Channel Parameterization Research Articles

Correlated and Superposed Signal Decomposition for Multipath Channel Parameterization

Correlated and Superposed Signal Decomposition for Multipath Channel Parameterization

Evaluation of a new observationally based channel parameterization for the National Water Model

Abstract. Accurate representation of channel properties is important for forecasting in hydrologic models, as it affects the height, celerity, and attenuation of flood waves. Yet, considerable uncertainty in the parameterization of channel geometry and hydraulic roughness (Manning's n) exists within the NOAA National Water Model (NWM), due largely to data scarcity; only ∼2800 out of the 2.7×106 river reach segments in the NWM have measured channel properties. In this study, we seek to improve channel representativeness by updating channel geometry and roughness parameters using a large, previously unpublished hydraulic geometry (HyG) dataset of approximately 48 000 gauges. We begin with a Sobol' sensitivity analysis of channel geometry parameters for 12 small, semi-natural basins across the continental U.S., which reveals an outsized sensitivity of simulated flow to Manning's n relative to channel geometry parameters. We then develop and evaluate a set of regression-based regionalizations of channel parameters estimated using the HyG dataset. Finally, we compare the model output generated from updated channel parameter sets to observations and the current NWM v2.1 parameterization. We find that while the NWM land surface model holds the most influence over flow, given its control over total volume, the updated channel parameterization leads to improvements in simulated streamflow performance relative to observed flows, with a statistically significant mean R2 increase from 0.479 to 0.494 across approximately 7400 gauge locations. HyG-based channel geometry and roughness provide a substantial overall improvement in channel representation over the default parameterization, updating the previous set value for most reaches of Manning's n=0.060 to a new range between 0.006 and 0.537 (median 0.077). This research provides a more representative, observationally based channel parameter dataset for the NWM routing module and new insight into the influence of the routing module within the overall modeling framework.

Hierarchical Data Decision Aided 2-Source BPSK H-MAC Channel Phase Estimator with Feed-Back Gradient Solver for WPNC Networks and Its Equivalent Model

This paper focuses on the channel state estimation (CSE) problem in parametrized Hierarchical MAC (H-MAC) stage in Wireless Physical Layer Network Coding (WPNC) networks with Hierarchical Decode and Forward (HDF) relay strategy. We derive a non-pilot based H-MAC channel phase estimator for 2 BPSK alphabet sources. The CSE is aided only by the knowledge of H-data decisions. At HDF relay, there is no information on individual source symbols available. The estimator is obtained by a marginalization over the hierarchical dispersion. The estimator uses a gradient additive update solver and the indicator function (gradient) is derived in exact closed form and in approximations for low and high SNR. We analyze the properties of the equivalent solver model, particularly the equivalent gradient detector characteristics and its main stable domain properties, and also the detector gain and equivalent noise properties under a variety of channel parameterization scenarios.

Testing the skill of numerical hydraulic modeling to simulate spatiotemporal flooding patterns in the Logone floodplain, Cameroon

Summary Recent innovations in hydraulic modeling have enabled global simulation of rivers, including simulation of their coupled wetlands and floodplains. Accurate simulations of floodplains using these approaches may imply tremendous advances in global hydrologic studies and in biogeochemical cycling. One such innovation is to explicitly treat sub-grid channels within two-dimensional models, given only remotely sensed data in areas with limited data availability. However, predicting inundated area in floodplains using a sub-grid model has not been rigorously validated. In this study, we applied the LISFLOOD-FP hydraulic model using a sub-grid channel parameterization to simulate inundation dynamics on the Logone River floodplain, in northern Cameroon, from 2001 to 2007. Our goal was to determine whether floodplain dynamics could be simulated with sufficient accuracy to understand human and natural contributions to current and future inundation patterns. Model inputs in this data-sparse region include in situ river discharge, satellite-derived rainfall, and the shuttle radar topography mission (SRTM) floodplain elevation. We found that the model accurately simulated total floodplain inundation, with a Pearson correlation coefficient greater than 0.9, and RMSE less than 700 km 2 , compared to peak inundation greater than 6000 km 2 . Predicted discharge downstream of the floodplain matched measurements (Nash–Sutcliffe efficiency of 0.81), and indicated that net flow from the channel to the floodplain was modeled accurately. However, the spatial pattern of inundation was not well simulated, apparently due to uncertainties in SRTM elevations. We evaluated model results at 250, 500 and 1000-m spatial resolutions, and found that results are insensitive to spatial resolution. We also compared the model output against results from a run of LISFLOOD-FP in which the sub-grid channel parameterization was disabled, finding that the sub-grid parameterization simulated more realistic dynamics. These results suggest that analysis of global inundation is feasible using a sub-grid model, but that spatial patterns at sub-kilometer resolutions still need to be adequately predicted.

The fan of influence of streams and channel feedbacks to simulated land surface water and carbon dynamics

AbstractLarge‐scale land models assume unidirectional land‐to‐river hydrological interactions, without considering feedbacks between channels and land. Using a tested, physically based model with explicit multiway interactions between overland, channel, wetland, and groundwater flows, we assessed how the representation and properties of channels influence simulated land surface hydrologic, biogeochemical, and ecosystem dynamics. A zone near the channels where various fluxes and states are significantly influenced by the channels, referred to as the fan of influence (FoI) of channels, has been identified. We elucidated two mechanisms inducing the model‐derived FoI: the base flow mechanism, in which incised, gaining streams lower the water table and induce more base flow, and the relatively more efficient conveyance of the channel network compared to overland flow. We systematically varied drainage density and grid resolution to quantify the size of the FoI, which is found to span a large fraction of the watershed (25–50%) for hydrologic variables including depth to water table and recharge, etc. The FoI is more pronounced with low‐resolution simulations but remains noticeable in hyperresolution (25 m) subbasin simulations. The FoI and the channel influence on basin‐average fluxes are also similar in simulations with alternative parameter sets. We found that high‐order, entrenched streams cause larger FoI. In addition, removing the simulated channels has disproportionally large influence on modeled wetland areas and inundation duration, which has implications for coupled biogeochemical or ecological modeling. Our results suggest that explicit channel representation provides important feedbacks to land surface dynamics which should be considered in meso or large‐scale simulations. Since grid refinement incurs prohibitive computational cost, subgrid channel parameterization has advantages in efficiency over grid‐based representations that do not distinguish between overland flow and channel flow.

Joint maximum likelihood time-delay estimation for LTE positioning in multipath channels

This paper presents a joint time-delay and channel estimator to assess the achievable positioning performance of the Long Term Evolution (LTE) system in multipath channels. LTE is a promising technology for localization in urban and indoor scenarios, but its performance is degraded due to the effect of multipath. In those challenging environments, LTE pilot signals are of special interest because they can be used to estimate the multipath channel and counteract its effect. For this purpose, a channel estimation model based on equi-spaced taps is combined with the time-delay estimation, leading to a low-complexity estimator. This model is enhanced with a novel channel parameterization able to characterize close-in multipath, by introducing an arbitrary tap with variable position between the first two equi-spaced taps. This new hybrid approach is adopted in the joint maximum likelihood (JML) time-delay estimator to improve the ranging performance in the presence of short-delay multipath. The JML estimator is then compared with the conventional correlation-based estimator in usual LTE conditions. These conditions are characterized by the extended typical urban (ETU) multipath channel model, additive white Gaussian noise (AWGN) and LTE signal bandwidths equal to 1.4, 5 and 10 MHz. The resulting time-delay estimation performance is assessed by computing the cumulative density function (CDF) of the errors in the absence of noise and the root-mean-square error (RMSE) and bias for signal-to-noise ratio (SNR) values between −20 and 30 dB.

Estimation of the Number of Clusters in Multipath Radio Channel Data Sets

This communication deals with the grouping of the multipath radio channel components. The estimation of the number of clusters that a given data set exhibits is an important step in channel modeling and parameterization. We present a performance assessment of several cluster validity indices using Monte Carlo simulations. Synthetic channels were generated by means of the extended Saleh-Valenzuela model and used as input to a clustering algorithm which outputs several solutions with different number of clusters. The cluster validity indices allow the selection of the best solution. Finally, an example is presented where the best performing indices were applied to an experimental data set.

Parameterizing both path amplitude and delay variations of underwater acoustic channels for block decoding of orthogonal frequency division multiplexing

There are no commonly-agreed mathematical models for the input-output relationship of underwater acoustic channels. For each path in a time-varying multipath channel within a short period of time (e.g., one short data block), this paper proposes to use one polynomial to approximate the amplitude variation and another polynomial up to the first order to approximate the delay variation within a block duration. Under such a channel parameterization, the discrete-time channel input- output relationship tailored to zero-padded orthogonal-frequency-division-multiplexing (OFDM) transmissions is then derived, based on which an OFDM receiver is validated using experimental data collected during the 2008 Surface Processes and Acoustic Communications Experiment. For channels with a short coherence time, the numerical results show that incorporating both the amplitude and delay variations improves the system performance.

Sediment Measurement and Transport Modeling: Impact of Riparian and Filter Strip Buffers

Well-calibrated models are cost-effective tools to quantify environmental benefits of conservation practices, but lack of data for parameterization and evaluation remains a weakness to modeling. Research was conducted in southwestern Oklahoma within the Cobb Creek subwatershed (CCSW) to develop cost-effective methods to collect stream channel parameterization and evaluation data for modeling in watersheds with sparse data. Specifically, (i) simple stream channel observations obtained by rapid geomorphic assessment (RGA) were used to parameterize the Soil and Water Assessment Tool (SWAT) model stream channel variables before calibrating SWAT for streamflow and sediment, and (ii) average annual reservoir sedimentation rate, measured at the Crowder Lake using the acoustic profiling system (APS), was used to cross-check Crowder Lake sediment accumulation rate simulated by SWAT. Additionally, the calibrated and cross-checked SWAT model was used to simulate impacts of riparian forest buffer (RF) and bermudagrass [ (L.) Pers.] filter strip buffer (BFS) on sediment yield and concentration in the CCSW. The measured average annual sedimentation rate was between 1.7 and 3.5 t ha yr compared with simulated sediment rate of 2.4 t ha yr Application of BFS across cropped fields resulted in a 72% reduction of sediment delivery to the stream, while the RF and the combined RF and BFS reduced the suspended sediment concentration at the CCSW outlet by 68 and 73%, respectively. Effective riparian practices have potential to increase reservoir life. These results indicate promise for using the RGA and APS methods to obtain data to improve water quality simulations in ungauged watersheds.

Model AVSWAT apropos of simulating non-point source pollution in Taihu lake basin

Accelerated eutrophication and nutrient loads in the lakes are of major concern for human health and environment. This study was undertaken for modeling the non-point source pollution of Taihu lake basin in eastern China. The SWAT model having an interface in ArcView GIS was employed. Model sensitive parameters related to hydrology and water quality were obtained by sensitivity analysis, and then calibrated and validated by comparing model predictions with field data. The GIS showed good potential for parameterization of hill-slopes, channels, and representative slope profiles for SWAT model simulations. In a monthly and daily time step, the model's Nash-Sutcliffe coefficient ( E) and the coefficient of determination ( R 2) indicated that values of simulated runoff, NH 4 +–N and total phosphorus were acceptably closer to the measured data. Surface water parameters especially CN, Soil-AWC and ESCO were the most sensitive and had more recognition in the model. It is concluded that runoff carrying N and P nutrients from chemical fertilizer inputs in agricultural areas is the major contributor to NPSP in the lake basin. So, decrease in excessive use of N and P fertilizers and their synergism with organic manures is recommended that would significantly reduce nutrient pollution in the lake ecosystem.

Performance Bounds for MIMO-OFDM Channel Estimation

The performance of a mobile multiple-input multiple-output orthogonal-frequency-division multiplexing (MIMO-OFDM) system depends on the ability of the system to accurately account for the effects of the frequency-selective time-varying channel at every symbol time and at every frequency subcarrier. Typically, pilot symbols are strategically placed at various times over various subcarriers in order to calculate sample channel estimates, and then these estimates are interpolated or extrapolated forward to provide channel estimates where no pilot data was transmitted. Performance is highly dependent on the distribution of the pilots with respect to the coherence time and coherence bandwidth of the channel, and on the chosen channel parameterization. In this paper, a vector formulation of the Cramer-Rao bound (CRB) for biased estimators and for functions of parameters is used to derive a lower bound on the channel estimation and prediction error of such a system. Numerical calculations using the bound demonstrate the benefits of multiple antennas for channel estimation and prediction and illustrate the impact of modeling errors on estimation performance when using channel models based on calibrated arrays.

Time-Frequency Channel Parameterization with Application to Multi-Mode Receivers

There is a trend towards flexible radios which are able to cope with a range of wireless communication standards. For the integrated processing of widely different signals—including single-carrier, multicarrier, and spread-spectrum signals—monolithic baseband receivers need universal formats for the signal representation and channel description. We consider a reconfigurable receiver architecture building on concepts from time-frequency (TF) signal analysis. The core elements are TF signal representations in form of a Gabor expansion along with a compatible parameterization of time-variant channels. While applicable to arbitrary signal types, the TF channel parameterization offers similar advantages as the frequency domain channel description employed by orthogonal frequency-division multiplexing receivers. The freedom in the choice of the underlying analysis window function and the scalability in time and frequency facilitate the handling of diverse signal types as well as the adaptation to radio channels with different delay and Doppler spreads. Optimized window shapes limit the inherent model error, as demonstrated using the example of direct-sequence spread-spectrum signaling.

Spatio-diversity gain of a system-dependent wideband directional channel

Estimations of spatio-diversity gain (SDIV) in the wideband directional channel suffer from imprecise modeling of multipath angular spread (AS). Using previously published measurements and a synthetic array and channel parameterization, we show that AS exhibits dependence on both line-source distribution and operating frequency. As a result, SDIV is calculated through the integration of a continuous density function defined on the entire signal space. Using this methodology, we show through numerical examples that the conventional diversity estimate for directional systems may lead to systematic prediction error of the achievable diversity gain.

Reduced-rank channel estimation for time-slotted mobile communication systems

In time-slotted mobile communication systems with antenna array at the receiver, the space-time channel matrix is conventionally estimated by transmitting pilot symbols within each data packet (or block). This work is focused on reduced rank (RR) estimation methods that exploit the low-rank property of the space-time channel matrix to estimate single or multiple user channels from the observation of single or multiple training blocks. The proposed RR methods allow to improve the estimate accuracy by reducing the set of unknown parameters (rank reduction) and extending the training set (multiblock processing). The maximum likelihood RR estimate is obtained as the projection of the prewhitened full-rank (FR) estimate onto the spatial or temporal signal subspace. The paper shows that, even for time varying channels, these subspaces can be considered to be slowly varying, and therefore, they can be estimated with increased accuracy by properly exploiting training signals from several blocks. The analytical and numerical performance in terms of mean square error for the RR estimate shows that the main advantage of the proposed method with respect to the conventional FR one can be ascribed to the reduced complexity of the channel parameterization.

Spatio-diversity gain of a system-dependent wideband directional channel

Estimations of spatio-diversity gain (SDIV) in the wideband directional channel suffer from imprecise modeling of multipath angular spread (AS). Using previously published measurements and a synthetic array and channel parameterization, we show that AS exhibits dependence on both line-source distribution and operating frequency. As a result, SDIV is calculated through the integration of a continuous density function defined on the entire signal space. Using this methodology, we show through numerical examples that the conventional diversity estimate for directional systems may lead to systematic prediction error of the achievable diversity gain.

MIMO Wireless Communication Channel Phenomenology

Wireless communication using multiple-input multiple-output (MIMO) systems enables increased spectral efficiency and link reliability for a given total transmit power. Increased capacity is achieved by introducing additional spatial channels which are exploited using space-time coding. The spatial diversity improves the link reliability by reducing the adverse effects of link fading and shadowing. The choice of coding and the resulting performance improvement are dependent upon the channel phenomenology. In this paper, experimental channel-probing estimates are reported for outdoor environments near the personal communication services frequency allocation (1790 MHz). A simple channel parameterization is introduced. Channel distance metrics are introduced. Because the bandwidth of the channel-probing signal (1.3 MHz) is sufficient to resolve some delays in outdoor environments, frequency-selective fading is also investigated. Channel complexity and channel stationarity are investigated. Complexity is associated with channel-matrix singular value distributions. Stationarity is associated with the stability of channel singular value and singular vector structure over time.