EVM optimization for OFDM system with a deterministic papr contrain

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AgilentDigital Modulation in Communications Systems—An IntroductionApplication Note 1298This application note introduces the concepts of digital modulation used in many communications systems today. Emphasis is placed on explaining the tradeoffs that are made to optimize efficiencies in system design.Most communications systems fall into one of three categories: bandwidth efficient, power efficient, or cost efficient. Bandwidth efficiency describes the ability of a modulation scheme to accommodate data within a limited bandwidth. Power efficiency describes the ability of the system to reliably send information at the lowest practical power level.In most systems, there is a high priority on band-width efficiency. The parameter to be optimized depends on the demands of the particular system, as can be seen in the following two examples.For designers of digital terrestrial microwave radios, their highest priority is good bandwidth efficiency with low bit-error-rate. They have plenty of power available and are not concerned with power efficiency. They are not especially con-cerned with receiver cost or complexity because they do not have to build large numbers of them. On the other hand, designers of hand-held cellular phones put a high priority on power efficiency because these phones need to run on a battery. Cost is also a high priority because cellular phones must be low-cost to encourage more users. Accord-ingly, these systems sacrifice some bandwidth efficiency to get power and cost efficiency. Every time one of these efficiency parameters (bandwidth, power, or cost) is increased, another one decreases, becomes more complex, or does not perform well in a poor environment. Cost is a dom-inant system priority. Low-cost radios will always be in demand. In the past, it was possible to make a radio low-cost by sacrificing power and band-width efficiency. This is no longer possible. The radio spectrum is very valuable and operators who do not use the spectrum efficiently could lose their existing licenses or lose out in the competition for new ones. These are the tradeoffs that must be considered in digital RF communications design. This application note covers•the reasons for the move to digital modulation;•how information is modulated onto in-phase (I) and quadrature (Q) signals;•different types of digital modulation;•filtering techniques to conserve bandwidth; •ways of looking at digitally modulated signals;•multiplexing techniques used to share the transmission channel;•how a digital transmitter and receiver work;•measurements on digital RF communications systems;•an overview table with key specifications for the major digital communications systems; and •a glossary of terms used in digital RF communi-cations.These concepts form the building blocks of any communications system. If you understand the building blocks, then you will be able to under-stand how any communications system, present or future, works.Introduction25 5 677 7 8 8 9 10 10 1112 12 12 13 14 14 15 15 16 17 18 19 20 21 22 22 23 23 24 25 26 27 28 29 29 30 311. Why Digital Modulation?1.1 Trading off simplicity and bandwidth1.2 Industry trends2. Using I/Q Modulation (Amplitude and Phase Control) to Convey Information2.1 Transmitting information2.2 Signal characteristics that can be modified2.3 Polar display—magnitude and phase representedtogether2.4 Signal changes or modifications in polar form2.5 I/Q formats2.6 I and Q in a radio transmitter2.7 I and Q in a radio receiver2.8 Why use I and Q?3. Digital Modulation Types and Relative Efficiencies3.1 Applications3.1.1 Bit rate and symbol rate3.1.2 Spectrum (bandwidth) requirements3.1.3 Symbol clock3.2 Phase Shift Keying (PSK)3.3 Frequency Shift Keying3.4 Minimum Shift Keying (MSK)3.5 Quadrature Amplitude Modulation (QAM)3.6 Theoretical bandwidth efficiency limits3.7 Spectral efficiency examples in practical radios3.8 I/Q offset modulation3.9 Differential modulation3.10 Constant amplitude modulation4. Filtering4.1 Nyquist or raised cosine filter4.2 Transmitter-receiver matched filters4.3 Gaussian filter4.4 Filter bandwidth parameter alpha4.5 Filter bandwidth effects4.6 Chebyshev equiripple FIR (finite impulse response) filter4.7 Spectral efficiency versus power consumption5. Different Ways of Looking at a Digitally Modulated Signal Time and Frequency Domain View5.1 Power and frequency view5.2 Constellation diagrams5.3 Eye diagrams5.4 Trellis diagramsTable of Contents332 32 32 33 33 34 3435 35 3637 37 37 38 38 39 39 39 40 41 41 42 434344466. Sharing the Channel6.1 Multiplexing—frequency6.2 Multiplexing—time6.3 Multiplexing—code6.4 Multiplexing—geography6.5 Combining multiplexing modes6.6 Penetration versus efficiency7. How Digital Transmitters and Receivers Work7.1 A digital communications transmitter7.2 A digital communications receiver8. Measurements on Digital RF Communications Systems 8.1 Power measurements8.1.1 Adjacent Channel Power8.2 Frequency measurements8.2.1 Occupied bandwidth8.3 Timing measurements8.4 Modulation accuracy8.5 Understanding Error Vector Magnitude (EVM)8.6 Troubleshooting with error vector measurements8.7 Magnitude versus phase error8.8 I/Q phase error versus time8.9 Error Vector Magnitude versus time8.10 Error spectrum (EVM versus frequency)9. Summary10. Overview of Communications Systems11. Glossary of TermsTable of Contents (continued)4The move to digital modulation provides more information capacity, compatibility with digital data services, higher data security, better quality communications, and quicker system availability. Developers of communications systems face these constraints:•available bandwidth•permissible power•inherent noise level of the systemThe RF spectrum must be shared, yet every day there are more users for that spectrum as demand for communications services increases. Digital modulation schemes have greater capacity to con-vey large amounts of information than analog mod-ulation schemes. 1.1 Trading off simplicity and bandwidthThere is a fundamental tradeoff in communication systems. Simple hardware can be used in transmit-ters and receivers to communicate information. However, this uses a lot of spectrum which limits the number of users. Alternatively, more complex transmitters and receivers can be used to transmit the same information over less bandwidth. The transition to more and more spectrally efficient transmission techniques requires more and more complex hardware. Complex hardware is difficult to design, test, and build. This tradeoff exists whether communication is over air or wire, analog or digital.Figure 1. The Fundamental Tradeoff1. Why Digital Modulation?51.2 Industry trendsOver the past few years a major transition has occurred from simple analog Amplitude Mod-ulation (AM) and Frequency/Phase Modulation (FM/PM) to new digital modulation techniques. Examples of digital modulation include•QPSK (Quadrature Phase Shift Keying)•FSK (Frequency Shift Keying)•MSK (Minimum Shift Keying)•QAM (Quadrature Amplitude Modulation) Another layer of complexity in many new systems is multiplexing. Two principal types of multiplex-ing (or “multiple access”) are TDMA (Time Division Multiple Access) and CDMA (Code Division Multiple Access). These are two different ways to add diversity to signals allowing different signals to be separated from one another.Figure 2. Trends in the Industry62.1 Transmitting informationTo transmit a signal over the air, there are three main steps:1.A pure carrier is generated at the transmitter.2.The carrier is modulated with the informationto be transmitted. Any reliably detectablechange in signal characteristics can carryinformation.3.At the receiver the signal modifications orchanges are detected and demodulated.2.2 Signal characteristics that can be modified There are only three characteristics of a signal that can be changed over time: amplitude, phase, or fre-quency. However, phase and frequency are just dif-ferent ways to view or measure the same signal change. In AM, the amplitude of a high-frequency carrier signal is varied in proportion to the instantaneous amplitude of the modulating message signal.Frequency Modulation (FM) is the most popular analog modulation technique used in mobile com-munications systems. In FM, the amplitude of the modulating carrier is kept constant while its fre-quency is varied by the modulating message signal.Amplitude and phase can be modulated simultane-ously and separately, but this is difficult to gener-ate, and especially difficult to detect. Instead, in practical systems the signal is separated into another set of independent components: I(In-phase) and Q(Quadrature). These components are orthogonal and do not interfere with each other.Figure 3. Transmitting Information (Analog or Digital)Figure 4. Signal Characteristics to Modify2. Using I/Q Modulation to Convey Information72.3 Polar display—magnitude and phase repre-sented togetherA simple way to view amplitude and phase is with the polar diagram. The carrier becomes a frequency and phase reference and the signal is interpreted relative to the carrier. The signal can be expressed in polar form as a magnitude and a phase. The phase is relative to a reference signal, the carrier in most communication systems. The magnitude is either an absolute or relative value. Both are used in digital communication systems. Polar diagrams are the basis of many displays used in digital com-munications, although it is common to describe the signal vector by its rectangular coordinates of I (In-phase) and Q(Quadrature).2.4 Signal changes or modifications inpolar formFigure 6 shows different forms of modulation in polar form. Magnitude is represented as the dis-tance from the center and phase is represented as the angle.Amplitude modulation (AM) changes only the magnitude of the signal. Phase modulation (PM) changes only the phase of the signal. Amplitude and phase modulation can be used together. Frequency modulation (FM) looks similar to phase modulation, though frequency is the controlled parameter, rather than relative phase.Figure 6. Signal Changes or Modifications8One example of the difficulties in RF design can be illustrated with simple amplitude modulation. Generating AM with no associated angular modula-tion should result in a straight line on a polar display. This line should run from the origin to some peak radius or amplitude value. In practice, however, the line is not straight. The amplitude modulation itself often can cause a small amount of unwanted phase modulation. The result is a curved line. It could also be a loop if there is any hysteresis in the system transfer function. Some amount of this distortion is inevitable in any sys-tem where modulation causes amplitude changes. Therefore, the degree of effective amplitude modu-lation in a system will affect some distortion parameters.2.5 I/Q formatsIn digital communications, modulation is often expressed in terms of I and Q. This is a rectangular representation of the polar diagram. On a polar diagram, the I axis lies on the zero degree phase reference, and the Q axis is rotated by 90 degrees. The signal vector’s projection onto the I axis is its “I” component and the projection onto the Q axisis its “Q” component.Figure 7. “I-Q” Format92.6 I and Q in a radio transmitterI/Q diagrams are particularly useful because they mirror the way most digital communications sig-nals are created using an I/Q modulator. In the transmitter, I and Q signals are mixed with the same local oscillator (LO). A 90 degree phase shifter is placed in one of the LO paths. Signals that are separated by 90 degrees are also known as being orthogonal to each other or in quadrature. Signals that are in quadrature do not interfere with each other. They are two independent compo-nents of the signal. When recombined, they are summed to a composite output signal. There are two independent signals in I and Q that can be sent and received with simple circuits. This simpli-fies the design of digital radios. The main advan-tage of I/Q modulation is the symmetric ease of combining independent signal components into a single composite signal and later splitting such a composite signal into its independent component parts. 2.7 I and Q in a radio receiverThe composite signal with magnitude and phase (or I and Q) information arrives at the receiver input. The input signal is mixed with the local oscillator signal at the carrier frequency in two forms. One is at an arbitrary zero phase. The other has a 90 degree phase shift. The composite input signal (in terms of magnitude and phase) is thus broken into an in-phase, I, and a quadrature, Q, component. These two components of the signal are independent and orthogonal. One can be changed without affecting the other. Normally, information cannot be plotted in a polar format and reinterpreted as rectangular values without doing a polar-to-rectangular conversion. This con-version is exactly what is done by the in-phase and quadrature mixing processes in a digital radio. A local oscillator, phase shifter, and two mixers can perform the conversion accurately and efficiently.Figure 8. I and Q in a Practical Radio Transmitter Figure 9. I and Q in a Radio Receiver102.8 Why use I and Q?Digital modulation is easy to accomplish with I/Q modulators. Most digital modulation maps the data to a number of discrete points on the I/Q plane. These are known as constellation points. As the sig-nal moves from one point to another, simultaneous amplitude and phase modulation usually results. To accomplish this with an amplitude modulator and a phase modulator is difficult and complex. It is also impossible with a conventional phase modu-lator. The signal may, in principle, circle the origin in one direction forever, necessitating infinite phase shifting capability. Alternatively, simultaneous AM and Phase Modulation is easy with an I/Q modulator. The I and Q control signals are bounded, but infi-nite phase wrap is possible by properly phasing the I and Q signals.This section covers the main digital modulation formats, their main applications, relative spectral efficiencies, and some variations of the main modulation types as used in practical systems. Fortunately, there are a limited number of modula-tion types which form the building blocks of any system.3.1 ApplicationsThe table below covers the applications for differ-ent modulation formats in both wireless communi-cations and video. Although this note focuses on wireless communica-tions, video applications have also been included in the table for completeness and because of their similarity to other wireless communications.3.1.1 Bit rate and symbol rateTo understand and compare different modulation format efficiencies, it is important to first under-stand the difference between bit rate and symbol rate. The signal bandwidth for the communications channel needed depends on the symbol rate, not on the bit rate.Symbol rate =bit ratethe number of bits transmitted with each symbol 3. Digital Modulation Types and Relative EfficienciesBit rate is the frequency of a system bit stream. Take, for example, a radio with an 8 bit sampler, sampling at 10 kHz for voice. The bit rate, the basic bit stream rate in the radio, would be eight bits multiplied by 10K samples per second, or 80 Kbits per second. (For the moment we will ignore the extra bits required for synchronization, error correction, etc.)Figure 10 is an example of a state diagram of a Quadrature Phase Shift Keying (QPSK) signal. The states can be mapped to zeros and ones. This is a common mapping, but it is not the only one. Any mapping can be used.The symbol rate is the bit rate divided by the num-ber of bits that can be transmitted with each sym-bol. If one bit is transmitted per symbol, as with BPSK, then the symbol rate would be the same as the bit rate of 80 Kbits per second. If two bits are transmitted per symbol, as in QPSK, then the sym-bol rate would be half of the bit rate or 40 Kbits per second. Symbol rate is sometimes called baud rate. Note that baud rate is not the same as bit rate. These terms are often confused. If more bits can be sent with each symbol, then the same amount of data can be sent in a narrower spec-trum. This is why modulation formats that are more complex and use a higher number of states can send the same information over a narrower piece of the RF spectrum.3.1.2 Spectrum (bandwidth) requirementsAn example of how symbol rate influences spec-trum requirements can be seen in eight-state Phase Shift Keying (8PSK). It is a variation of PSK. There are eight possible states that the signal can transi-tion to at any time. The phase of the signal can take any of eight values at any symbol time. Since 23= 8, there are three bits per symbol. This means the symbol rate is one third of the bit rate. This is relatively easy to decode.Figure 10. Bit Rate and Symbol Rate Figure 11. Spectrum Requirements3.1.3 Symbol ClockThe symbol clock represents the frequency and exact timing of the transmission of the individual symbols. At the symbol clock transitions, the trans-mitted carrier is at the correct I/Q(or magnitude/ phase) value to represent a specific symbol (a specific point in the constellation).3.2 Phase Shift KeyingOne of the simplest forms of digital modulation is binary or Bi-Phase Shift Keying (BPSK). One appli-cation where this is used is for deep space teleme-try. The phase of a constant amplitude carrier sig-nal moves between zero and 180 degrees. On an I and Q diagram, the I state has two different values. There are two possible locations in the state dia-gram, so a binary one or zero can be sent. The symbol rate is one bit per symbol.A more common type of phase modulation is Quadrature Phase Shift Keying (QPSK). It is used extensively in applications including CDMA (Code Division Multiple Access) cellular service, wireless local loop, Iridium (a voice/data satellite system) and DVB-S (Digital Video Broadcasting — Satellite). Quadrature means that the signal shifts between phase states which are separated by 90 degrees. The signal shifts in increments of 90 degrees from 45 to 135, –45, or –135 degrees. These points are chosen as they can be easily implemented using an I/Q modulator. Only two I values and two Q values are needed and this gives two bits per symbol. There are four states because 22= 4. It is therefore a more bandwidth-efficient type of modulation than BPSK, potentially twice as efficient.Figure 12. Phase Shift Keying3.3 Frequency Shift KeyingFrequency modulation and phase modulation are closely related. A static frequency shift of +1 Hz means that the phase is constantly advancing at the rate of 360 degrees per second (2 πrad/sec), relative to the phase of the unshifted signal.FSK (Frequency Shift Keying) is used in many applications including cordless and paging sys-tems. Some of the cordless systems include DECT (Digital Enhanced Cordless Telephone) and CT2 (Cordless Telephone 2).In FSK, the frequency of the carrier is changed as a function of the modulating signal (data) being transmitted. Amplitude remains unchanged. In binary FSK (BFSK or 2FSK), a “1” is represented by one frequency and a “0” is represented by another frequency.3.4 Minimum Shift KeyingSince a frequency shift produces an advancing or retarding phase, frequency shifts can be detected by sampling phase at each symbol period. Phase shifts of (2N + 1) π/2radians are easily detected with an I/Q demodulator. At even numbered sym-bols, the polarity of the I channel conveys the transmitted data, while at odd numbered symbols the polarity of the Q channel conveys the data. This orthogonality between I and Q simplifies detection algorithms and hence reduces power con-sumption in a mobile receiver. The minimum fre-quency shift which yields orthogonality of I and Q is that which results in a phase shift of ±π/2radi-ans per symbol (90 degrees per symbol). FSK with this deviation is called MSK (Minimum Shift Keying). The deviation must be accurate in order to generate repeatable 90 degree phase shifts. MSK is used in the GSM (Global System for Mobile Communications) cellular standard. A phase shift of +90 degrees represents a data bit equal to “1,”while –90 degrees represents a “0.” The peak-to-peak frequency shift of an MSK signal is equal to one-half of the bit rate.FSK and MSK produce constant envelope carrier signals, which have no amplitude variations. This is a desirable characteristic for improving the power efficiency of transmitters. Amplitude varia-tions can exercise nonlinearities in an amplifier’s amplitude-transfer function, generating spectral regrowth, a component of adjacent channel power. Therefore, more efficient amplifiers (which tend to be less linear) can be used with constant-envelope signals, reducing power consumption.Figure 13. Frequency Shift KeyingMSK has a narrower spectrum than wider devia-tion forms of FSK. The width of the spectrum is also influenced by the waveforms causing the fre-quency shift. If those waveforms have fast transi-tions or a high slew rate, then the spectrumof the transmitter will be broad. In practice, the waveforms are filtered with a Gaussian filter, resulting in a narrow spectrum. In addition, the Gaussian filter has no time-domain overshoot, which would broaden the spectrum by increasing the peak deviation. MSK with a Gaussian filter is termed GMSK (Gaussian MSK).3.5 Quadrature Amplitude ModulationAnother member of the digital modulation family is Quadrature Amplitude Modulation (QAM). QAM is used in applications including microwave digital radio, DVB-C (Digital Video Broadcasting—Cable), and modems.In 16-state Quadrature Amplitude Modulation (16QAM), there are four I values and four Q values. This results in a total of 16 possible states for the signal. It can transition from any state to any other state at every symbol time. Since 16 = 24, four bits per symbol can be sent. This consists of two bits for I and two bits for Q. The symbol rate is one fourth of the bit rate. So this modulation format produces a more spectrally efficient transmission. It is more efficient than BPSK, QPSK, or 8PSK. Note that QPSK is the same as 4QAM.Another variation is 32QAM. In this case there are six I values and six Q values resulting in a total of 36 possible states (6x6=36). This is too many states for a power of two (the closest power of two is 32). So the four corner symbol states, which take the most power to transmit, are omitted. This reduces the amount of peak power the transmitter has to generate. Since 25= 32, there are five bits per sym-bol and the symbol rate is one fifth of the bit rate. The current practical limits are approximately256QAM, though work is underway to extend the limits to 512 or 1024 QAM. A 256QAM system uses 16 I-values and 16 Q-values, giving 256 possible states. Since 28= 256, each symbol can represent eight bits. A 256QAM signal that can send eight bits per symbol is very spectrally efficient. However, the symbols are very close together and are thus more subject to errors due to noise and distortion. Such a signal may have to be transmit-ted with extra power (to effectively spread the symbols out more) and this reduces power efficiency as compared to simpler schemes.Figure 14. Quadrature Amplitude ModulationCompare the bandwidth efficiency when using256QAM versus BPSK modulation in the radio example in section 3.1.1 (which uses an eight-bit sampler sampling at 10 kHz for voice). BPSK uses80 Ksymbols-per-second sending 1 bit per symbol.A system using 256QAM sends eight bits per sym-bol so the symbol rate would be 10 Ksymbols per second. A 256QAM system enables the same amount of information to be sent as BPSK using only one eighth of the bandwidth. It is eight times more bandwidth efficient. However, there is a tradeoff. The radio becomes more complex and is more susceptible to errors caused by noise and dis-tortion. Error rates of higher-order QAM systems such as this degrade more rapidly than QPSK as noise or interference is introduced. A measureof this degradation would be a higher Bit Error Rate (BER).In any digital modulation system, if the input sig-nal is distorted or severely attenuated the receiver will eventually lose symbol lock completely. If the receiver can no longer recover the symbol clock, it cannot demodulate the signal or recover any infor-mation. With less degradation, the symbol clock can be recovered, but it is noisy, and the symbol locations themselves are noisy. In some cases, a symbol will fall far enough away from its intended position that it will cross over to an adjacent posi-tion. The I and Q level detectors used in the demodulator would misinterpret such a symbol as being in the wrong location, causing bit errors. QPSK is not as efficient, but the states are much farther apart and the system can tolerate a lot more noise before suffering symbol errors. QPSK has no intermediate states between the four corner-symbol locations, so there is less opportunity for the demodulator to misinterpret symbols. QPSK requires less transmitter power than QAM to achieve the same bit error rate.3.6 Theoretical bandwidth efficiency limits Bandwidth efficiency describes how efficiently the allocated bandwidth is utilized or the ability of a modulation scheme to accommodate data, within a limited bandwidth. The table below shows the theoretical bandwidth efficiency limits for the main modulation types. Note that these figures cannot actually be achieved in practical radios since they require perfect modulators, demodula-tors, filter, and transmission paths.If the radio had a perfect (rectangular in the fre-quency domain) filter, then the occupied band-width could be made equal to the symbol rate.Techniques for maximizing spectral efficiency include the following:•Relate the data rate to the frequency shift (as in GSM).•Use premodulation filtering to reduce the occupied bandwidth. Raised cosine filters,as used in NADC, PDC, and PHS, give thebest spectral efficiency.•Restrict the types of transitions.Modulation Theoretical bandwidthformat efficiencylimitsMSK 1bit/second/HzBPSK 1bit/second/HzQPSK 2bits/second/Hz8PSK 3bits/second/Hz16 QAM 4 bits/second/Hz32 QAM 5 bits/second/Hz64 QAM 6 bits/second/Hz256 QAM 8 bits/second/HzEffects of going through the originTake, for example, a QPSK signal where the normalized value changes from 1, 1 to –1, –1. When changing simulta-neously from I and Q values of +1 to I and Q values of –1, the signal trajectory goes through the origin (the I/Q value of 0,0). The origin represents 0 carrier magnitude. A value of 0 magnitude indicates that the carrier amplitude is 0 for a moment.Not all transitions in QPSK result in a trajectory that goes through the origin. If I changes value but Q does not (or vice-versa) the carrier amplitude changes a little, but it does not go through zero. Therefore some symbol transi-tions will result in a small amplitude variation, while others will result in a very large amplitude variation. The clock-recovery circuit in the receiver must deal with this ampli-tude variation uncertainty if it uses amplitude variations to align the receiver clock with the transmitter clock. Spectral regrowth does not automatically result from these trajectories that pass through or near the origin. If the amplifier and associated circuits are perfectly linear, the spectrum (spectral occupancy or occupied bandwidth) will be unchanged. The problem lies in nonlinearities in the circuits.A signal which changes amplitude over a very large range will exercise these nonlinearities to the fullest extent. These nonlinearities will cause distortion products. In con-tinuously modulated systems they will cause “spectral regrowth” or wider modulation sidebands (a phenomenon related to intermodulation distortion). Another term which is sometimes used in this context is “spectral splatter.”However this is a term that is more correctly used in asso-ciation with the increase in the bandwidth of a signal caused by pulsing on and off.3.7 Spectral efficiency examples inpractical radiosThe following examples indicate spectral efficien-cies that are achieved in some practical radio systems.The TDMA version of the North American Digital Cellular (NADC) system, achieves a 48 Kbits-per-second data rate over a 30 kHz bandwidth or 1.6 bits per second per Hz. It is a π/4 DQPSK based system and transmits two bits per symbol. The theoretical efficiency would be two bits per second per Hz and in practice it is 1.6 bits per second per Hz.Another example is a microwave digital radio using 16QAM. This kind of signal is more susceptible to noise and distortion than something simpler such as QPSK. This type of signal is usually sent over a direct line-of-sight microwave link or over a wire where there is very little noise and interference. In this microwave-digital-radio example the bit rate is 140 Mbits per second over a very wide bandwidth of 52.5 MHz. The spectral efficiency is 2.7 bits per second per Hz. To implement this, it takes a very clear line-of-sight transmission path and a precise and optimized high-power transceiver.。

目录摘要 (2)ABSTRACT (3)第一章绪论 (4)第二章OFDM系统的基本介绍 (5)2.1OFDM的基本原理 (5)2.1.1 OFDM的产生和发展 (6)2.1.2 DFT的实现 (7)2.1.3 保护间隔、循环前缀和子载波数的选择 (8)2.1.4 子载波调制与解调 (10)2.2OFDM系统的优缺点 (11)2.3OFDM系统的关键技术 (11)第三章OFDM系统仿真实现 (13)3.1OFDM信号的时域及频域波形 (13)3.2带外功率辐射以及加窗技术 (15)3.3在不同信道环境和系统不同实现方式下的仿真 (18)3.3.1 调制与解调 (18)3.3.2 不同信道环境下的系统仿真实现 (20)3.3.3 系统不同实现方式的仿真实现 (22)第四章OFDM系统的仿真结果及性能分析 (23)4.1不同信道环境下的误码特性 (23)4.2不同系统实现方式下的误码特性 (28)第五章总结 (30)摘要本论文以OFDM系统为基础，介绍了OFDM系统的基本原理，以及使用OFDM技术的优势所在，并且展望了今后的无线移动技术的发展前景。

在简单介绍OFDM原理的同时，着重阐述了OFDM系统在不同信道环境和不同实现方式下的误码性能。

主要包括了OFDM系统在加性白高斯信道，在加性白高斯信道和多径干扰两种不同信道环境下系统的误码性能，其中后者还研究了系统在有保护间隔与无保护间隔的误码性能比较。

在理论分析的基础上，用MATLAB进行仿真，最后做出误码性能的分析和比较。

关键字: 正交频分复用（OFDM），离散傅立叶变换，AWGN，，多径干扰，保护间隔。

ABSTRACTThis paper presents you the basic priciple of OFDM（Orthogonal Frequency Division Multiplexing）and where it excels based on OFDM system , following with the prospective of wireless mobile communication. After a brief introduction to OFDM principle , it mainly focuses on the effect of OFDM system under different channels and with different system realizations on the Binary Error Rate (BER). It mainly includes two kinds of channels: the AWGN channel and the AWGN channel with Rayleigh fading. In the latter, we compare the BER with two different system realizations: one with Guarded Intervals(GI), and the other without (GI).Key Words : OFDM, DFT, AWGN, Rayleigh fading ,GI第一章绪论现代移动通信是一门复杂的高新技术，不但集中了无线通信和有线通信的最新技术成就，而且集中了网络接收和计算机技术的许多成果。

“L TE 增强技术”专题12018年第3期TD-LTE 256QAM高阶调制关键技术探索为了满足高速热点接入速率的要求，系统需要能支持更高阶的调制方式，比如256QAM 。

因此详细介绍TD-LTE 高阶调制技术256QAM 的技术原理，及基于BICM-ID 与MLC 的256QAM 传输技术方案，利用高端频谱资源，可实现新型高低频段协作组网结构设计；利用低频段传输信令、高频段传输业务，解决小区覆盖问题，同时提高系统频谱利用率。

TD-LTE ；256QAM ；BICM-ID ；MLC ；高端频谱资源（中国移动通信集团江苏有限公司，江苏 南京 210029）张庆，郭华**通信作者收稿日期：2018-02-13doi:10.3969/j.issn.1006-1010.2018.03.001 中图分类号：TN929.533 文献标志码：A 文章编号：1006-1010(2018)03-0001-06引用格式：张庆,郭华. TD-LTE 256QAM高阶调制关键技术探索[J]. 移动通信, 2018,42(3): 1-6.【摘 要】【关键词】Research on the Key Technology of 256QAM High Order Modulation for TD-LTEIn order to meet the requirements of high-speed hotspot access rate, the system needs to be able to support higher order modulation, such as 256QAM. In this paper, the principle of 256QAM high order modulation technology for TD-LTE was introduced fi rstly. Then, the schemes of 256QAM transmission technology based on BICM-ID and MLC were learned. The design of a new type of high-low frequency band collaboration network structure can be achieved with the use of high-end spectrum resources. The low frequency signaling transmission and high frequency services transmission, not only solve the cell coverage problem, but also improve the system spectrum utilization.TD-LTE; 256QAM; BICM-ID; MLC; high-end spectrum resource(China Mobile Communications Group Jiangsu Co., Ltd., Nanjing 210029, China)ZHANG Qing, GUO Hua[Abstract][Key words] 1 引言传统的3G 网络已不能满足室内、慢速移动、热点等有大量数据业务的业务需求，TD-LTE 网络对无线数LTE 增强技术，也被称为千兆LTE 网络技术，它实现了4G ITU 标准初期制定的1 Gbps 速率目标，是4G 迈向5G 的桥梁。

Because BER computations are fundamental to the characterization of any communications system, the system toolbox provides the following tools and capabilities for configuring BER test scenarios and accelerating BER simulations:BERtool— A graphical user interface that enables you to analyze BER performance of communications systems. You can analyze performance via a simulation-based, semianalytic, or theoretical approach.Error Rate Test Console— A MATLAB object that runs simulations for communications systems to measure error rate performance. It supports user-specified test points and generation of parametric performance plots and surfaces. Accelerated performance can be realized when running on a multicore computing platform.Multicore and GPU acceleration— A capability provided by Parallel Computing Toolbox™that enables you to accelerate simulation performance using multicore and GPU hardware within your computer.Distributed computing and cloud computing support— Capabilities provided by Parallel Computing Toolbox and MATLAB Distributed Computing Server™that enable you to leverage the computing power of your server farms and the Amazon EC2 Web service.Performance VisualizationThe system toolbox provides the following capabilities for visualizing system performance:Channel visualization tool— For visualizing the characteristics of a fading channelEye diagrams and signal constellation scatter plots— For a qualitative, visual understanding of system behavior that enables you to make initial design decisionsSignal trajectory plots— For a continuous picture of the signal’s trajectory between decision pointsBER plots— For visualizing quantitative BER performance of a design candidate, parameterized by metrics such as SNR and fixed-point word sizeCommunication-specific displays for visualizing and analyzing signals at any point or step in your model. Displays include (clockwise from top left): Channel impulse response history, I/Q signal eye diagrams, BER performance plot for theoretical vs. simulated results, and received signal scatter plot.Analog and Digital ModulationAnalog and digital modulation techniques encode the information stream into a signal that is suitable for transmission. Communications System Toolbox provides a number of modulation and corresponding demodulation capabilities. These capabilities are available as MATLAB functions and objects, MATLAB System objects, and Simulink blocks.Modulation types provided by the toolbox are:Analog,including AM, FM, PM, SSB, and DSBSCDigital,including FSK, PSK, BPSK, DPSK, OQPSK, MSK, PAM, QAM, and TCMMATLAB function (left) and Simulink model (right) with scatter plot for 16 QAM simulation.Source and Channel CodingCommunications System Toolbox provides source and channel coding capabilities that let you develop and evaluate communications architectures quickly, enabling you to explore what-if scenarios and avoid the need to create coding capabilities from scratch.Source CodingSource coding, also known as quantization or signal formatting, is a way of processing data in order to reduce redundancy or prepare it for later processing. The system toolbox provides a variety of types of algorithms for implementing source coding and decoding, including:▪Quantizing▪Companding (µ-law and A-law)▪Differential pulse code modulation (DPCM)▪Huffman coding▪Arithmetic codingChannel CodingTo combat the effects noise and channel corruption, the system toolbox provides block and convolutional coding and decoding techniques to implement error detection and correction. For simple error detection with no inherent correction, a cyclic redundancy check capability is also available. Channel coding capabilities provided by the system toolbox include:▪BCH encoder and decoder▪Reed-Solomon encoder and decoder▪LDPC encoder and decoder▪Convolutional encoder and Viterbi decoder▪Orthogonal space-time block code (OSTBC) (encoder and decoder for MIMO channels)▪Turbo encoder and decoder demosThe system toolbox provides utility functions for creating your own channel coding. You can create generator polynomials and coefficients and syndrome decoding tables, as well as product parity-check and generator matrices.The system toolbox also provides block and convolutional interleaving and deinterleaving functions to reduce data errors caused by burst errors in a communication system:Block,including General block interleaver, algebraic interleaver, helical scan interleaver, matrix interleaver, and random interleaverConvolutional,including General multiplexed interleaver, convolutional interleaver, and helical interleaver Channel Modeling and RF ImpairmentsChannel ModelingCommunications System Toolbox provides algorithms and tools for modeling noise, fading, interference, and other distortions that are typically found in communications channels. The system toolbox supports the following types of channels:▪Additive white Gaussian noise (AWGN)▪Multiple-input multiple-output (MIMO) fading▪Single-input single-output (SISO), Rayleigh, and Rician fading▪Binary symmetricA MATLAB channel object provides a concise, configurable implementation of channel models, enabling you to specify parameters such as:▪Path delays▪Average path gains▪Maximum Doppler shifts▪K-Factor for Rician fading channels▪Doppler spectrum parametersFor MIMO systems, the MATLAB MIMO channel object expands these parameters to also include:▪Number of transmit antennas (up to 8)▪Number of receive antennas (up to 8)▪Transmit correlation matrix▪Receive correlation matrixSimulink model of an adaptive MIMO system with orthogonal space-time block codes (OSTBC).RF ImpairmentsTo model the effects of a nonideal RF front end, you can introduce the following impairments into your communications system, enabling you to explore and characterize performance with real-world effects:▪Memoryless nonlinearity▪Phase and frequency offset▪Phase noise▪Thermal noiseYou can include more complex RF impairments and RF circuit models in your design using SimRF™.An ideal 16 QAM scatter plot (left) impaired by a phase offset (middle) and a frequency offset (right).Equalization and SynchronizationCommunications System Toolbox lets you explore equalization and synchronization techniques. These techniques are generally adaptive in nature and challenging to design and characterize. The system toolbox provides algorithms and tools that let you rapidly select the appropriate technique in your communications system.EqualizationTo evaluate different approaches to equalization, the system toolbox provides you with adaptive algorithms such as:▪LMS▪Normalized LMS▪Variable step LMS▪Signed LMS▪MLSE (Viterbi)▪RLS▪CMAThese adaptive equalizers are available as nonlinear decision feedback equalizer (DFE) implementations and as linear (symbol or fractionally spaced) equalizer implementations.Scatter plot of a QPSK signal that shows the signal before and after equalization, as well as the ideal signal constellation.SynchronizationThe system toolbox provides algorithms for both carrier phase synchronization and timing phase synchronization.For timing phase synchronization, the system toolbox provides a MATLAB Timing Phase Synchronizer object that offers the following implementation methods:▪Early-late gate timing method▪Gardner’s method▪Fourth-order nonlinearity method▪Mueller-Muller methodSimulink model of timing, carrier frequency, and carrier phase recovery for an MSK receiver.Received signal scatter plot (left), after frequency recovery (middle), and after phase recovery (right).Stream Processing in MATLAB and SimulinkMost communication systems handle streaming and frame-based data using a combination of temporal processing and simultaneous multifrequency and multichannel processing. This type of streaming multidimensional processing can be seen in advanced communication architectures such as OFDM and MIMO. Communications System Toolbox enables the simulation of advanced communications systems by supporting stream processing and frame-based simulation in MATLAB and Simulink.In MATLAB, stream processing is enabled by System objects, which use MATLAB objects to represent time-based and data-driven algorithms, sources, and sinks. System objects implicitly manage many details of stream processing, such as data indexing, buffering, and management of algorithm state. You can mix System objects with standard MATLAB functions and operators. Most System objects have a corresponding Simulink block with the same capabilities.Simulink handles stream processing implicitly by managing the flow of data through the blocks that make up a Simulink model. Simulink is an interactive graphical environment for modeling and simulating dynamic systems that uses hierarchical diagrams to represent a system model. It includes a library of general-purpose, predefined blocks to represent algorithms, sources, sinks, and system hierarchy.Implementing a Communications SystemFixed-Point ModelingMany communications systems use hardware that requires a fixed-point representation of your design. Communications System Toolbox supports fixed-point modeling in all relevant blocks and System objects with tools that help you configure fixed-point attributes.Fixed-point support in the system toolbox includes:▪Word sizes from 1 to 128 bits▪Arbitrary binary-point placement▪Overflow handling methods (wrap or saturation)▪Rounding methods: ceiling, convergent, floor, nearest, round, simplest, and zeroFixed-Point Tool in Simulink Fixed Point™facilitates the conversion of floating-point data types to fixed point. For configuration of fixed-point properties, the tool tracks overflows and maxima and minima.Code GenerationOnce you have developed your algorithm or communications system, you can automatically generate C code from it for verification, rapid prototyping, and implementation. Most System objects, functions, and blocks in Communications System Toolbox can generate ANSI/ISO C code using MATLAB Coder™,Simulink Coder™, or Embedded Coder™. A subset of System objects and Simulink blocks can also generate HDL code.To leverage existing intellectual property, you can select optimizations for specific processor architectures and integrate legacy C code with the generated code. You can also generate C code for both floating-point andfixed-point data types.DSP PrototypingDSPs are used in communication system implementation for verification, rapid prototyping, or final hardware implementation. Using the processor-in-the-loop (PIL) simulation capability found in Embedded Coder, you can verify generated source code and compiled code by running your algorithm’s implementation code on a target processor.FPGA PrototypingFPGAs are used in communication systems for implementing high-speed signal processing algorithms. Using the FPGA-in-the-loop (FIL) capability found in EDA Simulator Link™, you can test RTL code in real hardware for any existing HDL code, either manually written or automatically generated HDL code.USRP2 SDR Device InterfaceTo support the real-time processing of received signals and the real-time generation of waveforms for transmission, the system toolbox provides a Simulink interface to the Universal Software Radio Peripheral 2 (USRP2) software defined radio (SDR) device.The interface consists of two Simulink blocks: a receiver block to stream data from the USRP2 and a transmitter block to stream data to the USRP2. Both blocks provide a concise configuration capability, consisting of specifying operating center frequency, gain, and interpolation/decimation rate.Product Details, Demos, and System Requirements/products/communicationsTrial Software/trialrequestSales/contactsalesTechnical Support/support Simulink transmitter test bench showing USRP2 Transmitter block (top right) and parameter mask (bottom).ResourcesOnline User Community /matlabcentral Training Services /training Third-Party Products and Services /connections Worldwide Contacts /contact。

1Features•Two independent clock channels•Frequency and Phase Sync over Packet Networks •Frequency accuracy performance for WCDMA-FDD, GSM, LTE-FDD and femtocell applications •Frequency performance for ITU-T G.823 and G.824 synchronization interface, as well as G.8261 PNT PEC and CES interfaces•Phase Synchronization performance forWCDMA-TDD, Mobile WiMAX, TD-SCDMA and CDMA2000 applications•Client holdover and reference switching between multiple Servers•Server, client and boundary clock operation•Any input clock rate from 1kHz to 750MHz •Automatic hitless reference switching and digital holdover on reference fail•Digital PLLs filter jitter at 5.2 Hz, 14 Hz, 28 Hz, 56 Hz, 112 Hz, 224 Hz, 448 Hz or 896 Hz•Operates from a single crystal resonator or clock oscillator•Electrical phase alignment to input 1 Hz frame pulse with associated reference clock (ref/sync pairing)•Programmable synthesizers •Any output clock rate from 1Hz to 750MHz •Low output jitter for 10G PHYs•Six LVPECL outputs and six LVCMOS outputs•Field programmable via SPI/I 2C interfaceApplications•OTN muxponders and transponders •10Gigabit line cards•Synchronous Ethernet, SONET/SDH, Fibre Channel, XAUIMarch 2014Figure 1 - Functional Block DiagramZL30367Dual Channel IEEE 1588 & SynchronousEthernet Clock Line Card TranslatorShort Form Data SheetOrdering Information:ZL30367GDG2144 Pin LBGATraysPb Free Tin/Silver/Copper-40o C to +85o CPackage size: 13 x 13 mmDetailed FeaturesGeneral•Two independent clock channels•Operates from a single crystal resonator or clock oscillator•Configurable via SPI or I2C interfaceTime Synchronization Algorithm•External algorithm controls software digital PLL to adjust frequency & phase alignment•Frequency, Phase and Time Synchronization over IP, MPLS and Ethernet Packet Networks•Frequency accuracy performance for WCDMA-FDD, GSM, LTE-FDD and femtocell applications, with target performance less than ± 15 ppb.•Frequency performance for ITU-T G.823 and G.824 synchronization interface, as well as G.8261 PNT EEC, PNT PEC and CES interface specifications.•Phase Synchronization performance for WCDMA-TDD, Mobile WiMAX, TD-SCDMA and CDMA2000 applications with target performance less than ± 1 s phase alignment.•Time Synchronization for UTC-traceability and GPS replacement.•Client reference switching between multiple Servers•Client holdover when Server packet connectivity is lostElectrical Clock Inputs•Nine input references configurable as single ended or differential and two singled ended input references •Synchronize to any clock rate from 1kHz to 750MHz on differential inputs•Synchronize to any clock rate from 1kHz to 177.75MHz on singled-ended inputs•Synchronize to sync pulse and clock pair•Flexible input reference monitoring automatically disqualifies references based on frequency and phase irregularities•LOS•Single cycle monitor•Precise frequency monitor•Coarse frequency monitor•Guard soak timer•Per input clock delay compensationElectrical Clock Engine•Flexible two-stage architecture translates between arbitrary data rates, line coding rates and FEC rates •Internal state machine automatically controls mode of operation (free-run, locked, holdover)•Automatic hitless reference switching and digital holdover on reference fail•Physical-to-physical reference switching•Physical-to-packet reference switching•Packet-to-physical reference switching•Packet-to-packet reference switching•Selectable phase slope limiting•Supports ITU-T G.823, G.824 and G.8261 for 2048kbit/s and 1544kbit/s interfacesElectrical Clock Generation•Three programmable synthesizers•Six LVPECL outputs•Two LVPECL outputs per synthesizer•Generate any clock rate from 1Hz to 750MHz•Low output jitter for 10G PHYs•Meets OC-192, STM-64, 1 GbE & 10 GbE interface jitter requirements•Six LVCMOS outputs•Two LVCMOS outputs per synthesizer•Generate any clock rate from 1 Hz to 177.75MHz•Programmable output advancement/delay to accommodate trace delays or compensate for system routing paths•Outputs may be disabled to save powerAPI Software•Interfaces to 1588-capable PHY and switches with integrated timestamping•Abstraction layer for independence from OS and CPU, from embedded SoC to home-grown•Fits into centralized, highly integrated pizza box architectures as well as distributed architectures with multiple line cards and timing cardsInformation relating to products and services furnished herein by Microsemi Corporation or its subsidiaries (collectively “Microsemi”) is believed to be reliable. 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优化WiFi测试分享Agenda•常见的挑战•理解功率校准•利用EVM进行IQ 不平衡测试•同步进行晶体调较•MIMO中的功率校准常见的挑战优化考虑•Combining factors in the most advantageous way•用最有利的方法结合需要的因素进行测试•Understanding interrelationships among variables•明白不同变数之间的互联关系•Identifying things that can be done in parallel•什麽事情可以同时进行•Reducing the number of steps by taking advantage of independent variables•利用独立变数减少编程步骤•Looking for ways to reduce test complexity•如何简化测试用最有利的方法结合需要的因素A功率校准功率校准?•用於电脑的WiFi通常发放固定功率–可能容许定议数个功率–在802.11协议中并未规范功率控制的要求–部份RSSI可用於检测传速率的变化–在较低OFDM调制时可调高发射功率•手机内置WiFi 功能有不同需要–UMA 要求准确功率控制•需要准确的RSSI (用於何时切换基站)•功率控制下可容纳更多用户–即使connection-oriented WiFi, 通常亦使用功率控制•发射信号会干扰移动网络信号–发射较低功率当移动功能在使用中•功率控制可确保高功率使用时保持最高速率射频设计结构•充份利用集成方案为现代的射频设计结构–直接上调–直接下调–通用增益控制–IQ不平衡+直流偏置•需调校或芯片内部自调–通常有发射回路设置XX PLLBase Band (digital)通用闭环功率控制图XADCPower couplerPowerdetect Powerselectvco ControlLogic闭环功率控制•通常使用参考电平作调校–在信号回路中校准存储目标参数•回路信号可快可慢–要小心确保回路信号的稳定性•闭环功率控制会复杂化单包的功率测量–功率不能保证稳定–为确保功率测量准确性需采用多次测试的平均值发射功率控制•重点於了解EEPROM中存储的资料和如何使用它–闭环通常存储回路值或曲线值–可以是测量值或开始值Power Low Mid High101121151171111611912012119123124131********14128130132151********16136139140优化校准•最简单的方法调校控制值以得出目标功率–通常需返覆进行调校才可达到目标功率•需确定一个目标功率–校准时可能没有调至绝对吻合的功率–需设定一个接受范围为目标功率之上下限–在一个指定范围存在多点•并不是一个非常有效率的方法!!!–可否在目标功率上考虑些甚麽?–所需要的资料都应在曲线图上–可利用插补法或曲线配合加快校准–目的是取得与EEPROM中同样数据•校准后, 无人知道数据是如何衍生•优化最大的效果是校准时间的提升Algorithm exampleSet start pointMeasure powerwhile (power outside target range){ Adjust controlMeasure power}Save control valueSelect next pointMeasure powerwhile (power outside target range){ Adjust controlMeasure power}Save control valueExtrapolate EEPROM dataSave EEROM data Set start pointMeasure powerSave control value Select next point Measure powerSave control value Extrapolate EEPROM dataSave EEROM data利用EVM进行IQ 不平衡测试利用EVM进行IQ 不平衡测试增益不平衡是来自在上调I和Q基带信号之间的电平误差,EVM此误差产生星座图的失真而劣化而劣化EVM通常IQ 不平衡校准•残余边带信号的问题(Undesired side band suppression (USB) of CW signal)–调校IQ不平衡可优化或劣化残余边带信号–IQ不平衡调校的控制参数•电平不平衡•相位不平衡–Typical algorithm takes 4 different values of the one, with the other fixed •找出最理想的点•重复其他数值•最少需8 + 1 次的测量•问题在於残余边带信号是电平和相位误差结合而成–其中一个参数可能主导另一个使推断残余边带信号的变化更为困难•通常都需要多次重复测试vco vcovco利用EVM进行IQ 不平衡测试•在EVM 分析中亦需对电平和相位分别测量–电平与控制属线性关系–相位与控制属线性关系•可同时进行校准过程–不需分开处理•在EVM中,它们相对独立较少互联–知道它们的斜度关系可加快测试电平误差****同步进行晶体调较同步进行晶体调较同步进行晶体调较•EVM 分析中亦有频率误差的报告•电平误差, 相位误差, 频率误差都是独立较少互联的参数–改变一个参数并不影响其化参数•可进行IQ不平衡同时进行晶体调校–不需增加成本一次过校准•在测量EVM同时获得功率值–用於IQ不平衡和频率测量•尽可能进行所需校准於一个步骤中–同时调校功率,电平,相位和频率–利用获得最理想EVM 值而得到最好的功率,电平,相位和频率校准–而后转换为单一功率测试功能为以后的项目测试IQ_CAL_TX_ALL______________________________________________________IQ_power cal result file: Log//TxCal_0611_1409_3627.txtIQAmpl_Offset: 2 ( 0.00 *................. 63.00)IQPhase_Offset: 59 ( 0.00 ................*. 63.00)IQ amplitude mismatch : -0.04 ( -0.05 ..*............... 0.05)IQ phase mismatch : -0.36 ( -0.50 ..*............... 0.50)Calibration PPM : 0.00 ( -1.00 ........*......... 1.00)Calibration DAC register : 63 ( 0.00 ....*............. 255.00)•单一校准功能包含4个信道的功率校准, IQ不平衡, 晶体调校–IQmismatch and frequency error (n ppm) are close to independent of channel, so calibration can be split over multiple channels as wellMIMO中的功率校准Tx1Rx1Tx2Rx2Rx3被测品RF Switch MatrixVSAVSGIQflexRFC o m b i n e rAtt1Att2Att4Att3Multi Port Test AdapterMIMO 中的功率校准•MIMO 通常需要对每个发射机作独立校准–校准是分开连续性地进行–为甚麽?????•MIMO 信号分析是一个结合多个发射机的信号后进行的•可提供开关式或结合式的MIMO 分析数据–个别功率–个别相位和电平–频率误差(晶体)MIMO中的功率校准多合一的MIMO 校准•同步进行MIMO 发射性能校准–频率–电平(Tx1..TxN)–相位(Tx1..TxN)–功率(Tx1..TxN)•相对单一功率测量的情况–单一功率测量较快–从结合性的EVM中计算功率需要额外时间–开关式的分析比结合式EVM的功率测量快–假若只需要功率校准, 要考虑是否真的需要开关式或结合式的MIMO分析–假若其他参数亦需要校准,则功率校准不会增加太多的负担问题?Thank YouLitePoint Corporation575 Maude CourtSunnyvale, California 94085USATel +1.408.456.5000Fax +1.408.456.0106。