Power Domain Research Articles

Enhancement of outage probability for down link cooperative non-orthogonal multiple access in fifth-generation network

<span lang="EN-US">Future wireless networks are expected to face several issues, but cooperative non-orthogonal multiple access (C-NOMA) is a promising technology that could help solve them by providing unprecedented levels of connection and system capacity. In this regard, the influence of the power location coefficient (PLC) for remote users adopting multiple-input-multiple-output (MIMO) and massive MIMO has been explored to provide effective performance. The goal of this study is to design fifth-generation (5G) downlink (DL) NOMA power domain (PD) networks with a variety of distances and PLCs for remote users and then to compare their outage probability (OP) performance versus signal to noise ratio (SNR). As a novel approach to improving OP performance rate and mitigating the influence of the PLC for remote users, DL C-NOMA is combined with 16×16, 32×23, and 64×64 MIMO and 128×128, 256×256, and 512×512 massive MIMO. The results were obtained that the 64×64 MIMO improves the OP for the remote user by 65.0E-03, while the 512×512 massive MIMO achieved an improvement that reaches 1.0E-06 for the PLC of 0.8 at SNR of 14 dB. The Rayleigh fading channels and MATLAB simulation tools were utilized to carry out the study work.</span>

Intelligent Resource Allocation in Backscatter-NOMA Networks: A Soft Actor Critic Framework

With the use of power domain non-orthogonal multiple access (NOMA) and backscatter communication (BAC), future sixth-generation ultra massive machine-type communications networks are expected to connect large-scale internet of things (IoT) devices. However, due to NOMA co-channel interference, the power allocation to large-scale IoT devices becomes critical. The existing convex optimization-based solutions are highly complex, and therefore it is difficult to find the optimal solution to the resource allocation problem in a highly dynamic environment. To alleviate this problem, this work develops an efficient model-free BAC approach with a NOMA system to assist the base station with complex resource scheduling tasks in a dynamic BAC-NOMA IoT network. The objective is to increase the sum rate of uplink backscatter devices. More specifically, we jointly optimize the transmit power of downlink IoT users and the reflection coefficient of uplink backscatter devices using a reinforcement learning algorithm, namely, the soft-actor critic (SAC) algorithm. With the advantage of entropy regularization, the SAC agent learns to explore and exploit the dynamic BAC-NOMA network efficiently. The proposed algorithm ensures the quality of service (QoS) requirements of downlink users while enhancing the sum rate of uplink backscatter devices. Numerical results reveal the superiority of the proposed algorithm over the conventional optimization (benchmark) approach in terms of the average sum rate of uplink backscatter devices. We show that the network with multiple downlink users obtained a higher reward with respect to a large number of iterations compared to episodes with a lower number of iterations. Moreover, the proposed algorithm outperforms the benchmark scheme and BAC with orthogonal multiple access in terms of the average sum rate with the different number of backscatter devices. Additionally, we show that our proposed algorithm enhances sum rate efficiency with respect to different self-interference coefficients and different noise levels. Finally, we evaluate and show the sum rate efficiency of the proposed algorithm with different QoS requirements and cell radii.

Next generation PON architecture using PD-NOMA employing OAM and WDM multiplexing

In this paper, we propose and experimentally demonstrate the efficacy of a next-generation passive optical network (PON) architecture for free space optical link, which utilizes power domain (PD) non-orthogonal multiple access (NOMA) along with simultaneous orbital angular momentum (OAM) mode and wavelength-division multiplexing (WDM) techniques. In this proposed architecture, many optical network units (ONUs) are accommodated by clustering them based on their power budgets and their data streams are allocated with different powers accordingly. The clustered ONUs are served with multiple OAM modes over multiple wavelengths to maintain high capacity, low latency, and increased reliability. As a proof-of-principle experimental demonstration of the proposed architecture, we have experimentally emulated two ONU clusters having a power ratio of (near:far)−3.17dB for implementing the PD-NOMA system for downlink. Each ONU cluster uses three 50 GHz spaced WDM channels, where each WDM channel carries two multiplexed OAM modes having opposite topological charge (l=±1 and ±2) values. Each cluster’s six ONUs is delivered with a 10 Gbps On-Off Keying (OOK) signal. We have demonstrated that all users can achieve a pre-forward error correction (pre-FEC) bit error rate (BER) below the 7% overhead-FEC (OH-FEC) BER limit of 3.8×10−3. We have also measured the x-talk due to WDM and mode multiplexing, and it has been revealed that the main contribution to the power penalty (relative to the no cross-talk condition) comes from OAM mode cross-talk.

CVT on-line error measurement hybrid-driven by domain knowledge and Stacking Model

The performance of Capacitive Voltage Transformer (CVT) degrades over time, making measurement error monitoring a research hotspot in the field of smart grid. At present, these are several challenges such as complex data features, a lack of criteria for selecting optimal measurement models, and low precision. CVT measurement errors can be classified into ideal error and additional one. The former is typically evaluated via mutual information and redundancy within the topology-level transformer group. Considering that a single model cannot process the time series, strong randomness and nonlinearity of the additional error, the Stacking model is selected. Based on the principle of heterogeneity and high-quality, correlation coefficient and feature contribution degree, Random Forest, eXtreme Gradient Boosting, Ridge Regression, K Nearest Neighbors, Support Vector Regression, and Long Short-Term Memory are chosen as base learners through correlation and feature contribution analysis; while extra-trees with strong generalization and robustness is chosen as the meta learner. To improve the measurement precision, the attention-like mechanism is used to scale time and accuracy weights. Finally, according to the power domain knowledge, a linear superposition model is developed to fuse the ideal and additional errors, and thus realize online error measurement for CVTs. The experimental results indicate that the improved Stacking model outperforms mainstream measurement models by an average reduction of 59.47%, and 52.58% in the root mean squared error and the mean absolute error with the best R2 closest to 1. It not only effectively improves the accuracy but also meets speed requirement for online error measurement.

Satisfying strict deadlines for cellular Internet of Things through hybrid multiple access

AbstractLatency‐constrained aspects of cellular Internet of Things (IoT) applications rely on Ultra‐Reliable and Low Latency Communications (URLLC), which highlight research on satisfying strict deadlines. In this study, we address the problem of latency‐constrained communications with strict deadlines under average power constraint using Hybrid Multiple Access (MA), which consists of both Orthogonal MA (OMA) and power domain Non‐Orthogonal MA (NOMA) as transmission scheme options. We aim to maximize the timely throughput, which represents the average number of successfully transmitted packets before deadline expiration, where expired packets are dropped from the buffer. We use Lyapunov stochastic optimization methods to develop a dynamic power assignment algorithm for minimizing the packet drop rate while satisfying time average power constraints. Moreover, we propose a flexible packet dropping mechanism called Early Packet Dropping (EPD) to detect likely to become expired packets and drop them immediately. Numerical results show that Hybrid MA improves the timely throughput compared to conventional OMA by up to and on average by more than . With EPD, these timely throughput gains improve to and , respectively.

At the intersection of science, technology, engineering, and mathematics and business management in Canadian higher education: An intentional equity, diversity, and inclusion framework

AbstractIn this study, the authors address the persistent discrimination cis women face in the Canadian science, technology, engineering and mathematics (STEM) higher education context. Pulling on the notion of interrelationships that cross educational faculty boundaries and on intersectionality scholarship to unsettle the structural and disciplinary domains of power, the authors ask, “How can business education and STEM education work together with respect to social considerations, such as gender/race/ethnicity/etc., and social equity and inclusivity, within the Canadian higher education system?” This study aims to build on these interrelationships among diverse, complex individuals who participated in a graduate‐level STEM and business management summer institute to provide an evidence‐based and intentional equity, diversity and inclusion (EDI) framework for STEM higher education contexts. Using a mixed‐methods approach, which saw data collection via a survey instrument and semi‐structured interviews, the subsequent quantitative analysis points to expanding interrelationships to broader areas beyond STEM and business management programs. The close reading of the collected qualitative data, via antenarrative spirals, elevates the participants' complexities beyond focusing “just” on their intersecting identities to looking at their perceptions of STEM fields, the order that ensues and the potential for the undoing of that order. The findings, results, and analyses of these collected data led to an intentional EDI framework, the main contribution of this study, constructed into three main pillars represented by the figure of a tree: the foundational elements (roots) built on individuals' complexities and experiences of Othering, the interrelationships (trunk) possible across various educational and professional dimensions, and a call to structural change initiatives (branches) with the possibility for growth in other areas. This work then contributes to not only filling a significant literature gap and building awareness regarding EDI concerns in STEM contexts via active interrelationship‐building activities but also to unsettling the structural and disciplinary domains of power by embracing a holistic strategy to address systemic discriminatory practices in the Canadian STEM higher education context.

Channel Measurement and Ray-Tracing Simulation for 77 GHz Automotive Radar

Millimeter-wave automotive radar is essential for realizing autonomous driving. Realistic channel model and simulation are important for system and sensing algorithm design. This work introduces channel measurements and ray-tracing (RT) channel simulations for frequency modulated continuous wave (FMCW) automotive mmWave radar. The 77 GHz channel measurements in an urban crossroads environment are presented. The dominant echoes (multi-path components) of the measurement are detected and matched with corresponding objects for each frame. A measurement-based electromagnetic (EM) parameter estimation method is proposed to find the optimal parameter set that minimizes the error of simulated radar cross section (RCS). As a result, the issue of lacking reliable EM material parameters for RT simulation at 77 GHz frequency band is tackled. Simulation results are validated in power, range, velocity, and angle domains with the provided EM parameter set. Extending validated RT simulations in similar environments with various configurations allows more reliable channels for rigorous testing without the limitation of channel measurement.

NON-ORTHOGONAL MULTIPLE ACCESS SCHEMES SURVEY: AN OVERVIEW OF NON-ORTHOGONAL MULTIPLE ACCESS TECHNIQUES

Non-Orthogonal Multiple Access (NOMA) is a promising technology that can significantly improve the performance of wireless communication systems, especially in applications with a high number of users and limited spectral resources. NOMA enables simultaneous transmission and reception of multiple signals at the same time and frequency resources. NOMA can be implemented using different methods, including Power Domain NOMA (PD-NOMA) and Code Domain NOMA (CD-NOMA). The implementation of NOMA requires advanced signal processing techniques and can be challenging in some scenarios. However, with the advancement of technology, NOMA is becoming more practical and is expected to play a significant role in the future of wireless communication systems. This paper will discuss what NOMA and NOMA schemes are. These schemes will be compared in terms of their benefits and drawbacks, and it will be explained which one performs better.

Performance Enhancement of Cooperative MIMO-NOMA Systems Over Sub-6 GHz and mmWave Bands

In this paper, two radio links with different frequency bands are considered for base stations (BS) serving users via decode-and-forward (DF) cooperative relays. Backhaul and access links are proposed with sub-6 GHz and millimeter wave (mmWave) bands, respectively. Non-orthogonal multiple access (NOMA) is employed in the backhaul link to simultaneously transmit a superposed signal in the power domain, using the same band. The superposed signals, containing two signals that differ in terms of power allocation factors (PAFs), are designed for two selected DF relays in the BS. The two relays are chosen from several relays to be serviced by the BS based on a pairing algorithm that depends on different users’ circumstances. The furthest DF relay detects the incoming NOMA signal directly, while the nearest one applies successive interference cancellation (SIC) before extracting its signal. Each DF relay forwards the detected signals toward their intended users over mmWave channels. Three performance metrics are utilized to evaluate the system’s performance: outage probability, achievable throughput, and bit error rate. Comparisons between two mmWave bands in the access link (28 and 73 GHz) are made to demonstrate the superiority of the 28 GHz band in terms of the three performance-related metrics.

An Analysis of Key Actor Networks for Scale-Up Strategies for Childhood Obesity Prevention and the Care of Children with Obesity in Brazil

BackgroundEffective scale-up of multisectoral strategies aimed to prevent and treat childhood obesity has been a challenge in Brazil, the largest country in Latin America. Implementation Science methods, such as Net-Map, can identify key actors and opinion leaders (OLs) to advance the implementation and promote sustainability. ObjectivesThis study aimed to analyze power relations between key actors and OLs who influence the scale-up of Brazilian strategies for childhood obesity at the federal and state/municipal (local) levels. MethodsA mixed method study, applying the Net-Map method, collected data through virtual workshops with federal and local level stakeholders. The Net-Map included key actors mapping, power mapping, and identification of OLs. Four domains of power were analyzed: command, funding, technical assistance, and dissemination. Network cohesion and centrality measures were calculated. A qualitative analysis was conducted to qualify power relations according to ∗ gears for a successful scale-up (i.e., coordination, goals, and monitoring; advocacy; political will; legislation and policy; funding and resources; training; program delivery; communication; and research and technical cooperation). ResultsA total of 121 federal key actors and 63 local key actors were identified across networks, of which 62 and 28 were identified as OLs, respectively. Whereas the command domain of power had the highest number of key actors, the funding domain had the least. The health sector executive branch emerged as an OL across all domains of power. ConclusionsBarriers that threatened successful scale-up include the lack of coordination between domains of power, missing leadership within key actors, and lack of mechanisms to manage conflict of interest. Governance strategies to enhance multisectoral coordination and communication are needed to effectively scale-up and sustain childhood obesity strategies in Brazil.

Adaptive Clustering of Users in Power Domain NOMA.

By enabling multiple non-orthogonal transmissions, power domain non-orthogonal multiple access (PD-NOMA) potentially increases a system's spectral efficiency. This technique can become an alternative for future generations of wireless communication networks. The efficiency of this method fundamentally depends on two previous processing steps: an appropriate grouping of users (transmission candidates) as a function of the channel gains and the choice of power levels that will be used to transmit each signal. Thus far, the solutions presented in the literature to address the problems of user clustering and power allocation do not consider the dynamics of communication systems, i.e., the temporal variation in the number of users and the channel conditions. In order to consider these dynamic characteristics in the clustering of users in NOMA systems, this work proposes a new clustering technique based on a modification of the DenStream evolutionary algorithm, chosen for its evolutionary capacity, noise robustness and online processing. We evaluated the performance of the proposed clustering technique considering, for simplicity, the use of an already widely known power allocation strategy called improved fractional strategy power allocation (IFSPA). The results show that the proposed clustering technique can follow the system dynamics, clustering all users and favoring the uniformity of the transmission rate between the clusters. Compared to orthogonal multiple access (OMA) systems, the proposed model's gain was approximately 10%, obtained on a challenging communication scenario for NOMA systems since the channel model adopted does not favor a large difference in the channel gains between users.

Enabling Network Power Savings in 5G-Advanced and Beyond

Energy consumption is a critical concern for the 5G mobile operators. 5G NR network may have increased energy consumption compared to its predecessors as it aims to support a plethora of services demanding diverse QoS constraints and requiring deployment of radios at different frequency layers with potentially wider bandwidth and more antennas. Moreover, it is important for the operators to keep the operational expenses and carbon emissions as low as possible as well. At 3GPP, UE power saving has mainly been the focus from Rel 15 till Rel 17 and in Rel 18, a new study item has been introduced to investigate different network power saving techniques. In this paper, we first discuss why 5G NR poses unique challenges for energy consumption with respect to its predecessors. We aim to explore different potential techniques for network power savings via resource adaptation in time, frequency, spatial, and power domain. We also investigate power consumption based on energy consumption model adopted by 3GPP and provide energy efficiency - throughput trade-off analysis to identify which domain has the highest potential for power savings.

SCMA-Enabled Multi-Cell Edge Computing Networks: Design and Optimization

Multi-access edge computing (MEC) is regarded as a promising approach for providing resource-constrained mobile devices with computing resources through task offloading. Sparse code multiple access (SCMA) is a code-domain non-orthogonal multiple access (NOMA) scheme that can meet the demands of multi-cell MEC networks for high data transmission rates and massive connections. In this paper, we propose an optimization framework for SCMA-enabled multi-cell MEC networks. The joint resource allocation and computation offloading problem is formulated to minimize the system cost, which is defined as the weighted energy cost and latency. Due to the nonconvexity of the proposed optimization problem induced by the coupled optimization variables, we first propose an algorithm based on the block coordinate descent (BCD) method to iteratively optimize the transmit power and edge computing resources allocation by deriving closed-form solutions, and further develop an improved low-complexity simulated annealing (SA) algorithm to solve the computation offloading and multi-cell SCMA codebook allocation problem. To solve the problem of partial state observation and timely decision-making in long-term optimization environment, we put forward a multiagent deep deterministic policy gradient (MADDPG) algorithm with centralized training and distributed execution. Furthermore, we extend the framework to the partial offloading case and propose an algorithm based on alternating convex search for solving the task offloading ratio. Numerical results show that the proposed multi-cell SCMA-MEC scheme achieves lower energy consumption and system latency in comparison to the orthogonal frequency division multiple access (OFDMA) and power-domain (PD) NOMA techniques.

MEF2C/p300-mediated epigenetic remodeling promotes the maturation ofinduced cardiomyocytes.

Cardiac transcription factors (TFs) directly reprogram fibroblasts into induced cardiomyocytes (iCMs), where MEF2C acts as a pioneer factor with GATA4 and TBX5 (GT). However, the generation of functional and mature iCMs is inefficient, and the molecular mechanisms underlying this process remain largely unknown. Here, we found that the overexpression of transcriptionally activated MEF2C via fusion of the powerful MYOD transactivation domain combined with GT increased the generation of beating iCMs by 30-fold. Activated MEF2C with GT generated iCMs that were transcriptionally, structurally, and functionally more mature than those generated by native MEF2C with GT. Mechanistically, activated MEF2C recruited p300 and multiple cardiogenic TFs to cardiac loci to induce chromatin remodeling. In contrast, p300 inhibition suppressed cardiac gene expression, inhibited iCM maturation, and decreased the beating iCM numbers. Splicing isoforms of MEF2C with similar transcriptional activities did not promote functional iCM generation. Thus, MEF2C/p300-mediated epigenetic remodeling promotes iCM maturation.

Intelligent Reflecting Surface-Aided Downlink SCMA

Recently, intelligent reflecting surfaces (IRSs) and nonorthogonal multiple-access (NOMA) have emerged as energy and spectrally efficient techniques for next-generation wireless networks. Thus, in this article, IRS-aided downlink sparse code multiple access (SCMA) system is analyzed for the next-generation wireless networks. In the proposed IRS-aided SCMA (IRS-SCMA), the base station (BS) communicates with single-antenna users with the help of an IRS. The impact of different phase shift methods at the IRS panel is studied in the IRS-SCMA, and observed that the average phase shift method has a very close performance to the perfect phase shift (optimal) with low complexity. We analyze symbol error rate and sum-rate performance of the IRS-SCMA. Simulation results show that the proposed IRS-SCMA outperforms the corresponding IRS-aided power domain nonorthogonal multiple access (PD-NOMA), and SCMA without IRS schemes. Further, the impacts of various system's parameters, such as the number of IRS reflecting elements, channel fading, SCMA codebooks, IRS location, and the number of users on the system performance are studied.

NOMA-based collaborative beam hopping frequency allocation mechanism for future LEO satellite systems

Low Earth orbit (LEO) satellite systems provide terrestrial users with services that are not limited by geographical location. However, the conflict between existing allocation schemes and the business variability between beams is becoming increasingly prominent. Beam hopping technology allows for a more flexible and versatile approach to satellite resource allocation. This paper proposes a beam hopping pattern optimization scheme that jointly considers the interference threshold distance and beam service priority, reducing the inter-beam co-channel interference (CCI). In the cluster area, a non-orthogonal multiple access (NOMA)-based collaborative beam hopping (NCBH) scheme is proposed to minimize the cell-edge user (CEU) interference. Since there is a difference in channel gain between the CEU and cellcenter user (CCU), this scheme forms a NOMA cluster to perform power domain multiplexing and formulates a NOMA cluster pairing strategy according to the user location to reduce the CCI of the CEU. After NOMA cluster pairing, the optimal carrier frequency of the NOMA cluster is selected by a reinforcement learning algorithm. The simulation results verify the excellent performance of the proposed NCBH scheme regarding the user's received power, transmission rate, and outage probability.

Throughput maximization and reliable wireless communication in NOMA using chained fog structure and weighted energy efficiency power allocation approach

Novel radio access strategies must be developed to support an unprecedented number of connected devices to increase radio spectral efficiency of 5G and outside, and non-orthogonal multiple features (NOMA) arisen as a possible contender. To support cognitive NOMA networks, power allocation and NOMA-secondary user allocation is the effective technique for enhancing the resource utilization proficiency in power and spectrum domain. NOMA approach provides throughput enhancement to fulfil the demands of next group of Wireless Communication Networks. In this manuscript, a Chained Fog Structure (CFS) with Weighted Energy Efficiency Power Allocation (WEE-PA) method is proposed for throughput maximization and reliable wireless communication (CFS-WEE-NOMA). The aim of this study is “to enhance the throughput by involving underlay NOMA with Chained Fog Structure and WEE-PA method”. Here, the proposed WEE-PA approach is applied to multicarrier NOMA with chained fog structure for enhancing the throughput. During this analysis, the computational complexity due to the consideration of high users and different subcarrier values are solved by the proposed CFS-WEE-NOMA approach. Thus, the proper user pairing, power allocation, and bandwidth sharing of the proposed methodology ensure seamless communication. The simulation of this work is done in MATLAB and the performance metrics like throughput, computational complexity, power consumption, energy efficiency, delay, sum rate is analysed. The proposed CFS-WEE-NOMA approach has achieved 8.6%, 7.7%, and 6.7% high throughput based on transmitted power, 13.6%, 8.6%, and 11.7% high throughput based on subcarrier, and 13.6%, 9.6%, and 12.7% high energy efficiency compared with the existing methods, like Dynamic Network Resource Allocation (DNRA) algorithm (DNRA-NOMA), Multiple Carrier Cell-Less Non-Orthogonal Multiple Access (MC-CL-NOMA), dynamic programming (DP) recursion framework based multicarrier NOMA systems (DPRF-MC-NOMA) methods respectively.

Jamming of LoRa PHY and Countermeasure

LoRaWAN forms a one-hop star topology where LoRa nodes send data via one-hop uplink transmission to a LoRa gateway. If the LoRa gateway can be jammed by attackers, it may not be able to receive any data from any nodes in the network. Our empirical study shows that although the LoRa physical layer (PHY) is robust and resilient by design, it is still vulnerable to synchronized jamming chirps. Potential protection solutions (e.g., collision recovery, parallel decoding) may fail to extract LoRa packets if an attacker transmits synchronized jamming chirps at higher power. To protect the LoRa PHY from such attacks, we propose a new protection method that can separate LoRa chirps from jamming chirps by leveraging their difference in power domain. We note that the new protection solution is orthogonal to existing solutions that leverage the chirp misalignment in the time domain or the frequency disparity in the frequency domain. We conduct experiments with COTS LoRa nodes and software-defined radios with varied experiment settings such as different spreading factors, bandwidths, and code rates. Results show that synchronized jamming chirps at high power can jam all previous solutions, whereas our protection solution can effectively protect LoRa gateways from the jamming attacks.

Resource allocation and BER performance analysis of NOMA based cooperative networks

Resource sharing and management can significantly improve the performance and spectral efficiency of wireless systems. In power domain non-orthogonal multiple access (NOMA) systems, users share a common bandwidth for simultaneous data transmission and therfore, the spectral efficiency of the system will be improved at the expense of increased complexity. Provided proper power allocation, it is possible to detect symbols at receivers. In this paper, the downlink of a cellular system is considered where a base station (BS) communicates with two users using NOMA with the assistance of a decode-and-forward (DF) relay. In the proposed scheme, receivers combine received signals from direct and cooperative links, and decode symbols by employing successive interference cancellation (SIC). The bit error rate (BER) performance of the proposed scheme is analyzed and the optimal power allocation is also derived through a Min–Max optimization, and a closed form approximate solution is proposed for binary phase shift keying (BPSK) modulation. Furthermore, it is proved that the proposed receiver achieves full diversity order for all users for proper choice of power allocation. Simulation results also corroborate BER and diversity analysis.

Introduction and Clinical Analyses of an Accelerometer-Based Mobile Gait Assessment to Evaluate Neuromotor Sequelae of Concussion in Adolescents and Adults

A growing consensus among concussion experts is that a formal gait assessment is an essential component in return-to-play decisions. Concussion research illustrates that gait variables follow a pattern of recovery that may be more protracted than cognitive recovery, suggesting that gait dynamics may be more sensitive to the sequelae of concussion, and accelerometer data may enhance that sensitivity. However, pediatric neuropsychologists have few available options for quantitatively assessing gait. We here introduce a novel gait technology, the BioKinetoGraph (BKG), that provides multiple metrics for assessing gait, including within the domains of power, stride, balance (stability), and symmetry. We demonstrate how BKG data can be collected using a mobile application called SportGait, which is available for use on any smartphone. We present data illustrating the test–retest reliability of the mobile BKG in a sample of 4150 ostensibly healthy individuals, with an overall mean correlation coefficient of .79 between two walks across the assessed domains. We also provide quantitative and qualitative data to illustrate recovery, including a presentation of norm- and self-referenced comparisons. Additional recovery data is presented using qualitative information in the form of stabilogram and displacement graphs. Because the BKG is broadly available, reliable, valid, and does not require extensive or costly equipment (i.e., only requiring a mobile device and the App), it represents a significant advancement in quantifying gait in a wide range of settings.