6 research outputs found

    Method of Error Floor Mitigation in Low-Density Parity-Check Codes

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    A digital communication decoding method for low-density parity-check coded messages. The decoding method decodes the low-density parity-check coded messages within a bipartite graph having check nodes and variable nodes. Messages from check nodes are partially hard limited, so that every message which would otherwise have a magnitude at or above a certain level is re-assigned to a maximum magnitude

    Compute-and-Forward Relay Networks with Asynchronous, Mobile, and Delay-Sensitive Users

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    We consider a wireless network consisting of multiple source nodes, a set of relays and a destination node. Suppose the sources transmit their messages simultaneously to the relays and the destination aims to decode all the messages. At the physical layer, a conventional approach would be for the relay to decode the individual message one at a time while treating rest of the messages as interference. Compute-and-forward is a novel strategy which attempts to turn the situation around by treating the interference as a constructive phenomenon. In compute-and-forward, each relay attempts to directly compute a combination of the transmitted messages and then forwards it to the destination. Upon receiving the combinations of messages from the relays, the destination can recover all the messages by solving the received equations. When identical lattice codes are employed at the sources, error correction to integer combination of messages is a viable option by exploiting the algebraic structure of lattice codes. Therefore, compute-and-forward with lattice codes enables the relay to manage interference and perform error correction concurrently. It is shown that compute-and-forward exhibits substantial improvement in the achievable rate compared with other state-of-the-art schemes for medium to high signal-to-noise ratio regime. Despite several results that show the excellent performance of compute-and-forward, there are still important challenges to overcome before we can utilize compute-and- forward in practice. Some important challenges include the assumptions of \perfect timing synchronization "and \quasi-static fading", since these assumptions rarely hold in realistic wireless channels. So far, there are no conclusive answers to whether compute-and-forward can still provide substantial gains even when these assumptions are removed. When lattice codewords are misaligned and mixed up, decoding integer combination of messages is not straightforward since the linearity of lattice codes is generally not invariant to time shift. When channel exhibits time selectivity, it brings challenges to compute-and-forward since the linearity of lattice codes does not suit the time varying nature of the channel. Another challenge comes from the emerging technologies for future 5G communication, e.g., autonomous driving and virtual reality, where low-latency communication with high reliability is necessary. In this regard, powerful short channel codes with reasonable encoding/decoding complexity are indispensable. Although there are fruitful results on designing short channel codes for point-to-point communication, studies on short code design specifically for compute-and-forward are rarely found. The objective of this dissertation is threefold. First, we study compute-and-forward with timing-asynchronous users. Second, we consider the problem of compute-and- forward over block-fading channels. Finally, the problem of compute-and-forward for low-latency communication is studied. Throughout the dissertation, the research methods and proposed remedies will center around the design of lattice codes in order to facilitate the use of compute-and-forward in the presence of these challenges

    A study on an improving method of launch vehicle telemetry system based on link analysis

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    The telemetry system for the launch operation is one of wireless communication system which acquires the data about the operational status and flight information of launch vehicle, and receives, processes, and distributes telemetry data in real time to determine the progress of launch mission and confirm the satellite separation. In NARO Space Center, four telemetry ground stations including two stations with large 11 m parabola antenna are in operation in order to ensure stable reception and acquisition of telemetry signal, and total five ground stations including additional ground station with 7 m antenna in south pacific, PALAU, will be operated to launch the NURI(KSLV-II) which scheduled to launch 2021. When designing a launch telemetry system, the antenna with large reflector over 7 m in a ground station is usually considered in order to ensure sufficient link margin. However, it should be required such supporting equipment, site for installation, and operating personnel because of that. If the size of antenna can be reduced significantly, the ground station can be operated in the form of VAN vehicle with small mobile antenna without the site and building for a large antenna, power generator and auxiliary facilities. This will makes it very easy to deploy ground station for various launch mission, and can help to reduce the cost of maintaining large ground stations especially in case of not frequent launch. The most widely used modulation method in aerospace telemetry since the 1970s is pulse code modulation/frequency modulation(PCM/ FM), which is still widely used in spite of the disadvantage of low spectrum efficiency. Forward error correction codes are also used in limited, even though they are now standard in most communications applications. These are the same for all the launch vehicles launched from the Naro Space Center so far, including NARO and NURI. Also, in case of on-board Tx. antenna, two antennas are mounted symmetrically on the surface of launch vehicle fuselage to have a omni directional pattern, and this causes large nulls at the overlapping section in the antenna pattern, especially in the forward and backward axes, and lots of loss in link budget. In this dissertation, it is analyzed that the margin required to perform the launch mission through link analysis based on the telemetry data which was acquired during the launch mission of the NURI Test Launch Vehicle, and verified the margin that can be acquired when designing a communication link using digital communication method and forward error correction code recommended by IRIG-106 which is the aerospace telemetry standard. On the basis of this, I propose a method to improve the on-board Tx. antenna to secure additional margin, and to make the size of antenna of the ground station as small as possible. In order to verify the validity of the proposed method, the actual received signal during the launch mission of NURI Test Launch Vehicle was used for analysis, and verification was performed through simulation.|๋ฐœ์‚ฌ์ฒด ํ…”๋ ˆ๋ฉ”ํŠธ๋ฆฌ ์‹œ์Šคํ…œ์€ ๋ฐœ์‚ฌ์ฒด์— ๋Œ€ํ•œ ๊ฐ์ข… ๋™์ž‘์ƒํƒœ ๋ฐ ๋น„ํ–‰์ •๋ณด ๋“ฑ์— ๊ด€ํ•œ ์ œ๋ฐ˜ ์ž๋ฃŒ๋ฅผ ํš๋“ํ•˜๋Š” ๋ฌด์„ ํ†ต์‹  ์‹œ์Šคํ…œ์œผ๋กœ ๋ฐœ์‚ฌ์ž„๋ฌด์ง„ํ–‰์˜ ํŒ๋‹จ ๋ฐ ์œ„์„ฑ๊ถค๋„ ์ง„์ž… ์ƒํƒœ๋ฅผ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•ด ์‹ค์‹œ๊ฐ„์œผ๋กœ ์ž๋ฃŒ๋ฅผ ์ˆ˜์‹ , ์ฒ˜๋ฆฌํ•˜๊ณ  ๋ถ„๋ฐฐํ•œ๋‹ค. ๋‚˜๋กœ์šฐ์ฃผ์„ผํ„ฐ์—๋Š” ๋ฐœ์‚ฌ์ฒด ๋ฐœ์‚ฌ๋กœ๋ถ€ํ„ฐ ์œ„์„ฑ๋ถ„๋ฆฌ ์‹œ์ ๊นŒ์ง€ ํ…”๋ ˆ๋ฉ”ํŠธ๋ฆฌ ์‹ ํ˜ธ์˜ ์•ˆ์ •์ ์ธ ์ˆ˜์‹  ๋ฐ ํš๋“์„ ์œ„ํ•ด 11 m ๊ธ‰ ๋Œ€ํ˜• ์•ˆํ…Œ๋‚˜๋ฅผ ๊ฐ€์ง„ ์ง€์ƒ๊ตญ 2๊ธฐ๋ฅผ ํฌํ•จํ•˜์—ฌ 4๊ธฐ์˜ ํ…”๋ ˆ๋ฉ”ํŠธ๋ฆฌ ์ง€์ƒ๊ตญ์„ ์šด์˜ ์ค‘์ด๋ฉฐ, 2021๋…„ ๋ฐœ์‚ฌ ์˜ˆ์ •์ธ ๋ˆ„๋ฆฌํ˜ธ(KSLV-II) ๋ฐœ์‚ฌ๋ฅผ ์œ„ํ•ด ๋‚จํƒœํ‰์–‘ ํŒ”๋ผ์šฐ์— 7 m ๊ธ‰ ์•ˆํ…Œ๋‚˜๋ฅผ ๊ฐ€์ง„ ์ง€์ƒ๊ตญ 1๊ธฐ๋ฅผ ์ถ”๊ฐ€ํ•˜์—ฌ ์ด 5๊ธฐ์˜ ์ง€์ƒ๊ตญ์„ ์šด์˜ ์˜ˆ์ •์ด๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ ๋ฐœ์‚ฌ์ฒด ํ…”๋ ˆ๋ฉ”ํŠธ๋ฆฌ ์‹œ์Šคํ…œ ์„ค๊ณ„์‹œ ์ถฉ๋ถ„ํ•œ ๋งํฌ ๋งˆ์ง„ ํ™•๋ณด๋ฅผ ์œ„ํ•ด 7 m ๊ธ‰ ์ด์ƒ์˜ ๋Œ€ํ˜• ๋ฐ˜์‚ฌํŒ์„ ๊ฐ€์ง„ ์•ˆํ…Œ๋‚˜๋ฅผ ๊ณ ๋ คํ•˜๊ณ  ์ง€์ƒ๊ตญ์— ์„ค์น˜ํ•˜์—ฌ ์šด์šฉํ•˜๊ฒŒ ๋˜๋Š”๋ฐ, ์ด๋ฅผ ์œ„ํ•ด ์—ฌ๋Ÿฌ ์ง€์› ์žฅ๋น„์™€ ์„ค์น˜ ๋ถ€์ง€ ๋ฐ ์šด์šฉ ์ธ๋ ฅ์ด ํ•„์ˆ˜์ ์ด๋‹ค. ๋งŒ์•ฝ ์ง€์ƒ๊ตญ ์•ˆํ…Œ๋‚˜๋ฅผ ๋น„์•ฝ์ ์œผ๋กœ ์†Œํ˜•ํ™” ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค๋ฉด ๋Œ€ํ˜• ์•ˆํ…Œ๋‚˜ ์„ค์น˜๋ฅผ ์œ„ํ•œ ๋ถ€์ง€์™€ ๊ฑด๋ฌผ, ๋Œ€ํ˜• ๋ฐœ์ „๊ธฐ ๋ฐ ๋ถ€๋Œ€์‹œ์„ค ์—†์ด ์ฐจ๋Ÿ‰ ๊ฒฌ์ธ์ด ๊ฐ€๋Šฅํ•œ ํ˜•ํƒœ๋กœ ์ง€์ƒ๊ตญ์„ ์šด์˜ํ•  ์ˆ˜ ์žˆ์–ด ๋‹ค์–‘ํ•œ ๋ฐœ์‚ฌ ์ž„๋ฌด์— ๋”ฐ๋ฅธ ์ง€์ƒ๊ตญ ๋ฐฐ์น˜๊ฐ€ ๋งค์šฐ ์šฉ์ดํ•ด ์ง€๊ณ , ๋ฐœ์‚ฌ๊ฐ€ ๋นˆ๋ฒˆํ•˜์ง€ ์•Š์€ ๊ฒฝ์šฐ ๋Œ€ํ˜• ์ง€์ƒ๊ตญ ์œ ์ง€์— ๋”ฐ๋ฅธ ๋น„์šฉ ๊ฐ์†Œ์—๋„ ํฌ๊ฒŒ ๋„์›€์ด ๋  ์ˆ˜ ์žˆ๋‹ค. 1970๋…„๋Œ€ ์ดํ›„๋กœ ์šฐ์ฃผํ•ญ๊ณต ํ…”๋ ˆ๋ฉ”ํŠธ๋ฆฌ ๋ถ„์•ผ์—์„œ ๊ฐ€์žฅ ํญ ๋„“๊ฒŒ ์‚ฌ์šฉ๋œ ๋ณ€์กฐ ๋ฐฉ์‹์€ ํŽ„์Šค ๋ถ€ํ˜ธ ๋ณ€์กฐ/์ฃผํŒŒ์ˆ˜ ๋ณ€์กฐ(PCM/FM) ๋ฐฉ์‹์œผ๋กœ ๋Œ€์—ญํญ ํšจ์œจ์ด ์ข‹์ง€ ์•Š์€ ๋‹จ์ ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์˜ค๋Š˜๋‚ ์—๋„ ๋งŽ์ด ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์ˆœ๋ฐฉํ–ฅ ์˜ค๋ฅ˜์ •์ • ๋ถ€ํ˜ธ์˜ ๊ฒฝ์šฐ๋„ ํ˜„์žฌ ๋Œ€๋ถ€๋ถ„์˜ ํ†ต์‹  ๋ถ„์•ผ์—์„œ ํ‘œ์ค€์ด ๋œ ๊ธฐ์ˆ ์ž„์—๋„ ์ œํ•œ์ ์œผ๋กœ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋Š” ๋‚˜๋กœํ˜ธ์™€ ๋ˆ„๋ฆฌํ˜ธ๋ฅผ ํฌํ•จํ•˜์—ฌ ๋‚˜๋กœ์šฐ์ฃผ์„ผํ„ฐ์—์„œ ์ง€๊ธˆ๊นŒ์ง€ ๋ฐœ์‚ฌํ•œ ๋ชจ๋“  ๋ฐœ์‚ฌ์ฒด๊ฐ€ ๋™์ผํ•˜๋‹ค. ๋ฐœ์‚ฌ์ฒด ํƒ‘์žฌ ์†ก์‹  ์•ˆํ…Œ๋‚˜์˜ ๊ฒฝ์šฐ ๋ฐœ์‚ฌ์ฒด ๋™์ฒด ํ‘œ๋ฉด์— ๋‘ ๊ฐœ์˜ ์•ˆํ…Œ๋‚˜๋ฅผ ๋Œ€์นญ์œผ๋กœ ๋ฐฐ์น˜ํ•˜์—ฌ ์ „๋ฐฉํ–ฅ์„ฑ ํŒจํ„ด์„ ๊ฐ€์ง€๋„๋ก ํ•˜์˜€๋Š”๋ฐ, ์ด๋กœ ์ธํ•ด ํŒจํ„ด ์ค‘์ฒฉ๊ตฌ๊ฐ„, ํŠนํžˆ ์ „๋ฐฉ๊ณผ ํ›„๋ฐฉ ์ง„ํ–‰ ์ถ•์—์„œ ํฐ ๋„์ด ๋ฐœ์ƒํ•˜์—ฌ ๋งํฌ๋ฒ„์ง“์ƒ ๋งŽ์€ ์†์‹ค์„ ๊ฐ€์ง€๊ฒŒ ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ˆ„๋ฆฌํ˜ธ ์‹œํ—˜๋ฐœ์‚ฌ์ฒด ๋ฐœ์‚ฌ์‹œ ํš๋“ํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋งํฌ ๋ถ„์„์„ ํ†ตํ•ด ๋ฐœ์‚ฌ์ž„๋ฌด ์ˆ˜ํ–‰์— ํ•„์š”ํ•œ ๋งˆ์ง„์„ ๋ถ„์„ํ•˜๊ณ , ํ•ญ๊ณต์šฐ์ฃผ๋ถ„์•ผ ํ…”๋ ˆ๋ฉ”ํŠธ๋ฆฌ ํ‘œ์ค€์ธ IRIG-106์—์„œ ๊ถŒ๊ณ ํ•˜๋Š” ๋””์ง€ํ„ธ ํ†ต์‹  ๋ฐฉ์‹๊ณผ ์ˆœ๋ฐฉํ–ฅ ์˜ค๋ฅ˜์ •์ • ๋ถ€ํ˜ธ๋ฅผ ์ ์šฉํ•ด ํ†ต์‹ ๋งํฌ๋ฅผ ์„ค๊ณ„ํ•  ๊ฒฝ์šฐ ํ™•๋ณด๊ฐ€๋Šฅํ•œ ๋งˆ์ง„์„ ๊ณ„์‚ฐํ•œ๋‹ค. ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํƒ‘์žฌ ์†ก์‹  ์•ˆํ…Œ๋‚˜๋ฅผ ๊ฐœ์„ ํ•ด ์ถ”๊ฐ€ ๋งˆ์ง„์„ ํ™•๋ณดํ•˜์—ฌ ์ง€์ƒ๊ตญ์˜ ์•ˆํ…Œ๋‚˜๋ฅผ ์ตœ๋Œ€ํ•œ ์†Œํ˜•ํ™” ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š” ๋ฐฉ์•ˆ์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์˜ ํƒ€๋‹น์„ฑ ์ž…์ฆ์„ ์œ„ํ•ด ๋ˆ„๋ฆฌํ˜ธ ์‹œํ—˜๋ฐœ์‚ฌ์ฒด ๋ฐœ์‚ฌ์ž„๋ฌด์—์„œ ์‹ค ์ˆ˜์‹ ๋œ ์‹ ํ˜ธ๋ฅผ ๋ถ„์„์— ์‚ฌ์šฉํ•˜์˜€์œผ๋ฉฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ๊ฒ€์ฆ์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค.์ œ 1 ์žฅ ์„œ๋ก  1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 1 1.2 ์—ฐ๊ตฌ ๋ชฉ์  4 1.3 ๋…ผ๋ฌธ ๊ตฌ์„ฑ 5 ์ œ 2 ์žฅ ํ†ต์‹ ๋งํฌ ๋ถ„์„ 2.1 ํ…”๋ ˆ๋ฉ”ํŠธ๋ฆฌ ์ง€์ƒ๊ตญ ๊ฐœ์š” 6 2.2 ๋ˆ„๋ฆฌํ˜ธ ์‹œํ—˜๋ฐœ์‚ฌ์ฒด ๋ฐœ์‚ฌ์‹œ ์ง€์ƒ๊ตญ ์šด์šฉ 8 2.3 ์ •์  ๋งํฌ๋ถ„์„ 12 2.4 ๋™์  ๋งํฌ๋ถ„์„ 20 ์ œ 3 ์žฅ ๋งํฌ ๋งˆ์ง„ ๊ฐœ์„  ๋ฐฉ์•ˆ 3.1 ๋””์ง€ํ„ธ ๋ณ€์กฐ - SOQPSK 33 3.2 ์ฑ„๋„ ๋ถ€ํ˜ธํ™” ๊ธฐ๋ฒ• - ์ €๋ฐ€๋„ ํŒจ๋ฆฌํ‹ฐ ๊ฒ€์‚ฌ ๋ถ€ํ˜ธ(LDPC) 43 3.3 ํƒ‘์žฌ ์†ก์‹  ์•ˆํ…Œ๋‚˜ ๊ฐœ์„  49 3.3.1 ์›ํ†ตํ˜• ๋ฐฐ์—ด ์ด๋ก  50 3.3.2 ์•ˆํ…Œ๋‚˜ ์„ค๊ณ„ ๋ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ 56 ์ œ 4 ์žฅ ์ง€์ƒ๊ตญ ์•ˆํ…Œ๋‚˜ ์ตœ์ ํ™” ๋ถ„์„ 83 ์ œ 5 ์žฅ ๊ฒฐ๋ก  87 ์ฐธ๊ณ ๋ฌธํ—Œ 90Docto

    Sparse graph-based coding schemes for continuous phase modulations

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    The use of the continuous phase modulation (CPM) is interesting when the channel represents a strong non-linearity and in the case of limited spectral support; particularly for the uplink, where the satellite holds an amplifier per carrier, and for downlinks where the terminal equipment works very close to the saturation region. Numerous studies have been conducted on this issue but the proposed solutions use iterative CPM demodulation/decoding concatenated with convolutional or block error correcting codes. The use of LDPC codes has not yet been introduced. Particularly, no works, to our knowledge, have been done on the optimization of sparse graph-based codes adapted for the context described here. In this study, we propose to perform the asymptotic analysis and the design of turbo-CPM systems based on the optimization of sparse graph-based codes. Moreover, an analysis on the corresponding receiver will be done

    VLSI decoding architectures: flexibility, robustness and performance

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    Stemming from previous studies on flexible LDPC decoders, this thesis work has been mainly focused on the development of flexible turbo and LDPC decoder designs, and on the narrowing of the power, area and speed gap they might present with respect to dedicated solutions. Additional studies have been carried out within the field of increased code performance and of decoder resiliency to hardware errors. The first chapter regroups several main contributions in the design and implementation of flexible channel decoders. The first part concerns the design of a Network-on-Chip (NoC) serving as an interconnection network for a partially parallel LDPC decoder. A best-fit NoC architecture is designed and a complete multi-standard turbo/LDPC decoder is designed and implemented. Every time the code is changed, the decoder must be reconfigured. A number of variables influence the duration of the reconfiguration process, starting from the involved codes down to decoder design choices. These are taken in account in the flexible decoder designed, and novel traffic reduction and optimization methods are then implemented. In the second chapter a study on the early stopping of iterations for LDPC decoders is presented. The energy expenditure of any LDPC decoder is directly linked to the iterative nature of the decoding algorithm. We propose an innovative multi-standard early stopping criterion for LDPC decoders that observes the evolution of simple metrics and relies on on-the-fly threshold computation. Its effectiveness is evaluated against existing techniques both in terms of saved iterations and, after implementation, in terms of actual energy saving. The third chapter portrays a study on the resilience of LDPC decoders under the effect of memory errors. Given that the purpose of channel decoders is to correct errors, LDPC decoders are intrinsically characterized by a certain degree of resistance to hardware faults. This characteristic, together with the soft nature of the stored values, results in LDPC decoders being affected differently according to the meaning of the wrong bits: ad-hoc error protection techniques, like the Unequal Error Protection devised in this chapter, can consequently be applied to different bits according to their significance. In the fourth chapter the serial concatenation of LDPC and turbo codes is presented. The concatenated FEC targets very high error correction capabilities, joining the performance of turbo codes at low SNR with that of LDPC codes at high SNR, and outperforming both current deep-space FEC schemes and concatenation-based FECs. A unified decoder for the concatenated scheme is subsequently propose

    Study on AR4JA code in deep space fading channel

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