Complementing the fiber evolution has been the evolution in signal modulation formats, resulting in more compact signal spectra and more robust channels. Finally, new coding methods, in particular forward-error correction schemes, have greatly increased the design margins possible for optical transport and have figured significantly in the enhancement of capacity and range over the past 5 or 6 years. Further technological advances in all-optical signal regeneration, modulation formats, and channel filtering are expected to continue to enable improvements in fiber-optic communications.
It is also worth reflecting on the many notable spin-offs of past telecommunications research.
Transistors, which spawned the entire semiconductor and computer industry, and an enormous range of applications in communications, computing, media, and entertainment;Lasers, which have seen widespread application in medicine (surgery), consumer electronics (CD and DVD players), manufacturing, and even toys and games; Karmarkar’s algorithm for linear programming, which solved a long-standing problem in computer science and is an example of the kind of widely applicable solutions to mathematical problems that arise in telecommunications; UNIX, created as a result of work aimed at constructing a simple operating system that facilitated the construction of widely reusable software tools; the telecommunication industry’s requirements for high performance helped push forefront research in simple yet powerful software systems, and today, various flavors of UNIX are the dominant open standard in operating systems;
Reduced instruction set computing, the first prototype system for which (the 801 Minicomputer at IBM Research) had as its application objective a telephone switching system; Satellite communications and the entertainment industry spawned by Telstar, which today are much broader in scope than the point-to-point communications Telstar was built for and were made possible by the initial investment in a single application; Coding and information theory, developed for data compression and error-correction, which has also found application in diverse areas such as cryptography, probability theory, biology, and investment theory.
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