There is a good analogy for explaining common information. Consider the news of the Indian Cricket Team winning a test match. It does not really matter from which source you heard the news. This is because the PTI has handed over the news commonly to all the "newsmakers". Now consider news of the retirement of SRT. The decision (and of course the feelings associated) about his retirement is only known to him (and his close people) and different media reports in its unique way. The uniqueness in the reporting generates new information, and as a reader (viewer/listener) it is required to gather all these distinct pieces of information.
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| SRT Retirement |
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| Lords Test Win |
The two news instances explains the term common information or shared information.
Relating this to the relay communication scenario, we can observe that if the source is able to send unique information to each of the relay nodes, then the relay nodes can be used to its full efficiency. But this is a seemingly difficult task. Natural information comes as a combination of common information and certain unique information.
Information needs to be processed at the source to identify the common and unique information, and then passed on to the relay. Each relay hence acts only as decode-forward nodes capable of only re-transmission of the information.
Information needs to be processed at the source to identify the common and unique information, and then passed on to the relay. Each relay hence acts only as decode-forward nodes capable of only re-transmission of the information.
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