Rate Control Algorithm Research Articles

QoE-Maximized Beam Assignment and Rate Control for Dynamic mm-Wave-Based Full-Duplex Small Cell Networks

This study investigates the resource management problem for millimeter-wave-based switched beam (SWB) full-duplex small cell networks with the consideration of user equipment’s (UE’s) quality of experience (QoE) requirement and time-varying wireless channels. An optimization problem is formulated to maximize the long-term QoE by implementing beam assignment (BA) and rate control (RC) under short-term beam and long-term energy efficiency constraints. By leveraging the Lyapunov optimization technique, the original problem is converted into a series of BA and RC problems in each time slot. To solve the converted problem with affordable complexity, novel closed-form solutions for BA and RC are first derived by considering beam constraints in SWB systems. A decomposition-based BA and RC (DBR) algorithm with only polynomial computational complexity is then proposed based on the derived closed-form solutions. The simulation results demonstrate that the proposed DBR method can effectively[‘effectively’ appears to be a more suitable word in this case.] balance the performance and complexity because the DBR scheme outperforms the benchmark scheme and achieves nearly optimal performance in terms of system delay and QoE.

Rate Control Technology for Next Generation Video Coding Overview and Future Perspective

Video data have become the main data traffic on the Internet, and their traffic is increasing explosively every year, thus increasing the pressure of video transmission. Video coding technology has become the key to compressing original videos. As an indispensable technology, rate control plays an important role in stabilizing video stream transmission. Rate control (RC) is part of rate distortion optimization (RDO) whose job is to find the optimal solution based on balancing rate and distortion. It not only needs to consider the buffer and network status but also adjust the corresponding bit rate according to the video content. This paper reviews the related technologies of rate control under high efficiency video coding (HEVC) and versatile video coding (VVC) standards so that subsequent researchers can quickly understand the field and promote the development of rate control algorithms. Firstly, the paper summarizes the various aspects of RC, including basic principles, rate-distortion models, major processes, and performance criteria. Secondly, the paper surveys, in detail, the research progress in the field of rate control and analyzes several mainstream research directions. Thirdly, we carry out relevant experiments on the standard reference software and analyze and discuss the experimental results of the existing studies. Finally, we look ahead to the future trends of rate control and provide feasible improvement suggestions.

Based on Fuzzy Measure Algorithm Message Adaptive Rate Algorithm of Internet of Things

In order to solve the problem that the existing LoRaWAN adaptive data rate control algorithm leads to low data transmission efficiency in the case of network congestion, a method combining a fuzzy logistic regression classifier and an improved adaptive data rate controller adjusting the avoidance time was proposed. The classifier could obtain the predicted congestion state by logistic regression learning. The data rate controller determined the data rate adjustment scheme according to the predicted congestion state. The experimental results showed that when the network congestion occurred in about 12s, the number of packet loss by the LoRaWAN default method was higher than that by the method in the research. The value of ADR_ MSG_CNT of the 15 source nodes in the method was 30 within 0–10 s, while the RCV_ACK_CNT of some nodes was 0. It proved that the method was more efficient than the original LoRaWAN adaptive data rate control algorithm.

Two-Timescale Resource Allocation for Automated Networks in IIoT

The rapid technological advances of cellular technologies will revolutionize network automation in industrial internet of things (IIoT). In this paper, we investigate the two-timescale resource allocation problem in IIoT networks with hybrid energy supply, where temporal variations of energy harvesting (EH), electricity price, channel state, and data arrival exhibit different granularity. The formulated problem consists of energy management at a large timescale, as well as rate control, channel selection, and power allocation at a small timescale. To address this challenge, we develop an online solution to guarantee bounded performance deviation with only causal information. Specifically, Lyapunov optimization is leveraged to transform the long-term stochastic optimization problem into a series of short-term deterministic optimization problems. Then, a low-complexity rate control algorithm is developed based on alternating direction method of multipliers (ADMM), which accelerates the convergence speed via the decomposition-coordination approach. Next, the joint channel selection and power allocation problem is transformed into a one-to-many matching problem, and solved by the proposed price-based matching with quota restriction. Finally, the proposed algorithm is verified through simulations under various system configurations.

Content-based coding tree unit level rate-quantization model for intra-coding in high efficiency video coding standard using convolutional neural network

In almost all video applications, a video rate control algorithm (RCA) is used by the encoder. The RCA tunes the quantization parameter (QP) to match the encoded bit rate to the available capacity of the communication channel or storage media. Conventional RCAs usually utilize a rate-quantization (R-Q) or a rate-distortion (R-D) model for rate control. A content-based R-Q model for intra coding tree units (CTUs) of the high-efficiency video coding standard is proposed. The model is a convolutional neural network that observes pixels of a CTU and its intraprediction reference pixels and it estimates required bit counts for intracoding the CTU for all QP values simultaneously. The proposed model can be easily used by any video RCA. A given RCA just selects a proper QP for which the estimated bit counts are closer to the allocated bit budget. The evaluation results show a high accuracy for the model. According to simulation results, the mean absolute normalized bit error at CTU level is 19.66% and it decreases to 6.85% at the frame level. Compared with similar networks, the proposed structure has a very low computational complexity.

High Efficiency Rate Control for Versatile Video Coding Based on Composite Cauchy Distribution

In this work, we propose a novel rate control algorithm for Versatile Video Coding (VVC) standard based on its distinct rate-distortion characteristics. By modelling the transform coefficients with the composite Cauchy distribution, higher accuracy compared with traditional distributions has been achieved. Based on the transform coefficient modelling, the theoretically derived R-Q and D-Q models which have been shown to deliver higher accuracy in characterizing RD characteristics for sequences with different content are incorporated into the rate control process. Furthermore, to establish an adaptive bit allocation scheme, the dependency between different levels of frames is modelled by a dependency factor to describe relationship between the reference and to-be-coded frames. Given the derived R-Q and D-Q relationships, as well as the dependency factor, an adaptive bit allocation scheme is developed for optimal bits allocation. We implement the proposed algorithm on VVC Test Model (VTM) 3.0. Experiments show that due to proper bit allocation, for low delay configuration the proposed algorithm can achieve 1.03% BD-Rate saving compared with the default rate control algorithm and 2.96% BD-Rate saving compared with fixed-QP scheme. Moreover, 1.29% BD-Rate saving and higher control accuracy have also been observed under the random access configuration.

A novel rate control algorithm for low latency video coding base on mobile edge cloud computing

The current low-latency video coding rate control algorithm has similar video sequence structure, low rate control accuracy, long control time, etc., which cannot meet the expectations of modern workers. Based on this, this paper proposes a mobile edge cloud computing-based Low-latency video coding rate control algorithm, optimize the original control algorithm, improve its rate control accuracy, etc. By analyzing the relationship between mobile edge computing and cloud computing, combined with edge computing in the context of cloud computing, this paper proposes a mobile edge cloud computing method and designs the mobile edge cloud computing architecture. Low latency video sequences are obtained using mobile edge cloud computing, and a mobile edge cloud computing model is established to control the update rate parameters of delayed video files. According to the principle of rate control, based on joint rate–distortion theory and frame coding complexity calculation model, the low latency video coding rate control is realized. The experimental results show that the byte data volume of the low-latency video coding sequence of the proposed method is 5653 dB. The rate control accuracy can be as high as 99.64%, and the rate control time is 1.37 s. The proposed method has a high similarity of video sequence structure and high rate control accuracy and can effectively shorten the rate control time of low latency video coding.

Rate Control Optimization Algorithm of Ubiquitous Power Sensor Network Tester Based on Multimedia

With more and more video application scenarios and increasing complexity, the popularization of multimedia information and the urgent need to update wireless sensor networks have led to the emergence and development of wireless multimedia sensor networks. This paper focuses on the rate control optimization algorithm of multimedia-based ubiquitous power sensor network, which is mainly studied from three aspects: constructing algorithm verification platform based on multimedia technology, performance analysis, and optimization of rate control optimization algorithm based on multimedia technology. An algorithm verification platform is established based on multimedia technology. This article uses a scalable video coding method to design a client-driven scalable video transmission system. The simulation results show that the algorithm can effectively improve the video quality. The algorithm of rate control based on multimedia technology is proposed. A reliable multipath routing algorithm based on AODV is proposed. Based on the energy balance algorithm, the node-independent routing mechanism and link quality estimation model are introduced. An independent and reliable active/standby communication link to the node of the destination node is established. Linux, the full name of GNU/Linux, is a free-to-use and freely disseminated Unix-like operating system. It is a POSIX-based multiuser, multitasking, multithreaded, and multi-CPU operating system. With the development of the Internet, Linux has gained support from software enthusiasts, organizations, and companies all over the world. In addition to maintaining a strong momentum of development in servers, it has made considerable progress in personal computers and embedded systems. Under the Linux platform, a large number of tests are performed and the performance of the control code rate is analyzed. The so-called sensor network is a distributed intelligent network system that is composed of a large number of small sensor nodes with wireless communication and computing capabilities deployed in the active area through a self-organizing method that can autonomously complete designated tasks according to the environment. The distance between the nodes of the sensor network is very short, and the multihop wireless communication method is generally used for communication. The sensor network can run in an independent environment, or it can be connected to the Internet through a gateway so that users can access it remotely. It is concluded that ABR is the most suitable rate control algorithm for video transmission. According to the CQP experiment results, the QP value set in the improved ABR algorithm is at most 40; the security from the construction of the ubiquitous power sensor network to the final monitoring data collection and upload process is verified by simulating the hypothesis attacks and faults. It is proved that the construction of ubiquitous power sensor network can reduce the energy consumption and delay of monitoring data collection and verify the superiority of constructing ubiquitous power sensor network.

Grid-connected photovoltaic system with power smoothing

This paper analyzes the power smoothing of grid-connected photovoltaic (PV) systems under fast irradiance changes. The analyzed converter is composed of a triple active bridge series-resonant (TABSR) DC-DC converter cascaded with a voltage source inverter (VSI). Two controlled variables are considered: battery current and the PV voltage. The TABSR DC-DC converter is modeled as controlled current sources for the battery and the PV ports. The ramp rate (RR) control algorithm is used to smooth the PV output power profile enhancing the power delivered to the grid. Four ramp rates (10%, 5%, 2% and 1%) are used to evaluate the RR control algorithm and the battery state of charge (SOC) response. Therefore, the battery can be sized appropriately. Real data for irradiance and temperature in an overcast day is used to verify the effectiveness of the proposed system.

APMC: Adjacent Pixels Based Measurement Coding System for Compressively Sensed Images

Compressed sensing is now regarded as an effective method for dimension reduction during signal acquisition. One significant, yet under-addressed issue regarding the transmission of compressively sensed images is how to compress and code measurements, the output of a compressed sensing sensor. As the spatially adjacent correlation in the measurement domain is weak, conventional encoding algorithms cannot be applied directly for measurements. In this paper, we propose the adjacent pixels based measurement coding system (APMC) to generate compressed image bit-streams. Firstly, an adjacent pixels based measurement matrix (APMM) is applied to embed the pixel-domain boundary information of each block to the measurement domain. By adopting APMM, the pixel-domain information can be efficiently used for measurement-domain intra prediction. Moreover, to avoid the interference of pixels that are far apart and achieve a high prediction accuracy, we employ boundary measurements of neighboring blocks as references for prediction. Finally, we propose a rate control algorithm to process the residuals between measurements and predictions, to generate a coded bit sequence for transmitting. Experimental results demonstrated superiority in rate-distortion performance and bandwidth costs in transmitting as compared to previous schemes. Compared to the state-of-the-art, this work achieves a 24% decrease in bitrate and a 1.68 dB increase in Peak Signal-to-Noise Ratio (PSNR) on average.

HBsAg Production in Methanol Controlled <i>P. pastoris</i> GS115 Mut<sup>S</sup> Bioreactor Process

When producing recombinant proteins with Pichia pastoris, cultivation parameters, such as induction temperature, dissolved oxygen level and residual methanol concentration play a crucial role in product biosynthesis and subsequent purification, therefore to maximize protein yields, the optimization of these parameters is imperative. Two different Pichia pastoris cultivation strategies for HBsAg VLP production in a 5 L stirred-tank bioreactor and the influence of different cultivation parameters on product yield were investigated. Residual methanol concentrations were controlled at low (>0.01 g/L), medium (1.5-2.0 g/L) and high (5.0-6.0 g/L) levels using a PI-based feed rate control algorithm based on the online methanol sensor signal. Product was purified using a novel and rapid purification method including steps of ammonium sulfate precipitation, size-exclusion chromatography and hydrophobic interaction chromatography. Employing an in-situ methanol sensor probe, the PI-based methanol feed rate control algorithm provided residual methanol concentration control with an average deviation of ±0.4 g/L from set-point value. Employing a cultivation protocol with an increased methanol concentration controlled at 6.0 g/L and a reduced DO level below 10 %, resulting in a final dry cell biomass concentration of 140 g/L and purified HBsAg VLPs yield of 186 mg/L. Developed purification method proved advantageous to other described methods, as it did not include time consuming extraction and centrifugation steps.

A neural network-based video bit-rate control algorithm for variable bit-rate applications of versatile video coding standard

Versatile video coding is a new video coding standard that has more capabilities and higher coding efficiency compared with its predecessor. Practical video storage and transmission applications face constrained buffer size and available bandwidth. It is necessary to design the appropriate rate control algorithm to overcome such challenges. In this paper, the non-linear relationship between consumed bits, buffer size, and quantization parameter is estimated by taking the advantages of artificial neural networks, and a rate control algorithm is developed for real-time variable bit rate applications of the versatile video coding standard. The proposed rate control algorithm performs the control action in only one step that results in faster control action. The experimental results show that the proposed algorithm controls the bit-rate as well as the buffer state. Also, the rate–distortion analysis shows that the well-known λ-domain algorithm has only 2.7% bit-rate reduction in comparison with the proposed method.

Structural similarity-based rate control algorithm for 3D video

Human vision easily identifies the structural degradation in a video and thus perceptual quality improvement is necessary. To adjust the video quality to match with the human vision we proposed a structural similarity (SSIM) based rate control algorithm for the 3D video. We incorporated a structural similarity index (SSIM) as the quality metric in rate control algorithm. The rate-distortion model and Lagrange multiplier are derived considering the structural dissimilarity (dSSIM) as the distortion metric to achieve the rate control with perceptual quality improvement. Furthermore, the optimal joint bit allocation scheme at texture video/depth map level, frame level, and basic unit (BU) level is modified to incorporate dSSIM for measuring distortion. The proposed algorithm is implemented in HEVC compression standard HTM-16.2. The performance of the proposed algorithm is compared using RD curves, BD-Rate comparison, and subjective evaluation. Besides, rate accuracy is also computed to measure the bit rate mismatch. Compared to the original λ-domain rate control algorithm, the proposed algorithm achieves a better SSIM along with a reduction in bit rate.

A Rate Control Algorithm Based on Psnr-Hvs For Hevc

HEVC/H.265 is the latest video coding standard. It has a higher compression rate under the requirement of ensuring video image quality. However, the currently used video image quality evaluation indicators cannot better fit the subjective perception of the human visual system and cannot effectively allocate target bits and update parameters so that results in reduced video image coding quality. This paper proposes a CTU-level rate control algorithm based on the image quality evaluation factor PSNR-HVS which is more in line with the perception of the human visual system. According to the PSNR-HVS of the CTU as the weight, the target bit is assigned to the current frame to be encoded. Then calculate the actual bits and PSNR-HVS after encoding the current CTU to update the parameters of the CTU at the same position in the next frame. The experimental results show that compared with HM16.20, the subjective performance of the video after encoding is improved, and the image details are more delicate, BD-Rate = -4.6, BD-PSNR-HVS = 0.17, ΔT = 4.6%.

Long-term rate control for concurrent multipath real-time video transmission in heterogeneous wireless networks

Concurrent multipath transmission provides an effective solution for streaming high-quality mobile videos in heterogeneous wireless networks. Rate control is commonly adopted in multimedia communication systems to fully utilize the available network bandwidth. This paper proposes a novel rate control for concurrent multipath video transmission. The existing rate control algorithms mainly adapt bit rate in the short-term pattern, i.e., without considering the long-term video transmission quality. We propose a long-term rate control scheme that takes into account the status of both the transmission buffer and video frames. First, a mathematical model is developed to formulate the non-convex problem of long-term quality maximization. Second, we develop a dynamic programming solution for online encoding bit rate control based on buffer status. The performance evaluation is conducted in a real test bed over LTE and Wi-Fi networks. Experimental results demonstrate that the proposed long-term rate control scheme achieves appreciable improvements over the short-term rate control schemes in terms of video quality and delay performance.

Stochastic joint rate control and resource allocation for wireless video surveillance

Wireless video surveillance has become increasingly prevalent due to the rapid development of cellular communication technology and the low deployment cost of cellular surveillance cameras. However, it is still a challenging task to deliver high-quality low-latency surveillance videos in resource-limited cellular networks due to the fluctuating characteristics of wireless channels. In this paper, we consider a wireless video surveillance system consisting of one base station and multiple cellular surveillance cameras, which upload their videos to the base station. To optimize the long-term system performance in terms of surveillance video quality and latency, we formulate a stochastic optimization problem that jointly considers video rate control and uplink resource allocation. The formulation captures the tradeoff between video quality and delivery latency while considering the different time scales of video rate control and channel resource allocation. With the application of Lyapunov optimization, we transform the problem into a sequence of per-slot deterministic problems, and propose an online joint rate control and resource allocation algorithm to solve these per-slot problems. Specifically, the proposed algorithm decomposes each of the per-slot problems into two independent subproblems, namely, the rate control subproblem at large time scale and the uplink resource allocation subproblem at small time scale. We derive the closed-form solution for the rate control subproblem, and design a fast-convergent iterative algorithm to solve the uplink resource allocation subproblem optimally. We prove the asymptotical optimality of our proposed algorithm. Extensive simulation results validate our theoretical analysis and demonstrate that the proposed algorithm can well balance the surveillance video quality and delivery latency.

Multi-Objective Optimization of Quality in VVC Rate Control for Low-Delay Video Coding.

In this paper, a multi-objective optimization of quality based coding tree unit (CTU) level rate control method, named MORC, for low-delay video coding of Versatile Video Coding (VVC) is proposed. Unlike the traditional rate control algorithms, objectives of minimizing average distortion and minimizing quality fluctuation are introduced and considered simultaneously to obtain the optimal solution. Weighting method is then used to convert the multi-objective optimization problem into a simplistic single-objective problem. Accordingly, given the target rate constraint, rate allocation is formulated as a convex optimization problem to achieve better trade-off among three multiple objectives: minimizing average video distortion, meeting rate constraint and minimizing video quality fluctuation. Based on the D- λ model, a two-stage method is further proposed to solve the optimization problem. Experiments have been conducted on the test model of VVC, which is VTM 3.0. Compared with the state-of-the-art rate control algorithms, the proposed method can obtain the Pareto optimal solution, which dominates the solution of other methods and is able to achieve better trade-off among multiple objectives.

Adaptive Queue Management and Traffic Class Priority Based Fairness Rate Control in Wireless Sensor Networks

Congestion control in Wireless Sensor Networks (WSNs) is one of the key areas of research and different algorithms have been proposed using either of the notions of fair rate allocation, traffic class priority, and queue management. Use of the any one of the above is not adequate to address the challenges. Hence, in this paper, we have proposed a novel congestion control algorithm using the combined notions of fair allocation of bandwidth, prioritizing traffic classes, and Adaptive Queue Management (ADQM). The proposed Weighted Priority based Fair Queue Gradient Rate Control (WPFQGRC) scheme achieves the fair distribution of spare bandwidth by considering the traffic class priority, average queue size, and the connected loads of a node. Average queue size at every node is adapted based on the proposed notion of the gradient of the differential of Global Priority (GP) with respect to the differential of queue size. The output rate of a given node is computed based on the GP of the node and the average queue size. The spare bandwidth of a node is fairly distributed by taking into account the connected load of the given node. The proposed algorithm is developed to suit to a general topology of WSN, however for the sake of illustration, we have considered a tree topology network that deals with both Real-Time (RT) and Non-Real Time (NRT) traffic classes. The proposed algorithm is implemented in NS3 platform in Linux environment and the performance of the algorithm is evaluated in terms of throughput, packet loss, packet delay, traffic class patterns, node mobility, and the average queue size. The performance of the proposed algorithm is found to be superior to that of Yaghmaee et al. ’s, Brahma et al. ’s, Monowar et al. ’s, Sarode et al. ’s, Difference of Differentials Rate Control (DDRC), Weighted Priority based DDRC (WPDDRC), and Priority based Fairness Rate Control (PFRC) algorithms respectively.

Feed rate control in robotic bone drilling process.

The bone drilling process is characterised by various parameters, the most important of which are the feed rate (mm/s) and the drill speed (rpm). They highly reflect the final effects and results of the drilling process, such as mechanical and thermal damages of bone tissue and hole quality. During manual drilling, these parameters are controlled by the surgeon based on his practical skills. But automatic drilling can assure an optimal result of the manipulation where such parameters are under control. During bicortical automatic bone drilling such a process consists of several stages: searching the contact with the first cortex, cortex drilling and automatic stop; searching the contact with the second cortex, cortex drilling and automatic stop; drill bit extraction. This work presents a way to control the feed rate during different stages of the bone drilling process (an original feed rate control algorithm) using the orthopaedic drilling robot (ODRO). The feed rate control is based on a proposed algorithm created and realised by specific software. During bicortical bone drilling process the feed rate takes various values in any stage in the range 0.5-6 mm/s. These values depend on drill bit position and real time force sensor data. The novelty of this work is the synthesis of an original feed rate control algorithm to solve the main problems of bone drilling in orthopaedic surgery - minimisation the drilling time (the heat generation); eliminating of the drill bit slip at the first (near) cortex and the drill bit bending at the second (far) cortex; minimising the risk of micro cracks which causes Traumatic Osteonecrosis; improving hole quality of the drilled holes; eliminating of the drill bit slip and the drill bit bending at the second cortex; minimising the value of the second cortex drill bit penetration by bicortical bone drilling.

Scene-level two-pass video rate controller for H.265/HEVC standard

A scene-level two-pass video rate controller for high efficiency video coding (HEVC) standard is proposed in this paper. The proposed rate controller is suitable for many pre-recorded applications in which encoded videos are transferred later on through a communication channel with limited bandwidth and buffering constraint. This rate controller operates in two passes. In the first pass, the video sequence is compressed and relevant information is collected. In the second pass, an optimal base quantization parameter (QP) for each video scene is calculated by simplifying the λ-domain rate-distortion model. Then, using the optimal base QP and the known QP cascading technique, a QP is computed for each picture in the scene. In this way, the quality of the compressed video is kept relatively constant during a scene and thus it provides a high-level perceptual quality for the compressed video. The base QP may be slightly modified during the second pass encoding by a fuzzy controller according to the second pass encoding results and the buffer status. The proposed rate controller has been implemented on H.265/HEVC standard reference software. Experimental results show that in comparison with the constant QP encoding and three known rate control algorithms the proposed algorithm provides a high-level quality for tested video sequences while the required buffering delay is low and the available bandwidth is fully used.