论文研究-OFDM subcarrier Interval Determination Scheme for Resisting Doppler Shift in LEO Satellite System.pdf

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低轨卫星OFDM系统中基于子载波间隔调整方案的抗频偏技术,孙春晖,刘鲁鹏,在低轨道卫星移动通信系统中,由于移动终端和通信卫星的相对移动,接收信号受到多普勒频移的影响,引起系统性能的下降.比如误比
国武技论文在线 tp://www.papcr.cdu.cn a d. 【 +7k Where n is the aWGn component on the k subcarrier, ar is the fading gain, ar, is the transmitted data, and Afr is the normalized frequency offset. The received signal after FFT is expressed as M-1 /27Mm/M Vie n7 n(l-m+△T) ,(N-1)( inx(-m+△T) +∑cm1a1+n The first polynomial is the desired signal, and the second part is the ICI. And c o can be written as: j2zKAT7N sin T(A/T)i(N-LXNTYN N sin(△T) Given that each link experiences Doppler frequency, the SinR of the kth subcarrier of one 85 link can be written as SINRE E[S] E[S:]]] k+M]印]+F Where S is the average power of desired signal, I, is the average power of interfere from other subcarriers, and N is the average power of AWGN. We can deduce the formulas as follow 90 [s 1=ETlcoa, 1=co El(a,) E1=印∑c1a1关ePE(a1)E[a)1=(1-E(a)E(a)1(6) l=0.l≠k Hence the sinr of the k, subcarrier is written as SINR= E[(a4)]EI(a)] (1-co)E(a)2EI(a1)2]+N Where f is the bandwidth of the subcarrier, which is also called subcarrier interval. In 95 order to simplify the system model, we assume that the SiNRs of every subcarrier are the same, and the total SINR value equals to the sinr of the k, subcarrier In the system model there are several links between lEOs and ms, and we can use the strategy of Maximum ratio combination to obtain a preferable performance. Hence the SINR of m links can be written as SNR=∑*SNR Where Bi means the weight of i link, 国武技论文在线 tp://www.papcr.cdu.cn SINR B SINR From formula(3)and(6), we can deduce that when the subcarrier bandwidth increases, the average power of ICi would decrease while the power of AWgn would increase, which would 105 result in the change of SiNR. The simulation of SINR is shown in Fig. 2 SINR 13.5 fixed subcarrier interval variable subcarrier interval 5000 subband hz Fig. 2. SINR In Fig. 2, the SINRs with fixed subcarrier interval of 8 kHz and variable subcarrier interval are compared. The straight line represents SiNR of the fixed subcarrier interval. with the increase 110 of subcarrier interval, the SiNR would first increase and then decrease, and there is a higher SINR than that with fixed subcarrier among a range of subcarrier bandwidth The subcarrier interval Adjusting Scheme BER role in measuring the performance of the communication system Assuming that the system uses BPSK modulation. the ber formula can be derived as follows! l0 BER=((√2*SNR (10) Where SiNR can be obtained from formula( 8). With different frequency offsets of several links, the ber of the combined signal was simulated as Fig 3 As shown in Fig 3, with subcarrier interval increasing, the ber decreases at first and then increases. The ber of fixed subcarrier bandwidth can be regard as a reference. The fixed 120 subcarrier interval is designed as 8 kIIZ, according to the European standard of dvb transfer mode 3 4 国武技论文在线 tp://www.papcr.cdu.cn X 16 fixed subcarrier interval variable subcarrier interva 1.4 1.2 0.8 0. 4000 5000 6000 10000 subbandHz Fig 3. BER versus subcarrier Bandwidth In the communication system, user capacity is usually one of the most important targets. In 125 OFDM system, a subcarrier can only be used by one subscriber. And the channel capacity of one subcarrier can be written as Where sut, is the subcarrier interval, and SINR indicates the S/NR of th iw stbcan y f u log(1+SINR) We can calculate the number of subcarriers one subscriber needs utilizing the following formula user rate(m) 130 (12) Where user rate(m) indicates the m, users data rate. And one subscriber probably needs several subcarriers, so the system with hundreds of subcarriers can hold many subscribers So the total user capacity named as UsrNum can be deduced as r Rate[m] (13) 135 As the subcarrier interval changes, the number of containable subscribers must be varied. Fig 4 shows that, with subcarrier interval increasing the user capacity would increase first and then decrease. The user capacity of fixed subcarrier interval can be regard as a reference. As shown in Fig. 4, there is a range of subcarrier interval, with the user capacity larger than the fixed subcarrier interval fixed subcarrier interval 5000 140 subband Fig. 4. User Numbers versus subcarrier interval 国武技论文在线 tp://www.papcr.cdu.cn Here we proposed an algorithm to search for the maximum user capacity of system under constrain of BEr threshold value, which equals to the ber with fixed subcarrier interval. Based on the analysis of BER and user capacity, the optimization problem model and the constraints can 145 be formulated as bj UsrNi L Usr RatemI max beR< (1 B N*f (15) Where Obj. refers to the objective lunction, while the Cons. means the constraint 150 conditions. And ah is the Ber threshold, equivalent to the ber of the fixed frequency interval system. Formulas(15)refers to the constraint of total bandwidth. Then the subcarrier interval adjusting scheme is given as follows A. General iteration procedure Generate frequency offset values of multiple links named fofserl offset 2\ fofiet3.,and 155 calculate ber with the fixed subcarrier bandwidth as a 2. ith an initial subcarrier interval fsw, calculate the sinr of every link and then deduce the lotal Sinr of all links utilizing maximum ratio combination stralegy according to formula(8) And then deduce Ber according to formula(10) 3. If BER>ah, increase the subcarrier bandwidth, h+fo f o is the step length. And then deduce BER again 4. Repeat step 3 until BER<a. Calculate user capacity named as UsrNum according to formula (13) B, Iterative search procedure 165 5. Continue to increase the subcarrier interval f., and calculate ber 6. If BER<a, calculate User Capacity named as USrNumI. And if UsrNum1 >UrNum update the User Capacity, UsrNum-UsrNum 7. Repeat step 5- step 6, until BER>n again. The Iterative Search Procedure is finished The first part includes step 1 step 4, which is named as General Iteration Procedure. In this 170 part we increase f'h and iterate over the incremental subcarrier interval to satisfy the constraint condition of BEr. And the second part includes Step 5-step 7, named as Iterative search procedure. In this part we search for the maximum user capacity based on the condition of BERn. Through the General Iteration Procedure and Iterative Search Procedure, we can mak sure that we find the maximum user capacity under the condition of satisfying the constraints, so 175 as to determine the most suitable subcarrier interval 3 Simulation results 3.1 Simulation Parameter Settings This section is primarily engaged in simulating and analyzing the performance of proposed algorithm above. The doppler frequency shift is randomly generated, ranging from 400Hlz 180 600Hz respectively in different links. The other parameters is designed at Tab. 1 Tab.I Parameters setting 国武技论文在线 tp://www.papcr.cdu.cn Parameters ues Description InKs nine SubbandFixed 8000/ Fixed subcarrier interval N 024 Fixed subcarrier number Subband 4000Hz-10000Hz Varied subcarrier interval SNBI 13dB SNB of st link SNB 14dB SNB of 2nd Link SB3 16dB SNB of 3rd link Ainha 0.8 Fading gain User Low Rate 15k 25k Data rate of general users User High Rate 5(k~100k Data rate of senior users In order to simulate the practical data rate, we divide users into two groups. One represents the general user required lower data rate, and the other represents the senior user required high data rate. The user numbers' proportion of the two groups is set to be 3: I 185 3.2 Simulation Parameter Settings Fig 5 shows the User Capacity performance of different schemes. In the general Iteration lgorithm, iteration stops when BER<uu. In the proposed Iterative Search algorithm, iteration carries on to search for a maximal user capacity. Obviously, the proposed Iterative Search algorithm needs more iterations than General Iteration algorithm, but it achieves a larger user capacit 710 700 Userdeapacity H+H+++++ 十+++HHH++HHHH++ ot terative search Fig. 5. USer Capacity of General Iteration and Iterative Search As shown in Fig. 5, General Iteration algorithm needs 25 iterations, and its user capacit achieve about 682, while Iterative Search algorithm needs 80 iterations and the user capacity can 195 rise to 728. Apparently, the proposed scheme needs much more iterations, but its user capacity is 6. 7% larger than general Iteration algorithm Fig. 6 shows the cumulative distribution function(CDF) of General Iteration scheme and Iterative Search scheme 国武技论文在线 tp://www.papcr.cdu.cn 0.7 种排手科什计册册出册删册 0.6 0.3 0.1 760740720700680660640620600580 200 Fig. 6. Performance comparison of General Iteration scheme and Iterative Search scheme In Iterative Search scheme, the probability of user capacity more than 700 is 68%, while in General Iteration scheme, the probability of user capacity more than 700 is 18%. Obviously, the Iterative Search scheme is more likely to achieve a larger user capacity than the General Iteration scheme 205 In the leo satellite communication system, the varied frequency offset does a great harm to the received signal performance. The General iteration Scheme presents an idea of adjusting the subcarrier interval, but it only searches for an available subcarrier interval to diminish the influence of frequency offset into an acceptable range. Then the lterative Search scheme not only decreases the inlluence of frequency offset, but also finds an optimal subcarrier interval to achieve 210 a largest user capacity at the expense of greater computational complexity 4 Conclusion An Iterative Search scheme based on resisting the varied frequency offset and maximizing uSer capacity by searching for the most suitable subcarrier interval is proposed in this context Though the proposed scheme somewhat increases computational complexity, it greatly improves 215 the user capacity. Generally speaking, with the system performance improved, the proposed scheme is of great significance for the coming development of LEO satellite communication system R eferences 220 noisy fading Doppler channels(ci! International Symposium on Signal Processing and ITS Application s with [1 Noor L, Anpalagan A, Kandeepan S SNR and ber derivation and analysis of downlink OFDM syster 2007:1-4 [2]A. Tripathi, V. Anand and A. K. Jain, "Study of OFDM and analysis of BER using intcr carrier inlcrferncc technique, "2016 International Conference on Innovation and Challenges in Cyber Security (ICICCS-INBUSH) Greater noida. India. 2016 225 [3]T C Lin and S M. Phoong, "A New Cyclic-Prefix Based Algorithm for Blind CFO Estimation in OFDM Systems, " in IEEE Transactions on Wireless Communications, vol. 15, no 6, pp. 3995-4008, June 2016 [4] Simon E P, Hijazi H, Ros L Joint Carrier Frequency OfFset and fast lime-varying channel estimation for MIMO-OFDM systems[J]. IEEE Transactions on Vehicular Technology, 2011, 60(3): 167-172 [5] Sreedevi s, Susan R J. Blind iterative carrier frequency offset estimation in orthogonal frequency division 230 multiplexing system with non-constant modulus signalling[C]' First International Conference on Computational ystems and Communications IEEE, 2014: 10-6 6 Zhang Z, Gc l, Tian F, cl al. Carrier frequcncy offsct cslimalion ofOFDM systems based on complementary sequence[C] International Congress on Image and Signal Processing. IEEE, 20 14 [7 Lei w, Dubey V K Performance of frequency and time domain coded OFDm over fast fading LEO 235 channels[C]//IEEE, 2000: 179-183 8 Zhang s, liu X, Jia M. a frequency synchronization algorithm for OFdm in mobile satellite communication 国武技论文在线 tp://www.papcr.cdu.cn systems[C]/ IEEE Conference Anthology. 2013: 1-4 [9 Xiao J, Feng S, Wei L, et al. Research on Cooperative Diversity in Mobile Satellite Communication System[J] Przeglad Elektrotechniczny, 2010, 1(9): 304-307 240 [10]Zhao Y, Haggman S G BER analysis of oFDM communication systems with intercarrier interference[C] Intcrnalional Confcrencc on CommunicaLion Tcchnology Procccdings 1998 低轨卫星OFDM系统中基于子载波间 245 隔调整方案的抗频偏技术 孙春晖,刘鲁鹏,张英海 电了工程学院,北京邮电大学,北京100876) 摘要:在低轨道卫星移动通信系统中,由于移动终端和通信卫星的相对移动,接收信号受创 多普勒频移的影响,引起系统性能的下降.比如误比特率的上升.鉴于一个地面移动终端同 250时被多颗低轨卫星覆盖,本文提出一种基于子载波间隔调整并利用多链路信号合并的抗频 偏方案,以实现最大的用户容量.同时,误比特率将被控制在一个合理的门限值以内.本文 首先分析了了载波间干扰,并推导了多普勒频移存在的前提下多链路信号合并的信丁噪比 公式.然后通过理论分析,推刭了误比特率和系统用户容量表达式.最后通过仿直对比分 析,验证了新方案可以实现更大的系统用户容量 255关键词:多普勒频移;信十噪比;多链路信号;用户容量;优化子载波间隔 中图分类号:TN927+.2

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