Channel Coding for Progressive Images in a 2-D Time-Frequency OFDM Block With Channel Estimation Errors

Coding and diversity are very effective techniques for improving transmission reliability in a mobile wireless environ- ment. The use of diversity is particularly important for multimedia communications over fading channels. In this work, we study the transmission of progressive image bitstreams using channel coding in a 2-D time-frequency resource block in an OFDM network, em- ploying time and frequency diversities simultaneously. In partic- ular, in the frequency domain, based on the order of diversity and the correlation of individual subcarriers, we construct symmetric -channel FEC-based multiple descriptions using channel erasure codes combined with embedded image coding. In the time domain, a concatenation of RCPC codes and CRC codes is employed to pro- tect individual descriptions. We consider the physical channel con- ditions arising from various coherence bandwidths and coherence times, leading to a range of orders of diversities available in the time and frequency domains. We investigate the effects of different error patterns on the delivered image quality due to various fade rates. We also study the tradeoffs and compare the relative effec- tiveness associated with the use of erasure codes in the frequency domain and convolutional codes in the time domain under different physical environments. Both the effects of intercarrier interference and channel estimation errors are included in our study. Specifi- cally, the effects of channel estimation errors, frequency selectivity and the rate of the channel variations are taken into consideration for the construction of the 2-D time-frequency block. We provide results showing the gain that the proposed model achieves com- pared to a system without temporal coding. In one example, for a system experiencing flat fading, low Doppler, and imperfect CSI, we find that the increase in PSNR compared to a system without time diversity is as much as 9.4 dB.

Published in:
IEEE Transactions on Image Processing, 18, 11, 2476-2490
Institute of Electrical and Electronics Engineers

 Record created 2012-12-20, last modified 2018-12-03

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