Network information theory is the fundamental theory on technologies such as wireless communications, sensor networks, and distributed video coding, which require the simultaneous optimization of communication rates for many users or terminals. In general, research in information theory is classified into two categories: the "direct theorem," which states that there exists a code which achieves a certain communication rate, and the "converse theorem," which states that there is no code above a certain communication rate. In many problems in network information theory, there is a gap between the region of communication rates where the existence of a code is guaranteed and another region where the absence of a code is proven, which implies that the true limits of coding efficiency have not been clarified. It is strongly desired to bridge this gap from the viewpoint of designing communication systems. To solve this problem, it is necessary to improve both the direct and converse theorems, but the converse theorem in particular is known to be significantly more difficult than the direct theorem since there are few existing mathematical techniques that can be used for its proof.

The award recipient has been known worldwide as one of the few researchers who have boldly challenged the research on converse coding theorems and achieved solid results. One of the unsolved problems to which he has made a major contribution is the proof of the converse theorem for the optimality of separate coding of analog and digital signals. This is the problem of proving that, in a system consisting of many nodes such as a sensor network (Fig.1), it is optimal to first quantize the observed analog data into digital signals and then perform distributed data compression on the obtained digital signals shown as Fig.2. Such a coding method has been used for a long time. It is considered to be highly superior because of ease of system design, but it has been unknown since the 1970’s whether it is truly optimal or not. In a series of papers(1)〜(3), the award recipient proved that separate analog-digital coding is optimal when the observed signals have a certain correlation structure. These results have attracted a lot of attention not only from theoretical researchers but also from researchers studying in applied fields. In fact, the three papers have been cited a total of about 1,000 times, and it is quite rare to have such a large impact in the field of information theory.

The award recipient has also made groundbreaking achievements in the field of information- theoretic security. For example, he proposed a model of wiretap channel in networks including relays and showed the optimal coding method for such networks(4). This research is known as an important achievement in physical layer security, where security is guaranteed at lower layers rather than at upper layers employed in technologies such as public key cryptography. In addition

to the high attention, these results were also ahead of their time since they were published before physical layer security gained attention in the late 2000s.

Recently, he proposed a completely new and original analysis method for the exponential strong converse theorem in distributed coding, which had been unsolved since the 1970s(5). He also performed security analysis for side-channel attacks on common key cryptography by applying this method of analysis(6). This result is very important in the sense that it connects network information theoretic methods to information-theoretic security analysis.

As described above, the award recipient has achieved remarkable results for many unsolved problems, and his achievements are highly regarded both nationally and internationally, and their future development is also anticipated. The recipient's achievements are extremely significant and worthy of the IEICE Achievement Award.

References

1. Y. Oohama, “Gaussian Multiterminal Source Coding,” IEEE Trans. Inform. Theory, vol.43, no.6, pp.1912-1923, Nov. 1997.
2. Y. Oohama, “The Rate-Distortion Function for the Quadratic Gaussian CEO Problem,” IEEE Trans. Inform. Theory, vol.44, no.3, pp.1057-1070, May 1998.
3. Y. Oohama, “Rate-Distortion Theory for Gaussian Multiterminal Source Coding System with Several Side Informations at the Decoder,” IEEE Trans. Inform. Theory, vol.51, no.7, pp.2577-2593, July 2005.
4. Y. Oohama, “Capacity Theorems for Relay Channels with Confidential Messages,” in Proc. IEEE Int. Symp. Inform. Theory, pp.926-930, June 2007.
5. Y. Oohama, “Exponential Strong Converse for One Helper Source Coding Problem,” Entropy, vol.21, no.6, p.567, June 2019.
6. B. Santoso and Y. Oohama, “Information Theoretic Security for Shannon Cipher System under Side-Channel Attack,” Entropy, vol.21, no.5, p.469, May 2019.