Rate Allocation for Noncollaborative Multiuser Speech Communication Systems Based on Bargaining Theory

Abstract

We propose a novel rate allocation algorithm for multiuser speech communication systems based on bargaining theory. Specifically, we apply the generalized Kalai-Smorodinsky bargaining solution since it allows varying bargaining powers to match the dynamic nature of speech signals. We propose a novel method to derive bargaining powers based on the short-time energy of the input speech signals, and subsequently allocate rates accordingly to the users. An important merit of the proposed framework is that it is general and can be applicable for resource allocation across a variety of multirate speech coders, and it is robust to a variety of speech quality metrics. The proposed system is also shown to involve a quick and low-complexity training process. We generalize the algorithm to scenarios in which users have unequally weighted priorities. These scenarios might arise in emergency situations, in which certain users are more important than others. The proposed rate allocation system is shown to increase the utility measures for both the Itakura and segmental signal-to-noise ratio (SNR) functions relative to the baseline system that performs uniform rate allocation. Additionally, although the instantaneous bitrate resolution of the speech encoder is not changed, the proposed system is shown to increase the short-time average bitrate resolution, and therefore provides a greater number of operational rate modes for the network