Joint source-channel coding for delay-constrained iterative resource allocation algorithms

Before achieving convergence, iterative resource allocation algorithms may result in degraded link quality that presents a challenge for the transmission of delay constrained multimedia traffic because of the impossibility for retransmission of frames received with errors. In this paper, a novel approach to solve this problem is presented by proposing the use of a source and channel coding scheme matched to the performance of the algorithm during iterations. The solution uses a JSCC scheme based on incremental redundancy and single feedback for transmission under strict delay constraints. The presented results, based on three widely representative iterative algorithms, show that the novel approach notably reduces the probability of transmissions with excessive distortion. The results show an increase of 12 % in relative values for the probability of links achieving target end-to-end distortion values, reduce the negative effects of degraded channels when performing iterations and also effectively absorb the effect of channel changes over time. These characteristics are specially useful for cognitive radio learning algorithms to mitigate the distortion increase during the exploratory phase.