UC San Diego

When we transmit multimedia through wireless channels, we need to protect source bits from channel noise. However, due to the constraints on the channel resources, source and channel bits should share the resources optimally in the sense of distortion or throughput. That is, the problem is how to allocate channel resources such as the bandwidth, diversity, or transmit power to the source and channel under system constraints. In addition, due to the unequal priority of source packets, performance can be improved by assigning unequal channel resources to the packets based on their priority. In this dissertation, we introduce an information-theoretic framework which allows us to analyze the system performance mathematically with unequal allocation of the channel resources with respect to the unequal priority of the source packets. By applying the information theoretic framework, an algorithm to find the throughput-optimal unequal error protection (UEP) is derived. The first example to apply this framework is the progressive image transmission over block fading channels with relay-assisted distributed spatial diversity. Assuming a progressive image coder with a constraint on the transmission bandwidth, we formulate a joint source- channel rate allocation scheme that maximizes the expected source throughput. Specifically, using Gaussian as well as BPSK inputs on at Rayleigh fading channels, we lower bound the average packet error rate by the corresponding mutual information outage probability, and derive the average throughput expression as a function of channel code rates as well as channel signal-to-noise ratio (SNR) for a frequency-division multiplexing-based system both without relaying and with a half-duplex relay using a decode-and- forward protocol. At high SNR, the optimization problem involves a convex function of the channel code rates, and we show that a known recursive algorithm can be used to predict the performance of both systems. The second example is the layered transmission of a Gaussian source over multiple relays using superposition coding. At first, we analyze the outage probability and performance in terms of average throughput and distortion for decodeand-forward (DF) protocols with single-layer and superposed two-layer coding. For the superposition coding approach, we consider different power allocations to the base and enhancement layers. Then, we propose a simple protocol which assigns a pre-determined number of relays to individual layers instead of repeating the superposition coded packet at the relay. We also present numerical results based on the analysis to compare the performance. We then consider a practical application where motion compensated fine granular scalable (MC-FGS) video is transmitted over multi -input multi-output (MIMO) wireless channels and the leaky and partial prediction schemes are applied in the enhancement layer of MC-FGS video to exploit the tradeoff between error propagation and coding efficiency. For reliable transmission, we propose UEP by considering a tradeoff between reliability and data rates, which is controlled by forward error correction (FEC) and MIMO mode selection to minimize the average distortion. In a high Doppler environment where it is hard to get an accurate channel estimate, we investigate the performance of the proposed MC-FGS video transmission scheme with joint control of both the leaky and partial prediction parameters and the UEP. In a slow fading channel where the channel throughput can be estimated at the transmitter, adaptive control of the prediction parameters is considered