Joint Source Channel Coding Techniques Research Articles

Utilization of multi-dimensional source correlation in multi-dimensional single parity check codes

This paper proposes a joint source-channel coding (JSCC) technique that well utilizes multi-dimensional (MD) source correlation using MD single parity check codes (MD-SPCCs). The source is assumed to be described by the coupling of multiple first-order binary Markov processes. The knowledge about the source correlation is utilized in the channel decoding process where each component decoder utilizes a single dimension correlation of the MD source. To enhance performance and reduce the error floor, a rate-1 recursive systematic convolutional code is serially concatenated to the MD-SPCC via a random interleaver. Two decoding techniques are proposed for each component decoder, and the selection of the decoding technique depends on the strength of the source correlation, which may further enhance the performance of the proposed JSCC technique. Simulation results reveal that a significant performance gain can be achieved by exploiting the MD source correlation with the proposed JSCC technique compared with the case in which the source correlation is not utilized; more significant gains can be achieved with stronger source correlation, and with a larger dimensionality source correlation as well.

Packet-by-Packet Adaptive Scheme for Video Coding and Transmission Over Wireless IP Networks Using Rate-Compatible Punctured Turbo (RCPT) Codes

In this paper, we consider real-time video coding and transmission over packet-switched wireless IP networks, such as WLAN, using RCPT codes and joint source-channel coding (JSCC) with concentration on a packet-by-packet adaptive scheme. We present a systematic design methodology to enable the applicability of JSCC techniques. The performance of H.263+ video coding and transmission over wireless channel modeled as slow Rician fading channels using this approach is studied. Results indicate that a packet-by-packet adaptive RCPT-JSCC approach is of significant advantage for real-time video applications and leads to more acceptable video delivery quality over interference-limited and time-varying wireless networks.

A joint source-channel distortion model for JPEG compressed images

The need for efficient joint source-channel coding (JSCC) is growing as new multimedia services are introduced in commercial wireless communication systems. An important component of practical JSCC schemes is a distortion model that can predict the quality of compressed digital multimedia such as images and videos. The usual approach in the JSCC literature for quantifying the distortion due to quantization and channel errors is to estimate it for each image using the statistics of the image for a given signal-to-noise ratio (SNR). This is not an efficient approach in the design of real-time systems because of the computational complexity. A more useful and practical approach would be to design JSCC techniques that minimize average distortion for a large set of images based on some distortion model rather than carrying out per-image optimizations. However, models for estimating average distortion due to quantization and channel bit errors in a combined fashion for a large set of images are not available for practical image or video coding standards employing entropy coding and differential coding. This paper presents a statistical model for estimating the distortion introduced in progressive JPEG compressed images due to quantization and channel bit errors in a joint manner. Statistical modeling of important compression techniques such as Huffman coding, differential pulse-coding modulation, and run-length coding are included in the model. Examples show that the distortion in terms of peak signal-to-noise ratio (PSNR) can be predicted within a 2-dB maximum error over a variety of compression ratios and bit-error rates. To illustrate the utility of the proposed model, we present an unequal power allocation scheme as a simple application of our model. Results show that it gives a PSNR gain of around 6.5 dB at low SNRs, as compared to equal power allocation.

Source-adaptive power allocation for digital modulation

A novel joint source channel-coding technique called source-adaptive power allocation is introduced for the transmission of continuous-amplitude waveform source samples over a noisy channel. Starting from a binary or quaternary digital modulation scheme we apply a power control, which depends on the unquantized source samples, to the modulation signal points before they are transmitted over the channel. The resulting system shows strongly superior performance compared with conventional schemes.