無線多媒體通訊已成為現今行動通訊中的一大熱門議題。對影像傳輸而言，在雜訊嚴重與頻寬有限的無線衰減通道中傳輸，壓縮技術與通道編碼是影像傳輸系統中必要的應用。然而，壓縮後的碼字位元有不同重要性的特性。我們在本論文中，利用位元重要性的不同，設計動態性通道編碼，使接收端能得到最佳的影像品質。

影像品質不只是由量化後位元的錯誤個數也由其錯誤的位置所影響。因此使用純量量化後採用位元平面分割傳輸，將資料依位元重要性使用不同的錯誤更正碼，此方法為非均勻錯誤保護編碼。依據頻寬、功率的限制及位元的不同重要性而使用非均勻錯誤保護編碼，搭配每個位元所對應的位元錯誤率，來估算接收影像的品質。並且在資料的功率分配也考慮非均勻錯誤保護的策略，優先滿足重要性較高之位元功率，此方法為非均勻功率配置。使得重要之位元除了可以得到較低碼率的錯誤更正碼保護外也得到較多位元功率使之抵抗通道雜訊的能力增強。

在本論文中我們加入了手機傳輸最大延遲時間和手機傳輸最大發射功率的限制。其目的是想模擬真實手機在作影像傳輸時，考慮到在有限傳輸頻寬和手機電池容量下，可以達到即時傳輸的效能。由實驗結果可以發現，在中、高通道訊雜比時動態性通道編碼所模擬的結果與窮舉搜尋的結果相同。而在低通道訊雜比時動態性通道編碼所模擬的結果與窮舉搜尋的結果稍差但是差距不大。

Multimedia communications over wireless channels have become a popular topic in recent mobile communication. It is necessary that we apply data compression and channel coding techniques in image transmission when we transmit images in wireless fading channel, which typically suffer serious signal degradation and have only limited bandwidths. However, different degrees of importance bits in a codeword are expectable. Therefore, we should design dynamic channel coding that takes this into account so that the decoded image at the receiver has the best quality.

Image quality is not only influenced by the number of incorrectly decoded data bits but also their positions in quantized pixels. We adopt the bit plane division to transmit after using scalar quantization and use different error correcting codes based on different degrees of importance bits. This method is called unequal error protection coding. According to unequal error protection applied on different bits, we can calculate the BER corresponding to each bit and estimate the quality of received image. Energy allocation is part of unequal error protection, where more energy is assigned to more important bits. We make the important bit not only receive more energy to make its ability to resist channel noise but also get lower code rate in its error correcting coding.

To simulate the practical situation in image transmission by cellular phones, we also consider the constraints of allowed maximum delay time and the maximum achievable launch energy of a data bit in cell-phone transmission. Simulation results show that dynamic channel coding has the SNR of image very close to exhaustive searching when the signal-to-noise ratio in channel is medium and high. Dynamic channel coding has slightly lower the SNR of image than exhaustive searching when the signal-to-noise ratio in channel is low.

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