parallel processing.

ABAP-SPTA并⾏处理Parallel Processing Technique in SAP ABAP using SPTA FrameworkWith the advent of HANA and In-Memory processing, this topic might look mis-timed. But, there are many organizations, which still have no plan to move to HANA within couples of years. As they say, the show must go on and that motivated us to publish this long pending article here for those ABAPers, who still have to deal millions of rows in batch jobs and who feel the “Nights are getting too shorter to execute those batch jobs in SAP” (inspired from a friends blog).Why parallel processing required?Parallel processing is required mainly to improve the performance of any ABAP program. Using parallel processing framework we can significantly improve the processing time of any program, particularly where data volume is very high. The basic concept behindthe parallel processing framework is to divide the large volume of data into several small work packets and process different work packets into different tasks. So each work process will be processed at the same time in parallels and it will significantly reduce time. Nowadays every distribution-related projects have a large volume of data so invoking parallel processing framework is very useful to reduce time.Conventional Parallel ProcessingWe can use parallel processing framework by calling any RFC enabled function module in NEW TASK. In this way, after determining the number of work packets we can create different tasks for each work packets and process them in parallel.Also Read:Why SPTA framework required?SPTA framework is the most sophisticated and secured framework for parallel processing provided by SAP. If we want to handle multiple records and want to update/check multiple database tables in parallel, in that case, using conventional way to invoke parallel processing is difficult and there can be some ABAP memory issue. But in SPTA framework there are build in security for all the ABAP memory related issues so it is very secure. Also, SPTA framework is very easy to implement and all the parallel processing work is handled by SAP we do not need to bother how to handle it. In this way, it is also a very sophisticated framework.SPTA Parallel Processing FrameworkTo invoke SPTA framework we need to call function module SPTA_PARA_PROCESS_START_2. This is a standard SAP provided function module. In this function module, we have to use three subroutines to build our own processing logic.1. BEFORE_RFC_CALLBACK_FORM: This routine is called by the function module before calling the RFC function module. Here wehave to build different work packets which we want to process in the RFC function module.2. IN_RFC_CALLBACK_FORM: This routine is called by the function module after work packets are created. In this routine, we can useour own RFC enabled function module or custom code to process each work packets.3. AFTER_RFC_CALLBACK_FORM: This routine is called at the end by the function module. After processing of all the work packets,we have to collect all the processed data.We have mentioned server group also when calling the function module. The server group can be maintained in the RZ12 transaction. But this is BASIS activity.In the changing parameter, we have to pass our total internal table which contains all the data. From this internal table, we will create different small work packets (i.e. Internal tables) for parallel processing.In the call back program name, we have to pass the calling program name.Hope you are not confusing Parallel Processing with Parallel Cursor Technique.Now we will discuss the main three subroutines and how to call them in details.BEFORE_RFC_CALLBACK_FORM: In this routine, we have to create small internal tables which we are referring as work packets for parallel processing in the IN RFC routine. Please refer the below screenshot.All the parameters which are passed in this subroutine are mandatory. Here first we have to create small work packets. In the above code, it is defined like one work packet will contain 10 records. After creating one work packet I have ENCODE the data for further downstream processing. Also, we have to inform task manager that one RFC can be started by passing ‘X’ in the START_RFC field.Also Read:IN_RFC_CALLBACK_FORM: In this routine, we have to write own processing logic to process all the data. We can call a RFC enabled function module from this routine or we can write our own logic inside this routine also. For each work packets, different tasks will be created and each task will call this routine for processing of data. Please refer below screenshot.In the above code, I have first decoded the encoded data which is coming from BEFORE_RFC_CALLBACK_FORM routine for each work packets. Then write your own logic or call RFC enabled function module for processing. In the above example, I just sorted the randomdata. Then again I have encoded data for the downstream processing in AFTER_RFC_CALLBACK_FORM routine.AFTER_RFC_CALLBACK_FORM: In this routine after processing of all the data we have to collect data. In this routine basically, we have to prepare final internal table after all the data processing. Please refer the attached screenshot.In the above example I have decoded the data again and then displayed all the record. Here if any unit fails during processingin IN_RFC_CALLBACK_FORM no data will be available to collect because if any unit fails we must not prepare final table with less number of valid records. We can catch the failed unit by using IF_RFCSUBRC and IF_RFCMSG.So by using this function module, we can invoke parallel processing framework in a sophisticated and secure manner.Please download the code used in the above demonstration from .Please note: We can design our own parallel processing technique without using SPTA Framework. The concept remains the same in the custom design too i.e. Records get processed into multiple different tasks and that runs parallel. So the processing time is reduced manifold.My friend Partha (whom I referred in the first paragraph) has explained the custom Parallel Processing using a Program. Please check here:Also, check SCN Blog onHere Partha has explained the concept and debugging of SPTA framework in a very illustrative way. Please check theDo you have any tips, tricks, tutorial, concept, config, business case or anything related to SAP to share? Write articles at SAPYardand EARN up to 500 INR per article? Please contact us at mail@ to know more.If you GENUINELY like our articles then it would be a HUGE help if you shared, subscribed and liked us on . It might seem insignificant, but it helps more than you might think.We have organized all our SAP Tutorials on one page. Please visit the below link to find all materials at one convenient place.。

parallel的用法总结大全parallel有平行的,相同的，类似的的意思。

那你们想知道parallel的用法吗?今天给大家带来了parallel的用法,希望能够帮助到大家，一起来学习吧。

parallel的用法总结大全parallel的意思adj. 平行的,相同的，类似的,[电]并联的,[计]并行的adv. 平行地，并列地n. 平行线(面),相似物,类比,纬线vt. 使平行,与…媲美,与…相比,与…相似变形：过去式: parallelled; 现在分词：parallelling; 过去分词：parallelled;parallel用法parallel可以用作形容词parallel用作形容词时,没有比较级与最高级形式。

parallel用作形容词的用法例句In the parallel world, there might be an answer for everything.在平行世界里,似乎有一切的答案。

Parallel processing is the most important peculiarity in this design.其中,并行化的设计理念是该设计的最大特点。

The railway lines run parallel to the road.铁路线和那条道路平行。

parallel用法例句1、Parallel lines will never meet no matter how far extended.无论延伸多长，平行线永不相交。

2、Farthing Lanes just above the High Street and parallel with it.法辛巷刚好在大街的北面，与大街平行。

3、Do the emotions develop in parallel with the intellect?情感与智力是并行发展的吗?词汇精选：parallel的用法和辨析一、详细释义：adj.平行的例句：Farthing Lanes just above the High Street and parallel with it.法辛巷刚好在大街的北面，与大街平行。

PHP Parallel Usage ExampleIntroductionPHP parallel processing is a powerful feature that allows you to execute multiple tasks simultaneously. In this article, we will explore the usage of PHP parallel and provide examples to demonstrate its capabilities.Understanding PHP ParallelPHP parallel is a feature that enables you to perform multiple tasks at the same time, increasing the efficiency and speed of your applications. It is particularly useful for handling tasks that require heavyputation, such as data processing, image manipulation, and web scraping.Example 1: Data ProcessingSuppose you have a large dataset that needs to be processed. Traditionally, this would be done sequentially, which could take a long time. With PHP parallel, you can divide the dataset into smaller chunks and process them simultaneously using parallel processes.```php<?phpuse parallel\Runtime;$runtime = new Runtime();$runtime->run(function () {// Process data chunk 1});$runtime->run(function () {// Process data chunk 2});// ... (Process remaining data chunks)$runtime->close();>```In this example, the dataset is split into multiple chunks, and each chunk is processed in parallel using the `run()` method of the `parallel\Runtime` class. This significantly reduces the processing time and improves overall efficiency.Example 2: Image ManipulationAnothermon use case for PHP parallel is image manipulation. Let's say you have a set of images that need to be resized and optimized. Using PHP parallel, you can perform these tasks concurrently, accelerating the image processing workflow.```php<?phpuse parallel\Runtime;$runtime = new Runtime();$runtime->run(function () {// Resize and optimize image 1});$runtime->run(function () {// Resize and optimize image 2});// ... (Resize and optimize remaining images)$runtime->close();>```By leveraging PHP parallel, you can resize and optimize multiple images simultaneously, reducing the time it takes toplete the image manipulation process.Example 3: Web ScrapingWeb scraping often involves fetching and processing large volumes of data from multiple web pages. With PHP parallel, you can fetch and process data from multiple web pages concurrently, making the web scraping process more efficient.```php<?phpuse parallel\Runtime;$runtime = new Runtime();$runtime->run(function () {// Fetch and process data from web page 1});$runtime->run(function () {// Fetch and process data from web page 2});// ... (Fetch and process data from remaining web pages)$runtime->close();>```By utilizing PHP parallel for web scraping, you can fetch and process data from multiple web pages in parallel, greatly reducing the time it takes toplete the web scraping task.Summary and ConclusionIn this article, we have explored the usage of PHP parallel and provided examples to demonstrate its capabilities in data processing, image manipulation, and web scraping. By harnessing the power of parallel processing, you can significantly increase the efficiency and speed of your PHP applications.Personally, I find PHP parallel to be a valuable tool for handling tasks that require heavyputation. Its ability to execute multiple tasks simultaneously has greatly improved the performance of my applications, especially in scenarios where time-consuming operations are involved.In conclusion, PHP parallel is a powerful feature that can greatly enhance the performance of PHP applications, and mastering its usage can lead to more efficient and scalable solutions. I highly rmend exploring and incorporating PHP parallel into your PHP development toolkit.By following the examples and rmendations provided in this article, you can leverage PHP parallel to optimize your data processing, image manipulation, and web scraping workflows, unlocking new levels of efficiency and productivity in your PHP projects.。

中国计算机学会推荐国际学术会议和期刊目录（2015年）中国计算机学会中国计算机学会推荐国际学术期刊（计算机体系结构/并行与分布计算/存储系统）一、A类二、B类三、C类中国计算机学会推荐国际学术会议计算机体系结构/并行与分布计算/存储系统一、A类二、B类三、C类中国计算机学会推荐国际学术期刊（计算机网络）一、A类二、B类三、C类中国计算机学会推荐国际学术会议（计算机网络）一、A类二、B类三、C类中国计算机学会推荐国际学术期刊（网络与信息安全）一、A类二、B类三、C类中国计算机学会推荐国际学术会议（网络与信息安全）一、A类二、B类三、C类中国计算机学会推荐国际学术期刊（软件工程/系统软件/程序设计语言）一、A类二、B类三、C类中国计算机学会推荐国际学术会议（软件工程/系统软件/程序设计语言）一、A类二、B类三、C类中国计算机学会推荐国际学术期刊(数据库/数据挖掘/内容检索)一、A类二、B类三、C类中国计算机学会推荐国际学术会议(数据库／数据挖掘／内容检索)一、A类二、B类三、C类中国计算机学会推荐国际学术期刊（计算机科学理论）一、A类二、B类三、C类中国计算机学会推荐国际学术会议（计算机科学理论）一、A类二、B类三、C类中国计算机学会推荐国际学术期刊（计算机图形学与多媒体）一、A类二、B类三、C类中国计算机学会推荐国际学术会议（计算机图形学与多媒体）一、A类二、B类三、C类中国计算机学会推荐国际学术期刊（人工智能）一、A类。

parallel的用法总结大全parallel的用法parallel的用法总结大全parallel的意思adj. 平行的,相同的，类似的,[电]并联的,[计]并行的adv. 平行地，并列地n. 平行线(面),相似物,类比,纬线vt. 使平行,与。

媲美,与。

相比,与。

相似变形：过去式: parallelled; 现在分词：parallelling; 过去分词：parallelled;parallel用法parallel可以用作形容词parallel用作形容词时,没有比较级与最高级形式。

parallel用作形容词的用法例句In the parallel world, there might be an answer foreverything.在平行世界里,似乎有一切的答案。

Parallel processing is the most important peculiarity in thisdesign.其中,并行化的设计理念是该设计的最大特点。

The railway lines run parallel to the road.铁路线和那条道路平行。

parallel用法例句1、Parallel lines will never meet no matter how far extended.无论延伸多长，平行线永不相交。

2、Farthing Lane's just above the High Street and parallel with it.法辛巷刚好在大街的北面，与大街平行。

3、Do the emotions develop in parallel with the intellect?情感与智力是并行发展的吗?词汇精选：parallel的用法和辨析一、详细释义：adj.平行的例句：Farthing Lane's just above the High Street and parallel with it.法辛巷刚好在大街的北面，与大街平行。

专利名称：A method of processing a program byparallel processing, and a processing unitthereof发明人：Seki, Mitsuho,Ikeda, Mitsuji,Kiyoshige,Yoshikazu申请号：EP93301747.7申请日：19930308公开号：EP0561541B1公开日：19981216专利内容由知识产权出版社提供摘要：In order to process a program by parallel processing using a plurality of processors, the program is divided (34) into a plurality of partial programs. Then one or more expressions are devided (38), the or each expression expressing a relationship between the partial programs, such as which can be executed independently and which require the execution of another partial program. The expression or expressions can then be investigated (37) to determine which has a desired characteristic, such as a characteristic corresponding to uniform loading of the processors. The expression can also be varied, to give more options for the selection of the expression with the desired characteristic. Then the partial programs can be distributed (14,15) to the processors on the basis of the relationship corresponding to the expression which has the desired characteristic. Furthermore, when the partial programs are being executed by the processors, any processor which has completed its processing broadcasts a signal to the other processors, which may then re-assign one or more of their partial programs. In this way, parallel processing can be carried out quickly, with substantially uniform loading ofthe processors.申请人：HITACHI LTD地址：JP国籍：JP代理机构：Calderbank, Thomas Roger 更多信息请下载全文后查看。

ABBYY FineReader EnginePerformance GuideIntegrating optical character recognition (OCR) technology will effectively extend the functionality of your application.Excellent performance of the OCR component is one of the key factors for high customer satisfaction.This document provides information on general OCR performance factors and the possibilities to optimize them in the Software Development Kit ABBYY FineReader Engine. By utilizing its advanced capabilities and options, the high OCR performance can be improved even further for optimal customer experience.When measuring OCR performance, there are two major parameters to consider:RECOGNITION ACCURACYPROCESSING SPEEDWhich Factors Influence the OCR Accuracyand Processing Speed?Image Type and Image QualityImages can come from different sources. Digitally createdPDFs, screenshots of computer and tablet devices, imagefiles created by scanners, fax servers, digital camerasor smartphones – various image sources will lead todifferent image types with different level of image quality.For example, using the wrong scanner settings can cause“noise” on the image, like random black dots or speckles,blurred and uneven letters, or skewed lines and shiftedtable borders. In terms of OCR, this is a ‘low-qualityimage’.Processing low-quality images requires high computingpower, increases the overall processing time and deterio-rates the recognition results.On the other hand, processing ‘high-quality images’ with-out distortions reduces the processing time. A dditionally,reading high-quality images leads to higher accuracyresults.Therefore, it is recommended to use high-quality imagesfor the OCR process.If it is not possible to influence the image quality in advance, it is recommended to enhance it prior to the recognition step. In FineReader Engine, various powerful image preprocessing functions are available:it is possible to use automatic language detection., a high number of preselected recognition languagesTo increase the recognition accuracy even more, FineReaderEngine provides dictionary and morphology support formany languages. When processing documents includingsubject-specific terms or …structures“ such as productcodes, telephone numbers or passport numbers, customcreated dictionaries can be imported to ensure high recog-nition quality.AAfrom a scanner or imported from the storage system or the memory stream. To obtain images from different sources will require different methods and influence the recognition speed. The image import from memory is generally faster than opening the images from a file storage.Image PreprocessingGenerally, the OCR process is faster for good-quality images. It is recommended to fine-tune the image preprocessing step accordingly and therefore savetime during the actual processing step.Images can be of different formats and quality. High-quality images, such as digitally created PDFs, typically do not require a lot of preprocessing work. For low-quality images, like scanned documents with incorrect scanner settings or old books, it is necessary to apply advanced imagepreprocessing functions to improve the recognition results. For the preprocessing of digital photos, the special ABBYYC amera OCR™ technology is applied. Here, the algorithms are optimized specifically for photo e nhancement. Usage of different preprocessing functions will individually influence the processing speed.The different methods and parameters used for specific processing scenarios will significantly influence the overall processing speed. Discarding unnecessary stages can speed up the entire OCR process. For example, when extracting data from predefined document areas, the document analysis is not required. When exporting the documents to TXT format or to PDF Image Only format, the synthesis stage can be skipped.Document AnalysisBrochures or newspapers often contain text in columns, tables, diagrams and pictures. Technical drawings might be large documents including complex engineering diagrams with different text orientation. For documents with such compli-cated layouts, the document analysis step will require more processing time. On the other hand, the analysis of simplelayout document like letters or contracts is very fast.Parallel Processing Using Multiple CoresFineReader Engine can be used to build applications of any scale and complexity – from a client workstation to a server- based solution or a large multi-million page project. When it comes to the OCR performance, it often makes sense to utilize multi-processor or multi-core systems to increase the processing speed.Built-in multi-core support in FineReader Engine allows different approaches to scale-up the OCR process:• Utilizing a single Engine instance• Loading several Engine instancesThere are different approaches for processing documents:Processing of Large Multi-Page DocumentsFor parallel processing of large documents with many pages the ‘FRDocument’ object is best suited. In this case, the pages of a multi-page document are processed in parallel on the CPUs available. At the end, the results are combined into one multi-page document. It is the most easy-to-code multiprocessing way. The number of processes needed is detected automatically, depending on factors such as the number of available physical or logical CPU cores, the number of free CPU cores available in the license, and the number of pages in the document. If nec-essary, the developer can easily change the multiprocess-ing settings and tune the number of processes to be run.Processing of Many Single-Page DocumentsTo process many one-page documents in parallel, which are received from the same source, e.g. a scanner, it is recommended to use the ‘BatchProcessor’ object. This object is most effective in terms of speed, when document export is not required, like in data capture scenarios with a custom output format.To perform full processing of many one-page documentsin parallel, it is recommended to use a pool of Engine in-stances. This approach is also best suited for web-service scenarios, when the input document should be processed directly after it was submitted. In this case, the document is passed to an available FineReader Engine instance from the pool and processed immediately.FineReader Engine - Speed Testing ResultsSystem ResourcesThe table presents the results of internal performance testing. Please be aware that testing results always depend on many factors, such as image quality, used recognition languages and other factors.During the OCR process, a range of different algorithms are applied. They depend on image quality, document languages, layout complexity and number of pages in the document. Accordingly, such algorithms might require higher memory resources. It is recommended to set up the system in accordance with the outlined memory requirements to optimize the processing speed by allocating adequate system memory.Technical Test InformationIntel® Core™ i5-4440 (3.10 GHz, 4 physical cores), 8 GB RAM, 4 processes running simultaneously.The performance was tested on 300 documents in E nglish, using the ‘DocumentArchiving_Speed’ predefined profile. In thescenarios …One-page d ocuments“ and …One multi-page d ocument“ the d ocuments were exported as PDF format.* The text was extracted from pre-defined areas on one-page documents. No export to any file format was performed.How to Increase the Overall Processing Speed in FineReader EngineHow to Improve the Text Recognition Quality in FineReader EngineThere are several possibilities to improve the performance of your system:• Fine-tune the image preprocessing settings to deliver the highest document quality for the processing step.• During the processing step, use one of the predefined processing profiles optimized for speed and the appropriate recognition mode – balanced or fast.• Specify the correct recognition languages. Incorrect language can significantly slow down document processing. The more recognition languages are selected, the slower the speed of processing. • Use the appropriate object (FRDocument or BatchProcessor) and enable parallel processing.• Specify appropriate parameters of analysis and recognition. For example, disable table detection and page orientation correction if images contain no tables and have correct page orientation.• Omit the synthesis stage if the processed documents will be exported to TXT format or PDF Image Only format.• Use the Fast PDF Export Profile, when exporting the documents to the PDF format.• Use the special object (ExportFileWriter), which is designed for the export of very large multi-page documents into PDF format.For more information, refer to the FineReader Engine Developer’s Help:FineReader Engine offers high recognition quality. The recognition quality will always depend on factors such as image quality, language and other factors. However, there are several ways to increase the recognition quality:• Specify the correct text type.• Specify the appropriate recognition languages.• Define unique languages and custom dictionaries for the recognition of special characters or documents with specific terminology, e.g. legal or healthcare texts.• Split the facing pages of scanned books into two separate images.• Apply the special Camera OCR technology, when digital photos are processed.• Correct resolution of the image, if it significantly differs from the recommended resolution.For more information refer to the FineReader Engine Developer’s Help:As you know, in document processing the OCR process can be a very complex task. Depending on the individual document processing scenario, the OCR performance results can significantly vary. The tips for recognition accuracy and processing speed optimisation in ABBYY FineReader Engine should help you to achieve the optimal performance for your business case.Additional Information ResourcesIndividual Project SupportTo learn more about the different aspects of OCR performance optimisation and about the SDK ABBYY FineReader Engine, please use following sources of information:• ABBYY Technology portal: https://abbyy.technology/• ABBYY OCR SDK forum: https:///• The help file provided in the ABBYY FineReader Engine distributive • ABBYY FineReader Engine product pages on /ocr-sdk .If you would like to discuss a particular project, please contact us. During the testing period, you can ask standard technical questions to our ABBYY Technical Support or use ABBYY Professional Services foradvanced consultancy, in-depth project analysis and individual code review. Using ABBYY’s technical resources can shorten your development work and speed up your project. Please contact the ABBYY sales manager, if you wish to further explore these options.If you have additional questions, contact your local ABBYY representative listed under /contacts or use the online contact form /ocr-sdk/#request-demo .This software includes ABBYY® FineReader® Engine 12 recognition technologies. © 2017, ABBYY Production LLC. ABBYY , FINEREADER and ABBYY FineReader are either registered trademarks or trademarks of ABBYY Software Ltd. All product names, trademarks and registered trademarks are property of their respective owners. Windows® is a registered trademark of Microsoft Corporation in the United States and other countries. The registered trademark Linux® is used pursuant to a sublicense from LMI, the exclusive licensee of Linus Torvalds, owner of the mark on a world-wide basis. Mac® and OS X® are trademarks of Apple Inc., registered in the U.S. and other countries. Datalogics®, The DL Logo®, PDF2IMG™ and DLE™ are trademarks of Datalogics, Inc. Adobe®, The Adobe Logo®, Adobe® PDF Library™, Powered by Adobe PDF Library logo, Reader® are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States and/or other countries. Portions of this computer program are copyright © 1996-2007 LizardTech, Inc. The software is based in part on the work of the Independent JPEG Group. Portions of this software are copyright ©2011 University of New South Wales. Unicode support: © 1991-2013 Unicode, Inc. Intel® Performance Primitives: Copyright © 2002-2008 Intel Corporation. Portions of this software are copyright © 1996-2002, 2006 The FreeType Project . WIBU, CodeMeter, SmartShelter, and SmartBind are registered trademarks of Wibu-Systems. All rights reserved. All other trademarks are the property of their respective owners. #9612en。

ISSN1004⁃9037，CODEN SCYCE4Journal of Data Acquisition and Processing Vol.34，No.6，Nov.2019，pp.1094-1100 DOI：10.16337/j.1004⁃9037.2019.06.016Ⓒ2019by Journal of Data Acquisition and Processinghttp：//E⁃mail：sjcj@ Tel/Fax：+86⁃025⁃84892742一种并行处理的联合频相估计杨茜1于中阳2（1.郑州大学体育学院，郑州，450044；2.西安邮电大学通信与信息工程学院，西安，710121）摘要：在高速移动通信系统中，收发端双方往往会面临较大的多普勒扩展和有限的导频开销，从而严重影响传统联合频相估计的性能。

鉴于此，本文提出了一种基于并行处理的联合频相估计。

首先利用可变有效延迟长度的自相关算子设计出一种频相解耦合算法，再将其应用到传统联合频相估计中。

理论分析和仿真结果表明，提出的频相解耦合算法可以实现传统联合频相估计的并行处理，同时还可以降低相偏估计的复杂度。

关键词：载波同步；串行处理；并行处理；频相解耦合；移动通信中图分类号：TN911.23文献标志码：AParallel Processing⁃Based Joint Frequency⁃Phase Offset EstimationYang Xi1，Yu Zhongyang2(1.Physical Education College of Zhengzhou University,Zhengzhou,450044,China;2.School of Communications and Information Engineering of Xi a n University of Posts&Telecommunications,Xi a n,710121,China)Abstract：In high⁃speed mobile communication systems，there exist two prominent issues⁃large Doppler spread and limited pilot resource between the transmitter and receiver，which has great influence on the performance of a traditional joint frequency⁃phase offset estimation.In this case，this paper proposes a parallel processing⁃based joint frequency⁃phase offset estimation.First，we utilize a variable delay⁃length auto⁃correlation operator to design a frequency⁃phase decoupling algorithm and apply it to the traditional joint frequency⁃phase offset estimation.Theoretical analysis and simulation results show that the proposed frequency⁃phase decoupling algorithm can decouple the phase offset estimation and frequency offset estimation，and can also reduce complexity of the phase offset estimation.Key words:carrier synchronization;serial processing;parallel processing;frequency⁃phase decoupling; mobile communications引言在高速移动通信系统（比如卫星通信等）中，收发两端往往会面临这样两个不利因素：较大的多普勒扩展和较少的导频资源，从而导致接收端无法实现相干解调。