Transmission Power Consumption Research Articles

Power Minimization for Age of Information Constrained Dynamic Control in Wireless Sensor Networks

We consider a status update system where multiple sensors communicate timely information about various random processes to a sink. The sensors share orthogonal sub-channels to transmit such information in the form of status update packets. A central controller can control the sampling actions of the sensors to trade-off between the transmit power consumption and information freshness which is quantified by the Age of Information (AoI). We jointly optimize the sampling action of each sensor, the transmit power allocation, and the sub-channel assignment to minimize the average total transmit power of all sensors, subject to a maximum average AoI constraint for each sensor. To solve the problem, we develop a dynamic control algorithm using the Lyapunov drift-plus-penalty method and provide optimality analysis of the algorithm. According to the Lyapunov drift-plus-penalty method, to solve the main problem, we need to solve an optimization problem in each time slot which is a mixed integer non-convex optimization problem. We propose a low-complexity sub-optimal solution for this per-slot optimization problem that provides near-optimal performance and we evaluate the computational complexity of the solution. Numerical results illustrate the performance of the proposed dynamic control algorithm and the performance of the sub-optimal solution for the per-slot optimization problem versus the different parameters of the system. The results show that the proposed dynamic control algorithm achieves more than <inline-formula> <tex-math notation="LaTeX">$60~\%$ </tex-math></inline-formula> saving in the average total transmit power compared to a baseline policy.

Intelligent Reflecting Surface Aided Full-Duplex Communication: Passive Beamforming and Deployment Design

This paper investigates the passive beamforming and deployment design for an intelligent reflecting surface (IRS) aided full-duplex (FD) wireless system, where an FD access point (AP) communicates with an uplink (UL) user and a downlink (DL) user simultaneously over the same time-frequency dimension with the help of IRS. Under this setup, we consider three deployment cases: 1) two distributed IRSs placed near the UL user and DL user, respectively; 2) one centralized IRS placed near the DL user; 3) one centralized IRS placed near the UL user. In each case, we aim to minimize the weighted sum transmit power consumption of the AP and UL user by jointly optimizing their transmit power and the passive reflection coefficients at the IRS (or IRSs), subject to the UL and DL users' rate constraints and the uni-modulus constraints on the IRS reflection coefficients. First, we analyze the minimum transmit power required in the IRS-aided FD system under each deployment scheme, and compare it with that of the corresponding half-duplex (HD) system. We show that the FD system outperforms its HD counterpart for all IRS deployment schemes, while the distributed deployment further outperforms the other two centralized deployment schemes. Next, we transform the challenging power minimization problem into an equivalent but more tractable form and propose an efficient algorithm to solve it based on the block coordinate descent (BCD) method. Finally, numerical results are presented to validate our analysis as well as the efficacy of the proposed passive beamforming design.

Optimal Frequency Reuse and Power Control in Multi-UAV Wireless Networks: Hierarchical Multi-Agent Reinforcement Learning Perspective

To overcome the problems caused by the limited battery lifetime in multiple-unmanned aerial vehicle (UAV) wireless networks, we propose a hierarchical multi-agent reinforcement learning (RL) framework to maximize the energy efficiency (EE) of UAVs by finding the optimal frequency reuse factor and transmit power. The proposed algorithm consists of distributed inner-loop RL for transmit power control of the UAV terminal (UT) and centralized outer-loop RL for finding the optimal frequency reuse factor. Specifically, the proposed algorithm adjusts these two factors jointly to effectively mitigate intercell interference and reduce undesired transmit power consumption in multi-UAV wireless networks. We show that, for this reason, the proposed algorithm outperforms conventional algorithms, such as a random action algorithm with a fixed frequency reuse factor and a hierarchical multi-agent Q-learning algorithm with binary transmit power controls. Furthermore, even in the environment where UTs are continuously moving based on the mixed mobility model, we show that the proposed algorithm can find the best reward when compared to conventional algorithms.

Demand and Interference Aware Adaptive Resource Management for High Throughput GEO Satellite Systems

The scarce spectrum and power resources, the inter-beam interference, together with the high traffic demand, pose new major challenges for the next generation of Very High Throughput Satellite (VHTS) systems. Accordingly, future satellites are expected to employ advanced resource/interference management techniques to achieve high system spectrum efficiency and low power consumption while ensuring user demand satisfaction. This paper proposes a novel demand and interference aware adaptive resource management for geostationary (GEO) VHTS systems. For this, we formulate a multi-objective optimization problem to minimize the total transmit power consumption and system bandwidth usage while matching the offered capacity with the demand per beam. In this context, we consider resource management for a system with full-precoding, i.e., all beams are precoded; without precoding, i.e., no precoding is applied to any beam; and with partial precoding, i.e., only some beams are precoded. The nature of the problem is non-convex and we solve it by jointly using the Dinkelbach and Successive Convex Approximation (SCA) methods. The simulation results show that the proposed method outperforms the benchmark schemes. Specifically, we show that the proposed method requires low resource consumption, low computational time, and simultaneously achieves a high demand satisfaction.

Joint Power Allocation for Remote State Estimation With SWIPT

In this paper, we consider remote state estimation with simultaneous wireless information and power transfer (SWIPT). A remote estimator receives the state estimate transmitted by a sensor and sends an acknowledgment (ACK) signal to the sensor via a feedback wireless channel. The sensor has no other energy supply except that it can harvest wireless energy from the received ACK signal, which carries information and energy simultaneously. Since the symbol error rate of the state estimate transmitted by the sensor depends on the sensor&#x2019;s transmission power allocation, there exists a tradeoff between the accuracy of the state estimate received by the remote estimator and the transmission power consumption of the sensor. Moreover, the sensor&#x2019;s transmission power is restricted by the remaining energy level in its battery, which is decided by the amount of the harvested wireless energy. Therefore, we jointly optimize the transmission power allocation of the remote estimator and the sensor and formulate the optimization problem into an infinite time-horizon average cost Markov decision process (MDP). We first prove the existence of the optimal stationary power allocation policy, and then present the monotonic structures of the optimal policy. Simulation results are provided to verify and illustrate the main results.

Energy-efficient opportunistic multi-carrier NOMA-based resource allocation for beyond 5G (B5G) networks

The interplay between the non-orthogonal multiple access (NOMA) and the opportunistic cognitive radio (CR)-based orthogonal frequency multiple access (OFDMA) has been recently realized as a promising paradigm to support the unprecedented massive connectivity demands of future beyond fifth-generation (B5G) wireless communication systems. In such systems, which are called multi-carrier NOMA CR-based systems, each licensed band reserved for primary users can be opportunistically utilized based on power-domain NOMA to serve a group of secondary users simultaneously. An important challenge in this domain is how to provide energy-efficient resource allocation techniques that attempt to strike a balance between the total throughput (i.e., the achieved sum-rate) and the power required to achieve that rate while satisfying network QoS demands and being aware of the unique characteristics of the CR operating environment. In this paper, we propose an energy-efficient resource allocation technique for multi-carrier NOMA CR-based systems, which aims at maximizing the overall energy efficiency (EE) of the system under a set of CR and NOMA constraints. The EE maximization problem is shown to be a fractional non-convex optimization, which is, in general, hard to optimize. To deal with the fractional and the non-convexity nature of the formulated EE maximization problem, we exploit the Dinkelbach’s algorithm to transfer the EE problem to a parameterized optimization problem. Then we use an iterative optimization approach to obtain the solution for the EE maximization problem. Simulation results reveal that this EE maximization-based resource allocation technique outperforms the existing resource allocation techniques in terms of the overall EE of the system while striking a good balance between the sum-rate and the transmit power consumption.

Energy-Efficient Topology Construction via Power Allocation for Decentralized Learning via Smart Devices With Edge Computing

Data privacy preservation has drawn much attention in emerging machine learning applications. Decentralized learning among smart devices over wireless networks is thus developed to guarantee data security and eliminate the involvement of parameter servers to avoid transmission bottlenecks. However, the previous research focuses on data compression and exchange rules of model parameters among smart devices. Still, it neglects the interplay between link cardinality, transmission power consumption, and collision in transmission. To jointly optimize these issues, in this paper, we first set collision and interference aside and formulate a new optimization problem, named GreenDL, and then extend GreenDL to be collision-aware, namely, GreenDL-CA, by restricting the maximum degree of each smart devices. We prove their hardness and propose two approximation algorithms dubbed as CoTRAIN and CoTRAIN-CA for GreenDL and GreenDL-CA, respectively. Experiment and simulation results manifest that both CoTRAIN and CoTRAIN-CA reduce more than 20% power compared with the other heuristics without sacrificing the convergence rate in the decentralized learning practices.

Energy-Efficient Precoding Designs for Multi-User Visible Light Communication Systems With Confidential Messages

This paper studies energy-efficient precoding designs for multi-user visible light communication (VLC) systems from the perspective of physical layer security where users’ messages must be kept mutually confidential. For such systems, we first derive a lower bound on the achievable secrecy rate of each user. Next, the total power consumption for illumination and data transmission is thoroughly analyzed. We then tackle the problem of maximizing energy efficiency, given that each user’s secrecy rate satisfies a certain threshold. The design problem is shown to be non-convex fractional programming, which renders finding the optimal solution computationally prohibitive. Our aim in this paper is, therefore, to find sub-optimal yet low complexity solutions. For this purpose, the traditional Dinkelbach algorithm is first employed to reformulate the original problem to a non-fractional parameterized one. Two different approaches based on the convex-concave procedure (CCCP) and Semidefinite Relaxation (SDR) are utilized to solve the non-convex parameterized problem. In addition, to further reduce the complexity, we investigate a design using the zero-forcing (ZF) technique. Numerical results are conducted to show the feasibility, convergence, and performance of the proposed algorithms depending on different parameters of the system.

Energy Performance Analysis and Modelling of LoRa Prototyping Boards.

LoRaWAN has gained significant attention for Internet-of-Things (IOT) applications due to its low power consumption and long range potential for data transmission. While there is a significant body of work assessing LoRA coverage and data transmission characteristics, there is a lack of data available about commercially available LoRa prototyping boards and their power consumption, in relation to their features. It is currently difficult to estimate the power consumption of a LoRa module operating under different transmission profiles, due to a lack of manufacturer data available. In this study, power testing has been carried out on physical hardware and significant variation was found in the power consumption of competing boards, all marketed as “extremely low power”. In this paper, testing results are presented alongside an experimentally-derived power model for the lowest power LoRa module, and power requirements are compared to firmware settings. The power analysis adds to existing work showing trends in data-rate and transmission power settings effects on electrical power consumption. The model’s accuracy is experimentally verified and shows acceptable agreement to estimated values. Finally, applications for the model are presented by way of a hypothetical scenario and calculations performed in order to estimate battery life and energy consumption for varying data transmission intervals.

Self-controlling photonic-on-chip networks with deep reinforcement learning

We present a novel photonic chip design for high bandwidth four-degree optical switches that support high-dimensional switching mechanisms with low insertion loss and low crosstalk in a low power consumption level and a short switching time. Such four-degree photonic chips can be used to build an integrated full-grid Photonic-on-Chip Network (PCN). With four distinct input/output directions, the proposed photonic chips are superior compared to the current bidirectional photonic switches, where a conventionally sizable PCN can only be constructed as a linear chain of bidirectional chips. Our four-directional photonic chips are more flexible and scalable for the design of modern optical switches, enabling the construction of multi-dimensional photonic chip networks that are widely applied for intra-chip communication networks and photonic data centers. More noticeably, our photonic networks can be self-controlling with our proposed Multi-Sample Discovery model, a deep reinforcement learning model based on Proximal Policy Optimization. On a PCN, we can optimize many criteria such as transmission loss, power consumption, and routing time, while preserving performance and scaling up the network with dynamic changes. Experiments on simulated data demonstrate the effectiveness and scalability of the proposed architectural design and optimization algorithm. Perceivable insights make the constructed architecture become the self-controlling photonic-on-chip networks.

Centralized Resource Allocation and Distributed Power Control for NOMA-Integrated NR V2X

The application of nonorthogonal multiple access (NOMA) technology to New Radio (NR) Vehicles-to-Everything (V2X) can further reduce communication delay and improve the system capacity of the vehicular network. However, due to the high mobility of the vehicles, it is difficult for the base station to obtain the channel information between vehicles in real time for resource allocation and vehicle transmission power control. To this end, we propose a two-stage scheme of centralized resource allocation and distributed power control to meet the NR V2X Mode 1 requirement while NOMA technology is employed in each vehicle group. First, at the beginning of a transmission period, the base station allocates resources to vehicle groups. For this centralized manner, we propose a graph-based matching approach to allocate resources to improve system capacity. Then, each vehicle group controls and adjusts transmission power for NOMA communication in the period. For this distributed manner, we propose a noncooperative game to control the power of the vehicle groups and then analyze the performance of the noncooperative game. Afterward, we further put forward a cooperative game approach to control the power of the vehicle group to increase system capacity. Compared with the noncooperative game, the proposed scheme can increase communication capacity by up to 5% and reduce transmission power consumption by 36%.

Fuzzy Logic Guided Load-Balanced User Association and Beamforming for Distributed mmWave Networks

In this letter, we are committed to obtaining load-balanced user association and optimal beamforming in an energy-saving downlink distributed Millimeter-Wave (mmWave) network, with per-user quality of service (QoS) requirements, user association constraints and remote radio unit (RRU) transmission power limits. A mixed discrete nonlinear programming (MINLP) problem is formulated, which is NP-hard. The traditional sparse beamforming method (SBM) can jointly optimize the user association and the beamforming vector by inducing the beamformer sparsity via the reweighted <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> norm technique. However, such existing scheme may cause unbalanced load of RRU, thus degrading the mmWave network performance. For better load-balanced user association, we introduce the Fuzzy inference System (FIS) to pursue further advancement of SBM. In addition, the good scalability of FIS framework can help itself to be extended to more indicators in the next generation of communication systems. Simulation results show that the improved algorithm can obtain a load-balanced user association, meanwhile the transmit power consumption of mmWave networks can be significantly reduced.

Mitigation of Data Packet Loss in Bluetooth Low Energy-Based Wearable Healthcare Ecosystem.

Bluetooth Low Energy (BLE) plays a critical role in wireless data transmission in wearable technologies. The previous work in this field has mostly focused on optimizing the transmission throughput and power consumption. However, not much work has been reported on a systematic evaluation of the data packet loss of BLE in the wearable healthcare ecosystem, which is essential for reliable and secure data transmission. Considering that diverse wearable devices are used as peripherals and off-the-shelf smartphones (Android, iPhone) or Raspberry Pi with various chipsets and operating systems (OS) as hubs in the wearable ecosystem, there is an urgent need to understand the factors that influence data loss in BLE and develop a mitigation solution to address the data loss issue. In this work, we have systematically evaluated packet losses in Android and iOS based wearable ecosystems and proposed a reduced transmission frequency and data bundling strategy along with queue-based packet transmission protocol to mitigate data packet loss in BLE. The proposed protocol provides flexibility to the peripheral device to work with the host either in real-time mode for timely data transmission or offline mode for accumulated data transmission when there is a request from the host. The test results show that lowered transmission frequency and data bundling reduce the packet losses to less than 1%. The queue-based packet transmission protocol eliminates any remaining packet loss by using re-request routines. The data loss mitigation protocol developed in this research can be widely applied to the BLE-based wearable ecosystem for various applications, such as body sensor networks (BSN), the Internet of Things (IoT), and smart homes.

Research on Application Scheme of Power Internet of Things in Power Grid

Introduction Power Internet of things is an important means for power grid companies to make digital transformation and improve the level of power grid intelligence. Method This paper introduced the general situation and architecture of power Internet of things， focused on the functional requirements and development goals of each level， and put forward the technical direction of developing power Internet of things according to the differences among comprehensive power companies， distribution network companies and power sales companies. Results Application solutions were put forward in the fields of transmission network， distribution network， marketing and power consumption， and enterprise management. Conclusion The scheme has been well applied in various power grid companies.

Reconfigurable Intelligent Surface for Green Edge Inference

Reconfigurable intelligent surface (RIS) as an emerging cost-effective technology can enhance the spectral- and energy-efficiency of wireless networks. In this article, we consider an RIS-aided green edge inference system, where the inference tasks generated from resource-constrained mobile devices (MDs) are uploaded to and cooperatively performed at multiple resource-enhanced base stations (BSs). Taking into account both the computation and uplink/downlink transmit power consumption, we formulate an overall network power consumption minimization problem, which calls for the joint design of the set of tasks performed by each BS, uplink/downlink beamforming vectors of BSs, transmit power of MDs, and uplink/downlink phase-shift matrices at the RIS. However, the resulting combinatorial optimization problem is nonconvex and highly intractable. We tackle the challenge of combinatorial variables by exploiting the group sparsity structure of the beamforming vectors. Moreover, a block-structured optimization with mixed <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1,2</sub> -norm and difference-of-convex-functions (DC) based three-stage framework is proposed to solve the problem, where the mixed <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1,2</sub> -norm and DC techniques are adopted to induce the group sparsity structure and handle the nonconvex rank-one constraint, respectively. Simulations demonstrate the supreme performance gain of deploying an RIS and confirm the effectiveness of the proposed algorithm over the baseline algorithms in reducing the overall network power consumption.

Scalable Two-Mode 3-Port and 4-Port Mode Insensitive Silicon Photonic Switches

We propose and experimentally demonstrate a novel design approach for scalable 3-port and 4-port mode insensitive multimode switching matrices for the first two quasi-transverse electric (TE) modes. The mode insensitive phase shifter ensures less power consumption for simultaneous multimode signal transmission in a mode division multiplexing (MDM) network. At 1550 nm, the 3-port switch exhibits approximately 2.6 dB and 3.3 dB insertion loss for the longest path with a crosstalk of at most 10 dB and 8 dB over a bandwidth of 40 nm (1530 nm to 1570 nm) for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\mathrm {TE}}_{\mathrm {0}}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\mathrm {TE}}_{\mathrm {1}}$ </tex-math></inline-formula> modes, respectively. The insertion loss measured for the 4-port switch is approximately 2.7 dB and 3.6 dB at 1550 nm with a corresponding crosstalk less than 8 dB for the two TE modes, respectively. The payload transmission is also performed using both 10 Gb/s non-return-to-zero (NRZ) and 14.0625 Gbaud 4-level pulse-amplitude modulation (PAM4) pseudorandom binary sequence (PRBS)-31 data signal to analyze the performance of the switches. Clear open eyes are observed for both single-mode and simultaneous two-mode transmissions. The low insertion loss, low intermodal crosstalk over a large optical bandwidth, and the clear open eye validate the scalability of the proposed switches for larger port count and higher-order modes.

Optimal sub‐harmonic injection‐locked MICS band transmitter for wireless CW‐fNIRS systems

AbstractPortable and wireless functional near‐infrared spectroscopy is a growing field of research for real‐time monitoring of brain functions. The most critical challenges in this field are the use of low‐power and calibrated circuits. A novel transmitter architecture is proposed to overcome these barriers. This transmitter is low power, capable of being calibrated against process variation, and has a better phase noise and spurious‐free dynamic range (SFDR) at the antenna. Besides that, the transmitter can be calibrated, which is not seen in similar research. In this transmitter, injection locking and frequency calibration lead to having an optimal and low‐power circuit. The circuit is capable of transmitting data with BFSK and OOK modulations in the frequency band of the medical implant communication service (MICS). The transmitter is designed and simulated in a typical CMOS 0.18‐μm technology with a 1‐V power supply. The transmitter's power consumption is around 146 and 123 μW, equal to 5.92 nJ/bit and 246–630 pJ/bit for BFSK and OOK modulations, respectively. The signal's phase noise at the antenna is almost −109 dBc/Hz at 1‐MHz frequency offset.

What is driving the remarkable decline of wind and solar power curtailment in China? Evidence from China and four typical provinces

The world’s key renewable power markets are generally challenged by wind and solar power curtailment. Research on the influencing factors of curtailment improvement can provide a reference for the further penetration of renewable energy (RE) into the power system. Based on the logarithmic mean Divisia index (LMDI) method, this paper analyzes the factors influencing the wind and solar power consumption rate in China from 2015 to 2018, and four typical provinces are discussed in detail. By decomposing the consumption rate into six factors (transmission structure, generation proportion, power self-sufficiency, resource development, resource utilization, and power consumption), and focusing on the transmission structure factors, this paper further clarifies the contributions of local use, ultra-high-voltage (UHV) transmission, and conventional transmission to the improvement of curtailment. The results reveal the following. (1) At the national level, the power mixing effect and the resource development effect have played major roles in the change of the consumption rate, but the influences of these two effects have been decreasing. (2) The UHV power lines provide a robust resource for the inter-provincial deployment of renewable power (such as the RE power transfer in Inner Mongolia and Gansu), but the role of UHV transmission has not yet been fully utilized. (3) The impact of the electricity consumption effect on renewable power consumption is increasing year by year, but the local consumption capacity remains insufficient (both at the national level and in the four typical provinces analyzed), so it is necessary to further increase the share of renewable electricity in UHV power transmission and the local consumption capacity. (4) The expanding development of wind and solar power may be the reason for the curtailment in Shaanxi, and a reasonable renewable power development plan must be further formulated.

A Digitally Controlled Multichannel Spectrally Efficient Low-Power Transceiver for Ultra-Wideband Cognitive Radio Applications

A multichannel transceiver design with low hardware complexity, flexibility and efficient spectrum use intended for Impulse Radio (IR) Ultra-Wideband (UWB) apertures, is proposed in this paper. The transceiver supports 14 channels and is implemented in TSMC CMOS process. The transmitter adopts a symmetrical triangular narrow pulse generator, a multiband LC-VCO, a mixer and a Variable-Gain Amplifier. A digital control of transmitter output power and carrier frequency is achieved by a current-steering Digital-to-Analog Converter (CS-DAC). The receiver follows the noncoherent Energy Detection (ED) scheme including Low-Noise Amplifier (LNA) which takes the benefits of the body biasing technique to further reduce power consumption, squarer and comparator. The LNA achieves high gain of up to 30[Formula: see text]dB allowing to enhance the receiver sensitivity which is [Formula: see text]83.7[Formula: see text]dBm at 25[Formula: see text]Mbps. The transmitter provides output pulses with a width of 3[Formula: see text]ns, a pulse repetition rate of 20[Formula: see text]ns and a maximum Power Spectral Density (PSD) of [Formula: see text]42[Formula: see text]dBm/MHz. The power consumptions of transmitter and receiver are 35.6[Formula: see text]pJ/bit and 0.207[Formula: see text]nJ/bit at 25[Formula: see text]Mbps, respectively. Maximizing utilization of the scarce wireless spectrum, enhancing spectral flexibility and efficiency and reducing power consumption are the main contributions brought by this work, enabling this transceiver to be able to deal with the current debate on producing single multifunctional Cognitive Radio (CR) UWB systems.

Wireless ECG and cardiac monitoring systems: State of the art, available commercial devices and useful electronic components

Wireless ElectroCardioGram (ECG) systems are employed in manifold application fields: tele-monitoring, sport applications, support to ageing people at home, fetal ECG, wearable devices and ambulatory monitoring. The presence of cables often hinders user’s free movements, alongside clinicians’ routine operations. Therefore, wireless ECG systems are desirable. This paper aims at reviewing the solutions described in the literature, besides commercially available devices and electronic components useful to setup laboratory prototypes. Several systems have been developed, different in terms of the adopted technology; when approaching the development of a wireless ECG system, some important aspects should be considered: electrodes (disposable, wet/dry, without contact, insulated), analog front-end, data acquisition systems (including amplifiers, multiplexer), wireless transmission technology (e.g. WiFi, Bluetooth) and power consumption (battery lifetime, miniaturization purposes). Technological advancements and continuous research have already brought to miniaturized and comfortable devices, but there is still room for improvement on multiple sides.