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Most of my research is around the central idea of Joint Source-Channel Coding, in here you may find everything related with the JSCC project in our research group: why we started this project, who is in the group, what we have accomplished so far, the impact of JSCC on real-life applications, who are also working on JSCC, and the future of this project.

Although Shannon's information separation theorem points out that in a communication system we can optimize the source coder and the channel coder separately without sacrificing overall performance, it is only valid upon the assumption of allowing infinitely long codewords (infinitely long delay) and point-to-point transmission (no multipath fading), which are not correct in general. For example, in real-time communication like videoconferencing, any delay greater than 100ms is not tolerable; in wireless transmission, multi-path fading is common. Joint source-channel coding takes advantage of this fact and jointly optimize the source-channel coders when the assumptions are invalidated, and thus achieving performance gains.

The easiest example is a channel capacity-limited video communication system: both the source and channel coders need bits, spending more bits on the source means not enough channel protection, which leads to channel errors, received video quality is bad; spending more bits on the channel means enough protection and no transmission errors, but then you have overcompressed the source material and received video quality is again bad. There is a trade-off and balance point where the channel capacity is optimally allocated between source and channel to achieve the best received video quality.

The JSCC project addresses the problems in establishing a JSCC framework and trying to optimize it. Up to now we have investigated image/video transmission in AWGN/fading wireless channels, for our next step we are looking into network links (Joint Source-Network Coding)