Adaptive bandwidth-constrained media-specific forward error correction for voice over Internet Protocol

Online video transmissions over wireless networks are rising in popularity and have already become part of our daily life. In the meantime, it is necessary to address a number of challenges ranging from the scarce resources, time-varying, and high error rates, to the fluctuating bandwidth, unveiling the need for an adaptive mechanism to ensure a good video transmission. Adaptive Forward Error Correction (FEC) techniques with Quality of Experience (QoE) assurance are appropriate to deliver QoE-aware video data to wireless users in dynamic and high error rates networks. This paper proposes an adaptive Video-aware FEC and Fuzzy Logic-based mechanism to shield realtime video transmissions against packet loss in wireless networks, improving both user experience and the usage of resources. The benefits and drawbacks of the proposed mechanism compared with exiting work are demonstrated through simulations and assessed with QoE metrics.

This paper introduces Adaptive and Reliable Forward Error Correction (AR_FEC), a novel mechanism that is designed to ensure reliable and efficient real-time video delivery for Unmanned Aerial Vehicles (UAVs). UAVs communicate using wireless channels that are inherently unreliable. AR_FEC is an application-layer solution that is inspired by edge computing. It incorporates several elements, specifically, adaptive Forward Error Correction (FEC), dynamic video quality, and Unequal Error Protection (UEP). AR_FEC dynamically adjusts the number of redundancy frames per video Group of Picture (GoP) based on packet loss rate, recent average round-trip times, and cross-layer information such as bandwidth usage and network traffic load. Moreover, AR_FEC reacts to congestion via a dynamic video quality algorithm. By adaptively determining suitable redundancy for the video I-frames and adjusting video quality, significant improvements are achieved. Comprehensive simulations demonstrate that the proposed AR_FEC protocol offers excellent performance for the number of delivered frames, latency, throughput, and delivery of frames, within the delay constraints for real-time multimedia streaming from UAVs.

Unmanned aerial vehicles (UAV) are rising in popularity together with video applications for both military and civilian use. Because of that, it is necessary to address a set of challenges related to the device movement, scarce resources as well as high error rates, making evident the need for an adaptive mechanism to strengthen video transmissions. Adaptive Forward Error Correction (FEC) techniques are known to be suitable to enhance the Quality of Experience (QoE) of video transmitted over error-prone wireless networks with high mobility. This book chapter proposes an adaptive video-aware FEC mechanism that uses motion vectors details to improve real-time UAV video transmissions, providing both higher user experience and better usage of resources. The benefits and drawbacks of the proposed mechanism along with the related work are analysed and put up for test through simulations and evaluated using QoE metrics.

Traditional Forward Error Correction (FEC) mechanisms can be divided into Packet level FEC (PFEC) mechanisms and Byte level FEC (BFEC) mechanisms. The PFEC mechanism of recovering from errors in a source packet requires an entire FEC redundant packet even though the error involves a few bit errors. The recovery capability of the BFEC mechanism is only half of the FEC redundancy. Accordingly, an adaptive Sub-Packet FEC (SPFEC) mechanism is proposed in this paper to improve the quality of video streaming data over wireless networks, simultaneously enhancing the recovery performance and reducing the end-to-end delay jitter. The SPFEC mechanism divides a packet into n sub-packets by means of the concept of a virtual packet. The SPFEC mechanism uses a checksum in each sub-packet to identify the position of the error sub-packet. Simulation experiments show the adaptive SPFEC mechanism achieves high recovery performance and low end-to-end delay jitter. The SPFEC mechanism outperforms traditional FEC mechanism in terms of packet loss rate and video Peak Signal-to-Noise Ratio (PSNR). SPFEC offers an alternative for improved efficiency video streaming that will be of interest to the designers of the next generation environments.

Video streaming over wireless channel encounters many challenges due to the time-varying characteristics of wireless channels and limited network bandwidth. In this paper, we investigate an adaptive forward error correction (FEC) scheme for streaming the stored MPEG-4 FGS bit-stream from the video server to the clients over wireless channel. In this scheme, the base layer is transmitted reliably and the enhancement layer is protected with unequal error protection (UEP) scheme. Taking the fine-grained characteristics of FGS into account, we propose a decodable rate maximized criterion to optimally allocate the bit rate between the source rate and the channel coding rate and dynamically adapt to the varying network condition. Experimental results show that Compared with fixed unequal error protection (UEP) and equal error protection (EEP), our proposed method can provide a better performance.

Real Time streaming Protocol (RTSP) is the de facto standard for streaming and almost all the set up boxes and media players support it. RTSP is a very simple text based protocol for streaming. And this simplicity is one of the main reasons for the popularity of the protocol. We propose the use of RTSP along with Real Time Protocol (RTP) for Adaptive Forward Error Correction (AFEC) based streaming. The idea is to use the existing semantics of the protocol with minimal overloading to achieve the goal. The use of the RTP is solely to provide a mechanism for the packet sequence number, which is the main requirement to ensure reliability. Since, we will be using existing protocol semantics (overloading the existing semantics), we do not have the luxury of using Negative Acknowledgements (NACKs) or information rich packet headers. However, we can add the intelligence in the client/server to interpret the overloaded data and achieve the same results.

IEEE 802.16/WiMAX-based broadband and mobile wireless access is expected to be a significant component in the next generation (e.g., beyond 3G, 4G) wireless systems. IEEE 802.16/WiMAX standard, which incorporates several advanced radio transmission technologies such as orthogonal-frequency division multiplexing (OFDM), adaptive modulation and coding, and adaptive forward error correction (FEC), is designed to provide broadband wireless capability using a well-defined quality-of-service (QoS) framework. Therefore, this is a promising technology for wireless services requiring high- rate transmission (in the range of tens of Mbps) and strict QoS requirements in both indoor and outdoor environments. This technology is currently of big interest to researchers and practitioners involved in the design, analysis, installation, and management of mobile broadband wireless access systems and networks. The objective of this tutorial is to provide a complete overview on the IEEE 802.16/WiMAX standard and the current state-of-the-art research on the design, analysis, and optimization of IEEE802.16/WiMAX-based networks. The key technical challenges related to protocol engineering in these networks are described. The aim is to provide a survey on the emerging IEEE 802.16/WiMAX technology rather than an in-depth study on a specific protocol engineering problem. An overview of the different evolutions of the IEEE 802.16/WiMAX standard broadband wireless access (BWA) is presented and the open research issues in protocol engineering (e.g., for radio resource management, mobility support, security) are identified. A comprehensive survey on radio resource management, traffic scheduling, admission control, mobility management, and security mechanisms for IEEE 802.16/WiMAX are provided. A comparative performance study among the third-generation (3G) and the IEEE 802.16-based systems is provided. Several applications (e.g., wireless telemedicine and e-health services), services and deployment scenarios are described and the necessary protocol design and engineering issues are outlined.

The video delivery over wireless networks has risen in popularity in the recent years. However, in order to provide a high quality of experience (QoE) to the end users, it is necessary to deal with several challenges ranging from the fluctuating bandwidth and scarce resources to the high error rates. The use of these error-prone networks unveils the need for an adaptive mechanism to ensure the quality of the delivered video streams. Adaptive forward error correction (FEC) techniques with QoE assurance are desired to protect the stream, preserving the video quality. The adaptive FEC-based mechanism proposed in this article uses several video characteristics and packet loss rate prediction to shield real-time video transmission over static wireless mesh networks, improving both user experience and the usage of resources. This is possible through a combination of a random neural network, to categorise motion intensity of the videos, and an ant colony optimisation scheme, for dynamic redundancy allocation. The benefits and drawbacks are demonstrated through simulations and assessed with QoE metrics, showing that the proposed mechanism outperforms both adaptive and non-adaptive schemes.

Congestion in ATM communications is a significant issue as it can have a dramatic effect on critical or real-time data. Forward error correction (FEC) can be used to decrease or eliminate this effect. Conventional FEC has a uniform error correction capability, which can result in poor bandwidth utilization. Adaptive FEC is more suitable because it allows a different quality of service for each data type. In this paper a versatile adaptive FEC technique is proposed. It is shown that this technique can decrease the effect of congestion and increase the channel utilization.

Recently, plenty of voice quality measuring devices of VoIP(Voice over Internet Protocol) service is developed to support high quality VoIP service for communication. However, the existing voice quality measuring devices select the unique measurement method, which uses PESQ(Perceptual Evaluation of Speech Quality) or R-factor only. However, the each voice quality measurement method differs from its usage and assumed range, which leads to the slightly different results at the same testing area for voice services. At the actual VoIP service business and related regulatory organizations, they request to use the above two types of algorithm at the same time for measuring voice quality. However, the development expenses are very high to use the above two types of algorithm at the same time for measuring voice quality due to additional resources and subsidiary devices. VoIP business and regulatory agencies also request the hardware specification of the voice quality measurement device is similar to that of VoIP service user terminal, considering VoIP service supply at the wireless mobile internet such as WiBro(Wireless Broadband). In this paper, we present the voice quality measurement method by using of the above two algorithms at the one physical measurement device at the same time for more accurate and reliable VoIP voice quality measurement. In addition, we introduce the development method of the voice quality measurement device with relatively low cost.

We report the implementation experience and experimental evaluation of a staggered adaptive forward error correction (FEC) system for video multicast over wireless LANs. In the system, the parity packets generated by a cross-packet FEC code are transmitted at a time delay from the original video packets, i.e. staggercasting video stream and FEC stream in different multicast groups. The delay provides temporal diversity to improve the robustness of video multicast, especially to enable the clients to correct burst packet loss using FEC and to achieve seamless handoff. A wireless client dynamically joins the FEC multicast groups based upon its channel conditions and handoff events. We have implemented the system including the streaming server and client proxy. A novel software architecture is designed to integrate the FEC functionality in the clients without requirement for changing the existing video player software. We conduct extensive experiments to investigate the impact of FEC overhead and the delay between the video stream and FEC stream to the video quality under different interference levels and mobile handoff durations. The efficacy of staggered adaptive FEC system on improving video multicast quality is demonstrated in real system implementation.

Network high definition video applications such as video calls and videoconferences have been increasingly developed recent years. When congestions occur and network environment becomes unstable, the network applications have to deal with such issues like delay, packet loss and bandwidth constraints. In this paper, we describe a high definition H.264/AVC video transmission system with network adaptive function based on real-time transport protocol (RTP) and real-time transport control protocol (RTCP). The adaptive system is composed of three components: 1) transmission management (TM) which focuses on network state monitoring, bandwidth allocating and transmission rate control; 2) a feedback-based adaptive forward error correction (AFEC) scheme using Reed Solomon (RS) code; 3) adaptive video encoding (AVE) that adjusts the bitrate of video streaming according to the bandwidth constraint information offered by TM. In our paper, delay, packet loss and bandwidth constraints are generated by the network bottleneck and congestions. Hence, the main idea is to enhance the bitrate of video streaming adapt to the bandwidth constraints. In addition, we integrate AFEC with RTCP to feedback bandwidth status and make the adaptive video streaming more robust under packet loss environment. Here we call it interactive adaptive forward error correction (IAFEC). The test result shows IAFEC can be adaptive to strict bandwidth constraints and high packet loss rates.

Visual and Vocal communication can be transferred through Circuit switched Network or Packet Switched Network. Public Switched Telephone Network (PSTN) is not an affordable option therefore over existing packet switched network, Voice over Internet Protocol (VoIP) has become a preferable alternative due to its reduced cost. However, despite its reduced cost it has so many challenges which affect its successful deployment. This is because; the quality of VoIP is mainly affected by jitter, delay, packet loss and some other parameters. This research was carried out to evaluate voice quality in VoIP experimentally under different scenarios using OPNET network simulator. A VoIP network was simulated using Riverbed modeler academic edition 17.5 and the behavior and quality of VoIP was studied and analyzed under different scenarios. The results of the analysis and the performance evaluation are presented in this paper. This work can guide researchers and designers to design a network for VoIP services and its deployment. It can also guide the operators to choose speech compression technique for better voice quality.

Voice over Internet protocol (VoIP) is the transmission of voice over networks using the internet protocol. IP networks have become increasingly popular in the past few years, due to the exponential growth of the public internet leading the way in to the IP world. Long distance calls, especially international subscriber dialing (ISD), can be made significantly less expensive when supported by an IP network rather than by the PSTN. Any call made is supported by VoIP technology and it involves the transmission of many individual packets over an IP network. Thus the cost of VoIP calls in part depends on the number and size of packets that must be transmitted. So voice (source) compression technology is used to reduce the amount of bandwidth required in order to reduce cost and to reduce the delay impact from network. But, compression techniques increase the network impairments also. When packets are transmitted through network they are affected by impairments, like packet drop and end-to-end delay. The main agenda of VoIP service providers is to provide good quality of service (QoS). The objective of this research work done is to minimize, the error introduced in channel due to the above mentioned network impairments and hence improve the quality of sound, and also analyze the voice quality with and without use of channel coding scheme. There are two measuring techniques, subjective and objective. In subjective method we measure the mean opinion score (MOS) and use matching algorithms in objective methods to measure the difference between decoded outputs of source coding system and joint source-channel coding system. In this work, the objective method is used and it is observed that the performance of the system improves significantly

The growth of Internet has led to the development of many new applications and technologies. Voice over Internet Protocol (VoIP) is one of the fastest growing applications. Calculating the quality of calls has been a complex task. The ITU E-Model gives a framework to measure quality of VoIP calls but the MOS element is a subjective measure. In this paper, we discuss a novel method using Random Neural Network (RNN) to accurately predict the perceived quality of voice and more importantly to perform this on real-time traffic to overcome the drawbacks of available methods. The novelty of this model is that RNN model provides a non-intrusive method to accurately predict and monitor perceived voice quality for both listening and conversational voice. This method has learning capabilities and this makes it possible for it to adapt to any network changes without human interference.