《通信与电子信息科技英语》课件unit 2.ppt

Channel CapacityNew words and phrases 1abstraction n.抽象；抽象观念2encompass vt.包括，包含3devise vt.设计,发明4whereby adv.凭那个；由此5arbitrarily adv.任意地6theorem n.定理7infrequent adj.很少发生的,罕见的8override vt.压倒,制服，凌驾9thereby adv.由此,因此,从而10gaussian adj.高斯的 Gauss高斯(17771855,德国数学家、天文学家)11unity n.一，单一12complementary adj.补充的；互补的Channel Capacity13derivation n.推导,导出，公式推导14formidable adj.困难的，棘手的,可怕的15undertake vt.进行,从事16presumed adj.假定的,推测的 presumably adv.推测起来,大概,估计,可能17likelihood n.可能,可能性likely adj.可能，可能的18interval n.间隔，时间间隔19rounding n.舍入(成整数);四舍五入20abrupt adj.不连续的，突然的，急剧的，陡的21reliably adv.可靠地，安全地，确实地22heuristic adj.启发式的,渐进的23intuitive adj.直觉的;直观的 intuitively adv.直觉地,直观地24contemplate vt.预期(料)Channel Capacity25vice versa adv.反之亦然（viceversa)26quantize vt.量化27reception n.接收28extreme adj.极端的，极度的,偏激的29attenuate vt.衰减，使衰减30distort vt.失真，使失真distortion n.失真,畸变31equalizer n.均衡器32recoverable adj.可恢复的1 enter into 参加，成为一部分，涉及2 due to 由于;起因于;归功于3 be something of 有一点4 in principle 原则上,大致上on principle 按照原则（或道德标准）Channel Capacity5 provided that 假如,设若6 probability of error(error probability)误码率，误差概率 7 be close to 接近,靠近8 bandlimited gaussian channel 限带高斯信道9 physical system 物理系统,实际系统10 turn out （常与to,that连用）结果，结果是11 lower bound 下界,下限12 upper limit 上限13 rootmeansquare 均方根，均方根值；均方根(的)rootmeansquare error 均方根(有效值)误差14 amount of information （information content;quantity of information;information quantity）信息量15 ideal lowpass filter 理想低通滤波器Channel Capacity16 rise time 上升时间17 as a matter of convenience 为方便起见18 white Gaussian noise(white gaussian noise)高斯白噪声 19 on the other hand 另一方面20 trade off 交替换位，折衷选择(tradeoffn.折衷，权衡)21 signaltonoise ratio 信号噪声比，信噪比（SNR,S/N）22 be free to 随意,任意,不受拘束23 make up for 补偿Channel Capacity The importance of the concept of information rate is that it enters into a theorem due to Shannon which is fundamental to the theory of communications.This theorem is concerned with the rate of transmission of information over a communication channel.While we have used the term communication channel on many occasions，it is well to emphasize at this point,that the term,which is something of an abstraction,is intended to encompass all the features and component parts of the transmission system which introduce noise or limit the bandwidth.Shannons Theorem,Channel Capacity Shannons theorem says that it is possible,in principle,to devise a means whereby a communications system will transmit information with an arbitrarily small probability of error provided that the information rate R is less than or equal to a rate C called the channel capacity.To put the matter more formally,we have the following:Channel CapacityTheorem Given a source of M equally likely messages,with M1,which is generating information at a rate R.Given a channel with channel capacity C.Then,ifRCthere exists a coding technique such that the output of the source may be transmitted over the channel with a probability of error in the received message which may be made arbitrarily small.The important feature of the theorem is that it indicates that for RC transmission may be accomplished without error in the presence of noise.This result is surprising.For in our consideration of noise,say,gaussian noise,we have seen that the probability density of the noise extends to infinity.We should then imagine that there will be some times,however infrequent,when the noise must override the signal thereby resulting in errors.However,Shannons theorem says that this need not cause a message to be in error.Channel CapacityThere is a negative statement associated with Shannons theorem.It states the following:Theorem Given a source of M equally likely messages,with M1,which is generating information at a rate R;then if RC the probability the probability of error is close to unity for every possible set of M transmitter signals.This negative theorem states that if the information rate R exceeds a specified value C,the error probability will increase toward unity as M increases,and that also,generally,in this case where RC,increasing the complexity of the coding results in an increase in the probability of error.Capacity of a Gaussian Channel A theorem which is complementary to Shannons theorem and applies to a channel in which the noise is gaussian is known as the ShannonHartley theorem.Channel CapacityTheorem The channel capacity of a white,bandlimited gaussian channel is C=Blog2(1+S/N)bits/s(2.1)where B is the channel bandwidth,S is the signal power,and N is the total noise within the channel bandwidth,that is,N=B,with 1/2 the(two-ided)power spectral density.This theorem,although restricted to the gaussian channel,is of fundamental importance.First,we find that channels encountered in physical systems generally are,at least approximately,gaussian.Second,it turns out that the results obtained for a gaussian channel often provide a lower bound on the performance of asystem operating over a nongaussian channel.Thus,if a particular encoderdecoder is used with a gaussian channel and an error probability Pe 。