Net Throughput Research Articles

A Low-Cost High-Throughput C-Band Communication System for CubeSats

This paper presents the physical layer of a proprietary broadband communication system for CubeSats. The system operates in the C band (5.8 GHz), delivering at least 10 Mbps of the net user throughput. Operation at low elevation angles (and therefore low SNRs) and high Doppler shifts is made possible thanks to a sophisticated synchronization subsystem. The system can be adapted to propagation conditions experienced during a given visibility window by changing the signal bandwidth and coding rate. It is implemented using Software Defined Radio (SDR) technology. The system will be used in two missions that are scheduled for 2023 and 2024 and are planned in cooperation with the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” and SatRev S.A.

Pilot-Partitioning Protocol and Anti-Jamming Methods in Distributed Massive MIMO Systems

Accurate channel state information (CSI) is crucial for effective beamforming in wireless communication systems. Unfortunately, the estimation of CSI might not be accurate due to pilot contamination, which happens when the transmission of pilots from the users to access points (APs) is interfered. In systems with a large number of users, non-orthogonal pilot training can increase pilot contamination resulting in incorrect CSI estimation. To address this issue, we propose a pilot-partitioning protocol for distributed massive multiple-input multiple-output (MIMO) systems. The protocol decomposes long-length orthogonal pilots into short-length sub-pilots, transmits them in consecutive slots, and uses the channel correlation among consecutive slots to regenerate orthogonal pilots. In addition, we consider the impact of adversarial transmissions, such as jamming attacks, on CSI estimation. To protect the system against jamming attacks, we propose an AP selection framework to eliminate ineffective APs where the estimated CSI is strongly distorted by jammers. Furthermore, we develop power control strategies for achieving the net throughput maximization and user fairness. Our numerical results show that the proposed designs improve system performance by up to 6.47 times compared to non-optimized scenarios.

Joint Learning and Optimization-Based Resource Management in Hybrid Network of Cooperative and Non-Cooperative Massive MIMO Systems

Multi-cell multiple-input multiple-output (MIMO) systems have the potential to significantly improve wireless network throughput. However, the cooperative MIMO network experiences the limited backhaul capacity, while the non-cooperative MIMO network requires high fronthaul bandwidth. To overcome these issues, we consider the hybrid MIMO networks to take advantages of both non-cooperative and cooperative MIMO network. In such hybrid system, the decision of whether cells operate in non-cooperative or cooperative mode, as well as the allocated bandwidth for cells are challenging due to the unavailability of channel state information (CSI). Furthermore, cells operating in the cooperative mode should optimize the quantized level selection and power allocation when the backhaul capacity is limited. To address this problem, we propose a joint learning-based and optimization-based framework. Particularly, we employ both large-scale and small-scale fading models to formulate the optimization problems, and then use the obtained solutions of these problems to determine fixed-size features in dynamic networks for the learner. Our numerical results show when the placement decision and the bandwidth assignment for cells are determined, the proposed algorithm can compute the quantized level and allocate power to significantly improve the system performance. Moreover, the proposed hybrid network model controlled by our algorithms outperforms both the non-cooperative and the cooperative MIMO systems in term of net throughput.

Analysis and optimization for non-orthogonal pilot sequence sets in massive MIMO systems

In modern wireless communication systems, orthogonal pilot signals has been generally employed in estimation of the channel state information. However, orthogonal pilot signals are inadequate for supporting the rapidly increasing requirements of communication throughput for 5G-and-beyond wireless environments, owing to the pilot contamination and short coherence times in high-mobility situations. To address these concerns, we present a new strategy for making use of non-orthogonal pilot sequences in channel estimation for multi-cell massive multiple-input multiple-output systems. First, we extend prior pilot assignment strategies based on the orthogonality of pilots to the general case of non-orthogonal pilot signals. Based on the proposed non-orthogonal pilot assignment strategy, we establish the minimal pilot length that fulfills a requirement for the channel estimate error, under a given degree of non-orthogonality. Then, we demonstrate validity of the pilot assignment strategy with the minimal length, which maximizes the entire network throughput. Simulation results show that our proposed method gives a significantly enhanced performance in terms of the net throughput compared to that with orthogonal pilot sequences. The performance gain becomes particularly significant with a higher density of users or shorter coherence time intervals.

Velocity Optimization for UAV-Mounted Transmitter in Population-Varying Fields

This paper proposes a spectrally efficient aviation strategy for unmanned aerial vehicle (UAV)-mounted transmitters (Txs) operating in a service area with heterogeneous user density. We discover that two distinct tradeoffs contribute to the network throughput: A speed-dependent tradeoff between inter-carrier interference and crowd chasing; and an altitude-dependent tradeoff between the shadowing possibility and source proximity. It is then analytically demonstrated that optimal throughput and reliability can be achieved by balancing the physical movement of UAV Tx. In concern of economical battery use, the velocity vector is optimized to obtain maximum net throughput during the UAV's flight, and computer simulations verify the feasibility of the proposed flight strategy.

Dielectric layer modulated nanofluidic transport: Formation of parent–sister vortices

Our analysis, consistent with the induced-charge electrokinetic, aptly discusses the effect of gate potential on the formation of vortices of disparate scales in a nanofluidic channel. The nanochannel considered here is connected with reservoirs at its ends, while a pair of dielectric gate electrodes is also embedded on the outer layer of the channel wall. In this endeavor, we establish that a suitable modulation of the dielectric polarization and inherent surface charge of the channel wall leads to the development of pair of “parent–sister” vortices in the flow field alongside yields a net flow in the channel, as well a unique fluidic functionality achieved at small scale is reported here for the first time. Moreover, we identify for the first time that the critical value of surface charge density (“critical-sigma,” i.e., σc) for two different typical heights of the nanofluidic channel, leading to the formation of maximum strength and size vortices by ceasing the net throughput. Also, we establish a critical range of surface charge density for a window of an arbitrary dimension of the dielectric gate electrode—a range for which optimum vortices are generated in the pathway, simultaneously producing adequate net flow through the channel. Under the present modeling configuration, we obtain that |σc|∼O(1 mC/m2) for a 1 μm long nanochannel having embedded quartz layer gate electrodes with gate potential |Vg|∼O(1 V). We believe that critical-sigma would be a crucial parameter for the design and fabrication of state-of-the-art nanodevices/nanosystems intended for augmented fluidic functionalities, for example, efficient solute mixing.

Effect of sinusoidal heated blocks on electroosmotic flow mixing in a microchannel with modified topology

The present study is focused on micromixing enhancement techniques for electroosmotic flows in a modulated microchannel with a modified topology by utilizing heated blocks on the surface of the microchannel. The heated blocks carry higher temperatures as compared to the other portions of the channel wall, resulting in a sharp variation in the temperature of the fluid. The species transport is governed by the Nernst–Planck equation in a modified form by adding a thermo-electrochemical migration term due to the temperature variation in the ions, justifying the electrochemical equilibrium conditions. The fluid considered for the study is non-Newtonian and is governed by a power-law model. The Navier–Stokes equations, along with the thermal energy equation, are simulated numerically in a coupled form utilizing a finite volume-based semi-implicit method for the pressure-linked equation algorithm to interpret the behavior of the electric potential distribution, the external electric field, the flow field, the temperature distribution, and the species concentration, which are the major contributors for the mixing efficiency. The numerically simulated results are varied with the analytical results for the simple electroosmotic flow in the microchannel, indicating that the mixing efficiency can be enhanced by increasing the temperature of the heated blocks. Due to the thermo-electrochemical migration, ions are redistributed along the heated blocks, oscillating the flow velocity by creating vortices, resulting in the mixing enhancement. The effects of the geometrical parameters, the Debye–Hückel parameter, the temperature gradient, the power-law index, and the Nusselt number are elaborated for the effective flow rate and micromixing. The mixing efficiency is found to be optimum for higher temperature gradients and higher power-law indices. The net throughput analysis that combines the geometrical modulation and wall temperature variation will aid in improving the design and fabrication of microfluidic mixers.

Biomimetic micropump: Leveraging a novel propagative rhythmic membrane function

We discuss bioinspired pumping mechanism in a microfluidic configuration, consistent with the newly formulated propagative rhythmic contraction–expansion of a membrane attached to the channel wall. We aptly demonstrate the kinematics of the proposed membrane function and describe the wall profile developed due to the propagative expansion–contraction phases of the actuation cycle. The transport equations governing the flow dynamics are solved analytically in the purview of the lubrication theory. An analysis of the proposed model establishes that the fluidic functionality of a channel equipped with a single elastic membrane that operates following the propagation expansion-contraction modes can produce a unidirectional flow, and acts as a micropump in the process. By depicting the flow velocity, velocity contours, and streamlines patterns in the flow pathway, we discuss and demonstrate the eventual consequence of these flow parameters to the net throughput during both the compression and expansion phases of the process. We establish the efficacy of the novel membrane function by demonstrating augmented net throughput obtained from the proposed configuration. The membrane function developed in this endeavor will provide greater flexibility to the researchers to carry out further research in the field and will make the underlying analysis even easier in systems that utilize electromagnetic fields in the flow system.

Sparse I/Q-joint DNN nonlinear equalization based on progressive pruning for a photonics-aided 256-QAM MMW communication system.

An efficient nonlinear equalizer based on the pruning I/Q-joint deep neural network (DNN) is proposed and experimentally demonstrated to mitigate the nonlinearity in a photonics-assisted millimeter-wave (MMW) system with a high-order 256 quadrature-amplitude-modulation (QAM) format. Experimental findings reveal that implementing pruning on the I/Q-joint DNN can compress the computational overhead by 32% while accommodating 256-QAM E-band MMW transmission for a net throughput of 66.67 Gbps with 20.21% less complexity than the traditional Volterra nonlinear equalizer. Compared with the I/Q dual DNN with the same complexity, a 16% pruning ratio improvement is enabled by a robust pruning I/Q-joint DNN that further deciphers the I/Q relationship.

Prediction of electrodiffusio-osmotic transport of shear-thinning fluids in a nanochannel using artificial neural network

We have numerically investigated the electrodiffusio-osmotic (EDO) transport of non-Newtonian electrolytic solution, governed by an externally applied electric field and concentration difference, in a charged nanochannel connected with two reservoirs. We have examined the EDO transport characteristics by varying electrical, chemical, and rheological parameters. The relative augmentation in net throughput due to EDO transport is compared to the pure electro-osmotic flow and is found to be greater than unity [reaches up to the order of ∼O(103)] for the considered range of concentration difference and flow-behavior index. As shown, the EDO throughput with concentration difference follows an increasing–decreasing trend at the smaller nanochannel height (<10 nm), while exhibiting an increasing trend at the higher nanochannel height (>10 nm). Notably, the net flow for shear-thinning fluid gets fully reversed at higher concentration differences and for a higher value of zeta potential. In the second part of the work, we discuss the use of an artificial neural network (ANN) essentially to predict the net EDO throughput from the nanochannel. The ANN model considered here is of a single-hidden-layer feedforward type. For activation, we used a sigmoid-purelinear transfer function between the layers. Additionally, the Levenberg–Marquardt algorithm is used to perform the backpropagation. To predict the volume flow rate per unit width, we have used four input features: concentration difference, flow-behavior index, nanochannel height, and zeta potential. We have established that an ANN model with eight neurons in the hidden layer accurately predicts the flow rate per unit width with a very small root mean squared error. The inferences of this analysis could be of huge practical importance in designing the state-of-the-art nanodevices/systems intended for offering finer control over the underlying transport.

Ultra-wideband discrete Raman amplifier optimization for single-span S-C-L-band coherent transmission systems.

We experimentally compare the performance of two key ultra-wideband discrete Raman amplifier structures, a cascaded dual-stage structure and an in-parallel dual-band structure, in fully loaded S-C-L band coherent transmission systems over 70 km of single-mode fiber. Our results show that dual-band discrete Raman amplifier with minimized backreflections can effectively avoid unstable random distributed feedback lasing, reduce the noise figure, and therefore improve the transmission performance for signals at shorter wavelengths, versus the cascaded dual-stage structure. The average noise figure for S-band signals is 6.8 dB and 7.2 dB for the dual-band structure and cascaded dual-stage structure, respectively, while the average S-band Q2 factor is similarly improved by 0.6 dB. Moreover, the cascaded dual-stage discrete Raman amplifier requires guard bands around the 1485-nm and 1508-nm pumps as the signal and pump wavelengths overlap, which results in a bandwidth loss of ∼10 nm and reduces the potential net data throughput to 28.6 Tb/s for 30-GBaud DP-16QAM signals. However, the dual-band structure can utilize the bandwidth more effectively, which leads to a higher estimated net data throughput of 31.2 Tb/s.

Propagative-rhythmic membrane contraction modulated efficient micropumping of non-Newtonian fluids

We here discuss a novel bioinspired pumping mechanism of non-Newtonian fluids in a microfluidic configuration, consistent with the propagative rhythmic contraction–expansion of a membrane attached to the wall of the fluidic channel. We consider the Rabinowitsch model to represent the rheology of non-Newtonian fluids. By employing lubrication theory and approximating the underlying flow to be in the creeping regime, the transport equations governing the pumping process are framed pertaining to the chosen setup. The transport equations are then evaluated by employing a well-established perturbation technique. By depicting the flow velocity components, streamline patterns, and velocity contours graphically, we aptly discuss the flow structure developed in the flow pathway and demonstrate the eventual consequence of these flow parameters to the net throughput during both compression and expansion phases of the pumping process. Finally, by demonstrating a phase-space diagram, we also discuss the impact of fluid rheology and membrane kinematics on the pumping capacity. The results obtained from the proposed model establish that the net flow owing to propagative rhythmic membrane contraction strongly relies on exponent parameter M and rheological parameter β. These consequences are expected to be of substantial practical relevance in designing micropumps intended to yield unidirectional flow of the complex fluids with improved efficiency, commonly used in biochemical/biomicrofluidic applications.

Spatially Correlated RIS-Aided CF Massive MIMO Systems With Generalized MR Combining

In this correspondence, we study the uplink ergodic net throughput of a spatially correlated reconfigurable intelligent surface (RIS)-aided cell-free (CF) massive multiple-input multiple-output (MIMO) system over Rayleigh fading channels. We investigate the impact of the generalized maximum ratio (GMR) combining and obtain the closed-form expression for characterizing the uplink net throughput revealing that the GMR can double the system performance compared with the maximum ratio (MR) in our system. Then, we compare the performance and complexity of the MR, GMR, and large-scale fading decoding (LSFD). Moreover, we consider a practical fractional power control to mitigate the inter-user interference. The obtained interesting results show that the system performance decreases with the increasing number of RIS elements. It reveals that efficient interference cancellation processing is needed to cope with severer pilot contamination brought by the large number of RIS elements to improve the system performance. Finally, the accuracy of our derived analytical results has been verified by Monte-Carlo simulations.

5G NOMA Defense Application Environment and Stacked LSTM Network Architectures

In 5G and beyond 5G wireless communication networks, the NOMA scheme is widely considered a major non-orthogonal access technique for improving system capacity and data rates. The main challenges in current NOMA systems are limited channel feedback and the difficulty of integrating it with advanced adaptive coding and modulation algorithms. This study analyses S-LSTM-based DL NOMA receivers in i.i.d. Nakagami-m fading channel circumstances as opposed to previously presented solutions. The LSTM has the advantage of responding dynamically to changing channel conditions. When compared to a typical NOMA system, a typical NOMA system has a 12% lower outage probability, a 39% increase in net throughput, and a maximum SER reduction of 48%. Complex modulated M-ary PSK and M-ary QAM data symbols are employed in D/L NOMA transmission. Classic receivers such as LS and MMSE are outperformed by the S-LSTM-based DL-NOMA receiver. The CP and non-linear clipping noise simulation curves compare the performance of the MMSE and LS receivers with that of the DL NOMA receiver in real-time propagation circumstances. The DL-based detector outperforms the MMSE for SNRs greater than 15 dB because the S-LSTM method is more robust than the clipping noise.

Boundaries control active channel flows

Boundary conditions dictate how fluids, including liquid crystals, flow when pumped through a channel. Can boundary conditions also be used to control internally driven active fluids that generate flows spontaneously? By using numerical simulations and stability analysis we explore how parallel surface anchoring of active agents at the boundaries and substrate drag can be used to rectify coherent flow of an active polar fluid in a 2D channel. Upon increasing activity, a succession of dynamical states is obtained, from laminar flow to vortex arrays to eventual turbulence, that are controlled by the interplay between the hydrodynamic screening length and the extrapolation length quantifying the anchoring strength of the orientational order parameter. We highlight the key role of symmetry in both flow and order and show that coherent laminar flow with net throughput is only possible for weak anchoring and intermediate activity. Our work demonstrates the possibility of controlling the nature and properties of active flows in a channel simply by patterning the confining boundaries.

Influence of viscoelectric effect on diffusioosmotic transport in nanochannel.

We have investigated the role of viscoelectric effect on diffusioosmotic flow (DOF) through a nanochannel connected with two reservoirs. The transport equations governing the flow dynamics are solved numerically using the finite element technique. We have extensively analyzed the variation of induced field due to electric double layer (EDL) phenomenon, relative viscosity as modulated by the viscoelectric effect as well as reservoir's concentration difference, and their eventual impact on the underlying flow characteristics. It is revealed that the induced electric field in the EDL enhances fluid viscosity substantially near the charged wall at a higher concentration. We have shown that neglecting viscoelectric effect in the paradigm of diffusioosmotic transport overestimates the net throughput, particularly at a higher concentration difference. Furthermore, we show that pertaining to chemiosmosis dominated regime, the average flow velocity modifies with the increase in concentration difference up to a critical value. In comparison, the rise in the strength of resistive electroosmotic actuation by the accumulation of anions in the upstream reservoir reduces the average flow velocity at a higher concentration difference. We have reported a reduction in critical concentration with the increase in viscoelectric effect. The inferences of this analysis are deemed pertinent to reveal the bearing of viscoelectric effect as a flow control mechanism pertaining to DOF at nanoscale.

Reconfigurable Intelligent Surface-Assisted Cell-Free Massive MIMO Systems Over Spatially-Correlated Channels

Cell-Free Massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surface (RIS) are two promising technologies for application to beyond-5G networks. This paper considers Cell-Free Massive MIMO systems with the assistance of an RIS for enhancing the system performance under the presence of spatial correlation among the engineered scattering elements of the RIS. Distributed maximum-ratio processing is considered at the access points (APs). We introduce an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">aggregated channel</i> estimation approach that provides sufficient information for data processing with the main benefit of reducing the overhead required for channel estimation. The considered system is studied by using asymptotic analysis which lets the number of APs and/or the number of RIS elements grow large. A lower bound for the channel capacity is obtained for a finite number of APs and engineered scattering elements of the RIS, and closed-form expressions for the uplink and downlink ergodic net throughput are formulated in terms of only the channel statistics. Based on the obtained analytical frameworks, we unveil the impact of channel correlation, the number of RIS elements, and the pilot contamination on the net throughput of each user. In addition, a simple control scheme for optimizing the configuration of the engineered scattering elements of the RIS is proposed, which is shown to increase the channel estimation quality, and, hence, the system performance. Numerical results demonstrate the effectiveness of the proposed system design and performance analysis. In particular, the performance benefits of using RISs in Cell-Free Massive MIMO systems are confirmed, especially if the direct links between the APs and the users are of insufficient quality with high probability.

An advanced coal-based zero-emission polygeneration system using water-gas shift reaction and syngas recycle to achieve different methanol and electricity distributions

To achieve different products distributions and improve energy conversion performance for the coal utilization with zero carbon emission, an advanced polygeneration system incorporating the methanol synthesis and Allam power cycle (an oxy-combustion, direct-fired supercritical carbon dioxide Brayton cycle) is proposed. The water-gas shift reaction is combined with the syngas recycle to obtain different products (i.e., methanol and electric power) distributions. Moreover, different from the conventional coal-to-methanol process, the carbon dioxide generated by the shift reaction is not separated from the shifted syngas but enters the Allam cycle, which can be simply split from the cooled exhaust without additional energy penalty. In other words, the carbon dioxide separation energy penalty of the methanol production is reduced to zero by connecting the coal-to-methanol process and the Allam cycle. In this study, the material flow and energy conversion characteristics of the proposed polygeneration system is revealed. The influences of the carbon monoxide shift ratio and syngas recycle ratio on the methanol productivity, net electric power throughput and the corresponding fuel saving ratio are comprehensively analyzed. The optimum strategy of the combination of the water-gas shift reaction and syngas recycle is obtained with the methanol/electricity energy ratio ranging from 0.75 to 2.71; and the highest fuel saving ratio soars to 5.79% as the methanol/electricity ratio is 1.55 at the carbon monoxide shift ratio of 0.17 and the syngas recycle ratio of 0.8.

Combined electromechanically driven pulsating flow of nonlinear viscoelastic fluids in narrow confinements.

Controlled microscale transport is at the core of many scientific and technological advancements, including medical diagnostics, separation of biomolecules, etc., and often involves complex fluids. One of the challenges in this regard is to actuate flows at small scales in an energy efficient manner, given the strong viscous forces opposing fluid motion. We try to address this issue here by probing a combined time-periodic pressure and electrokinetically driven flow of a viscoelastic fluid obeying the simplified linear Phan-Thien-Tanner model, using numerical as well as asymptotic tools, in view of the fact that oscillatory fields are less energy intensive. We establish that the interplay between oscillatory electrical and mechanical forces can lead to complex temporal mass flow rate variations with short-term bursts and peaks in the flow rate. We further demonstrate that an oscillatory pressure gradient or an electric field, in tandem with another steady actuating force can indeed change the net throughput significantly-a paradigm that is not realized in Newtonian or other simpler polymeric liquids. Our results reveal that the extent of augmentation in the flow rate strongly depends on the frequency of the imposed actuating forces along with their waveforms. We also evaluate the streaming potential resulting from an oscillatory pressure-driven flow and illustrate that akin to the volume throughput, the streaming potential also shows complex temporal variations, while its time average gets augmented in the presence of a time-periodic pressure gradient in a nonlinear viscoelastic medium.

In Silico Structure-Based Approach for Group Efficiency Estimation in Fragment-Based Drug Design Using Evaluation of Fragment Contributions.

The notion of a contribution of a specific group in an organic molecule’s property and/or activity is both common in our thinking and is still not strictly correct due to the inherent non-additivity of free energy with respect to molecular fragments composing a molecule. The fragment- based drug discovery (FBDD) approach has proven to be fruitful in addressing the above notions. The main difficulty of the FBDD, however, is in its reliance on the low throughput and expensive experimental means of determining the fragment-sized molecules binding. In this article we propose a way to enhance the throughput and availability of the FBDD methods by judiciously using an in silico means of assessing the contribution to ligand-receptor binding energy of fragments of a molecule under question using a previously developed in silico Reverse Fragment Based Drug Discovery (R-FBDD) approach. It has been shown that the proposed structure-based drug discovery (SBDD) type of approach fills in the vacant niche among the existing in silico approaches, which mainly stem from the ligand-based drug discovery (LBDD) counterparts. In order to illustrate the applicability of the approach, our work retrospectively repeats the findings of the use case of an FBDD hit-to-lead project devoted to the experimentally based determination of additive group efficiency (GE)—an analog of ligand efficiency (LE) for a group in the molecule—using the Free-Wilson (FW) decomposition. It is shown that in using our in silico approach to evaluate fragment contributions of a ligand and to estimate GE one can arrive at similar decisions as those made using the experimentally determined activity-based FW decomposition. It is also shown that the approach is rather robust to the choice of the scoring function, provided the latter demonstrates a decent scoring power. We argue that the proposed approach of in silico assessment of GE has a wider applicability domain and expect that it will be widely applicable to enhance the net throughput of drug discovery based on the FBDD paradigm.