A novel adaptive mapping from physical measurements in a non-stationary wireless environment to a variable length Markov chain (VLMC) model is proposed in this research. The proposed scheme consists of two main components: the estimation of channel signal-to-noise ratio (SNR) distribution and discrete VLMC modeling. To obtain the channel SNR distribution, a kernel density stimation algorithm is used to track local hanges of channel statistics resulting from varying mobile environments. With the estimated channel SNR distribution, an iterative partitioning mechanism is performed to construct the VLMC model, which yields a much larger and structurally richer class of models than ordinary higher order Markov chains. Application of this model is presented, which is the computation of fading parameters such as the fading duration and the level crossing rate. The accuracy of the proposed VLMC scheme and the performance of its applications are demonstrated via simulation in a micro-cell non-stationary wireless environment.
Dynamic throughput estimation for wireless multimedia transmission is examined in this research. A novel dynamic mapping scheme from measurements of a real-world wireless environment to a discrete Markov model is first proposed to simulate wireless video packet-based transmission. Then, the available throughput is estimated by using the derived discrete Markov model together with the number of negative acknowledgments (NACK) that are fed back from the receiver to the transmitter. The estimated throughput is used to perform the adaptive region-of-interest (ROI) rate control based on the multiple constraint optimization. The performance of the channel mapping scheme, the throughput estimation, and the region-of-interest rate control is demonstrated by simulating a micro-cell environment and ITU-T H.263+ video standard. Performance variation due to different estimation of throughput is compared and the performance improvement due to the multiple constraint optimization is demonstrated both in objective and subjective quality.
This research presents a robust video transmission scheme over fading wireless channels that relies on a coordinated protection effort in handling channel and source variations dynamically. Given the priority of each source packet and the estimated channel condition, an adaptive protection scheme based on joint source-channel criteria is investigated via proactive forward error correction (FEC). A product code is developed based on both the Reed-Solomon (RS) code and rate- compatible punctured convolutional (RCPC) codes. We explore the dynamic programming algorithm in matching the relative priority of source packets to instantaneous channel conditions. To obtain a realistic joint source-channel adaptation scheme, special attention has been paid to the channel status feedback in terms of accuracy and delay, the product code tradeoff, and the involved packetization efficiency. The performance improvement due to adaptation via a dynamic programming solution is demonstrated by simulating the wireless transmission of error resilient ITU-T H.263+ video.
Quality of video transmitted over time-varying wireless channels relies heavily on the coordinated effort to cope with both channel and source variations dynamically. Given the priority of each source packet and the estimated channel condition, an adaptive protection scheme based on joint source-channel criteria is investigated via proactive forward error correction (FEC). With proactive FEC in Reed Solomon (RS)/Rate-compatible punctured convolutional (RCPC) codes, we study a practical algorithm to match the relative priority of source packets and instantaneous channel conditions. The channel condition is estimated to capture the long-term fading effect in terms of the averaged SNR over a preset window. Proactive protection is performed for each packet based on the joint source-channel criteria with special attention to the accuracy, time-scale match, and feedback delay of channel status estimation. The overall gain of the proposed protection mechanism is demonstrated in terms of the end-to-end wireless video performance.
Transmission of continuous media such as video over time- varying wireless communication channels can benefit from the use of adaptation techniques in both source and channel coding. An adaptive feedback-based wireless video transmission scheme is investigated in this research with special emphasis on feedback-based adaptation. To be more specific, an interactive adaptive transmission scheme is developed by letting the receiver estimate the channel state information and send it back to the transmitter. By utilizing the feedback information, the transmitter is capable of adapting the level of protection by changing the flexible RCPC (rate-compatible punctured convolutional) code ratio depending on the instantaneous channel condition. The wireless channel is modeled as a fading channel, where the long-term and short- term fading effects are modeled as the log-normal fading and the Rayleigh flat fading, respectively. Then, its state (mainly the long term fading portion) is tracked and predicted by using an adaptive LMS (least mean squares) algorithm. By utilizing the delayed feedback on the channel condition, the adaptation performance of the proposed scheme is first evaluated in terms of the error probability and the throughput. It is then extended to incorporate variable size packets of ITU-T H.263+ video with the error resilience option. Finally, the end-to-end performance of wireless video transmission is compared against several non-adaptive protection schemes.
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