【導讀】圖1-1-1顯示了一個數(shù)字通信系統(tǒng)的功能性框圖和基本組成部分。信號在時間上是離散的，并且只有有限個輸出字符。產(chǎn)生的消息變換成二進制數(shù)字序列。理論上，應當用盡可能少的二進制數(shù)字表示。換句話說.我們要尋求一種信源輸出的有效的表示方法,使其。的處理過程稱為信源編碼或數(shù)據(jù)壓縮。由信源編碼器輸出的二進制數(shù)字序列稱為信息序列，它被傳送到信道編碼器。接收機中用來克服信號在信道中傳輸時所遭受的噪聲和干擾的影響。加的冗余是用來提高接收數(shù)據(jù)的可靠性以及改善接收信號的逼真度的。信息序列中的冗余有助于接收機譯出期望的信息序列。序列映射成惟一的n比特序列，該序列稱為碼字。以這種方式對數(shù)據(jù)編碼所引人。以數(shù)字調(diào)制的主要目的是將二進制信息序列映射成信號波形。在這種方式中，信道編碼器輸出的每一比特是分別傳輸?shù)?。因此，當信道比特率R固定,與一個b. 在數(shù)字通信系統(tǒng)的接收端,數(shù)字解調(diào)器對受到信道惡化的發(fā)送波形進行處理，

　　

【正文】 other example, microwave radio relay systems used extensively for telephone and video transmission at frequencies above I GHz have antennas mounted on tall towers or on the top of tall buildings. The dominant noise limiting the performance of a munication system in VHF and UHF frequency ranges is thermal noise generated in the receiver front end and cosmic noise picked up by the antenna. At frequencies in the SHF band above 10 GHz, atmospheric conditions play a major role in signal propagation. For example, at 10 GHz, the attenuation ranges from about dB/km in light rain to about dB/km in heavy rain. At 100 GHz, the attenuation ranges from about dB/km in light rain to about 6 dB/km in heavy rain. Hence, in this frequency range, heavy rain introduces extremely high propagation losses that can result in service outages (total breakdown in the munication system). At frequencies above the EHF (extremely high frequency) band, we have the infrared and visible light regions of the electromagic spectrum, which can be used to provide LOS optical munication in free space. To date, these frequency bands have been used in experimental munication systems, such as satellitetosatellite links. Underwater Acoustic Channels Over the past few decades, ocean exploration activity has been steadily increasing. Coupled with this increase is the need to transmit data, collected by sensors placed under water, to the surface of the ocean. From there, it is possible to relay the data via a satellite to a data collection center. Electromagic waves do not propagate over long distances under water except at extremely low frequencies. However, the transmission of signals at such low frequencies is prohibitively expensive because of the large and powerful transmitters required. The attenuation of electromagic waves in water can be expressed in terms of the skin depth, which is the distance a signal is attenuated by 1/r. For sea water, the skin depth 250/v7, where f is expressed in Hz and 8 is in m. For example, at 10 kHz. the skin depth is m. In contrast, acoustic signals propagate over distances of tens and even hundreds of kilometers. An underwater acoustic channel is characterized as a multipath channel due to signal reflections from the surface and the bottom of the sea. Because of wave motion, the signal multipath ponents undergo timevarying propagation delays that result in signal fading. In addition, there is frequency dependent attenuation, which is approximately proportional to the square of the signal frequency. The sound velocity is nominally about 1500 m/s, but the actual value will vary either above or below the nominal value depending on the depth at which the signal propagates. Ambient ocean acoustic noise is caused by shrimp, fish, and various mammals. Near harbors, there is also manmade acoustic noise in addition to the ambient noise. In spite of this hostile environment, it is possible to design and implement efficient and highly reliable underwater acoustic munication systems for transmitting digital signals over large distances. Storage Channels Information storage and retrieval systems constitute a very significant part of datahandling activities on a daily basis. Magic (ape, including digital audio tape and video tape, magic disks used for storing large amounts of puter data, optical disks used for puter data storage, and pact disks are examples of data storage systems that can be characterized as munication channels. The process of storing data on a magic tape or a magic or optical disk is equivalent to transmitting a signal over a telephone or a radio channel. The read back process and the signal processing involved in storage systems to recover the stored information are equivalent to the functions performed by a receiver in a telephone or radio munication system to recover the transmitted information. Additive noise generated by the electronic ponents and interference from adjacent tracks is generally present in the read back signal of a storage system, just as is the case in a telephone or a radio munication system. The amount of data that can be stored is generally limited by the size of the disk or tape and the density (number of bits stored per square inch) that can be achieved by the write/read electronic systems and heads. For example, a packing density of 10 bits per square inch has been recently demonstrated in an experimental magic disk storage system. (Current mercial magic storage products achieve a much lower density.) The speed ai which data can be written on a disk or tape and the speed at which it can be read back are also limited by the associated mechanical and electrical subsystems that constitute an information storage system. Channel coding and modulation are essential ponents of a welldesigned digital magic or optical storage system. In the read back process, (he signal is demodulated and the added redundancy introduced by the channel encoder is used to correct errors in the read back signal. 13 MATHEMATICAL MODELS FOR COMMUNICATION CHANNELS In the design of munication systems for transmitting information through physical channels, we find it convenient to construct mathematical models that reflect the most important characteristics of the transmission medium. Then, the mathematical model for the channel is used in the design of the channel encoder and modulator at the transmitter and the demodulator and channel decoder at the receiver. Below, provide a brief description of the channel models that are frequently used to characterize many of the physical channels that we encounter in practice. The Additive Noise Channel The simplest mathematical model for a munication channel is the additive noise channel, illustrated in Fig. this model, the transmitted signal s(r) is corrupted by an additive random noise proc