Joint Source-channel Rate Allocation Research Articles

Joint source–channel rate allocation with unequal error protection for space image transmission

High reliable and efficient image transmission is of primary importance for space communications. In the traditional space image transmission system design, the source coding module and channel coding module are separated. This separate design, although simple to be implemented, cannot explore the transmission performance to the most. In this article, we propose a joint source–channel rate allocation framework to improve the space image transmission performance. A joint rate allocation algorithm based on the packet loss rate is proposed. For certain required system transmission rate, the optimal source coding and channel coding rate pair can be selected from pre-configured code rate sets by sliding search. In addition, our design has taken into account the progressive scalability feature of the image compression results. Each of the source coding output packets is divided into several sub-packets with different levels of significance and then channel coding with different rates is applied on these sub-packets to achieve unequal error protection. Simulation results show that the proposed joint design can significantly improve the image reconstruction quality. Compared with the traditional separate design, the proposed joint design can achieve 3–5 dB performance gain in terms of peak signal-to-noise ratio.

Joint source-channel rate allocation and client clustering for scalable multistream IPTV.

We design a system framework for streaming scalable internet protocol television (IPTV) content to heterogenous clients. The backbone bandwidth is optimally allocated between source and parity data layers that are delivered to the client population. The assignment of stream layers to clients is done based on their access link data rate and packet loss characteristics, and is part of the optimization. We design three techniques for jointly computing the optimal number of multicast sessions, their respective source and parity rates, and client membership, either exactly or approximatively, at lower complexity. The latter is achieved via an iterative coordinate descent algorithm that only marginally underperforms relative to the exact analytic solution. Through experiments, we study the advantages of our framework over common IPTV systems that deliver the same source and parity streams to every client. We observe substantial gains in video quality in terms of both its average value and standard deviation over the client population. In addition, for energy efficiency, we propose to move the parity data generation part to the edge of the backbone network, where each client connects to its IPTV stream. We analytically study the conditions under which such an approach delivers energy savings relative to the conventional case of source and parity data generation at the IPTV streaming server. Finally, we demonstrate that our system enables more consistent streaming performance, when the clients' access link packet loss distribution is varied, relative to the two baseline methods used in our investigation, and maintains the same performance as an ideal system that serves each client independently.

Source-channel rate optimization for progressive image transmission over block fading relay channels [Transactions Papers

In this paper, we are concerned with the design and analysis of joint source-channel coding schemes for block fading channels with relay-assisted distributed spatial diversity. Assuming a progressive image coder with a constraint on the transmission bandwidth, we formulate a joint source-channel rate allocation scheme that maximizes the expected source throughput. Specifically, using Gaussian as well as BPSK inputs on flat Rayleigh fading channels, we lower bound the average packet error rate by the corresponding mutual information outage probability, and derive the average throughput expression as a function of channel code rates as well as channel SNR for both a frequency-division multiplexing-based baseline system without relaying, and a half-duplex relay system with a decode-and- forward protocol. At high signal-to-noise ratio (SNR), for the systems considered in this paper, we show that our rate optimization problem is a convex function of the channel code rates, and we show that a known recursive algorithm can be used to predict the performance of both systems.

Joint Source-Channel Rate Allocation in Parallel Channels

A fast rate-optimal rate allocation algorithm is proposed for parallel transmission of scalable images in multichannel systems. Scalable images are transmitted via fixed-length packets. The proposed algorithm selects a subchannel, as well as a channel code rate for each packet, based on the signal-to-noise ratios (SNRs) of the subchannels. The resulting scheme provides unequal error protection of source bits and significant gains are obtained over equal error protection schemes. An application of the proposed algorithm to JPEG2000 transmission shows the advantages of exploiting differences in SNRs between subchannels. Multiplexing of multiple sources is also considered, and additional gains are achieved by exploiting information diversity among the sources.

Adaptive Joint Source Channel Rate Allocation Policies for Delay Sensitive Applications Over Fading Channels

In this correspondence, we consider a problem of optimal source, channel coding rate pair allocation over a wireless link based on the channel fading state and the queue length of the transmitter. The source is delay sensitive. Therefore, our objective is to minimize the mean delay under given mean power and distortion constraints. We show that by jointly optimizing the source and channel rates, one can gain substantially in performance as compared to only source or channel rate optimization, as is usually considered in the literature. This is shown for single user, single-input-single-output (SISO), multiple-input-multiple-output (MIMO), and multiuser systems. The methods used are from Markov decision theory

Dependent Source and Channel Rate Allocation for Video Transmission

A general joint source-channel rate allocation scheme for a dependent video coding environment is presented. It is assumed that the source coders rely on motion-compensated prediction, and thus error propagation will contribute significantly to the degradation of the reconstructed video. The rate allocation methodology is based upon generation of operational distortion-rate characteristics. In order to reduce computational complexity, these surfaces and the channel code performance are modeled. An analytic method for computing optimal rate allocation across frames in a video sequence is then introduced. Comparisons are made between equal error protection and unequal error protection over video frames. Results are shown for H.263 compressed video used in conjunction with rate-compatible punctured convolutional codes.