协同通信与AF和DF中继协议详情

AbstractNowadays, there is a trend for communication system that the whole network system is becoming dynamic so that there are always having devices should be embedded and removed. Conventional wired communication, due to the complexity of cabling, does not adapt to the modern communication system. Wireless technique has been used widely because devices can be connected by electromagnetism wave without cabling. However, low transmitting reliablity because of inter-interference between electromagnetism waves is the key problem of wireless communication. Based on this, this thesis investigates one of the technique called cooperative communication and it cooperative protocols.Cooperative communication is a virtual multiple-input multiple-output(MIMO) system. To increase the reliability of signal transmitted without increasing the amount of communication devices, this technology tries to make each antennas have one or more partners that assist them to transmit the signal. In wireless network, the devices not only transmit their own signal but also assist their “partner” to transmit their signal for saving the cost of installation of additional antennas at both receiver and senderIn this thesis, we focus on introducing three main protocols in cooperative communication: Amplify-and –Forward(AF), Decode-and-Forward(DF) and Coded Cooperation(CC). The performance and mathematical equations of AF and DF are analysed , and then MATLAB programs were created to simulate the performance of these two protocols.About the three protocols, the main procedures are also introduced. The performance comparison for AF and DF in different signal-to-noise(SNR) aredemonstrated. The result presents that the DF protocols has better performance than AF. Finally, some recommendations and future work are mentioned at the end of the thesis.Table of ContentsAbstractTable of containsList of figuresList of abbreviations and Symbols1 Introduction.................................................................... .. (9)1.1Background.............................................................. (9)1.2Objectives.............................................................. (9)1.3Approaches.............................................................. (9)1.4Thesisoutline................................................................. (10)2LiteratureReview....................................................................... (12)2.1Overview................................................................ (12)2.2Spatial diversitytechnology.............................................................. (13)2.3Basic Model forWireless................................................................ (13)2.3.1SISOsystem.......................................................... (13)2.3.2MIMOsystem.......................................................... (14)2.3.3Cooperativemodel........................................................... (14)2.4Cooperativeschemes................................................................. (15)2.4.1Amplify-and-forwardmethod.......................................................... (16)2.4.2Decode-and-forwardmethod.......................................................... (16)2.4.3Codedcooperation..................................................... (17)3Simulation and Analyses ofAF........................................................................... (21)3.1Overview................................................................ (21)3.2Maximum likelihoodmethod.................................................................. (21)3.3Simulation andAnalysis................................................................ (21)3.3.1The whole procedure andanalysis........................................................ (21)3.3.2Simulation...................................................... (24)3.4Summary................................................................. (26)4Simulation and Analysis ofDF........................................................................... (27)4.1Overview................................................................ (27)4.2Quantizationmethod.................................................................. (27)4.3Convolutional Code and Viterbidecode.................................................................. (27)4.3.1Convolutionalcode............................................................ (28)4.3.2Viterbidecode.......................................................... (28)4.4Simulation andanalysis................................................................ (28)4.4.1The whole procedure andanalysis........................................................ (29)4.4.2Simulation...................................................... (30)4.5Performance comparison between AF andDF (31)4.6Mainchallenges.............................................................. (32)4.7Summary................................................................. (33)5Conclusions and futurework......................................................................... (34)5.1Conclusion.............................................................. (34)5.2Prospect................................................................ (34)5.3Futurework.................................................................... (35)Reference.............................................................. (36)Appendix A Thesisspecification.......................................................... (37)Appendix B Logbook SummarySignature.............................................................. (40)Appendix C MATLABprograms............................................................... (41)C.1 Amplify-and-ForwardProtocol (41)C.2 Decode-and –Forwardprotocol……………………………………………………..................……42C.3 Rayleighchannel………………………………………………………...................... (45)List of FiguresFigure 2.1 virtual MIMOsystem (13)Figure 2.2 Cooperativecommunication ………………………………………………………………………….....……14Figure 2.3 MIMO system............................................................................................................. .. (15)Figure 2.4 Cooperative model (16)Figure 2.5 Relay amplify model………………………………………………………………………………………...……..17Figure 2.6 Decoded and forward model (18)Figure 2.7 Coded cooperative model (19)Figure 2.8 Coded cooperation data allocation (20)Figure 2.9 Four cases in coded cooperative (20)Figure 3.1 first time slot in AF method (23)Figure 3.2 Second time slot in AFmethod (24)Figure 3.3 AF protocol BERdiagram (26)Figure 4.1 (n,k,m) convolutional encoder (29)Figure 4.2 first time slot of DF (3)Figure 4.3 Second time slot (30)Figure 4.4 DF protocol BER diagram (32)Figure 4.5 DF whole procedures (32)Figure 4.6 performance compared between AF and DF (33)List of Abbreviations and SymbolsMIMO Multiple input multiple outputSISO Single input single outputAF Amplify-and-ForwardDF Decode-and-ForwardCC Coded CooperationBER Bit error rateQPSK Quadrature phase-shift keyingi.i.d independently and identically distribution ML Maximum likelihoodSNR Signal –noise-ratio1 Introduction1.1 BackgroundWireless communication is, recently, the fastest improving segment and most widely used way of the communication industry. For utilizing the broadcast property of electromagnetism wave, the information can be transmitted in wireless environment, which saves much cost for cabling and makes the change of network structure easily. On the other hand, as wireless technique is used more widely, there are also many problems appearing. For example, the wireless signal can be affected a lot by the transmitting medium and interfered with other signal and the destination will receive not only the direct wave but also some extra waves. These sorts of wave signal will generate and form the received signal at the destination, which will result in sharply differing with the original signal so that decreases the quality of signal and reliability. This is called multipath fading[11]. To solve these problems, cooperative communication is one of the methods.Cooperative communication technique is a method based on MIMO(multiple-input multiple-output)system. MIMO system is a model that installing more than one antennas in both the sender and receiver, which achieve one signal is transmitted by different channels. In practical, due to the limitation of size, power waste and hardware, it is hard to install a lot of antennas in one communication device so that MIMO technique is hard to utilize in practical directly. Thus, cooperative communication is a model that builds a virtual MIMO system among existing antennas instead of building additional antennas but achieves the gain of MIMO system[8].Compared with traditional transmitting method, cooperative communication builds a cooperative work relationship between each antenna which means each antenna will have a helper to assist them to transmit signal and these helper antennas will take some measures to optimize the quality of signal. Therefore, at the destination, lots of signals will be received so that receiver can have gain of diversity. Some protocols describe what functions these antennas apply for optimizing signal. In this report, some explanations and literature reviews focused on amplify and forward protocol, decoded and forward protocol and coded cooperative protocol are demonstrated. Otherwise, simulation result for amplify and forward and decoded and forward protocol is made.1.2 ObjectivesThe purpose of this project is to analyse the advantages of cooperative communication by analysis of three main cooperative protocols. In this half year, this project can have a conclusion about three objectives:1.Trying to understand the concept of cooperative communication and itsworking system models. Research for how the signal delivered through nodes.2.Finding the three cooperative protocols that antennas obey—AF( amplify—and-- forward), DF (decode- and- forward) and CC (coded cooperation) protocols and how they works.e the MATLAB to simulate the performance of AF and DF and do acomparison about them.1.3 ApproachesFirstly, analyzing the concept of cooperative communication and finding the fundamental protocols about it. Secondly, finding the important described equations and the used coefficients. Finally, use MATLAB to simulate the procedures of AF and DF and try to get the BER( bit errorrate)-SNR(signal-Noise ratio) diagram and compare the their performance.1.4 Thesis outlineThis report includes five parts: first part introduce the background of cooperative communication. Second part explains several literature reviews about wireless, diversity technology, MIMO and cooperative protocols. Third and forth parts demonstrate the simulation about AF and DF and get the result diagram. Additional, the forth part also includes the performance comparison between AF and DF. Last part makes a conclusion and the future work about the project.2 Literature Review2.1 OverviewTo overcome the lack of multiple antennas limited by size or hardware complexity, cooperative communication is proposed. Cooperative communication can be understood a virtual multiple input multipleoutput(MIMO) system between source and destination.In another words, the cooperative communication build a cooperative relationship among existing antennas. For utilizing the broadcast property of electromagnetism wave, not only the destination, there are also some other antennas receive the source signal. Instead of discarding this signal, this relationship asks these antennas to take some measures to process this signal and retransmit it to the appointed destination.Figure 2.1 virtual MIMO systemTo decrease the bit error rate and recover the source signal well, there are three common protocols for the helper antennas applying: amplify and forward(AF) protocol, decoded and forward (DF) protocol and coded cooperative(CC) protocol.Figure 2.2 Cooperative communication2.2 Spatial diversity technologyCooperative communication utilizes the spatial diversity technology. Diversity is an idea that transmitting a signal through many independent channels, it is described in [1]. When source sends one signal in different independent channels, the destination will receive many formats about this signal. In this way, it can increase the signal-to-noise ratio(SNR) at the receiver which result in recovering the source signal better. There are three common diversity technologies: time diversity, frequency diversity and spatial diversity. Spatial technology is to build many relays to retransmit the signal which creates additional channels in space. The cooperative communication applies the spatial diversity technology mainly[4].2.3 Basic Model for Wireless2.3.1 Single input and single output (SISO) systemSingle input and single output is the tradition model which both transmitter and receiver have one antenna to send or receive signal. In this way, the information is transmitted by electromagnetism wave in the air. Due to the effect of multiple path fading, the destination is hard to recover the source signal from receiver signal.2.3.2 Multiple input and multiple output(MIMO) systemAs the name said, MIMO allows both the source and destination to have multiple antennas to send and receive signal[9]. Due to the effect of multiple path fading, the quality of signal will be decreased. However, by buildingadditional ways between source and destination, more information will be transmitted at the same time and for the destination many formats of source signal will be received so that MIMO can greatly improve the spectrum utilization and channel capacity without increasing the bandwidth. But more antennas mean more communication devices in both source and destination. It has to cost a lot to build enormous system to support the multiplexing technology[9].Figure 2.3 MIMO system2.3.3 Cooperative modelThe basic cooperative model is the source-relay-destination model. Here we defined the cooperative antenna as relay. This model is naturally represented by the graph below [3]. Here we set the source-to-relay channel gain to H1, noise is N1; the gain of source-to-destination to H2, noise is N2; the gain of relay-to-destination to H3, noise is N3. At the first time slot, the source sent the source signal X1 to the relay and destination:Y2=H1*X1+N1Y3=H2*X1+N2At the second time slot, the relay takes some measures to process the received signal Y2, we set the process to C: X2=C*Y2. Then, the relay retransmitted the X2 to the destination: Y4=H3*X2+N3. As a result, at the destination Y4 and Y3 are received:Y3=H2*X1+N2Y4=C*H3*H1*X1+C*H3*N1+N2The destination’s task is recovering X1 from Y3 and Y4.2.4 Cooperative schemesAlthough the spatial diversity technology can increase the rate of successful packet receipt and the receiver SNR, during the signal transmitting through the channel (Rayleigh fading channel), the signal still suffer from the fading like noise. Due to the negative effect of Rayleigh fading, the signal density and phase will be changed. To weakened this effect, the relay node need to take some cooperative coding strategies.2.4.1 Amplify-and-forward method (AF)In practical, during the signal transmitted in channel, one of the fading problems is amplitude fading, which may lead to packets loss and power efficiency decreasing [4].Amplify-and-forward method is quite simple. After the relay received the signal from source, the relay just amplifies the signal and retransmits it to the destination. Although the noise part is amplified as well, the destination can have gain of diversity[8]. However, the amplify coefficient should meet the constraint of power. Here, we set the power of source sending signal to P, the power of noise between source and relay is n1. The power of retransmitting is P1. We can get(the energy is amplified, not the power): sqrt*P1=B*sqrt*(P+n1) B=sqrt*(P1/(P+n1))Figure 2.5 Relay amplify model2.4.2 Decoded-and-forward (DF) methodThere is another method for the relay to process the received signal. Compared to the AF, this method is more complex.In this method the relay attempts to detect the received signal from source. At the first time slot, the source sends the signal to relay and source in 50% of total power respectively. At the second time slot, after the relay received the signal from source, it will decode it and detect if error happens during source-to-relay channel. If there are errors, the relay will stay silent and the source will send the signal to the destination in 50% of total power again. If no errors, the relay will encode the signal and retransmit it to the destination. In this way, because the relay only retransmits the right signal the error bits will be decreased. However, it should notice that DF is limited by the quality of source-to-relay channel[8].Figure 2.6 Decoded and forward model2.4.3 Coded cooperationInstead of simple processing signal by relay in the AF or DF method, coded cooperation is a combination of channel coding and cooperative communication[6]. Coded cooperation is a idea that by two independently and identically distribution channels transmitting one host’s different parts of data bits. Its basic idea is that each hosts transmit their incremental redundancy to their partner. If the quality of channel between hosts is bad, it will change to non-cooperative model.Figure 2.7 Coded cooperative modelThe communication among users is with no feedback for the transmission operated automatically through the code design. The signal to be transmitted will be divided into blocks and each block will be sent in two frames[6].Figure 2.8 Coded cooperation data allocationIn the first frame, each user tries to decode partner’s data. If decoded successfully, it will send partner’s second part data. If not, send the second part data of its own. Due to no feedback among users, each user does not know if partner decoded its first data part successfully or not so there are four possible situations. Each user decoded partner’s data successfully, no user decoded successfully. One of users decoded successfully.Figure 2.9 Four cases in coded cooperative[6]For recovering the original signal from the corresponding users, the destination needs to know which case is occurred. One of the methods is that destination thinks about and checks every case according to their emergence possibilities until the CRC bits present correct result. The other method is each user attaches an additional information bits in their second part codeword that includes which case is occurred [6]. The first method takes too much time and the second method makes the whole process complex.3 Simulations and Analyses of AF3.1 OverviewAmplify and forward method is a simple method to decrease the bit error rate at receiver based on diversity technology. Its main idea is to amplify the signal and noise. Then this signal is retransmitted to the destination. The challenge is how to recover the original signal at the receiver. The Maximum Likelihood method (ML) can meet the requirement.3.2 Maximum likelihood methodAs the destination receives much signal with noise, it is the destination’s responsibility for recovering the original signal from received signal. Maximum likelihood method is just an estimation method instead of getting accurate signal, which is described in [7]. The data set and the statistical model are known. The task is to estimate the model's parameters. Always, the maximum likelihood makes a approximate model with some selected parameters to forecast the wanted value. Here we consider QPSK signal. For a discrete time block and the signal is transmitted through Rayleigh fading channel. The received signal can be: y=Hx+n, where H is a known channel matrix and n is the noise. The fading coefficients are i.i.d. To recover the original signal x, where xis one of (1, -1, -i, i), then minimizes |y-Hx|2 [10].i3.3 Simulation and Analysis3.3.1 The whole procedure and analysisBefore source broadcasting the signal, the source will modulate the digital signal into Quadrature Phase Shift Keying(QPSK) signal Xs (1, -1, i, -i). The whole procedure is divided into two time slot. At the first time slot, the source sent the signal to the relay and destination respectively. The mathematical equation can be present as below:Source to relay: Y1=sqrt(P*1/2)*h1*S+n1 (3.1)Source to destination: Y2=sqrt(P*1/2)*h2*S+n2 (3.2)Where P means the signal power, h1 and h2 is the Rayleigh channel gain of source to relay and destination respectively. n1 and n2 are the additive Gaussian noise during each channel. The figure below describes the behaviourof the source at the first time slot.At the second time slot, the relay receive the noisy signal Y1 from sourceand amplifies it by amplify coefficient B. For efficient B, there are someconstraints for it. It is impossible that the signal will not be amplifiedinfinite. To ensure the power of the relay is limited, B needs to satisfythe condition:)) (3.3)B=sqrt(P/(P*|h1|2+NWhere Nis the power of the noise.After amplified, the signal will be:))* (sqrt(P*1/2)*h1*S+n1)Y3=b*Y1= sqrt(P/(P*|h1|2+N(3.4)The Y3 is transmitted to destination through Rayleigh channelY4=sqrt(P)*h3*Y3+n3))* (sqrt(P)*h1*S+n1)+n3=sqrt(P)*h3* sqrt(P/(P*|h1|2+N))* sqrt(P)*h1*S+=sqrt(P)*h3* sqrt(P/(P*|h1|2+Nsqrt(P)*h3* sqrt(P/(P*|h1|2+N))*n1+n3(3.5)So far, the destination received Y4 and Y3 two signal. The destination’sresponsibility here is to recover “S” by Y4 and Y3 used Maximum Likelihood(ML)method. After the digital signal transmitted to QPSK signal, every symbolof the signal has four different valuesdh=[1 -1 i -i] (3.6)By selecting the value of “S(i)” from the dh that minimums the D3, constitutea string of signal which is likely to the original signal.D1=|Y4- sqrt(P)*h3* sqrt(P/(P*|h1|2+N))* sqrt(P)*h1*S|2(3.7)D2=|Y2- sqrt(P)*h2*S|2 (3.8)D3=D1+D2 (3.9)(which S selected fromdh)Using this method, we can get the processed signal “S’“. Finally, thedestination will use the QPSK demodulation method to get the original signal“s’“.To judge the performance of AF protocol, a parameter “bit error rate(BER)”is used.BER=E/N (3.10) Which E is the error bits of processed signal compared with the original,N is the number bits of original signal. The BER is changed in different numberof signal-to-noise ratio (SNR) due to the noise amplitude.SNR=Ps /Pn(3.11)Where Ps stands for the signal power and Pn means the noise power. As the increasing of the SNR, it can be seen that the noise is decreasing in the channel which leads to the decreasing of BER.3.3.2 SimulationTo make the result more accurate, it is a good idea to use the as much as symbols signal. The signal length is set to 100000. Otherwise, due the signal power is calculated by SNR, we set the range of SNR to 0 to 30 . Before transform the signal, the source will modulate the binary signal to QPSK signal.Build the QPSK modulator:x=randint(1,N);X=modulate(modem.pskmod(4),x)For simple the program , we assume that the transmitting channel is Rayleigh channel which the signal magnitude is random distribution. This channel can be simulated as:For example:function H=Rayleigh(signal_size)H=sqrt(1/2)*(randn(1,signal_size)+j*randn(1,signal_size)); Apart for that, during signal transmitted in Rayleigh channel, it will be affected by noise. Here, we assume the noise is additive white Gaussion noise(AWGN). Using the MATLAB we can simulate the noise below:For example:N=sqrt(1/2)*(randn+j*randn);After destination received two signals from relay and source, it will use ML method to recover the original signal. The ML method can be simulated below:For example:dh = [1 -1 j -j];l=1:4;D2=abs(Ysd-sqrt(R*sig)*Hsd*dh(l)).^2;D1=abs(Yrd-Hrd*(sqrt(R*sig)*Hsr*dh(l)+Nsr)*B).^2; D3=D1+D2;[minScale1 positionmin1]=min(D3); Xd=[Xd dh(positionmin1)]Xd is the signal that has recovered. Then, as Xd is QPSK signal it is needed to demodulate Xd to binary signal xd. By comparing xd with the original x, it easy to find the error bits and its number. Recording the error number and the corresponding SNR value, the diagram that show the relationship between SNR and BER can be obtained. The simulation result is illustrated below:5101520253010-310-210-110t h e a v e r a g e B E RSNR(db)AF protocolFigure 3.3 AF protocol BER diagram3.4 SummaryEven though it is successful to simulate AF use MATLAB, but it seems that the line is shown with many curves and it is not smooth. By increasing the number of symbols and the times of repeating the experiment, the line became more smooth.4 Simulations and Analysis of DF4.1 OverviewThe decoded and forward (DF) method is more complex than AF. The source will use not only QPSK modulation method but also convolution coding and viterbi decoding method to process the signal. Otherwise, to adapt the data to the fading channel, the quantization method is used.4.2 Quantization methodWhen the data signal is transmitted in the format of beamforming, the performance can be improved[5]. But the quantization is needed. Quantization is a method that mapping several data bits to a symbol and assigning level to each symbols. For using these continuous symbol levels to make a databeamforming. For example, a bits flow [00 10 11 01 01 10 11]. Because we use the QPSK signal, there are four symbols and assigning two bits to a symbol. 00=0*21+0*20=0, 01=0*21+1*20=1, 10=1*21+0*20=2, 11=1*21+1*20=3.So the bits flow can be described as a beamforming like:4.3 Convolutional Code and Viterbi decodeConvolutional code is a method of error correction coding and viterbi decode is the corresponding decoding method. The main reason to apply error correction coding in a wireless system is to decrease the effects of fading channel and reduce the probability of bit error. The bit error probability for a coded system is the probability that a bit is decoded in error.4.3.1 Convolutional codeConvolutional code is an idea that adding redundancy after a code flow. The common pattern of convolutional code is like this:Figure 4.1 (n,k,m) convolutional encoderIt means that every k input symbols have n output symbols. The n-k is the redundancy code. The redundancy code plays a role of supervising. The n output symbols are called a group. The redundancy code has a relationship with n group’s input symbols before it. Plus the input symbol in its own group, there are n+1 correlation symbols. We called n+1 traceback length[2].4.3.2 Viterbi decodeViterbi decode is a common decoding method for convolutional code. It applies the correlation property between redundancy codes to recover the original symbols. Otherwise, it should note that the decoding operation causes a delay in bits that equal to the traceback length[2].4.4 Simulation and analysis4.4.1 The whole procedure and analysisThe whole procedure of DF is divided into 3 time slot. In the first time slot, the source acts same as AF source dose that broadcast the signal to the relay。