Channel Modeling for a Wireless Transmission System

The resulting system provides video transmission over severely impaired wireless links within airborne networks.

A wireless transmission system provides high-quality video transmission over severely impaired wireless links between nodes that are connected within airborne networks. The target bit rate for the proposed video communication can be in the range between 24 Kbps and 384 Kbps with relatively high visual quality. However, the system may operate at extreme low bit rates down to 10 Kbps and at high bit rates up to 1.5 Mbps. To accommodate the large range of the data rate for heterogeneous wireless links and devices, the H.264 SVC standard for video coding and decoding was adopted.

Building blocks for the Video Communication System and the relationship among those building blocks.

To overcome the adversity of the video transmission in tactical airborne wireless networks with various constraints in terms of bandwidth, channel impairments, bursty errors, and packet loss, and media access control for battery operated end users, an end-to-end design principle embraces the joint source and channel coding as the key strategy, and the channel estimation and feedback as the means of providing adaptation. Various building blocks of the proposed system and the relationship between these building blocks are shown in the figure.

The proposed system can be divided into three major functionalities: (1) video source encoding and decoding, (2) error correction channel encoding and decoding, and (3) channel modeling and estimation. Since it has been well known that the joint source and channel coding is able to significantly improve the end-to-end quality of service for video transmission, these functional components can no longer be treated separately. This is evident from the figure that many of these building blocks are interconnected to facilitate joint design of the end-to-end system.

  • Video Encoding and Decoding. H.264 SVC standard video coding was used as a base for video encoding and decoding. Such a selection of standard video codec will enable the smooth exchange of motion imagery among different DoD agencies. In addition to this important consideration, H.264 SVC video encoding and decoding schemes are inherently able to facilitate the required error control strategies, including error resilience tools, data partition for unequal error protection, and error concealment. Significantly improved results have been obtained by joint source and channel coding based on MPEG-4 codec for video delivery over both packet loss network and wireless fading channels.
  • Channel Encoding and Decoding. The main reason for the incorporation of channel encoding and decoding is that the communication links between platform nodes within airborne networks can be severely impaired. The embedded error resilience in H.264 SVC video codec is inadequate to overcome such channel impairment. Additional error control strategies need to be implemented. A combination of error control codes was selected for the proposed system in order to combat the bursty error in the wireless links, as well as the packet loss error due to networking manageing management. In combination with intelligent interleaving, and the error-resilient MPEG-4 tools, a joint design of channel coding and source coding has been shown to achieve high end-to-end quality of service for composite channel impairments with both packet loss and burst fading errors.
  • Channel Modeling, Estimation, and Feedback. The design issues related to these functionalities will be crucial to the success of the end-to-end system design. The joint source and channel coding will rely on these functionalities to provide channel feedback information for an optimal allocation of bit budget for source coding and channel coding. Since the network links are changing constantly while there is latency between the channel feedback and algorithm adaptation, there is a need for the trade-off between accuracy and speed of the channel estimation. The fast estimation of partial channel information was investigated, and the corresponding adaptation schemes were developed. An additional functionality of the channel feedback is to decide whether or not the transcoding or scalable coding needs to be activated in order to reach certain edge users or edge devices that have considerably different bandwidth than the majority of the platforms within airborne networks.

The ultimate goal in robust video communication system design is to control and optimize the end-to-end performance adaptively according to the instantaneous channel conditions of the communication links. In the civil and commercial wireless communication applications, extensive studies on the channel and networking characteristics have been carried out and the design of communication systems can be optimized based on the instantaneous feedback of the channel information or the statistical behavior of the channel characteristics. To develop a robust video communication system for airborne networks, the first task will be to model and simulate the channel characteristics of these dynamic, ad hoc, and often hostile wireless links. Once adequate information on the channel characteristics of these links has been obtained, the joint source and channel

coding principles will be applied that have been successfully employed in commercial applications to the Air Force airborne networks.

In the project, the first-order Finite-State Markov Model (FSMM) has been employed to characterize the error and loss behavior of a dynamic wireless network and its implementation. To use the finite-state Markov model to model a dynamic wireless communication channel, one should decide the parameters of a finite-state Markov model. The process of using a series of known data to estimate the parameters of a finite-state Markov mode is called training a finite-state Markov model. After determining the parameters of a finite-state Markov mode, one generates a series of states, which hopefully can model the characteristics of the modeled wireless channel.

This work was done by Chang Wen Chen of the Florida Institute of Technology for the Air Force Research Laboratory. For more information, download the Technical Support Package (free white paper) at  under the Information Sciences category. AFRL-0114

This Brief includes a Technical Support Package (TSP).
Channel Modeling for a Wireless Transmission System

(reference AFRL-0114) is currently available for download from the TSP library.

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