ieee sPectrum feature an underclassman at Princeton in the late 1950s, Forney wasn't necessarily set on a career in engineering. He did ultimately decide to pursue a bachelor of science in engineering, but not out of any burning desire to invent or design. "I thought, 'I'll keep my options open,' but without any great intention to become an engineer," Forney recalls, relaxing in the sunny sitting area off the kitchen of his Cambridge, Mass., home one December afternoon last year. But an elective course in thermodynamics taught by John Archibald Wheeler stirred a sense of discovery in him. "I really liked his approach," Forney says of the legendary physicist's downto-earth teaching style. "It was much more of an engineering course than a physics course. And he [assigned] a term paper instead of a final exam." For the paper, Forney decided to read Léon Brillouin's 1956 book, Science and Information Theory. The book tackled thermodynamics in the context of information theory, then a fledgling field, founded about a decade earlier with a groundbreaking paper by Claude Shannon. In that 1948 paper, "A Mathematical Theory of Communication," Shannon laid out the mathematical foundation for the transmission of information (the centenary of his birth is being celebrated this year). For ne y s ay s he w a s s t r uck by Brillouin's resolution of the problem pusHing tHe liMits: Forney [right] and Robert Gallager confer at MIT� This photograph was taken around 1965, Forney says� of Maxwell's demon, a thought experiment in which energy appears to be created for free by sorting molecules by their speed. Brillouin noted that every physical system contains information, and extracting that information-in the case of Maxwell's demon, the speed of particles-always costs energy, enough to precisely satisfy the laws of thermodynamics. "Information isn't free; it comes at a cost," Forney says, in summary. "Probably I could poke holes in that now. But certainly as an undergraduate this was all very interesting." He carried this interest to graduate school at MIT, in 1961, where he found a whirlwind of research activity. Shannon himself had recently arrived from Bell Labs, and a research group was trying to extend his work and find practical uses for it. In a master's thesis on information theory and quantum mechanics, and a doctoral dissertation on error-correcting codes, Forney displayed a bloodhound's nose for f inding the right problems and the right questions to ask about those problems. The 1990 IEEE Medal of Honor recipient, Rob18 | 2016 IEEE AWARDS BooKLET ert Gallager, a young faculty member in the mid-1960s and now an emeritus professor at MIT's Research Laboratory of Electronics, singles out Forney's doctoral thesis as a leap forward in the field. At that time, digital technology was taking off, and researchers were hunting for coding schemes-ways of transforming those 1s and 0s into a form that could be carried from place to place with little power and few errors. In his celebrated 1948 paper, Shannon had already worked out the ultimate limit to such efficiency, a maximum achievable error-free data rate for any communications channel. But reaching that limit was easier said than done. Disturbances during transmission will flip bits at random. To tackle errors, Shannon proposed adding redundant bits to a sequence of data before transmission to create an encoded packet. The longer the packet, the less likely it would be corrupted to look like another potential sequence. This approach could push transmission to its limits, but it posed a practical challenge at the decoding stage. The straightforward, brute-force approach would compare the incoming sequence with every possible transmitted sequence to find the most likely one. This process could work for relatively short packets, Forney says. But longer packets, which would be needed to obtain very low error rates, would quickly exhaust the computational power of a decoder, even with today's technology. Researchers proposed various coding schemes to try to achieve data rates close to the Shannon limit with low error rates and reasonable decoding complexity. But there was no single code that could do it all. Forney had another idea. Why not break the problem down and use multiple, complementary codes to encode and decode data, one operating on the outcome of the other? A simple inner code operating directly on the input and output of a communications channel could achieve a moderate error rate at data rates near Shannon's limit. An outer code, used before data enters the inner code and after exiting it, could drive error rates down further using a

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