Soft decoding algorithms for optimized JPEG 2000 wireless transmission over realistic MIMO-OFDM systems

In this paper, we investigate a new cross layer PHYsical/APPlication (PHY-APP) communication strategy for scalable JPEG 2000 wireless image transmission over a realistic Multiple-Input Multiple-Output (MIMO) system. To exploit the channel diversity, we use a closed-loop MIMO-OFDM scheme. In the proposed scheme, the MIMO channel is decomposed into several hierarchical Single-Input Single-Output (SISO) subchannels by using a precoding approach. The scalable bitstream is divided into hierarchical quality layers which are passing through these SISO subchannels. In this paper, we propose a Joint Source-Channel (JSC) decoding approach based on soft-inputs decoding techniques to decrease the error rates at the reception without introducing extra redundancy. This scheme involves the serial concatenation of a soft-input soft-output Reed-Solomon (RS) decoder and a soft-input arithmetic decoder that were integrated into the JPEG 2000 wireless decoder. The objective of our approach is to guarantee the Quality of Service (QoS) required by the user for varying channel states. To this end, a link adaption strategy adjusting all the systems parameters of each SISO sub-channel (number of used subchannels, modulation order, Forward Error Correction (FEC) code capability, source coding rate) is also adopted in order to maximize the image visual quality at the reception. Thus, Unequal Error Protection (UEP), Unequal Power Allocation (UPA), adaptive modulation and source coding rate are provided for each quality layer. Simulation results of the optimized adaptive strategy illustrate good image quality improvements at the receiver side compared to a non adaptive strategy, with significant Peak Signal to Noise Ratio (PSNR) gains, especially for a realistic noisy channel provided by a 3D ray-tracing software.