Adaptive quality of service for integrated multimedia over wireless networks

Multimedia services are expected to become ubiquitous in wireless networks. This work addresses the problem of adaptive quality of service for mobile multimedia services under a power controlled wireless network using antenna arrays.; In the first part of this dissertation, we chose the signal to interference and noise ratio (SINR) of each user's channel as the quality of service index. Here, we direct our attention towards two problems. The first is to increase the SINR levels for multimedia users in a TDMA system, as much as the system can provide for, under the channel fading and interference conditions. Different users have distinct desired SINR levels according to their requested service types; our algorithm uses an iterative method to drive the SINR levels as close as possible to those desired levels. One result that we present in this dissertation, is that we prove that finding the optimum SINR for all users is an intractable problem. The SINR levels are improved without deteriorating quality for other types of users. Simulations presented here show a significant increase in the average SINR levels for multimedia users.; The second problem considered in this part is how to speedily initiate new users into the network by using lower complexity algorithms that yield reliable results. As shown in the simulations, our fast activation scheme can substantially reduce the time for activating new users into the system.; In the second part of this dissertation, we chose the channel rate as our quality of service index. Here, we focus on a CDMA system. We split the multimedia users' data into separately coded substreams. Each substream is treated as a virtual user. We show that choosing the optimal number of substreams per user, and the optimal SINR level per substream is also intractable. However, we show that under certain conditions, we can separate the problem into two parts: assigning a total power for each user, and finding the optimum number of substreams and SINR level per substream for each user. We show that the former problem can be handled by the same algorithm presented in the first part of the dissertation. Finally, we show how to find an optimal solution for the latter problem.