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1、期末考试考试形式：考试形式：闭卷、英文试卷、英文答题试题类型：试题类型：判断题 填空题 综合题成绩构成成绩构成：平时成绩10%、期末考试90%平时成绩平时成绩：出勤、作业课程网站：课程网站：http:/ 8 Multiuser Radio CommunicationsnRadio link analysisnlink (power) budget analysis - the totaling of all the gains and losses incurred in operating a communication linknTwo particular values of Eb/N0
2、:o1. Required Eb/N0o2. Received Eb/N0nlink margin(8.2)()()()()(00dBNEdBNEdBMreqbrecb复习提纲Chapter 8 Multiuser Radio CommunicationsnRadio link analysisneffective aperture (8.11)nThe path loss(8.15)nFree-space lossnRatio of received carrier power-to-noise spectral density (8.31)2101010log () 10log ()4tr
3、PLGGdGA4221010log ()4freespaceLdkdTGEIRPNCer142terminalearthsatellitedownlink0复习提纲Chapter 8 Multiuser Radio CommunicationsnWireless communications (mobility and the multipath phenomenon)nreverse link (uplink): mobile base stationforward link (downlink): base station mobilenoffers mobility (communica
4、te with anyone, anywhere)ntetherless (total freedom of location is permitted)nthe presence of multipath (no longer the idealized AWGN channel model)nDoppler-shiftcosdvfa复习提纲Chapter 8 Multiuser Radio CommunicationsnWireless communications (mobility and the multipath phenomenon)co-channel interference
5、multipath fading delay spreadspecialize techniques used, such as:diversityadaptive array antennasRAKE receiversignal-dependent phenomena复习提纲Chapter 8 Multiuser Radio CommunicationsnAdaptive antennasndelay spread coherent bandwidth BcDoppler spread coherence timenmultipath, delay spread (ISI) and co-
6、channel interference (CCI)cancel the CCI array signal processor (spatial)cancel the ISI linear equalizer (temporal)5.space-time processor, which combines temporal and spatial processingc复习提纲Chapter 9 Fundamental Limits in Information TheorynEntropy - basic measure of informationnAmount of informatio
7、nn bits(9.4)PropertiesnEntropy - mean of I(sk) bits/symbol(9.9)Boundary(9.10)log()(1kpksI101210)(log)()()(kkpkkkkkkkpsIpsIEHKH2log)(0复习提纲Chapter 9 Fundamental Limits in Information TheorynSource coding and data compaction (1)nAverage code-word length (9.18)nSource-Coding Theorem, Shannons first theo
8、remGiven a discrete memoryless source of entropy , the average code-word length for any distortionless source encoding scheme is bounded as(9.20)2.Data compaction, lossless compression of data10KkkklpL)(HL( )HL复习提纲Chapter 9 Fundamental Limits in Information TheorynSource coding and data compaction (
9、2)nPrefix Coding nHuffman Coding nHuffman tree nas high as possible or as low as possible?2.Lempel-Ziv Coding复习提纲Chapter 9 Fundamental Limits in Information TheorynMutual information - channel capacity (1)nconditional entropyn(9.41)nMutual information)()()()()(Y/XYX/YXYX;HHHHI1011200()()()1(,) lo g
10、()KkkkKJjkkjjkHHYypypxypxy XYX11200()(,) lo g()KJkjjkkjkpyxpxypy 复习提纲Chapter 9 Fundamental Limits in Information Theory3.Mutual information - channel capacity (2)(max)(YX;ICjxp(9.59)Subject toand0)(jxpfor all j101)(Jjjxp复习提纲Chapter 9 Fundamental Limits in Information Theory4.Channel Coding Theorem,
11、Shannons second theorem(i) If csTCTH)(Exists a coding scheme. C/Tc - critical rate(ii) If csTCTH)(Not.(9.61)(9.62)average information rate channel capacity per unit time For BSC, if code rate r channel capacity C , codes do exist such that the average probability of error is as small as we want it.复
12、习提纲Chapter 9 Fundamental Limits in Information TheorynInformation Capacity Theorem, Shannons third theorem5.differential entropy of a continuous random variable XdxxfxfXhXX)(1log)()(2(9.66)n The information capacity of a continuous channel is given byondperbitsBNPBCsec)1(log02There is a maximum to t
13、he rate at which any communication system can operate reliably (i.e., free of errors) when the system is constrained in power.复习提纲Chapter 9 Fundamental Limits in Information TheorynRate-distortion theory - source coding (1)nSource coding with a fidelity criterionnRate Distortion Function The smalles
14、t coding rate possible for which the average distortion not to exceed D.(9.131);(min)()|(YXIDRDijPxypsubject to the constraint(9.132)MiforxypNjij,.,2, 11)|(1复习提纲Chapter 9 Fundamental Limits in Information TheorynRate-distortion theory - source coding (2)nSignal compression (i.e., solving the problem
15、 of source coding with a fidelity criterion)6.data compression (if lossless) data compaction (such as Huffman coding, Lempel-Ziv coding) data encryption复习提纲Chapter 10 Error-Control CodingoLinear block codes (Cyclic codes)ogenerator matrix (polynomial)oparity-check matrix (polynomial)oSyndromeominimu
16、m distance dmin1.Encoder for cyclic codes复习提纲Chapter 10 Error-Control CodingoConvolutional codesoGenerator polynomialoGraphical formsnCode TreenTrellis nState DiagramoThe Viterbi algorithm2.Catastrophic code复习提纲Chapter 10 Error-Control Coding3. Compound codesoTurboo Low-density parity-check codes o Irregular codes4. TCM Combine coding and modulation to attain a more effective utilization of the available bandwidth and power. .预祝同学们考出满意的成绩！27 结束语结束语