DOCSLIB.ORG

Performance of Turbo Encoder and Turbo Decoder for LTE Patel Sneha Bhanubhai, Mary Grace Shajan, Upena D

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Performance of Turbo Encoder and Turbo Decoder for LTE Patel Sneha Bhanubhai, Mary Grace Shajan, Upena D ISSN: 2277-3754 ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 2, Issue 6, October 2012 Performance of Turbo Encoder and Turbo Decoder for LTE Patel Sneha Bhanubhai, Mary Grace Shajan, Upena D. Dalal Latency 1. Control-plane: Less than 100 msec to Abstract— LTE (Long Term Evolution) is the upcoming establish U-plane standards towards 4G, which is designed to increase the capacity 2. User-plane: Less than 10 msec from UE and throughput performance when compared to UMTS and to Server WiMax. Turbo codes are the recent development in the area of Mobility 1. Optimized for low speeds (0-15 km/hr) forward error correction codes that achieve near-Shannon limit 2. High performance at speeds up to 120 performance.This codes have been successfully implemented in km/hr satellite and video conferencing systems and provision has been 3. Maintain link at speeds up to 350 km/hr made in 3rd generation mobile systems. The decoder systems are Coverage 1. Full performance up to 5 km compared for complexity as well as for equal numbers of 2. Slight degradation 5 km – 30 km iterations. The following figure shows the bit error rate 3. Operation up to 100 km should not be performance of the parallel concatenated coding scheme in an precluded by standard AWGN channel over a range of Eb/No values for two sets of code block lengths and number of decoding iterations. Results show II. TURBO CODES that less complex decoder strategies produce good results for voice quality bit error rates. Turbo codes were first introduced in 1993 by Berrou, Glavieux, and Thitimajshima, [2] where a scheme is Index Terms— Convolutional Interleaver, Turbo encoder described that achieves a bit-error probability of 10-5 using a Turbo decoder, MAP decoder, 3GPP LTE. rate 1/2 code over an additive white Gaussian noise (AWGN) channel and BPSK modulation at an Eb/N0 of 0.7 dB. The I. INTRODUCTION codes are constructed by using two or more component codes Long Term Evolution [1] has long been seen as the first on different interleaved versions of the same information advancement towards stronger, faster and more efficient 4G sequence. Turbo codes are a high performance forward error data networks. The technology under LTE can currently reach correction at a given code rate. These codes are especially downlink peak rates of 100Mbps and uplink speeds of used in deep space satellite communication and the 50Mbit/s. The LTE technology is also a scalable bandwidth application, which requires reliable transformation of technology for carriers operating anywhere from 20 MHz information over the communication links in the presence of town to 1.4 MHz. Long Term Evolution offers some excellent data corrupting noise. At present, these codes are competing advantages over current 3G systems including higher with Low Density Parity Check (LDPC) codes, which throughput, plug and play compatibility, FDD (Frequency produce similar performance. Turbo code implementation is Division Duplexing) and TDD (Time Division Duplexing), by a parallel concatenation of two recursive systematic low latency and lower operating expenditures. It also offers convolutional encoder codes depend on pseudo-random legacy modes to support devices operating on GPRS systems, permutation (the interleaver). The encoder performs a long bit while supporting seamless pass-through of technologies information frame. The interleaver to produce permuted operating on other older cellular towers. The authors of the frame interleaves this input bit. The first encoder RSC1 (Global system for mobile communications) and UMTS encodes the original input and the interleaved frame (Universal Mobile Telecommunications System). The (permuted frame) is encoded by RSC2. Then the two encoded technologies put forth by LTE will not only be implemented bits are merged together with the real input bits to produce the over time, they are designed to be scalable. This scalability output. means the company can slowly introduce LTE technologies over time, without disrupting current services. III. FUNDAMENTAL TURBO CODES Table I. Lte Performance Requirements [5]. The fundamental turbo code encoder is built using two Metric Requirements identical recursive systematic convolutional (RSC) codes Spectral Flexibility 1.4, 3, 5, 10, 15 and 20 MHz with parallel concatenation [3] as shown in Figure 1. An RSC Peak data rate 1. Downlink (2 Ch MIMO): 100 Mbps encoder is typically a rate 1/2 encoder and is termed a 2. Uplink (Single Ch Tx): 50 Mbps (20 constituent encoder. The input to the second constituent MHz ch) encoder is interleaved using an internal turbo code Supported antenna 1. Downlink: 4x2, 2x2, 1x2, 1x1 interleaver. Only one of the systematic outputs from the two configurations. 2. Uplink: 1x2, 1x1 component encoders is used. This is because the systematic Spectrum efficiency 1. Downlink: 3 to 4 times HSDPA Rel. 6 2. Uplink: 2 to 3 times HSUPA Rel. 6 125 ISSN: 2277-3754 ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 2, Issue 6, October 2012 output from the other component encoder is just a permuted which is the case for downlink and uplink data transmission, version of the chosen systematic output. paging and broadcast multicast (MBMS) transmissions. A rate 1/3 tail biting convolutional coding is used for downlink Xk control and uplink control as well as broadcast control Ck RSC encoder 1 channel (BCH). Zk DL-SCH Turbo code UL-SCH internal interleaver RSC encoder 2 Z’k Turbo Coding (1/3) PCH Fig 1: Turbo Code Encoder [3] MCH BCH Tail biting Convolutional DCI Coding (1/3) UCI Block Code w/ variable Rate Block Code 1/16 CFI Fig 3: Channel Coding Schemes in the LTE System [3]. VI. TURBO DECODER STRUCTURE Fig 2: Conventional Convolution Encoder and Equivalent RSC Encoder [3] The basic structure of a Turbo decoder is functionally illustrated in Fig.2. A turbo decoder consists of two maximum IV. MATH a posteriori (MAP) decoders separated by an interleaver that A conventional convolution encoder shown in [Fig. 2] is permutes the input sequence. The decoding is an iterative represented by the generator sequences process in which the so-called extrinsic information is g0(D) = 1+D2+D3 and exchanged between MAP decoders. Each Turbo iteration is g1(D) = 1+D+D3……………………………………..(1) divided in to two half iterations. During the first half iteration, It can equivalently be represented in a more compact form as MAP decoder 1 is enabled. It receives the soft channel G = [g0(D), g1(D)]………………………….(2) information (soft value Ls for the systematic bit and soft value The RSC encoder of this conventional convolutional encoder Lp1 for the parity bit) and the a priori information La1 from is represented as the other constituent MAP decoder through deinterleaving to G(D) =[1,g1(D)/g0(D)]……………………..(3) generate the extrinsic information Le1 at its output. Likewise, where the first output represented by g0(D) is fed back to the during the second half iteration, MAP decoder 2 is enabled, input. In the above representation, 1 denotes the systematic and it receives the soft channel information (soft value Ls for a output, g1(D) denotes the feed-forward output and g0(D) is permuted version of the systematic bit and soft value Lp 2 for the feedback to the input of the RSC encoder. the parity bit) and the a priori information La2 from MAP decoder1 through interleaving to generate the extrinsic V. CHANNEL CODING SCHEME IN LTE information Le2 at its output. This iterative process repeats The major channel coding schemes [3] used for different until the decoding has converged or the maximum number of transport channels in the LTE system are summarized in iterations has been reached. Figure 3. The turbo coding is used for large data packets, 126 ISSN: 2277-3754 ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 2, Issue 6, October 2012 In order to verify the Verilog HDL models for the interleaver and deinterleaver the authors have developed another top level Verilog HDL model, combining interleaver and deinterleaver [8]. The scrambled code words from the output of the interleaver is applied as input to the deinterleaver block along with clock as synchronization signal. It is observed in Fig 4 that the scrambled code word is converted into its original form at the output of the deinterleaver block. VIII. SOFTWARE MODEL Fig 4: Basic Structure of an Iterative Turbo Decoder [4]. VII. CONVOLUTIONAL INTERLEAVER A convolutional interleaver consists of N rows of shift registers, with different delay in each row. In general, each successive row has a delay which is J symbols duration higher than the previous row as shown in Fig. 5. The code word symbol from the encoder is fed into the array of shift registers, one code symbol to each row. With each new code word symbol the commutator switches to a new register and the new code symbol is shifted out to the channel. The i-th (1 ≤ i ≤ N-1) shift register has a length of (i-1)J stages where J = M/N and the last row has M-1 numbers of delay elements. Fig 7: Parallel Concatenated Convolutional coding: Turbo codes [7] Table II. RESULTS Block 512 BER-1024 BER-2048 length Eb/No BER 0 0.4825 0.4875 0.4906 3 0.4757 0.4829 0.4879 6 0.4655 0.4765 0.4829 9 0.4519 0.4668 0.4755 12 0.4327 0.4517 0.4657 [A]. Turbo Encoder Software Model Fig 5: Convolutional Interleaver [4] The convolutional deinterleaver performs the inverse operation of the interleaver and differs in structure of the arrangement of delay elements.
Load more

Recommended publications
  • Ts 136 212 V11.1.0 (2013-02)
    ETSI TS 136 212 V11.1.0 (2013-02) Technical Specification LTE; Evolved Universal Terrestrial Radio Access (E-UTRA); Multiplexing and channel coding (3GPP TS 36.212 version 11.1.0 Release 11) 3GPP TS 36.212 version 11.1.0 Release 11 1 ETSI TS 136 212 V11.1.0 (2013-02) Reference RTS/TSGR-0136212vb10 Keywords LTE ETSI 650 Route des Lucioles F-06921 Sophia Antipolis Cedex - FRANCE Tel.: +33 4 92 94 42 00 Fax: +33 4 93 65 47 16 Siret N° 348 623 562 00017 - NAF 742 C Association à but non lucratif enregistrée à la Sous-Préfecture de Grasse (06) N° 7803/88 Important notice Individual copies of the present document can be downloaded from: http://www.etsi.org The present document may be made available in more than one electronic version or in print. In any case of existing or perceived difference in contents between such versions, the reference version is the Portable Document Format (PDF). In case of dispute, the reference shall be the printing on ETSI printers of the PDF version kept on a specific network drive within ETSI Secretariat. Users of the present document should be aware that the document may be subject to revision or change of status. Information on the current status of this and other ETSI documents is available at http://portal.etsi.org/tb/status/status.asp If you find errors in the present document, please send your comment to one of the following services: http://portal.etsi.org/chaircor/ETSI_support.asp Copyright Notification No part may be reproduced except as authorized by written permission.
    [Show full text]
  • Tm Synchronization and Channel Coding—Summary of Concept and Rationale
    Report Concerning Space Data System Standards TM SYNCHRONIZATION AND CHANNEL CODING— SUMMARY OF CONCEPT AND RATIONALE INFORMATIONAL REPORT CCSDS 130.1-G-3 GREEN BOOK June 2020 Report Concerning Space Data System Standards TM SYNCHRONIZATION AND CHANNEL CODING— SUMMARY OF CONCEPT AND RATIONALE INFORMATIONAL REPORT CCSDS 130.1-G-3 GREEN BOOK June 2020 TM SYNCHRONIZATION AND CHANNEL CODING—SUMMARY OF CONCEPT AND RATIONALE AUTHORITY Issue: Informational Report, Issue 3 Date: June 2020 Location: Washington, DC, USA This document has been approved for publication by the Management Council of the Consultative Committee for Space Data Systems (CCSDS) and reflects the consensus of technical panel experts from CCSDS Member Agencies. The procedure for review and authorization of CCSDS Reports is detailed in Organization and Processes for the Consultative Committee for Space Data Systems (CCSDS A02.1-Y-4). This document is published and maintained by: CCSDS Secretariat National Aeronautics and Space Administration Washington, DC, USA Email: [email protected] CCSDS 130.1-G-3 Page i June 2020 TM SYNCHRONIZATION AND CHANNEL CODING—SUMMARY OF CONCEPT AND RATIONALE FOREWORD This document is a CCSDS Report that contains background and explanatory material to support the CCSDS Recommended Standard, TM Synchronization and Channel Coding (reference [3]). Through the process of normal evolution, it is expected that expansion, deletion, or modification of this document may occur. This Report is therefore subject to CCSDS document management and change control procedures, which are defined in Organization and Processes for the Consultative Committee for Space Data Systems (CCSDS A02.1-Y-4). Current versions of CCSDS documents are maintained at the CCSDS Web site: http://www.ccsds.org/ Questions relating to the contents or status of this document should be sent to the CCSDS Secretariat at the email address indicated on page i.
    [Show full text]
  • Ioag Infusion Plans and Roadmaps
    IOAG ROADMAP DRAFT IOAG INFUSION PLANS AND ROADMAPS (this version contains all IOAG agency(s) input) (Draft IOAG-8 Version – July 2005) (Draft IOAG-8 Version, Revision 1 – August 2005) IOAG ROADMAP This document is uncontrolled when printed. Please check the IOAG web site at http://www.ioag.org prior to use to ensure this is the latest version. IOAG ROADMAP TABLE OF CONTENTS 1 – INTRODUCTION .................................................................................................................1 2 – STRUCTURE AND MANAGEMENT OF THE PRESENT DOCUMENT...........................1 2-1 STRUCTURE ..................................................................................................................1 2-2 DOCUMENT MANAGEMENT..........................................................................................2 3 – IOAG STRATEGY PLAN....................................................................................................2 3-1 IOAG OBJECTIVES ........................................................................................................2 3-2 IOAG AREAS OF INTEREST ..........................................................................................3 4 – IOAG INTEROPERABILITY ITEMS...................................................................................6 5 – AGENCIES’ INFUSION PLANS AND ROADMAPS..........................................................7 ANNEX-1 – ASI INFUSION PLAN AND ROADMAP ...........................................................1-1 ANNEX-2 – CNES INFUSION PLAN AND ROADMAP
    [Show full text]
  • Short Low-Rate Non-Binary Turbo Codes Gianluigi Liva, Bal´Azs Matuz, Enrico Paolini, Marco Chiani
    Short Low-Rate Non-Binary Turbo Codes Gianluigi Liva, Bal´azs Matuz, Enrico Paolini, Marco Chiani Abstract—A serial concatenation of an outer non-binary turbo decoding thresholds lie within 0.5 dB from the Shannon code with different inner binary codes is introduced and an- limit in the coherent case, for a wide range of coding rates 1 alyzed. The turbo code is based on memory- time-variant (1/3 ≤ R ≤ 1/96). Remarkably, a similar result is achieved recursive convolutional codes over high order fields. The resulting codes possess low rates and capacity-approaching performance, in the noncoherent detection framework as well. thus representing an appealing solution for spread spectrum We then focus on the specific case where the inner code is communications. The performance of the scheme is investigated either an order-q Hadamard code or a first order length-q Reed- on the additive white Gaussian noise channel with coherent and Muller (RM) code, due to their simple fast Hadamard trans- noncoherent detection via density evolution analysis. The pro- form (FHT)-based decoding algorithms. The proposed scheme posed codes compare favorably w.r.t. other low rate constructions in terms of complexity/performance trade-off. Low error floors can be thus seen either as (i) a serial concatenation of an outer and performances close to the sphere packing bound are achieved Fq-based turbo code with an inner Hadamard/RM code with down to small block sizes (k = 192 information bits). antipodal signalling, or (ii) as a coded modulation Fq-based turbo/LDPC code with q-ary (bi-) orthogonal modulation.
    [Show full text]
  • Tm Synchronization and Channel Coding
    Recommendation for Space Data System Standards TM SYNCHRONIZATION AND CHANNEL CODING RECOMMENDED STANDARD CCSDS 131.0-B-3 BLUE BOOK September 2017 Recommendation for Space Data System Standards TM SYNCHRONIZATION AND CHANNEL CODING RECOMMENDED STANDARD CCSDS 131.0-B-3 BLUE BOOK September 2017 CCSDS RECOMMENDED STANDARD FOR TM SYNCHRONIZATION AND CHANNEL CODING AUTHORITY Issue: Recommended Standard, Issue 3 Date: September 2017 Location: Washington, DC, USA This document has been approved for publication by the Management Council of the Consultative Committee for Space Data Systems (CCSDS) and represents the consensus technical agreement of the participating CCSDS Member Agencies. The procedure for review and authorization of CCSDS documents is detailed in Organization and Processes for the Consultative Committee for Space Data Systems (CCSDS A02.1-Y-4), and the record of Agency participation in the authorization of this document can be obtained from the CCSDS Secretariat at the e-mail address below. This document is published and maintained by: CCSDS Secretariat National Aeronautics and Space Administration Washington, DC, USA E-mail: [email protected] CCSDS 131.0-B-3 Page i September 2017 CCSDS RECOMMENDED STANDARD FOR TM SYNCHRONIZATION AND CHANNEL CODING STATEMENT OF INTENT The Consultative Committee for Space Data Systems (CCSDS) is an organization officially established by the management of its members. The Committee meets periodically to address data systems problems that are common to all participants, and to formulate sound technical solutions to these problems. Inasmuch as participation in the CCSDS is completely voluntary, the results of Committee actions are termed Recommended Standards and are not considered binding on any Agency.
    [Show full text]
  • Download Special Issue
    Wireless Communications and Mobile Computing Error Control Codes for Next-Generation Communication Systems: Opportunities and Challenges Lead Guest Editor: Zesong Fei Guest Editors: Jinhong Yuan and Qin Huang Error Control Codes for Next-Generation Communication Systems: Opportunities and Challenges Wireless Communications and Mobile Computing Error Control Codes for Next-Generation Communication Systems: Opportunities and Challenges Lead Guest Editor: Zesong Fei Guest Editors: Jinhong Yuan and Qin Huang Copyright © 2018 Hindawi. All rights reserved. This is a special issue published in “Wireless Communications and Mobile Computing.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, pro- vided the original work is properly cited. Editorial Board Javier Aguiar, Spain Oscar Esparza, Spain Maode Ma, Singapore Ghufran Ahmed, Pakistan Maria Fazio, Italy Imadeldin Mahgoub, USA Wessam Ajib, Canada Mauro Femminella, Italy Pietro Manzoni, Spain Muhammad Alam, China Manuel Fernandez-Veiga, Spain Álvaro Marco, Spain Eva Antonino-Daviu, Spain Gianluigi Ferrari, Italy Gustavo Marfia, Italy Shlomi Arnon, Israel Ilario Filippini, Italy Francisco J. Martinez, Spain Leyre Azpilicueta, Mexico Jesus Fontecha, Spain Davide Mattera, Italy Paolo Barsocchi, Italy Luca Foschini, Italy Michael McGuire, Canada Alessandro Bazzi, Italy A. G. Fragkiadakis, Greece Nathalie Mitton, France Zdenek Becvar, Czech Republic Sabrina Gaito, Italy Klaus Moessner, UK Francesco Benedetto, Italy Óscar García, Spain Antonella Molinaro, Italy Olivier Berder, France Manuel García Sánchez, Spain Simone Morosi, Italy Ana M. Bernardos, Spain L. J. García Villalba, Spain Kumudu S. Munasinghe, Australia Mauro Biagi, Italy José A. García-Naya, Spain Enrico Natalizio, France Dario Bruneo, Italy Miguel Garcia-Pineda, Spain Keivan Navaie, UK Jun Cai, Canada A.-J.
    [Show full text]
  • Configurable and Scalable Turbo Decoder for 4G Wireless Decoder
    Configurable and Scalable Turbo Decoder for 4G Wireless Receivers Yang Sun Rice University, USA Joseph R. Cavallaro Rice University, USA Yuming Zhu Texas Instruments, USA Manish Goel Texas Instruments, USA ABSTRACT The increasing requirements of high data rates and quality of service (QoS) in fourth-generation (4G) wireless communication require the implementation of practical capacity approaching codes. In this chapter, the application of Turbo coding schemes that have recently been adopted in the IEEE 802.16e WiMax standard and 3GPP Long Term Evolution (LTE) standard are reviewed. In order to process several 4G wireless standards with a common hardware module, a reconfigurable and scalable Turbo decoder architecture is presented. A parallel Turbo decoding scheme with scalable parallelism tailored to the target throughput is applied to support high data rates in 4G applications. High-level decoding parallelism is achieved by employing contention-free interleavers. A multi-banked memory structure and routing network among memories and MAP decoders are designed to operate at full speed with parallel interleavers. A new on-line address generation technique is introduced to support multiple Turbo interleaving patterns, which avoids the interleaver address memory that is typically necessary in the traditional designs. Design trade-offs in terms of area and power efficiency are analyzed for different parallelism and clock frequency goals. KEYWORDS Error Correction Codes, Turbo Codes, MAP Algorithm, BCJR Algorithm, Turbo Decoder, Interleaver, Wireless PHY, 4G Receiver, VLSI Architecture INTRODUCTION The approaching fourth-generation (4G) wireless systems are promising to support very high data rates from 100 Mbps to 1 Gbps. This consequently leads to orders of complexity increases in a 4G wireless receiver.
    [Show full text]
  • BER Comparison Between Convolutional, Turbo, LDPC, and Polar Codes
    BER Comparison Between Convolutional, Turbo, LDPC, and Polar Codes Bashar Tahir∗, Stefan Schwarzy, and Markus Ruppz Institute of Telecommunications Technische Universitat¨ (TU) Wien Vienna, Austria Email: f∗bashar.tahir, ystefan.schwarz, [email protected] Abstract—Channel coding is a fundamental building block in A major breakthrough happened in 1993 when turbo codes any communications system. High performance codes, with low were introduced [5]. They represent a class of codes that complexity encoding and decoding are a must-have for future can perform very close to the capacity limit. In its common wireless systems, with requirements ranging from the operation in highly reliable scenarios, utilizing short information messages form, turbo encoding is done using two recursive convolutional and low code rates, to high throughput scenarios, working with encoders. The input stream is passed to the first encoder, and a long messages, and high code rates. permuted version is passed to the second one. At the receiving We investigate in this paper the performance of Convolutional, side, two decoders are used, each one decodes the streams Turbo, Low-Density Parity-Check (LDPC), and Polar codes, in of the corresponding encoder. By exchanging probabilistic terms of the Bit-Error-Ratio (BER) for different information block lengths and code rates, spanning the multiple scenarios information, the two decoders can iteratively help each other of reliability and high throughput. We further investigate their in a manner similar to a turbo engine. convergence behavior with respect to the number of iterations Another class of capacity-approaching codes, are the LDPC (turbo and LDPC), and list size (polar), as well as how their per- codes.
    [Show full text]
  • Services Catalog
    Deep Space Network Deep Space Network Services Catalog Document Owner: Approved by: Signature Provided 02/03/15 Signature Provided 01/22/15 Jeff Berner Date Alaudin M. Bhanji Date DSN Project Chief Engineer DSN Project Manager Prepared by: Approved by: Signature Provided 01/16/15 Signature Provided 01/16/15 Timothy Pham Date Charles Scott Date DSN Chief Systems Engineer DSN Commitment Office Manager Signature Provided 02/20/15 DSN Document Release Date DSN No. 820-100, Rev. F Issue Date: February 24, 2015 JPL D-19002 Jet Propulsion Laboratory California Institute of Technology Users must ensure that they are using the current version in PDMS: https://pdms.jpl.nasa.gov Copyright 2015 California Institute of Technology. U.S. Government sponsorship acknowledged 820-100, Rev. F Review Acknowledgment By signing below, the signatories acknowledge that they have reviewed this document and provided comments, if any, to the signatories on the Cover Page. Signature Provided 02/19/15 Signature Provided 02/17/15 Ana Guerrero Date Pat Beyer Date DSN TTC &Data Delivery Office Manager DSN Service Management Office Manager Signature Provided 02/17/15 Signature Provided 02/23/15 Peter Hames Date James A. O’dea Date DSN Antenna Front-End, Facilities and TTC System Engineer Infrastructure Office Manager Signature Provided 02/16/15 Signature Provided 02/17/15 Tim Cornish Date Alina Bedrossian Date Uplink System Engineer Science System Engineer Signature Provided 02/17/15 Signature Provided 02/17/15 Leslie Deutsch Date Cathy Cagle Date Architecture Strategic Planning and Mission Support Definition and System Engineering Manager Commitments Manager ii 820-100, Rev.
    [Show full text]
  • Dynamic Code Selection Method for Content Transfer in Deep Space Network
    University of Mississippi eGrove Electronic Theses and Dissertations Graduate School 2019 Dynamic Code Selection Method for Content Transfer in Deep Space Network Rojina Adhikary University of Mississippi Follow this and additional works at: https://egrove.olemiss.edu/etd Part of the Electrical and Computer Engineering Commons Recommended Citation Adhikary, Rojina, "Dynamic Code Selection Method for Content Transfer in Deep Space Network" (2019). Electronic Theses and Dissertations. 1528. https://egrove.olemiss.edu/etd/1528 This Dissertation is brought to you for free and open access by the Graduate School at eGrove. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of eGrove. For more information, please contact [email protected]. DYNAMIC CODE SELECTION METHOD FOR CONTENT TRANSFER IN DEEP SPACE NETWORK A Dissertation presented in partial fulfillment of requirements for the degree of Doctor of Philosophy in the Department of Electrical Engineering The University of Mississippi by Rojina Adhikary May 2019 Copyright Rojina Adhikary 2019 ALL RIGHTS RESERVED ABSTRACT Space communications feature large round-trip time delays (for example, be- tween 6.5 and 44 minutes for Mars to Earth and return, depending on the actual distance between the two planets) and highly variable data error rates, for example, bit error rate (BER) of 10−5 is very common and even higher BERs on the order of 10−1 is observed in the deep-space environment. We develop a new content transfer protocol based on RaptorQ codes and turbo codes together with a real-time channel prediction model to maximize file transfer from space vehicles to the Earth stations.
    [Show full text]
  • A 150Mbit/S 3GPP LTE Turbo Code Decoder
    A 150Mbit/s 3GPP LTE Turbo Code Decoder Matthias May, Thomas Ilnseher, Norbert Wehn Wolfgang Raab Microelectronic Systems Design Research Group, University of Kaiserslautern Infineon Technologies AG 67663 Kaiserslautern, Germany 81726 Munchen,¨ Germany {may, ilnseher, wehn}@eit.uni-kl.de wolfgang.raab@infineon.com Abstract—3GPP long term evolution (LTE) enhances the wire- parallel TC decoder architectures. In Section V, the acquisition less communication standards UMTS and HSDPA towards higher length for the decoding of highly punctured LTE TC is throughput. A throughput of 150 Mbit/s is specified for LTE discussed. Further, we investigate the scalability of different using 2×2 MIMO. For this, highly punctured Turbo codes with rates up to 0.95 are used for channel coding, which is a big TC decoder architectures to a throughput of 300 Mbit/s and challenge for decoder design. This paper investigates efficient higher for upcoming releases of LTE. The implementation of decoder architectures for highly punctured LTE Turbo codes. a 150 Mbit/s 3GPP LTE compliant TC decoder is presented in We present a 150 Mbit/s 3GPP LTE Turbo code decoder, which Section VI. is part of an industrial SDR multi-standard baseband processor chip. II. TURBO CODE DECODING I. INTRODUCTION For TC decoding a complete data block is iteratively pro- cessed in a loop which comprises two component decoders us- The outstanding forward error correction capabilities of ing the Log-MAP algorithm [1]. These two decoders exchange Turbo codes [1] made them part of many today’s communica- so called a posteriori probability information (Λe). The itera- tions standards.
    [Show full text]
  • Gallaeer Codes for CDMA Applications
    Gallaeeru Codes for CDMA Applications Vladislav Sorokine A t hesis submit ted in conformity with the requirement s for the Degree of Doctor of Philosophy, Graduate Department of Electrical asd Computer Engineering, University of Toronto @ Copyright by Vladislav Sorokine 1998 National Library Bibliothèque nationale du Canada Acquisitions and Acquisitions et Bibliographie Services services bibliographiques 395 Weilingtan Street 395, nie WelIingtan OtrawaON KlAûN4 OttawaON K1AON4 Canada canada The author has granted a non- L'auteur a accordé une licence non exclusive licence allowing the exclusive permettant à la National Libmy of Canada to Bibliothèque nationale du Canada de reproduce, loaq distribute or sell reproduire, prêter, distriîuer ou copies of this thesis in microform, vendre des copies de cette thèse sous paper or electronic formats. la fome de microfiche/nlm, de reproduction sur papier ou sur format électronique. The author retains ownership of the L'auteur consewe la propriété du copyright in this thesis. Neither the droit d'auteur qui protège cette thèse. thesis nor subsîantial extracts fiom it Ni Ia thèse ni des extraits substantiels rnay be printed or othenvise de celle-ci ne doivent être imprimés reproduced without the author's ou autrement reproduits sans son permission. autorisation. To My Teachers Gallager Codes for CDMA Applications A thesis for the degree of Doctor of Philosophy, 1998 Depart ment of Elect rical and Computer Engineering University of Toront O Abstract In this thesis, we develop a new coding system for direct sequence code-division multiple access (DS-CDMA) that supports more multiple users than many previously reported DS-CDMA systems. The most important distinctive feature of this new approach is the use of powerful short fiame Gallager codes for data error protection.
    [Show full text]