1. Communication Theory.
Communication theory deals primarily with systems for transmitting information or data form one point to another. A rather general block diagram for visualizing the behavior of such systems is given in Fig. 4.1. The source output might represent, for example, a voice waveform, a sequence of binary digits form a magnetic tape, the output of a set of sensors in a space probe, a sensory input to a biological organism, or a target in a radar system. The channel might represent, for example, a telephone line, a high frequency radio link, a space communication link, a storage medium, or a biological organism (for the case where the source output is a sensory input to that organism). The channel is usually subjected to various types of noise disturbances, which on a telephone line, for example, might take the form of a time-varying frequency response, crosstalk from other lines, thermal noise, and impulsive switching noise. The encoder in Fig. 4.1. represents any processing of the source output performedprior to transmission. The processing might include, for example, any combination of modulation, data reduction, and insertion of redundancy to combat the channel noise. The decoder represents the processing of the channel output with the objective of producing at the destination an acceptable replica of (or response to) the source output.
2. Information Theory.
In the early 1940's a mathematical theory, for dealing with the more fundamental aspects of communication systems, was developed. The distinguishing characteristics of this theory are, first, a great emphasis on probability theory and, second, a primary concern with the encoder and decoder, both in terms of their functional roles and in terms of the existence (or nonexistence) of encoders and decoders that achieve a given level of performance. In the past 20 years, information theory has been made more precise, has been extended, and brought to the point where it is being applied in practical communication systems.
As in any mathematical theory, the theory deals only with mathematical models and not with physical sources and physical channels. One would think, therefore, that the appropriateway to begin the development of the theory would be with a discussion of how to construct appropriate mathematical models for physical sources and channels. This, however, is not the way that theories are constructed, primarily because physical reality is rarely simple enough to be precisely modeled by mathematically tractable models. The procedure will be rather to start by studying the simplest classes of mathematical models of sources and channels, using the insight and the results gained to study progressively more complicated classes of models. Naturally, the choice of classes of models to study will be influenced and motivated by the more important aspects of real sources and channels, but the view of what aspects are important will be modified by the theoretical results. Finally, after understanding the theory, it can be found to be useful in the study of real communication systems in two ways. First, it will provide a framework within which to construct detailed models of real sources and channels. Second, and more important, the relationship established by the theory provide an indication of the types of tradeoffs that exist in constructing encoders and decoders for given systems. While the above comments can be applied to almost any mathematical theory, they are particularly necessary here
Системы связи и Теория информации
1. Теория коммуникации.
Дела Теории коммуникации прежде всего с системами для передачи информации или данных формируют один пункт{*точку*} к другому. Довольно общая блок-схема для визуализирующего поведение таких систем дается в рис. 4.1. Исходный вывод мог бы представлять, например, звуковая форма волны, последовательность двоичных символов формирует магнитную ленту, вывод набора датчиков в космическом исследовании, сенсорный ввод{*вход*} к биологическому организму, или цели в радиолокационной сети. Канал мог бы представлять, например, телефонная линия, высокочастотная радиорелейная линия, линия космической связи, носитель данных, или биологический организм (для случая, где исходный вывод - сенсорный ввод{*вход*} к тому организму). Канал обычно подвергается различным типам шумовых помех, которые на телефонной линии, например, могли бы брать форму изменяющейся во времени частотной характеристики, перекрестные помехи от других строк, тепловых помех, и импульсных шумов переключателя. Кодер в рис. 4.1. Представляет любую обработку исходного вывода, выполненного до передачи. Обработка могла бы включать, например, любая комбинация модуляции, обработки данных, и включения статической неопределимости, чтобы сразиться с шумом канала. Декодер представляет обработку вывода канала с целью создания в адресате приемлемая точная копия (или ответ на) исходный вывод.
2. Теория информации.
В начале 1940-ых математическая теория, для имеющий дело с более фундаментальными аспектами систем связи, была разработана. Различающие характеристики этой теории, сначала, большой акцент на теории вероятности и, во вторых, первичное предприятие{*беспокойство*} с кодером и декодером, и в терминах их функциональных ролей и в терминах существования (или несуществование) кодеров и декодеров, которые достигают данного уровня выполнения{*работы*}. В прошлых 20 годах, теория информации была сделана более точной, была расширена{*продлена*}, и принесена к сути, где это обращается{*применяется*} в практических системах связи.
Как в любой математической теории, теория имеет дело только с математическими моделями а не с физическими источниками и физическими каналами. Можно было бы думал бы, поэтому, что соответствующий способ начинать развитие теории будет с обсуждением того, как создать соответствующие математические модели для физических источников и каналов. Это, однако, - не путь, которым теории созданы, прежде всего, потому что физическая действительность редко достаточно проста быть точно смоделированной математически послушными моделями. Процедура будет должна довольно запустить, изучая самые простые классы математических моделей источников и каналов, используя понимание и результаты, полученные изучать прогрессивно более сложные классы моделей. Естественно, на выбор классов моделей, чтобы учиться будут повлиять и мотивироваться более важными аспектами реальных источников и каналов, но представление{*вид*} что аспекты важны, будет изменяться теоретическими
because quite an extensive theory must be developed before
the more important implications for the design of communication systems will become apparent.
3. The source and Channel Encoders.
In order to further simplify the study of source models and channel models, it is helpful to partly isolate the effect of the source in a communication system from that of the channel. This can be done by breaking the encoder and decoder of Fig. 4.1. each into two parts as shown in Fig. 4.2.The purpose of the source encoder is to representthe source output by a sequence of binary digits and one of the major questions of concern is to determine how many binary digits per unit time are required to represents the output of any given source model. The purpose of the channel encoder and decoder is to allow the binary data sequences to be reliably reproduced at the output of the channel decoder, and one of course, whether restricting the encoder and decoder to the form of Fig. 4.2. imposes any fundamental limitations on the performance of the communication system. One of the most important results ofthe theory, however, is that under very broad conditions no such limitations are imposed (this does not say, however, that encoder and decoder of the form in Fig. 4.2. is always the most economical way to achieve a given performance). From a practical standpoint, the splitting of encoder and decoder is particularly convenient since it makes the design of the channel encoder and decoder virtually independent of the source encoder and decoder, using binary data as an interface. This, of course, facilitates the use of different sources on the same channel.
4. Conclusion.
Much of modern communication theory stems from the works of communication systems and also the desirability of modeling both signal and noise as random processes. Wiener was interested in finding the best linear filter to separate the signal from additive noise with a prescribed delay and his work had an important influence on subsequent research in modulation theory. Also Wiener's interest in reception with negative delay (that, is, prediction) along with Kolmogorov's work on prediction if the absence of noise have had an important impact on control theory. Similarly, Kotelnikov was interested in the detection and estimation of signals at the receiver.
результатами. Наконец, после понимания теории, может быть найдено быть полезным в изучении реальных систем связи в двух путях. Сначала, это обеспечит структуру, чтобы создать детальные модели из реальных источников и каналов. Во вторых, и что более важно, отношения, установленные в соответствии с теорией обеспечивают индикацию относительно типов сделок, которые существуют в построении кодеров и декодеров для данных систем. В то время как вышеупомянутые комментарии могут применяться к почти любой математической теории, они особенно необходимы здесь, потому что весьма обширная теория должна быть разработана прежде, чем более важные значения для проекта систем связи станут очевидными.
3. Источник и Кодеры Канала.
Чтобы далее упростить изучение источника моделирует и модели канала, полезно частично изолировать эффект источника в системе связи от такового канала. Это может быть сделано, ломая{*нарушая*} кодер и декодер рис. 4.1. Каждый в две части как показано в рис. 4.2. Цель исходного кодера состоит в том, чтобы представить источник, выводимый последовательностью двоичных символов, и один из главных вопросов предприятия{*беспокойства*} должен определить, сколько двоичных символов в единицу времени требуются к, представляет вывод любой данной исходной модели. Цель кодера канала и декодера состоит в том, чтобы позволить последовательностям данных в двоичном коде быть надежно воспроизведенной при выводе декодера канала, и один конечно, ли ограничение кодера и декодера к форме рис. 4.2. Налагает любые фундаментальные ограничения на выполнение{*работу*} системы связи. Один из наиболее важных результатов теории, однако, - то, что при очень широких условиях{*состояниях*} никакие такие ограничения не наложены (это не говорит, однако, что кодер и декодер формы в рис. 4.2. Является всегда наиболее экономическим способом достичь данного выполнения{*работы*}). С практической точки зрения, разбивание кодера и декодера особенно удобно, так как это делает проект из кодера канала и декодера, фактически независимого от исходного кодера и декодера, используя данные в двоичном коде как интерфейс. Это, конечно, облегчает использование различных источников на том же самом канале.
4. Заключение.
Многое из современных основ теории коммуникации от работ систем связи и также желательность моделирования и сообщает и шум как случайные процессы. Винер был заинтересован обнаружением лучшего линейного фильтра, чтобы отделить сигнал от аддитивного шума с предписанной задержкой, и его работа имела важное влияние на последующее исследование в теории модуляции. Также интерес{*процент*} Винера на приеме с отрицательной задержкой (что,, предсказание) наряду с работой Колмогорова на предсказании если отсутствие шум имел важное воздействие{*столкновение*} на теорию контроля{*управления*}. Точно так же Kotelnikov был заинтересован обнаружением и оценкой сигналов в приемнике.
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