Constant Bit Rate Research Articles

Improved VoWiFi cell capacity using A‐MPDU for frame aggregation in sixth‐generation WLAN standard

AbstractThe rapid progress in wireless communication technology and proliferation of multimedia applications, including voice over WiFi (VoWiFi), demand exploration of innovative approaches to enhance the network performance and quality of service. We propose a technique for enhancing the cell capacity of wireless local area network (WLAN) access point that provides VoWiFi service in the sixth‐generation WLAN standard. The proposed technique uses the aggregate media access control protocol data unit (A‐MPDU) for frame aggregation with constant bit rate (CBR) traffic in the WiFi 6 standard (i.e., IEEE 802.11ax). On the other hand, the retransmission of voice packets substantially deteriorates the VoWiFi cell capacity. We compare the results obtained from the use of WiFi 6 with currently existing WLAN standards, such as IEEE 802.11b/g/n/ac. This comparison focuses on distributed coordination function interframe spacing (DIFS) and arbitration interframe spacing (AIFS) using CBR traffic. Using our technique, we can increase the VoWiFi cell capacity for CBR traffic by 24.25% and 25.20% when using DIFS and AIFS, respectively, while considering the A‐MPDU frame aggregation technique.

Enhancement of VoWiFi cell capacity using A‐MPDU frame aggregation technique in WiFi 6 considering VBR traffic

SummaryThe rapid growth in wireless communication technology and the proliferation of multimedia applications, specifically Voice over Wireless Fidelity (VoWiFi), necessitate the exploration of innovative techniques for improving network performance and quality‐of‐service (QoS). This research paper presents an innovative approach to enhance VoWiFi cell capacity using aggregate medium access control protocol data unit (A‐MPDU) frame aggregation for variable bit rate (VBR) traffic. In this research article, we investigated the effect that the retransmission of voice packets has on the cell capacity of a wireless local area network (WLAN) standard that provides VoWiFi service while taking into account the A‐MPDU approach. When taking into consideration the constant bit rate (CBR) and VBR traffics, we compared the results obtained using WiFi 6 (i.e., IEEE 802.11ax) with older WLAN standards such as IEEE 802.11b/g/n/ac.

VoWiFi Cell Capacity Evaluation using WiFi 7 considering VBR Traffic

Deployment for Wireless Local Area Network (WLAN) technology is experiencing substantial growth. The transmission of Voice over WiFi (VoWiFi) is half-duplex due to its single-talk nature. In order to mitigate the inefficient utilization of available bandwidth, the technique of silent suppression is employed. This feature decreases the level of ambient noise and provides Variable Bit Rate (VBR) communication. To enhance the VoWiFi cell capacity, we utilized VBR traffic instead of Constant Bit Rate (CBR) traffic. In this study, we developed a mathematical model to find the number of VoWiFi users possible within a WLAN Access Point (AP) considering G.729 vocoder. Arbitration inter-frame space (AIFS) has been utilized in our study to evaluate the channel state prior to transmitting real-time data between user equipment (UE) devices. Additionally, short inter-frame spacing (SIFS) has been employed to transmit Request To Send (RTS)/Clear To Send (CTS) and Acknowledgement (ACK) frames, enabling an examination of the VoWiFi cell capacity. Again, to increase the VoWiFi cell capacity, we incorporated the compressed RTP (cRTP) protocol. Further, we conducted an analysis on the impact of retransmission on VoWiFi cell capacity. This analysis involved a comparison of the results using VBR traffic with the previous WLAN standards, namely IEEE 802.11b/g/n/ac/ax. We observed that the improvement in VoWiFi cell capacity in VBR traffic is approximately 2.6 times more than the CBR traffic. Further, our research revealed that the enhancement in VoWiFi cell capacity is approximately 1.5% higher when utilizing AIFS compared to Distributed Coordination Function (DCF) inter-frame spacing (DIFS).

Neural Speech Coding for Real-Time Communications Using Constant Bitrate Scalar Quantization

Neural Speech Coding for Real-Time Communications Using Constant Bitrate Scalar Quantization

Enhancing TCP via Hysteresis Switching: Theoretical Analysis and Empirical Evaluation

In this paper we study the relationship between the TCP packet loss cycle and the performance of time-sensitive traffic in data centers. Using real traffic measurements and analysis, we find that such loss cycles are not long enough to enable most partition-aggregate time-sensitive TCP applications to recover their packet losses via the TCP 3-dup ACKs mechanism. As a result, the Timeout (RTO) mechanism is frequently triggered, leading to the expansion of the flow completion times (FCT) of such applications by orders of magnitude. Hence, we seek an alternative method that does not change the virtual machines and that can effectively expand the loss cycle duration to enable short flows to finish their transfer without incurring the cost of the RTO. To this end, we propose a novel TCP-AQM mechanism that alternates between a slow constant bitrate (CBR) mode and a fast TCP rate via hysteresis switching to expand the loss cycle. We prove the stability of the proposed TCP-AQM via a control theoretic model, then evaluate its performance gains via small and large scale NS2 simulation and by real FPGA implementation of a prototype on the NetFPGA platform. The results show considerable improvements in FCT distribution and reduction of missed deadlines in simulation and real experiments.

Performance Enhancement of MANET based on Cross-layered Reconfigurable Hierarchical Routing Protocol

High speed data communication is the demanding factor in both commercial and defence applications. Several algorithms are proposed to support the high-speed data exchange while ensuring the quality, performance and reliability. However, there is still a gap, citing various compatibility issues with variety of transceiver technologies. This paper proposes a novel algorithm for enhancing the performance of mobile ad-hoc networks using Free-Space Optics (FSO). The FSO has the natural ability to the interference while capable of large bandwidth and excellent compatibility. Low power and adaptability are the features with which it has contributed to the latest technologies like storage area network, wireless area network etc. The proposed work uses optical spheres with a multi-transceiver system and a cross-layered reconfigurable routing mechanism. Parameters such as delay, residual energy, throughput, and drop are verified for the Crosslayered Reconfigurable Hierarchical Routing Optical Sphere (CRHROS) protocol for varying numbers of optical transceivers. The proposed work also compares the performance of two traffic sources, Constant Bit Rate (CBR) and Variable Bit Rate (VBR), for the proposed algorithm.

PreSR: Neural-Enhanced Adaptive Streaming of VBR-Encoded Videos With Selective Prefetching

Variable Bitrate (VBR) video encoding can significantly improve the quality-of-experience (QoE) of viewing users due to its capability to provide much higher quality-to-bits ratio compared to Constant Bitrate (CBR) video encoding. However, the streaming of VBR-encoded videos suffers from large variance of video chunk size, which may directly result in frequent rebuffering if not properly handled. In this paper, we propose a novel neural-enhanced adaptive streaming framework for VBR-encoded videos called PreSR, which performs selective prefetching of video chunks to achieve a higher QoE for viewers. The design of PreSR is motivated by an important observation obtained from our measurement, namely, the video quality improvement and bandwidth savings brought by neural enhancement are more pronounced for low-resolution video chunks with complex scenes. By taking the above fact and the time required for neural enhancement into account, we formulate the problem into an optimization problem. Given that the problem is NP-hard, we design the PreSR framework, which is based on the model predictive control theory and also considers key features of VBR-encoded videos. PreSR parallelizes the download of video chunks and model inference processes to fully utilize the available compute resources. Finally, we conduct extensive experiments with real traces, and the results show that PreSR outperforms the state-of-the-art algorithms with an improvement up to 11.25% in terms of the average QoE.

Opportunistic Routing with Multi-Channel Cooperative Neighbour Discovery

Due to the scattered nature of the network, data transmission in a distributed Mobile Ad-hoc Network (MANET) consumes more energy resources (ER) than in a centralized network, resulting in a shorter network lifespan (NL). As a result, we build an Enhanced Opportunistic Routing (EORP) protocol architecture in order to address the issues raised before. This proposed routing protocol goal is to manage the routing cost by employing power, load, and delay to manage the routing energy consumption based on the flooding of control packets from the target node. According to the goal of the proposed protocol technique, it is possible to manage the routing cost by applying power, load, and delay. The proposed technique also manage the routing energy consumption based on the flooding of control packets from the destination node in order to reduce the routing cost. Control packet exchange between the target and all the nodes, on the other hand, is capable of having an influence on the overall efficiency of the system. The EORP protocol and the Multi-channel Cooperative Neighbour Discovery (MCCND) protocol have been designed to detect the cooperative adjacent nodes for each node in the routing route as part of the routing path discovery process, which occurs during control packet transmission. While control packet transmission is taking place during the routing path discovery process, the EORP protocol and the Multi-channel Cooperative Neighbour Discovery (MCCND) protocol have been designed to detect the cooperative adjacent nodes for each node in the routing. Also included is a simulation of these protocols in order to evaluate their performance across a wide range of packet speeds using Constant Bit Rate (CBR). When the packet rate of the CBR is 20 packets per second, the results reveal that the EORP-MCCND is 0.6 s quicker than the state-of-the-art protocols, according to the findings. Assuming that the CBR packet rate is 20 packets per second, the EORP-MCCND achieves 0.6 s of End 2 End Delay, 0.05 s of Routing Overhead Delay, 120 s of Network Lifetime, and 20 J of Energy Consumption efficiency, which is much better than that of the state-of-the-art protocols.

Performance Analysis of Grid-Oriented Underwater Wireless Sensor Network by Deploying Constant Bit Rate Application

Underwater Wireless Sensor Network, often known as UWSN, is an appealing research zone because of the mysterious aspect of the ocean. A network of sensor nodes and vehicles that work together as part of the UWSN to collect information and carry out activities in collaboration. Because of the sensor nodes and the limited battery capacity, it is essential for UWSN to have an efficient network. The significant delay in propagation, network dynamics, and probability of error all influence underwater communication, making it difficult to exchange or update sensor nodes. This article put up the idea of a Grid-oriented underwater wireless sensor network (GO-UWSN) and carried out an analysis based on the criteria of energy consumption, utilization, average transmission delay, average jitter, average path loss and average E- 2- E delay in various modes.

A quality enhancement network with coding priors for constant bit rate video coding

Video coding can effectively compress data, while the introduction of compression artifacts degrades the visual quality and the performance of artificial intelligence video applications. Video quality enhancement (VQE) methods can improve compressed video quality without modifying the coding standard’s main modules. The existing VQE works mainly aim to improve video quality in the constant quantization parameter (CQP) coding mode. However, constant bit rate (CBR) coding mode is widely used in some streaming playback video applications, and VQE at CBR is more challenging than that at CQP. This article presents a novel Constant bit rate Video quality enhancement Network combined with Coding priors (CVCN). The proposed CVCN can be inserted into High Efficiency Video Coding (HEVC) codec as a CNN-based in-loop filter (LF) module or a post-processing module out of the codec. Moreover, we design a two-pass training strategy for the LF module to overcome multiple filtering. To adapt the QP diversity of CBR videos, we utilize the coding unit (CU)-wise QP prior by constructing a CU-wise QP adaptive module (CQAM) and a QP adaptive multi-scale residual block (QAMSRB) based on CQAM. We construct the CU-partition prior (CPP) by exploiting the relationship between the compression noise and CU partition information. A novel CPP spatial-attention block is proposed to combine the CPP with the self-attention module. Furthermore, the proposed CVCN can effectively enhance CBR videos at different bits per pixel (BPP) via a single model. Extensive experimental results show the superiority of the CVCN over state-of-the-art VQE approaches for CBR videos.

CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhancement

Constant bit rate (CBR) videos are widely used in streaming playback applications. However, the image quality of the CBR video is often unstable, especially for scenes with large motion. To this end, we design a new model to represent the distortion of High Efficiency Video Coding (HEVC) constant bit rate video, and propose a neural network for a constant bit rate video quality enhancement (CBREN). We propose a dual-domain restoration module (DRM) to jointly learn the prior knowledge in the pixel domain and the frequency domain. To address the degradation resulting from compression, we propose a two-step quantization degradation estimation strategy. The Inverse DCT (IDCT) Translation Unit (ITU) is used to constrain the quantization table of the constant bit rate video to a suitable range, and the Dynamic Alpha Unit (DAU) is used to fine-tune the quantization table according to the content of each frame. In order to effectively reduce the block distortion of different sizes produced in the compression process, we adopt a multi-scale network. Extensive experiments show that our approach can greatly enhance the quality of CBR compressed video. Moreover, our method can also be applied to constant quantization parameter (CQP) video enhancement tasks, and is certainly superior to existing methods.

Resilient quantized control under Denial-of-Service: Variable bit rate quantization

In this paper, we investigate a networked control problem in the presence of Denial-of-Service (DoS) attacks, which prevent transmissions over the communication network. The communication between the process and controller is also subject to bit rate constraints. For mitigating the influences of DoS attacks and bit rate constraints, we develop a variable bit rate (VBR) encoding–decoding protocol and quantized controller to stabilize the control system. We show that the system’s resilience against DoS under VBR is preserved comparing with those under constant bit rate (CBR) quantized control, with fewer bits transmitted. The proposed VBR quantized control framework in this paper is general enough so that the results of CBR quantized control under DoS and moreover the results of minimum bit rate in the absence of DoS can be recovered. In the last part of the paper, we propose two random VBR transmission protocols, in which not only the bit rate but also the interval between two transmission attempts are time-varying. These protocols enable us to prevent attackers from learning how transmissions are scheduled and to mitigate the influence of attacks specifically targeting at periodic transmission instants. A numerical example is given to illustrate the proposed solution approach.

Delay Jitter Performance Analysis and Traffic Splitting in Cellular-Based Multi-Access System

This paper addresses the problem of traffic splitting in the multi-access system for real-time applications in the uplink. We first understand the Long Term Evolution (LTE)-uplink-scheduling mechanism using Network Simulator () and then analyse the LTE-Packet Data Convergence Protocol queue length process at the end of User Equipment (UE). We provide an end-to-end delay jitter analysis on a single LTE network for the Constant Bit Rate (CBR) Traffic. We observe that the delay jitter only depends on the allocation (Transport Block Size) provided by eNodeB but not on the allocation rate. The main finding is the structural dependency of the delay jitter on one of the CBR parameters: inter-burst time. We then utilize this to develop an online-adaptive traffic splitting algorithm in the multi-access system to improve the overall delay jitter performance of the system. We formulate the traffic splitting problem as an optimization problem applicable to different objective functions. We validate and share our real-world experimental results for the video/Real-time Transport Protocol traffic.

Architecture of a Low Latency H.264/AVC Video Codec for Robust ML based Image Classification

The use of neural networks is considered as the state of the art in the field of image classification. A large number of different networks are available for this purpose, which, appropriately trained, permit a high level of classification accuracy.Typically, these networks are applied to uncompressed image data, since a corresponding training was also carried out using image data of similar high quality. However, if image data contains image errors, the classification accuracy deteriorates drastically. This applies in particular to coding artifacts which occur due to image and video compression. Typical application scenarios for video compression are narrowband transmission channels for which video coding is required but a subsequent classification is to be carried out on the receiver side. In this paper we present a special H.264/Advanced Video Codec (AVC) based video codec that allows certain regions of a picture to be coded with near constant picture quality in order to allow a reliable classification using neural networks, whereas the remaining image will be coded using constant bit rate. We have combined this feature with the ability to run with lowest latency properties, which is usually also required in remote control applications scenarios. The codec has been implemented as a fully hardwired High Definition video capable hardware architecture which is suitable for Field Programmable Gate Arrays.

Selective Encryption of the Versatile Video Coding Standard

versatile video coding (VVC) is the next generation video coding standard developed by the joint video experts team (JVET) and released in July 2020. VVC introduces several new coding tools providing a significant coding gain over the high efficiency video coding (HEVC) standard. It is well known that increasing the coding efficiency adds more dependencies in the video bitstream making format-compliant encryption with the standard more challenging. In this paper we tackle the problem of selective encryption of the VVC standard in format-compliant and constant bitrate. These two constraints ensure that the encrypted bitstream can be decoded by any VVC decoder while the bitrate remains unchanged by the encryption. The selective encryption of all possible VVC syntax elements is investigated. A new algorithm is proposed to encrypt in format-compliant and constant bitrate the transform coefficients (TCs) together with other syntax elements at the level of the entropy encoder. The proposed solution was integrated and assessed under the VVC reference software model version 6.0. Experimental results showed that encryption drastically decreases the video quality while the encryption is robust against several types of attacks. The encryption space is estimated in the range of 15% to 26% of the bitstream size resulting in a lightweight encryption process. The web page of this work is publicly available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://gugautie.github.io/sevvc/</uri> .

Visual Protection Using RC5 Selective Encryption in Telemedicine

The dissemination of the COVID-19 viruses now extends the usage of video consultations to share perspectives and virtual medical consultations, save expenses and health procedures, track the success of care proposals with detail, consistency, and ease from moment to time. The research aims to study the security of video consultations. We will also present the advantages and disadvantages of video consultations and the complications of their implementation. This paper mainly proposes a practical, high-efficiency video encoding technique for the new video encoding technique (HEVC) used in video consultations. The technology offered uses the RC5 block encryption algorithm for encrypting the sensitive bits of HEVC with low complexity, short encoding times in real-time implementations, format-compliant HEVC, and constant bitrate. In addition, this paper presents experimental results comparing the proposed HEVC RC5-based selective encryption (SE) algorithm with the other algorithms used in various operating modes using the Advanced Encryption Standard (AES). Also, this paper provides the security analysis of the proposed HEVC RC5-based SE algorithm for video consultation, including; the correlation analysis between the ciphered video and the original one, the histogram of the ciphered video, and the cipher cycle analysis. The security analysis results ensured that the proposed HEVC RC5-based SE algorithm for video consultation is safe and stable.

An MIH-enhanced fully distributed mobility management (MF-DMM) solution for real and non-real time CVBR traffic classes in mobile internet

The integration of wireless access networks has progressed rapidly in recent years. Within the mobile communication environment, the operator provides multiple interface options for the mobile node (MN) to switch its connection to any access network during mobility to achieve the quality of service (QoS) for various traffic classes. The conventional centralised mobility management (CMM) scheme lacks reliability, dynamic anchoring and a single point of failure. This stimulates the distributed mobility management (DMM) scheme to handle mobility at the access network rather in a centralised manner. Therefore, in this paper, an IEEE 802.21 media independent handover (MIH) enhanced fully DMM (MF-DMM) solution is proposed for real- and non-real-time constant and variable bit rate (CVBR) traffic classes for mobile internetworking applications. The performance factors of handover delay, packet loss rate, throughput and signalling overheads are compared with the existing CMM scheme. The simulation results prove that the presented MF-DMM technique considerably reduces the handover delay while switching to different access technologies and, thus, achieves seamless connection by managing mobile internet protocol (IP) traffic locally.

How index selection, compression, and recording schedule impact the description of ecological soundscapes.

Acoustic indices derived from environmental soundscape recordings are being used to monitor ecosystem health and vocal animal biodiversity. Soundscape data can quickly become very expensive and difficult to manage, so data compression or temporal down‐sampling are sometimes employed to reduce data storage and transmission costs. These parameters vary widely between experiments, with the consequences of this variation remaining mostly unknown.We analyse field recordings from North‐Eastern Borneo across a gradient of historical land use. We quantify the impact of experimental parameters (MP3 compression, recording length and temporal subsetting) on soundscape descriptors (Analytical Indices and a convolutional neural net derived AudioSet Fingerprint). Both descriptor types were tested for their robustness to parameter alteration and their usability in a soundscape classification task.We find that compression and recording length both drive considerable variation in calculated index values. However, we find that the effects of this variation and temporal subsetting on the performance of classification models is minor: performance is much more strongly determined by acoustic index choice, with Audioset fingerprinting offering substantially greater (12%–16%) levels of classifier accuracy, precision and recall.We advise using the AudioSet Fingerprint in soundscape analysis, finding superior and consistent performance even on small pools of data. If data storage is a bottleneck to a study, we recommend Variable Bit Rate encoded compression (quality = 0) to reduce file size to 23% file size without affecting most Analytical Index values. The AudioSet Fingerprint can be compressed further to a Constant Bit Rate encoding of 64 kb/s (8% file size) without any detectable effect. These recommendations allow the efficient use of restricted data storage whilst permitting comparability of results between different studies.

Performance Evaluation of AODV and DSR Routing Protocols for Flying Ad hoc Network Using Highway Mobility Model

The Flying Ad hoc Network (FANET) is a special type of mobile ad hoc network (MANET) that provides communications among Unmanned Aerial Vehicles (UAVs). These UAVs can reduce human intervention to a great extent by giving numerous applications under different domains such as transportation, military, healthcare, traffic monitoring, surveillance, etc. In FANET, communication is relatively challenging due to its complex infrastructure, unspecified architecture and rapid mobility of nodes. The work embodied in this paper is focused on traffic surveillance of highways using UAVs. UAVs can help to reduce the number of accidents by sharing real-time as well as the accurate status of highways among vehicles and the control station. On the other hand, they can also be used to track specific vehicles on the road. In FANET, both routing protocols and mobility models play a crucial role in the process of information exchange. In this paper, the comparison and performance evaluation of two well-known reactive routing protocols viz. Ad hoc On-demand Distance Vector (AODV) and Dynamic Source Routing (DSR) have been carried out using highway mobility model for traffic surveillance in FANET environment. Implementation of both protocols has been tested on several traffic patterns, mobility and varying network loads. Both AODV and DSR enable significant performance variations; however, they share on-demand behavior. Packet delivery fraction, average end-to-end delay, normalized routing load, packet loss, routing overhead and throughput are used to analyze the performance of both protocols. Based on experimental analysis using NS-2 under constant bit rate (CBR) and TCP traffic sources, it can be stated that AODV outperforms DSR in almost every aspect.

Stream-Based Visually Lossless Data Compression Applying Variable Bit-Length ADPCM Encoding.

Video applications have become one of the major services in the engineering field, which are implemented by server–client systems connected via the Internet, broadcasting services for mobile devices such as smartphones and surveillance cameras for security. Recently, the majority of video encoding mechanisms to reduce the data rate are mainly lossy compression methods such as the MPEG format. However, when we consider special needs for high-speed communication such as display applications and object detection ones with high accuracy from the video stream, we need to address the encoding mechanism without any loss of pixel information, called visually lossless compression. This paper focuses on the Adaptive Differential Pulse Code Modulation (ADPCM) that encodes a data stream into a constant bit length per data element. However, the conventional ADPCM does not have any mechanism to control dynamically the encoding bit length. We propose a novel ADPCM that provides a mechanism with a variable bit-length control, called ADPCM-VBL, for the encoding/decoding mechanism. Furthermore, since we expect that the encoded data from ADPCM maintains low entropy, we expect to reduce the amount of data by applying a lossless data compression. Applying ADPCM-VBL and a lossless data compression, this paper proposes a video transfer system that controls throughput autonomously in the communication data path. Through evaluations focusing on the aspects of the encoding performance and the image quality, we confirm that the proposed mechanisms effectively work on the applications that needs visually lossless compression by encoding video stream in low latency.