附录一、英文原文OFDM Channel Estimation in the Presence of Frequency Offset andPhase NoiseAbstract–In this paper, we consider OFDM channel estimation in the presence of frequency offset and phase noise. In the literatures, most channel estimation methods assume perfect frequency synchronization and the knowledge of channel statistics. Phase noise and residual frequency offset cause inter-carrier interference (ICI), which consequently impairs the accuracy of channel estimation. The lack of knowledge of channel statistics can make channel estimation much harder. To resolve these problems, we propose with the aid of cyclic prefix (CP) based frequency offset estimation statistics-independent channel estimation. We iteratively search for the most likely channel impulse response (CIR) length, and use it not only for the optimum compensation of frequency offset, but also for finding the optimum window to filter the least square (LS) channel estimate which further suppress the effects of ICI and noise. The proposed scheme is compared with conventional methods for both non-interpolation and interpolation cases2. Numerical results are presented to illustrate the effectiveness of the proposed scheme.I. INTRODUCTIONOrthogonal frequency division multiplexing (OFDM) is a bandwidth efficient transmission technique which provides high bandwidth efficiency and is quite effective in handling time dispersion of multipath fading channels. It has been chosen as the transmission method of many standards in wire and wireless communications, such as Digital Subscribe Line (DSL), European Digital Audio and Video Broadcasting (DAB/DVB), IEEE 802.11a and European HIPERLAN/2 for wireless local area network (WLAN) etc..Based on multi-carrier modulation [1], OFDM has symbol period long enough to eliminate inter-symbol interference (ISI) caused by time dispersive channels. Nevertheless, the multicarrier modulation is also sensitive to frequency offset and phase noise. Frequency offset and phase noise cause loss of orthogonality among subcarriers and consequently introduce inter-carrier interference (ICI). The effect of phase noise has been analyzed in many papers [2]-[4]. Many approaches have also been proposed to analyze, estimate and compensate frequency offset [2][5]-[10]. Though it is impossible to estimate random phase noise, frequency offset estimation can be achieved by using pilot signals [5][6]. As these methods cause loss of bandwidth efficiency, non-pilot-aided frequency offset estimation has be used [7]-[10]. The cyclic prefix (CP) based method, initially proposed in [9], is quite attractive among non-pilot-aided approaches due to its simplicity. Nevertheless, the accuracy of the CP-based method could not be guaranteed for multipath fading channels. Later, asproposed in [10], the method of [9] was improved by considering the channel impulse response (CIR) length. The proposed method in [10], however, is not feasible in cases when the CIR length is unknown.Furthermore, channel estimation is a very important issue for OFDM systems. Blind channel estimation is a desirable approach as it does not require pilot signals. It does require, however, a large amount of data and thus higher computational complexity. With perfect frequency synchronization (without residual frequency offset), different pilot-symbol-aided channel estimation methods can be applied in OFDM [11]-[14]. The maximum likelihood/least square (ML/LS) estimators of [11] and [12] can readily be implemented without knowing channel statistics. The minimum mean square error (MMSE) estimators in [12]-[14], however, are more robust against noise and perform better than the ML/LS estimators. Nevertheless, its dependence on channel statistics and the operating signal to noise ratio (SNR) makes it disadvantageous. Despite its robustness against mismatch [13][14], when there is no a priori knowledge of channel statistics and the operating SNR, the performance inevitably degrades. Without the assumption of perfect frequency synchronization, the performance may further degrade due to frequency offset and phase noise.In this paper, we consider statistics-independent channel estimation in the presence of frequency offset and phase noise. As a function of the CIR length, the LS channel estimate results, which is based on the CP-based frequency offset estimation and compensation, are used to search for the CIR length iteratively. The minimization of channel estimation errors leads to the most likely CIR length, which is then used to optimize frequency offset estimate, and filter the LS channel estimate reducing its sensitivity to noise and ICI. Thus better performance is achieved.The paper is organized as follows. The OFDM system model is introduced in Section II. Section III presents and analyzes the proposed frequency offset and channel estimation scheme. Section IV provides the numerical results to illustrate the effectiveness of the proposed scheme. The paper is concluded in Section V.II. OFDM SYSTEM MODELThe basic principle of OFDM is to divide each data symbol into N samples (subcarriers). The length N discrete Fourier transform (DFT) is applied to those samples and a cyclic prefix(CP) is added to eliminate ISI. Data is recovered at the receiver in reverse order. We define the length of CP as g N and the length of CIR as L , and further assume that CIR is finite and its length is less than that of CP, i.e., L < g N .At OFDM receiver, following the DFT and due to the presence of frequency offset and phase noise, the received k th sample of the m th symbol in frequency domain can be expressed by()()()()()()2F g m n m N N n j N m m m m n r k s n g n eπεφξ++⎛⎫+ ⎪ ⎪⎝⎭⎧⎫⎪⎪=⊗+⎨⎬⎪⎪⎩⎭(1)where sm (n), gm (n) and ()n n φ denote the transmitted signal, the CIR and phase noise, respectively. ξm (n ) indicates the AWGN noise. ε is the normalized frequency offset3. We assume ε ≤ 0.5 and the 3 dB line width of phase noise is much less than frequency offset. Equivalently, (1) can be given by()()()()()()()()1m m 0I 0I N m m m m m m l l k r k x k h k x l h l l k z k -=≠=+-+∑(2)where x m (k ), h m (k ) and z m (k ) are the corresponding frequency domainexpressions of s m (n ) , g m (n ) and ξm (n ) respectively. I m (i )is a function of ε and φm (n ) , given by:()()()()2120g n n j m N N N N j n i N m n e I i eN πεπεφ+⎡⎤-⎣⎦++⎡⎤⎣⎦==∑(3)where i = 0,..., N −1 . From (2) together with (3), frequency offset and phase noise cause the common phase error (CPE) and introduce inter-carrier interference (ICI) as well. For the m th symbol, Representing (2) by matrix yields=+r pxh z(4)The frequency offset and phase noise in P affects the accuracy of channel estimation. We cannot measure phase noise, but frequency offset can be estimated and compensated to reduce its effects on channel estimation. The effects of phase noise and residual frequency offset (due to estimation errors) can possibly be suppressed by filtering channel estimate. For perfect frequency and phase synchronization, P reduces to identity matrix and therefore the performance of channel estimation canbe guaranteed.III. FREQUENCY OFFSET AND CHANNELESTIMATORSIn the presence of frequency offset and phase noise, both offset and channel response should be estimated to guarantee good receiver performance. Phase noise variance is assumed to be much less than unity.We a new scheme with which, by iteratively searching for the most likely CIR length and using it for both frequency offset and channel estimation, performance is greatly improved in comparison with conventional approaches. The proposed scheme is shown in Fig.1.A. CP-based Frequency Offset EstimatorCP-based frequency offset estimator in [9] is quite simple and bandwidth efficient,but it does not consider the effects of multipath fading and estimation results may not be accurate as it is based on the CP of one symbol only. The method proposed in [10] improves that of [9] by considering CIR length and taking more symbols into consideration. However, when averaging frequency offset estimates obtained separately from each symbol, accumulated errors may be larger than expected.Moreover, its dependence on the CIR length is quite a problem when channel statistics is not available. A different method is thus proposed in this paper to solve these problems. Like [10], several symbols are used to estimate frequency offset, but it does not accumulate errors by using the following expression for estimation.()()()()11*011ˆ2g M m m g m k N p p angle r k r k N N M επ--==-+⎛⎫=+ ⎪⋅⎝⎭∑∑ (5) where p is the CIR length which is unknown, M is the number of symbols used for averaging. The unknown parameter p (as we will show later) can be set initially to one and be found by iteration. Therefore, we can still get the accurate estimate of (5) even without channel statistics.B. Channel EstimatorChannel estimation is quite crucial for OFDM systems. Also as stated earlier, LS method is advantageous over MMSE method due to its simplicity and independence of channel statistics. Hence assuming in this paper unknown channel statistics, we will focus on LS method. The estimate of (5) can be used to compensate for the frequency offset, after which, we will get from (4) thatp '=+r p xh z (6)where p P 'takes the same form of P except that I (i ) is replaced by()()n 12(m n)((p))/N 2m/N (n)01g N j N N p n I i e N πεεπφ-++-++⎡⎤⎣⎦='=∑ (6a)As shown in Fig. 1, channel estimate is easily obtained by using the LS method, which can be expressed by1ls p p -=p x r (7)The LS method is quite sensitive to interference and noise. Therefore without perfect frequency and phase synchronization, the effects of frequency offset and phase noise become worse. Furthermore, there would still be residual frequency offset even after compensation, which, together with phase noise, introduces CPE and ICI. Though CPE might partially be compensated by channel estimation itself, ICI will definitely affect the accuracy of such estimation. Therefore, some method must be introduced to reduce the sensitivity of channel estimation to interference and noise.As CIR has a finite length in time domain, the response beyond this CIR length is thus due to ICI and noise. Hence, a window function may be used to filter out these effects of ICI and noise on channel estimates. In time-domain, using a window function on (7) yieldsH s ls l p p p h WW B h = (8)()()()()()011T p p diag diag b bp bp N ==-⋯⎡⎤⎣⎦p B b is an N × N diagonal matrix defined by the window function[]()[]()[]10,2(i)0.420.5cos()0.08cos(),2021,1m i p i p i p b i p p p p i p N ππ⎧∈⎪⎪⎪--⎪=++∈⎨⎪⎪∈+-⎪⎪⎩ (9)Note that rectangular window is not used here as it introduces more high frequency components than is tolerated which causes a distortion of channel frequency response. Instead, due to its excellent descending properties, Blackman function is used in (9), as the intermediate part of the designed window.C. The Most Likely CIR Length and Final SolutionThe most likely CIR length can be found by minimizing the cost function2ls p -h h(10)To simplify the process, the window function is not used during the search, and we only have to find the proper p that produces the frequency offset estimate minimizing (10). Unfortunately, there are two unknown parameters, h and ε in (10), which makes such direct minimization difficult.However, we notice that, in the absence of AWGN noise, as p increases, frequency offset estimate of (5) becomes more accurate and the difference of channel estimates of (7) for adjacent p ’s values becomes smaller, and minimum when p isgreater than or equal to CIR length. Therefore, the minimization of (10) can be obtained by the first occurrence of the minimum of21l s l s p p --h h(11)In the presence of AWGN noise, we have to assert that the value p that minimizes (10) is the same as that of (11) before we can use (11). Statistically the minimum of (11) would occur when p is close to the CIR length when noise is not so high. (11) decreases when p increases from 1 to the CIR length since the CIR effects decreases. For increasing p, which is equivalent to using fewer samples (see (5)), the frequency offset estimation becomes less accurate and so does the channel estimate. Thus when p becomes greater than CIR length but less than CP, the difference of (11) is statistically higher when p is greater than the CIR length than when p is close to the CIR length. Hence, the minimum of (11) occurs with high probability at the point where p is equal to the CIR length. Hence, the most likely CIR length can be found by varying p between 1 and g N , and choosing the value which satisfies the following criteria22112ls ls ls ls p p p p ----≤-h h h h(12)2211ls ls ls ls p p p p -+-≤-h h h h(13)To examine the effectiveness of the criteria, we resort to computer simulation. The final channel estimate is expressed by1H ls p p P h WB W r -= (14)Where P represents the estimated value of p . Note that CIR length can found with only a single search as in most cases it does not change even in a time variant channel and the result might be used for quite a few OFDM symbols.D. Interpolated Pilot SymbolsThe aforementioned channel estimator is for non-interpolation case. However, interpolation case is often used where pilot signals are multiplexed into the transmitted data stream, i.e., pilot signals are inserted into data stream every f D samples.Without loss of generality, we assume that / f K = N D is integer, i.e., there are K pilot samples per symbol. In this case, the principle of the proposed scheme remains correct, except that the size of DFT matrix W and the window diagonal matrix p B become K × K diagonal matrices. The searching process for p remains the same, but the interpolation must be applied to the result of (8) to get the complete channel estimate.IV. NUMERICAL RESULTSThe proposed scheme was evaluated by simulation. Part of simulation parameters is based on IEEE 802.11a standard e.g., DFT length, CP length and sample period s T are 64, 16 and 0.05μ s , respectively. 3dB line width of phase noise equals 0.1% of subcarrier spacing. The actual frequency offset ε is set to 0.1382. Number of symbols used to estimate frequency offset M equals 8. Exponential Rayleigh fading channel is used with the exponential power delay profile specified by ()maxmax 1s LT rms e e ττττ-where rms τ , s T and L are the mean delay spread, sample period and CIR length respectively. rms τ is set to 0.05μ s , which equals s T . L is set to 6. There are 16 symbols per packet. The total energy of CIR has been normalized to one. Channel changes independently from symbol to symbol, but remains static within a symbol.16QAM is used to examine our scheme. The proposed scheme is compared with the frequency offset estimator of [10] plus the LMMSE channel estimator of [13] (which is termed conventional method) for both non-interpolation and interpolation cases. For fair comparison, the frequency offset estimator uses the first M symbols of each packet with unknown CIR length. Simulation results are shown in Fig. 2-5. As can be seen from Fig. 2, the proposed scheme performs quite well in estimating frequency offset. For SNR ≥ 5dB , the mean square error of the estimation is of the order of 10−3 or less. The accurate frequency offset estimate also reflects the fact that the proposed scheme is quite successful in searching for the CIR length. From Fig. 3, the most likely CIR length is 5 and an estimated length between 5 and 7 accounts for over 80percent of total possibilities, which indicates the effectiveness of CIR length searching method. Note that, since the AWGN noise affects the searching process and we use the exponential power delay profile with the maximum delay spread of 6 s T , the earch result in between 5-7 is quite reasonable.With the estimated CIR length obtained, the receiver performance is shown in Fig. 4-5, where conventional method is designated by LMMSE+FOE and the perfect case indicates OFDM signal reception with perfect frequency synchronization and the LMMSE channel estimator. Note that, in order to meet the Nyquist sampling theorem, f D must be less than N /(2L ) to guarantee the estimation accuracy for the interpolation case. The proposed scheme outperforms the conventional method and approaches the perfect situation for both non-interpolation and interpolation cases. It is shown that the proposed scheme successfully eliminates the effect of phase noise and frequency offset by approaching the perfect case as SNR increases, while conventional method exhibits an error floor.V. CONCLUSIONIn this paper, we proposed a new statistics-independent channel estimation scheme in the presence of frequency offset and phase noise. By searching for the most likely CIR length, we optimize the frequency offset estimation result. Based on thesearched CIR length, a time domain window is designed to suppress noise as well as ICI caused by phase noise and residual frequency offset. By this means, the excellent performance is achieved. This scheme approaches the performance of the LMMSE channel estimator in the absence of frequency offset and phase noise while outperforms the conventional methods for frequency offset estimation and channel estimation.二、英文翻译OFDM信道估计中的频率偏移和相位噪声摘要在本文中，我们主要考虑了OFDM信道估计中存在频率偏移和相位噪声。
BOC信号的伪码周期和组合码盲估计阳锐;张天骐;石穗;张亚娟【摘要】For the blind estimation problem of pseudo code period and combination code ( combination of spread spectrum sequence and subcarrier sequence) for BOC( Binary-Offset-Carrier) signals with residual carrier at the low signal-to-noise ratio( SNR) ,the method which combines the second power spectrum with matrix decomposition is proposed. First,this method calculates the second power spectrum of BOC signals with residual carrier. There are sharp pulses appearing at the integer times period of the pseudo code. De-tecting distance of these peaks can estimate the period of the pseudo code. Then the sampling signals are sectioned according to the period of the pseudo code to get the data vector. The correlation matrix of the da-ta vector is calculated and matrix decomposition of the correlation matrix is performed. The combined code sequence can be estimated with the two largest singular values and their vectors. The simulation results show that the method has accurate estimation performance for the signals with larger residual carrier at the lower SNR. The research in this paper has a certain reference value for those engaged in satellite navigation receiver design.%针对在低信噪比下存在残余频偏的BOC( Binary-Offset-Carrier)调制信号的伪码周期以及组合码(扩频序列和副载波序列的组合)盲估计问题，提出了功率谱二次处理结合矩阵分解的方法。
缩略语英文全称中文全称ABE Average Bioequivalence 平均生物等效性AC Active control 阳性对照ADE Adverse Drug Event 药物不良事件ADR Adverse Drug Reaction 药物不良反应AE Adverse Event 不良事件AI Assistant Investigator 助理研究者ALB Albumin 白蛋白ALD Approximate Lethal Dose 近似致死剂量ALP Alkaline phosphatase 碱性磷酸酶ALT Alanine aminotransferase 丙氨酸转氨酶ANDA Abbreviated New Drug Application 简化新药申请ANOVA Analysis of variance 方差分析AST Aspartate aminotransferase 天冬氨酸转氨酶ATR Attenuated total reflection 衰减全反射法BA Bioavailability 生物利用度BE Bioequivalence 生物等效性BMI Body Mass Index 体质指数BUN Blood urea nitrogen 血尿素氮CATD Computer-assisted trial design 计算机辅助试验设计CDER Center of Drug Evaluation and Research 药品评价和研究中心CFR Code of Federal Regulation 美国联邦法规CI Co-Investigator 合作研究者CI Confidence Interval 可信区间COI Coordinating Investigator 协调研究者CRC Clinical Research Coordinator 临床研究协调者CRF Case Report/Record Form 病历报告表/病例记录表CRO Contract Research Organization 合同研究组织CSA Clinical Study Application 临床研究申请CTA Clinical Trial Application 临床试验申请CTP Clinical Trial Protocol 临床试验方案CTR Clinical Trial Report 临床试验报告CTX Clinical Trial Exemption 临床试验免责CHMP Committee for Medicinal 人用药委会Products for Human UseDSC Differential scanning 差示扫描热量计DSMB Data Safety and monitoring Board 数据安全及监控委员会EDC Electronic Data Capture 电子数据采集系统EDP Electronic Data Processing 电子数据处理系统EWP Europe Working Party 欧洲工作组FDA Food and Drug Administration 美国食品与药品管理局FR Final Report 总结报告GCP Good Clinical Practice 药物临床试验质量管理规范GCP Good Laboratory Practice 药物非临床试验质量管理规范GLU Glucose 葡萄糖GMP Good Manufacturing Practice 药品生产质量管理规范HEV Health economic evaluation 健康经济学评价IB Investigator’s Brochure 研究者手册IBE IndividualBioequivalence 个体生物等效性IC Informed Consent 知情同意ICF Informed Consent Form 知情同意书ICH International Conference on Harmonization 国际协调会议IDM Independent Data Monitoring 独立数据监察IDMC Independent Data Monitoring Committee 独立数据监察委员会IEC Independent Ethics Committee 独立伦理委员会IND Investigational New Drug 新药临床研究IRB Institutional Review Board 机构审查委员会ITT Intention-to –treat 意向性分析IVD In Vitro Diagnostic 体外诊断IVRS Interactive Voice Response System 互动语音应答系统LD50 Medial lethal dose 半数致死剂量LLOQ Lower Limit of quantitation 定量下限LOCF Last observation carry forward 最接近一次观察的结转LOQ Limit of Quantitation 检测限MA Marketing Approval/Authorization 上市许可证MCA Medicines Control Agency 英国药品监督局MHW Ministry of Health and Welfare 日本卫生福利部MRT Mean residence time 平均滞留时间MTD Maximum Tolerated Dose 最大耐受剂量ND Not detectable 无法定量NDA New Drug Application 新药申请NEC New Drug Entity 新化学实体NIH National Institutes of Health 国家卫生研究所（美国）NMR Nuclear Magnetic Resonance 核磁共振PD Pharmacodynamics 药效动力学PI Principal Investigator 主要研究者PK Pharmacokinetics 药物动力学PL Product License 产品许可证PMA Pre-market Approval (Application) 上市前许可（申请）PP Per protocol 符合方案集PSI Statisticians in the Pharmaceutical Industry 制药业统计学家协会QA Quality Assurance 质量保证QAU Quality Assurance Unit 质量保证部门QC Quality Control 质量控制QWP Quality Working Party 质量工作组RA Regulatory Authorities 监督管理部门REV Revision 修订SA Site Assessment 现场评估SAE Serious Adverse Event 严重不良事件SAP Statistical Analysis Plan 统计分析计划SAR Serious Adverse Reaction 严重不良反应SD Source Data/Document 原始数据/文件SD Subject Diary 受试者日记SDV Source Data Verification 原始数据核准SEL Subject Enrollment Log 受试者入选表SFDA State Food and Drug Administration 国家食品药品监督管理局SI Sponsor-Investigator 申办研究者SI Sub-investigator 助理研究者SIC Subject Identification Code 受试者识别代码SOP Standard Operating Procedure 标准操作规程SPL Study Personnel List 研究人员名单SSL Subject Screening Log 受试者筛选表T&R Test and Reference Product 受试和参比试剂T－BIL Total Bilirubin 总胆红素T－CHO Total Cholesterol 总胆固醇TG Thromboglobulin 血小板球蛋白Tmax Time of maximum concentration 达峰时间TP Total proteinum 总蛋白UAE Unexpected Adverse Event 预料外不良事件WHO World Health Organization 世界卫生组织WHO- WHO International Conference WHO 国际药品管理当局会议ICDR A of Drug Regulatory AuthoritiesAberrant result 异常结果Absorption phase 吸收相Absorption 吸收Accuracy 准确度Accurate 精密度Administer 给药Amendment修正案Approval 批准Assess 估计Audit Report 稽查报告Audit 稽查Auditor 稽查员Analytical run/batch：分析批Benefit 获益Bias 偏性，偏倚Bioequivalence 生物等效Biosimilar /Follow-on biologics 生物仿制药Blank Control 空白对照Blind codes 编制盲底Blind review 盲态检查 /盲态审核Blinding method 盲法Blinding/masking 盲法/设盲Block size 每段的长度Block 层 /分段BCS 生物药剂学分类系统Carryover effect 延滞效应Case history 病历Clinical equivalence 临床等效性Clinical study 临床研究Clinical Trial Report 临床试验报告Comparison 对照Compensation 补偿，赔偿金Compliance 依从性Concomitant 伴随的Conduct 行为Confidence level 置信水平Consistency test 一致性检验Contract/ agreement 协议／合同Control group 对照组Coordinating Committee 协调委员会Crossover design 交叉设计Cross-over Study 交叉研究Cure 痊愈Data management 数据管理Descriptive statistical analysis 描述性统计分析Dichotomies 二分类Dispense 分布Diviation 偏差Documentation 记录／文件Dosage forms 剂型Dose dumping 剂量倾卸（药物迅速释放入血而达到危险浓度）Dose-reaction relation 剂量－反应关系Double blinding 双盲Double dummy 双模Drop out 脱落Effectiveness 疗效Elimination phase 消除相Emergency envelope 应急信件Enantiomers 对映体End point 终点Endpoint criteria/ measurement 终点指标Enterohepatic recycling 肠肝循环Essential Documentation 必需文件Ethical 伦理的Ethics committee 伦理委员会Evaluate 评估Exclusion Criteria 排除标准Excretion 排泄Expedite 促进Extrapolated 外推的Essentially similar product：基本相似药物Factorial design 析因设计Failure 无效，失败Finacing 财务，资金Final point 终点First pass metabolism 首过代谢Fixed-dose procedure 固定剂量法Full analysis set 全分析集GC－FTIR 气相色谱－傅利叶红外联用GC－MS 气相色谱－质谱联用Generic drug 通用名药Gene mutation 基因突变Genotoxicity tests 生殖毒性试验Global assessment variable 全局评价变量Group sequential design 成组序贯设计Hypothesis test 假设检验Highly permeable：高渗透性Highly soluble：高溶解度Highly variable drug：高变异性药物Highly：Variable Drug 高变异性药物HVDP：高变异药物制剂Identification 鉴别，身份证Improvement 好转In vitro 体外In vivo 体内Inclusion Criteria 入选表准Information Gathering 信息收集Initial Meeting 启动会议Inspection 检察/视察Institution Inspection 机构检察Instruction 指令，说明Integrity 完整，正直Intercurrent 中间发生的，间发的Inter-individual variability 个体间变异性Interim analysis 期中分析Investigational Product 试验药物Investigator 研究者Involve 引起，包括IR 红外吸收光谱Innovator Product：原创药Ka 吸收速率常LC－MS 液相色谱－质谱联用logarithmic transformation 对数转换Logic check 逻辑检查Lost of follow up 失访Mask 面具，掩饰Matched pair 匹配配对Metabolism 代谢Missing value 缺失值Mixed effect model 混合效应模式Modified release products 改良释放剂型Monitor 监查员Monitoring Plan 监察计划Monitoring Report 监察报告MS－MS 质谱－质谱联用Multi-center Trial 多中心试验Negative 阴性，否定的Non-clinical Study 非临床研究Non-inferiority 非劣效性Non-Linear Pharmacokinetics 非线性药代动力学Non-parametric statistics 非参数统计方法NTID：窄治疗指数制剂Obedience 依从性Open-blinding 非盲Open-label 非盲Original Medical Record 原始医疗记录Outcome Assessment 结果评价Outcome measurement 结果指标Outlier 离群值OIP 经口服吸收药物Parallel group design 平行组设计Parameter estimation 参数估计Parametric statistics 参数统计方法Patient file 病人档案Patient History 病历Per protocol， PP 符合方案集Permeability 渗透性Pharmacodynamic characteristics 药效学特征Pharmacokinetic characteristics 药代学特征Placebo Control 安慰剂对照Placebo 安慰剂Polytomies 多分类Post-dosing postures 给药后坐姿Potential 潜在的Power 检验效能Precision 精密度Preclinical Study 临床前研究Precursor 母体前体Premature 过早的，早发Primary endpoint 主要终点Primary variable 主要变量Prodrug 药物前体Protocol amendment 方案补正Protocol Amendments 修正案Protocol 试验方案Quality Control Sample：质控样品Rapidly dissolving：快速溶出Racemates 外消旋物Randomization 随机 /随机化Range check 范围检Rating scale 量表Recruit 招募，新会员Replication 可重复Retrieval 取回，补修Revise 修正Risk 风险Run in 准备期Safety evaluation 安全性评价Safety set 安全性评价的数据集Sample Size 样本量、样本大小Sampling schedules 采血计划Scale of ordered categorical ratings 有序分类指标Secondary variable 次要变量Sequence 试验次序Seriousness 严重性Severity 严重程度Significant level 检验水准Simple randomization 简单随机Single Blinding 单盲Site audit 试验机构稽查Solubility 溶解度Specificity 特异性Specify 叙述，说明Sponsor-investigator 申办研究者Standard curve 标准曲线Statistical model 统计模型Statistical tables 统计分析表Steady state 稳态Storage 储存Stratified 分层Study Audit 研究稽查Study Site 研究中心Subgroup 亚组Sub-investigator 助理研究者Subject Enrollment Log 受试者入选表Subject Enrollment 受试者入选Subject Identification Code List 受试者识别代码表Subject Recruitment 受试者招募Subject Screening Log 受试者筛选表Subject 受试者Submit 交付，委托Superiority 检验Supplemental 增补的Supra-bioavailability 超生物利用度（试验药的生物利用度大于对照药）Survival analysis 生存分析System Audit 系统稽查SmPC：药品说明书Standard Sample：标准样品Target variable 目标变量Treatment group 试验组Trial error 试验误差Trial Initial Meeting 试验启动会议Trial Master File 试验总档案Trial Objective 试验目的Trial site 试验场所Triple Blinding 三盲Two one-side test 双单侧检验Therapeutic equivalence：治疗等效性Un-blinding 破盲/揭盲Verify 查证、核实Visual analogy scale 直观类比打分法Vulnerable subject 弱势受试者Wash-out Period 洗脱期Well-being 福利，健康Withdraw 撤回，取消药代动力学参数Ae(0-t)：给药到t时尿中排泄的累计原形药。
