parameters; and (2) we solved an online optimization problem to obtain the updated traffic control inputs for the signal timing that minimizes future traffic delays. We evaluated the proposed method in a microscopic traffic simulation environment (VISSIM) with a 35-intersection network of Bellevue city in Washington. Two different traffic demand patterns: (1) normal traffic demands; and (2) time-varying traffic demands were simulated to compare the performance of different control strategies. Experimental results show that (1) the proposed bilinear system model can better describe traffic system dynamics than linear-model based methods, such as our previously developed linear-quadratic regulator control; and (2) the proposed method outperforms the state-of-the-art signal control strategies, namely the max-pressure and the self-organizing traffic light control methods. We have also shown that the proposed method is applicable to all other possible network layouts and signal controller phasing structures.

42 ENGINEERING↗
DOE OSTI2023

Quantification and prediction of error in MIMO tests

Dynamic testing of systems is most realistic of real-world conditions when multiple input and multiple output (MIMO) techniques are used. To replicate measured environmental conditions, a series of desired outputs (responses) on the system must be realized by inverting the frequency response functions (FRF) matrix for input estimation. System identification is dependent on the number of inputs and outputs, which affect the type of solutions. In input estimation, the auto spectra of the determined inputs are affected by both the auto spectra and cross spectra of the desired outputs. This research evaluates errors and investigates two sources in an experimental setting. The first significant error source is test-to-test variability in FRFs from system identification tests, quantified by magnitude variability from long-duration tests. The second significant error source is the realization of time histories from frequency domain inputs. The spectral content of the realized random process deviates from the desired content and is also quantified. The structure is a linear three-story frame fixed at the base; two inputs are provided uniaxially with the use of suspended electrodynamic shakers. The proposed model for error sources was found to be effective in predicting errors in a SISO (single-input single-output) and a square (2-input 2-output) MIMO test.

Yousef, Odey↗
DOE OSTI2022

Single Carrier Modulation Resource Allocation for Massive MIMO with Virtual Antennas

Today’s Massive MIMO cellular operation is dominated by orthogonal frequency division multiplexing (OFDM) modulation. One of the advantages of OFDM is the flexibility to carve up the available spectrum into resource blocks (RBs) that can operate adjacent to one another. Massive MIMO adds spatial multiplexing layers on top of the RBs, enabling the simultaneous operation of dozens of UEs. Cyclic prefixed single carrier modulation (CP-SCM) is an alternative to OFDM that also benefits from massive MIMO and is useful as an OFDM alternative in specific scenarios. However, until recently, no resource allocation method has been proposed for CP-SCM. In this paper, we present a CP-SCM resource allocation scheme using virtual antennas in a massive MIMO time domain duplexed scenario. By creating several virtual antennas for each physical antenna, the benefits of massive MIMO are achieved with a smaller physical antenna count. Resources are quantized into data streams, and each user can be assigned a variable number of simultaneous streams. This paper presents a detailed development and analysis of multi-stream processing (MSP) for both uplink detection and downlink precoding. We also introduce heterogeneous MSP, where CP-SCM and OFDM signals can be processed in the same MSP framework.

5G and beyond communications↗
DOE OSTI2021

A MIMO AAA Agorithm for Frequency Dependent Line Modeling

Modeling of power distribution system components that are valid for a wide range of frequencies are crucial for highly accurate modeling of electromagnetic transient (EMT) events. This has recently become of interest due to the improvements needed for the resilient operation of distribution systems. Vector fitting (VF) is a very popular and commonly used algorithm for wide band representations of power system components in EMT simulations. In this research, we present a new multi-input rational approximation algorithm (MIAAA) and illustrate its advantages with respect to VF using examples of approximations of admittance matrices discussed in the literature. We show that MIAAA not only outperforms VF in terms of achieving better accuracy using lesser number of poles, but also has no numerical issues achieving convergence. In contrast to VF, MIAAA is not sensitive to the location of input sample points and it does not require good estimates for the location of the desired approximation poles. The novelty of this research work is the use of recent mathematical results to solve existing challenges in distribution system modeling and to develop rational approximations for power system models that intend to be optimal in terms of accuracy and performance.

AAA algorithm↗
DOE OSTI2023

Assessing Tropical Pacific-induced Predictability of Southern California Precipitation Using a Novel Multi-input Multi-output Autoencoder

We construct a novel Multi-Input Multi-Output Autoencoder-decoder (MIMO-AE) to capture the non-linear relationship of Southern California precipitation and tropical Pacific Ocean sea surface temperature. The MIMO-AE is trained on both monthly TP-SST and SC-PRECIP anomalies simultaneously. The co-variability of the two fields in the MIMO-AE shared nonlinear latent space can be condensed into an index, termed the MIMO-AE index. We use a transfer learning approach to train a MIMO-AE on the combined dataset of 100 years of output from a historical simulation with the Energy Exascale Earth Systems Model version 1 and a segment of observational data. We further use Long Short-Term Memory networks to assess sub-seasonal predictability of SC-PRECIP using the MIMO-AE index. We find that the MIMO-AE index provides enhanced predictability of SC-PRECIP for a lead-time of up-to four months as compared to Niño 3.4 index and the El Niño Southern Oscillation Longitudinal Index.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Sub-nanosecond RF synchronization for MIMO software defined radio sensor networks

This disclosure presents distributed and decentralized synchronization for wireless transceivers. The disclosed system, device, and method achieve sub-nanosecond synchronization using low-cost commercial off the shelf software defined radios. By providing a decentralized mechanism that does not rely on a hierarchical master-slave structure, networks constructed as disclosed are robust to sensor drop-out in contested or harsh environments. Such networks may be used to create phased array radars and communication systems without requiring wired connections to distribute a common clock or local oscillator reference.

Moghaddam, Mahta↗
DOE OSTI2021

Sequence Impedance Measurement of Utility-Scale Wind Turbines and Inverters – Reference Frame, Frequency Coupling, and MIMO/SISO Forms

Sequence impedance responses with or without considering frequency coupling in both MIMO and SISO forms are increasingly used for the stability analysis of three-phase power electronic systems; however, many aspects of sequence impedance measurement are not fully explored. It is not clear if the sequence impedance has a reference frame similar to the dq impedance. If so, the role of the grid voltage angle estimation in aligning the sequence impedance reference frame has not been discussed. Additionally, existing methods for measuring the sequence impedance with frequency coupling are complicated, are not feasible for large wind turbines and inverters, and provide the sequence impedance responses in only either MIMO or SISO form. This paper presents a sequence impedance measurement method that considers the frequency coupling, performs reference frame alignment, demonstrates the impact of the grid voltage angle estimation, and obtains the sequence impedance response in both MIMO and SISO forms. This paper demonstrates the proposed method and practical problems associated with the sequence impedance measurement of utility-scale wind turbines and inverters on a 1.9-MW Type III wind turbine and a 2.2-MVA inverter using an impedance measurement system built around a 7-MW/13.8-kV grid simulator and a 5-MW dynamometer.

17 WIND ENERGY↗
DOE OSTI2025

RFSoC based digital low level RF control firmware and software suite (mimo_llrf) v1.0

It features a framework of a firmware and software architecture in support of building a digital low-level RF control system for accelerators, where precised digital RF generation and measurement are needed across many RF channels. It primarily supports the Xilinx RFSoC chips (xczu48dr, xczu47dr, xczu29dr) and their evaluation boards (zcu208, zcu216), for a highly integrated solution enabling the need for synchronous low-level RF systems, including: multi-tile synchronization, external reference for sampling clocks, deterministic delay, aligned NCO phase for digital mixers, and built-in EPICS IOC.

Du, Qiang [Lawrence Berkeley National Laboratory (↗
DOE OSTI2023

A New Proposal Generalized Predictive Control Algorithm With Polynomial Reference Tracking Applied for Sodium Fast Reactors

This paper proposes a generalized predictive control (GPC) with constraints and orthonormal Laguerre functions using the simplified model of the primary system (reactor core and intermediate heat exchanger (IHX)) of a prototypical sodium fast reactor (SFR). This paper develops a multiple-input multiple-output (MIMO) GPC with input constraints able to track polynomial references of any degree applied in coolant temperature difference across the core and fractional power. The manipulated variables of the GPC-SFR are the reactivity and the sodium flow rate of the primary and secondary pipes. Moreover, orthonormal Laguerre functions and step down condition number techniques were also applied to avoid the numerical ill-conditioning issue in quadratic programming of large systems. Thus, a GPC type-2 was designed to control fractional power, coolant temperature difference across the core and sodium tank temperature of the SFR primary system when temperature references change according to a linear ramp after reaching their steady-state operation, sustaining 100% power operation on the reactor. In order to analyze the load tracking capability of the GPC-SFR type-2, the load following from 100% fractional power (FP) to 60% FP at 0.8% FP/min rate is simulated. Constraints on the rate of coolant temperature difference across the core and reactivity were applied for the design safety. For comparison criteria, this paper compares the GPC-SFR type-2 with the GPC-SFR type-1, i.e., standard model predictive control (MPC), to verify the viability and superior performance of the proposal regarding: (a) ramp-tracking capability of temperature and load; (b) the rejections of a reactivity disturbance of -1 cent and a secondary sodium inlet temperature disturbance of +10°F; and (c) a simulation with uncertainty in reactor design. The simulations show that the GPC-SFR type-2 overcome the GPC-SFR type-1 robustness and performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗