378 research outputs found

    Reducing Energy Consumption of a Modem via Selective Packet Transmission Delaying

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2017. 2. ํ™์„ฑ์ˆ˜.์Šค๋งˆํŠธํฐ์„ ๋น„๋กฏํ•œ ์ƒํ™œ ๋ฐ€์ฐฉํ˜• ๋ชจ๋ฐ”์ผ ์žฅ์น˜์—์„œ ๋ชจ๋Ž€์ด ์†Œ๋ชจํ•˜๋Š” ์ „๋ ฅ๋Ÿ‰์„ ์ค„์ด๊ณ ์ž ํ•˜๋Š” ๋…ธ๋ ฅ๋“ค์ด ๋Š์ž„์—†์ด ๊ฒฝ์ฃผ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ชจ๋Ž€์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰ ์ ˆ๊ฐ ๋ฐฉ์•ˆ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ ๊ธฐ๋ฒ•์— ๊ธฐ๋ฐ˜ํ•œ๋‹ค. ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ ๊ธฐ๋ฒ•์ด๋ž€ ๋ชจ๋ฐ”์ผ ์žฅ์น˜์—์„œ ์ง€์—ฐ ์ „์†ก์ด ๊ฐ€๋Šฅํ•œ ํŒจํ‚ท์˜ ์ „์†ก ์š”์ฒญ์ด ๋ฐœ์ƒํ•˜๋Š” ๊ฒฝ์šฐ, ํ•ด๋‹น ํŒจํ‚ท์˜ ์ „์†ก์„ ์ง€์—ฐ์‹œ์ผฐ๋‹ค๊ฐ€ ์ดํ›„์— ์ „์†ก ์š”์ฒญ๋œ ํŒจํ‚ท๋“ค๊ณผ ํ•จ๊ป˜ ํ•œ ๋ฒˆ์— ์ „์†กํ•˜๋Š” ๊ธฐ๋ฒ•์ด๋‹ค. ์ด ๊ธฐ๋ฒ•์€ ๋ชจ๋Ž€์ด ์—ฌ๋Ÿฌ ๊ฐœ์˜ ํŒจํ‚ท์„ ๊ธด ์‹œ๊ฐ„์— ๊ฑธ์ณ ์‚ฐ๋ฐœ์ ์œผ๋กœ ์ „์†กํ•˜๋Š” ๊ฒƒ์— ๋น„ํ•ด์„œ, ๊ฐ™์€ ํŒจํ‚ท๋“ค์„ ์งง์€ ์‹œ๊ฐ„ ๋™์•ˆ ํ•œ๊บผ๋ฒˆ์— ์ „์†กํ•  ๋•Œ ํ›จ์”ฌ ์ ์€ ์–‘์˜ ์ „๋ ฅ์„ ์†Œ๋ชจํ•˜๋Š” ํŠน์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค๋Š” ์ ์— ์ฐฉ์•ˆํ•˜์—ฌ ๊ฐœ๋ฐœ๋œ ๊ธฐ๋ฒ•์ด๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ ๊ธฐ๋ฒ•์„ ๋ชจ๋ฐ”์ผ ์žฅ์น˜์˜ ๋‹ค์–‘ํ•œ ๋™์ž‘ ์ƒํ™ฉ์—์„œ ํšจ๊ณผ์ ์œผ๋กœ ์ ์šฉํ•˜๋Š” ๊ฐ๊ธฐ ๋‹ค๋ฅธ ๋ฐฉ์•ˆ๋“ค์„ ์ œ์‹œํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์Šค๋งˆํŠธํฐ๊ณผ ๊ฐ™์€ ์ตœ์‹  ๋ชจ๋ฐ”์ผ ์žฅ์น˜์˜ ๋ณต์žกํ•œ ๋™์ž‘ ํ™˜๊ฒฝ์—์„œ ๋ชจ๋Ž€์˜ ๋ฌด์„  ์ž์› ์ œ์–ด ์ƒํƒœ๋ฅผ ์น˜๋ฐ€ํ•˜๊ฒŒ ๊ณ ๋ คํ•˜์ง€ ์•Š๊ณ  ์ ์šฉํ•˜๋Š” ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ ๊ธฐ๋ฒ•์€ ์˜คํžˆ๋ ค ์˜ˆ๊ธฐ์น˜ ๋ชปํ•œ ์ถ”๊ฐ€์ ์ธ ์ „๋ ฅ ์†Œ๋ชจ๋ฅผ ์•ผ๊ธฐํ•˜๊ธฐ๋„ ํ•œ๋‹ค. ์ด ๋ฌธ์ œ๋Š” ๊ธฐ์กด์˜ ๋ชจ๋Ž€ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰ ์ ˆ๊ฐ ๊ธฐ๋ฒ•๋“ค์˜ ํšจ์šฉ์„ฑ์„ ํฌ๊ฒŒ ํ•ด์นจ์œผ๋กœ์จ ์‹ค์ œ ์‚ฐ์—…์— ์ ์šฉ๋˜๊ธฐ ์–ด๋ ต๊ฒŒ ๋งŒ๋“ ๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” ์•ž์„œ ์„ค๋ช…ํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์„ ๋ณ„์  ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆํ•˜๋Š” ๊ธฐ๋ฒ•์€ ํŒจํ‚ท ์ „์†ก์„ ์ง€์—ฐํ•œ ๊ฒฐ๊ณผ๋กœ ๋ชจ๋Ž€์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์ด ์ค„์–ด๋“ค ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋  ๋•Œ์—๋งŒ ์„ ๋ณ„์ ์œผ๋กœ ํŒจํ‚ท ์ „์†ก์„ ์ง€์—ฐํ•œ๋‹ค. ์ด ๊ธฐ๋ฒ•์˜ ํ•ต์‹ฌ ๊ณจ์ž๋Š” ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ์— ๋”ฐ๋ฅธ ์ „๋ ฅ๋Ÿ‰ ์ด๋“ ์ถ”์‚ฐ ๋ชจ๋ธ์ด๋‹ค. ์ด ๋ชจ๋ธ์€ ๋ชจ๋ฐ”์ผ ์žฅ์น˜์—์„œ ์–ด๋–ค ํŒจํ‚ท์˜ ์ „์†ก ์š”์ฒญ์ด ๋ฐœ์ƒํ–ˆ์„ ๋•Œ, ํ•ด๋‹น ์‹œ์ ์˜ ๋ชจ๋Ž€์˜ ๋ฌด์„  ์ž์› ์ œ์–ด ์ƒํƒœ์™€ ๋‹ค์Œ ๋ฒˆ ํŒจํ‚ท ์ „์†ก ์š”์ฒญ์˜ ์˜ˆ์ƒ ๋ฐœ์ƒ ์‹œ์ ์„ ์‚ฌ์šฉํ•˜์—ฌ, ํ•ด๋‹น ํŒจํ‚ท์„ ์ง€์—ฐ ์ „์†กํ•˜๋Š” ๊ฒฝ์šฐ ๋ชจ๋Ž€์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์ด ์–ด๋–ป๊ฒŒ ๋ณ€ํ™”ํ• ์ง€๋ฅผ ๊ณ„์‚ฐํ•˜๋Š” ๋ชจ๋ธ์ด๋‹ค. ์ œ์•ˆํ•˜๋Š” ์„ ๋ณ„์  ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ ๊ธฐ๋ฒ•์€ ์„ธ ๊ฐœ์˜ ํ•ต์‹ฌ ์ปดํฌ๋„ŒํŠธ๋“ค๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ์ง€์—ฐ ๊ฐ€๋Šฅ ํŒจํ‚ท ํŒ๋ณ„๊ธฐ(Deferrable Packet Identifier)์ด๋‹ค. ์ด ์ปดํฌ๋„ŒํŠธ๋Š” ํŒจํ‚ท ์ „์†ก ์š”์ฒญ์ด ๋ฐœ์ƒํ–ˆ์„ ๋•Œ, ํ•ด๋‹น ํŒจํ‚ท์˜ ์ „์†ก ์ง€์—ฐ์„ ๋ชจ๋ฐ”์ผ ์žฅ์น˜์˜ ์‚ฌ์šฉ์ž๊ฐ€ ์ธ์ง€ํ•  ์ˆ˜ ์žˆ๋Š”์ง€ ์—ฌ๋ถ€๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๊ทธ ํŒจํ‚ท์˜ ์ง€์—ฐ ๊ฐ€๋Šฅ ์—ฌ๋ถ€๋ฅผ ํŒ๋‹จํ•œ๋‹ค. ๋‘ ๋ฒˆ์งธ๋Š” ํŒจํ„ด ๊ธฐ๋ฐ˜ ๋‹ค์Œ ํŒจํ‚ท ์˜ˆ์ธก๊ธฐ(Pattern-based Next Packet Predictor)์ด๋‹ค. ์ด ์ปดํฌ๋„ŒํŠธ๋Š” ์‚ฌ์ „ ํ•™์Šต ๋‹จ๊ณ„์™€ ์˜จ๋ผ์ธ ์ ์šฉ ๋‹จ๊ณ„๋กœ ๋‚˜๋ˆ„์–ด ๋™์ž‘ํ•œ๋‹ค. ๋จผ์ € ์‚ฌ์ „ ํ•™์Šต ๋‹จ๊ณ„์—์„œ๋Š” ๋ชจ๋ฐ”์ผ ์žฅ์น˜์—์„œ ์ˆ˜ํ–‰๋˜๋Š” ์‘์šฉ๋“ค์˜ ํŒจํ‚ท ์ „์†ก ์š”์ฒญ๋“ค์„ ๋ชจ๋‹ˆํ„ฐ๋งํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ๊ฐ ์‘์šฉ์˜ ํŒจํ‚ท ์ „์†ก ์š”์ฒญ ํŒจํ„ด๋“ค์„ ๋„์ถœํ•œ๋‹ค. ์ดํ›„ ์˜จ๋ผ์ธ ์ ์šฉ ๋‹จ๊ณ„์—์„œ๋Š” ๋„์ถœ๋œ ํŒจํ„ด๋“ค์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ชจ๋ฐ”์ผ ์žฅ์น˜์—์„œ ๋‹ค์Œ ํŒจํ‚ท ์ „์†ก ์š”์ฒญ์ด ์–ธ์ œ ๋ฐœ์ƒํ• ์ง€๋ฅผ ์˜ˆ์ธกํ•œ๋‹ค. ๋งˆ์ง€๋ง‰ ์ปดํฌ๋„ŒํŠธ๋Š” ํŒจํ‚ท ์ „์†ก ์‹œ์  ๊ฒฐ์ •๊ธฐ(Packet Transmission Time Designator)์ด๋‹ค. ์ด ์ปดํฌ๋„ŒํŠธ๋Š” ํŒจํ‚ท ์ „์†ก ์š”์ฒญ์ด ๋ฐœ์ƒํ–ˆ์„ ๋•Œ, ์•ž์„œ ์–ธ๊ธ‰ํ•œ ๋‘ ์ปดํฌ๋„ŒํŠธ์˜ ์ˆ˜ํ–‰ ๊ฒฐ๊ณผ์™€ ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ์— ๋”ฐ๋ฅธ ์ „๋ ฅ๋Ÿ‰ ์ด๋“ ์ถ”์‚ฐ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ตœ์ข…์ ์œผ๋กœ ๋ชจ๋Ž€์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์ด ์ ˆ๊ฐ๋˜๋„๋ก ํ•ด๋‹น ํŒจํ‚ท์˜ ์‹ค์ œ ์ „์†ก ์‹œ์ ์„ ๊ฒฐ์ •ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆํ•œ ๊ธฐ๋ฒ•์˜ ํšจ์šฉ์„ฑ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด์„œ ์‹ค์ œ ์ด๋™ํ†ต์‹  ๋„คํŠธ์›Œํฌ๋ง์— ์—ฐ๊ฒฐ๋œ ์ƒ์šฉ ์Šค๋งˆํŠธํฐ์„ ์‚ฌ์šฉํ•˜์—ฌ ๋‹ค์–‘ํ•œ ์‹คํ—˜์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ, KT์˜ 4์„ธ๋Œ€ LTE ๋„คํŠธ์›Œํฌ ๋ง์— ์—ฐ๊ฒฐ๋œ Google Nexus 5 ์Šค๋งˆํŠธํฐ์— ์•ž์„œ ์„ค๋ช…ํ•œ ์„ธ ๊ฐ€์ง€ ํ•ต์‹ฌ ์ปดํฌ๋„ŒํŠธ๋“ค์„ ๊ตฌํ˜„ํ•˜๊ณ  ์‹คํ—˜์ ์œผ๋กœ ๋ชจ๋Ž€์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰ ์ ˆ๊ฐ ํšจ๊ณผ๋ฅผ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ, ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์„ ์ ์šฉํ•จ์œผ๋กœ์จ ๋ชจ๋Ž€์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์ด ์ตœ๋Œ€ 22.5% ์ค„์–ด๋“œ๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์•ˆํ•˜๋Š” ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ์— ๋”ฐ๋ฅธ ์ „๋ ฅ๋Ÿ‰ ์ด๋“ ์ถ”์‚ฐ ๋ชจ๋ธ๊ณผ ์ด๋ฅผ ํ™œ์šฉํ•œ ์„ ๋ณ„์  ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ ๊ธฐ๋ฒ•์ด ์ตœ์‹  ๋ชจ๋ฐ”์ผ ์žฅ์น˜์— ํƒ‘์žฌ๋œ ๋ชจ๋Ž€์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰์„ ์ค„์ด๋Š” ์‹ค์šฉ์ ์ด๊ณ  ํšจ๊ณผ์ ์ธ ์ˆ˜๋‹จ์ž„์„ ๋ณด์—ฌ์ค€๋‹ค.1. ์„œ๋ก  1 1.1 ์—ฐ๊ตฌ ๋™๊ธฐ 3 1.2 ์—ฐ๊ตฌ ๋‚ด์šฉ 5 1.3 ๋…ผ๋ฌธ ๊ตฌ์„ฑ 9 2. ๋ฐฐ๊ฒฝ ์ง€์‹๊ณผ ๊ด€๋ จ ์—ฐ๊ตฌ 10 2.1 ๋ฌด์„  ์ž์› ์ œ์–ด ํ”„๋กœํ† ์ฝœ๊ณผ ๋น„์—ฐ์†์  ์ˆ˜์‹  ๊ธฐ๋ฒ• 10 2.2 ๋ชจ๋Ž€์˜ ์ „๋ ฅ ์†Œ๋ชจ๋Ÿ‰ ์ ˆ๊ฐ ๊ธฐ๋ฒ• 19 2.1.1 Tail ์‹œ๊ฐ„์˜ ๋น ๋ฅธ ์ข…๋ฃŒ 24 2.2.2 Tail ์‹œ๊ฐ„๋“ค์˜ ์ค‘์ฒฉ 28 3. ๋ฌธ์ œ ์„ค๋ช…๊ณผ ํ•ด๊ฒฐ ๋ฐฉ์•ˆ ๊ฐœ๊ด€ 33 3.1 ์‹œ์Šคํ…œ ๋ชจ๋ธ 33 3.2 ๋ฌธ์ œ ์„ค๋ช… 39 3.3 ํ•ด๊ฒฐ ๋ฐฉ์•ˆ ๊ฐœ๊ด€ 45 4. ์„ ๋ณ„์  ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ ๊ธฐ๋ฒ• 50 4.1 ์ง€์—ฐ ๊ฐ€๋Šฅ ํŒจํ‚ท์˜ ํŒ๋ณ„ 50 4.2 ๋ชจ๋ฐ”์ผ ์žฅ์น˜์˜ ๋‹ค์Œ ํŒจํ‚ท ์ „์†ก ์š”์ฒญ ์‹œ์  ์˜ˆ์ธก 53 4.2.1 ํŒจํ‚ท ์ „์†ก ์š”์ฒญ ๊ทธ๋ฃน์˜ ์ƒ์„ฑ 53 4.2.2 ํŒจํ„ด ๊ฒ€์ถœ 57 4.2.3 ๋‹ค์Œ ํŒจํ‚ท ์ „์†ก ์š”์ฒญ ์‹œ์ ์˜ ์˜ˆ์ธก 63 4.3 ์˜ˆ์ƒ ์ „๋ ฅ ์ด๋“์— ๊ธฐ๋ฐ˜ํ•œ ํŒจํ‚ท ์ „์†ก ์‹œ์ ์˜ ๊ฒฐ์ • 66 5. ๊ตฌํ˜„๊ณผ ์‹คํ—˜์  ํ‰๊ฐ€ 78 5.1 ์„ ๋ณ„์  ํŒจํ‚ท ์ „์†ก ์ง€์—ฐ ๊ธฐ๋ฒ•์˜ ๊ตฌํ˜„ 78 5.2 ์‹คํ—˜ ์„ค์ • 89 5.3 ์‹คํ—˜ ๊ฒฐ๊ณผ 92 5.4 ๋ถ„์„์  ํ‰๊ฐ€ 99 6. ๊ฒฐ๋ก  104 ์ฐธ๊ณ  ๋ฌธํ—Œ 107 Abstract 115Docto

    Satellite technology : reinforcement of computer data transmission technology : implications for the maritime world communications, data transfer and maritime education

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    This dissertation is a study of the impact of data transmission via satellite on the maritime world of communication, data transfer and education. The aim of the study is to understand the technological reinforcement of the maritime industry and the changes taking place in it. With the avalanche of changes that are taking place in the field of information technology, they can be used to facilitate the shipping industry. This dissertation assists in understanding some of the technological evolution of satellite technology and data communication and in the needs of the maritime industry as well. This dissertation describes satellite technology and data communication and analyses the data communication software (protocols), compression software, and other application software combinations with maritime communication system provided to improve ship operation and management for safety. The conclusion and recommendations chapter examines the implications of the technology changes on developing countries, the need to be harmonised in training and education for the maritime industry, maritime communication systems and the equipment, policy of shipping companies and communication costs

    Smart grid

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    Tese de mestrado integrado em Engenharia da Energia e do Ambiente, apresentada ร  Universidade de Lisboa, atravรฉs da Faculdade de Ciรชncias, 2016The SG concept arises from the fact that there is an increase in global energy consumption. One of the factors delaying an energetic paradigm change worldwide is the electric grids. Even though there is no specific definition for the SG concept there are several characteristics that describe it. Those features represent several advantages relating to reliability and efficiency. The most important one is the two way flow of energy and information between utilities and consumers. The infrastructures in standard grids and the SG can classified the same way but the second one has several components contributing for monitoring and management improvement. The SGโ€™s management system allows peak reduction, using several techniques underlining many advantages like controlling costs and emissions. Furthermore, it presents a new concept called demand response that allows consumers to play an important role in the electric systems. This factor brings benefits for utilities, consumers and the whole grid but it increases problems in security and that is why the SG relies in a good protection system. There are many schemes and components to create it. The MG can be considered has an electric grid in small scale which can connect to the whole grid. To implement a MG it is necessary economic and technical studies. For that, software like HOMER can be used. However, the economic study can be complex because there are factors that are difficult to evaluate beyond energy selling. On top of that, there are legislation and incentive programs that should be considered. Two case studies prove that MG can be profitable. In the first study, recurring to HOMER, and a scenario with energy selling only, it was obtained a 106% reduction on production cost and 32% in emissions. The installer would have an 8000000profitintheMGโ€™slifetime.Inthesecondcase,itwasconsideredeconomicservicesrelatedtopeakloadreduction,reliability,emissionreductionandpowerquality.TheDNOhadaprofitof8 000 000 profit in the MGโ€™s lifetime. In the second case, it was considered economic services related to peak load reduction, reliability, emission reduction and power quality. The DNO had a profit of 41,386, the MG owner had 29,319profitandtheconsumershada29,319 profit and the consumers had a 196,125 profit. We can conclude that the MG with SG concepts can be profitable in many cases

    Unified Framework for Multicarrier and Multiple Access based on Generalized Frequency Division Multiplexing

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    The advancements in wireless communications are the key-enablers of new applications with stringent requirements in low-latency, ultra-reliability, high data rate, high mobility, and massive connectivity. Diverse types of devices, ranging from tiny sensors to vehicles, with different capabilities need to be connected under various channel conditions. Thus, modern connectivity and network techniques at all layers are essential to overcome these challenges. In particular, the physical layer (PHY) transmission is required to achieve certain link reliability, data rate, and latency. In modern digital communications systems, the transmission is performed by means of a digital signal processing module that derives analog hardware. The performance of the analog part is influenced by the quality of the hardware and the baseband signal denoted as waveform. In most of the modern systems such as fifth generation (5G) and WiFi, orthogonal frequency division multiplexing (OFDM) is adopted as a favorite waveform due to its low-complexity advantages in terms of signal processing. However, OFDM requires strict requirements on hardware quality. Many devices are equipped with simplified analog hardware to reduce the cost. In this case, OFDM does not work properly as a result of its high peak-to-average power ratio (PAPR) and sensitivity to synchronization errors. To tackle these problems, many waveforms design have been recently proposed in the literature. Some of these designs are modified versions of OFDM or based on conventional single subcarrier. Moreover, multicarrier frameworks, such as generalized frequency division multiplexing (GFDM), have been proposed to realize varieties of conventional waveforms. Furthermore, recent studies show the potential of using non-conventional waveforms for increasing the link reliability with affordable complexity. Based on that, flexible waveforms and transmission techniques are necessary to adapt the system for different hardware and channel constraints in order to fulfill the applications requirements while optimizing the resources. The objective of this thesis is to provide a holistic view of waveforms and the related multiple access (MA) techniques to enable efficient study and evaluation of different approaches. First, the wireless communications system is reviewed with specific focus on the impact of hardware impairments and the wireless channel on the waveform design. Then, generalized model of waveforms and MA are presented highlighting various special cases. Finally, this work introduces low-complexity architectures for hardware implementation of flexible waveforms. Integrating such designs with software-defined radio (SDR) contributes to the development of practical real-time flexible PHY.:1 Introduction 1.1 Baseband transmission model 1.2 History of multicarrier systems 1.3 The state-of-the-art waveforms 1.4 Prior works related to GFDM 1.5 Objective and contributions 2 Fundamentals of Wireless Communications 2.1 Wireless communications system 2.2 RF transceiver 2.2.1 Digital-analogue conversion 2.2.2 QAM modulation 2.2.3 Effective channel 2.2.4 Hardware impairments 2.3 Waveform aspects 2.3.1 Single-carrier waveform 2.3.2 Multicarrier waveform 2.3.3 MIMO-Waveforms 2.3.4 Waveform performance metrics 2.4 Wireless Channel 2.4.1 Line-of-sight propagation 2.4.2 Multi path and fading process 2.4.3 General baseband statistical channel model 2.4.4 MIMO channel 2.5 Summary 3 Generic Block-based Waveforms 3.1 Block-based waveform formulation 3.1.1 Variable-rate multicarrier 3.1.2 General block-based multicarrier model 3.2 Waveform processing techniques 3.2.1 Linear and circular filtering 3.2.2 Windowing 3.3 Structured representation 3.3.1 Modulator 3.3.2 Demodulator 3.3.3 MIMO Waveform processing 3.4 Detection 3.4.1 Maximum-likelihood detection 3.4.2 Linear detection 3.4.3 Iterative Detection 3.4.4 Numerical example and insights 3.5 Summary 4 Generic Multiple Access Schemes 57 4.1 Basic multiple access and multiplexing schemes 4.1.1 Infrastructure network system model 4.1.2 Duplex schemes 4.1.3 Common multiplexing and multiple access schemes 4.2 General multicarrier-based multiple access 4.2.1 Design with fixed set of pulses 4.2.2 Computational model 4.2.3 Asynchronous multiple access 4.3 Summary 5 Time-Frequency Analyses of Multicarrier 5.1 General time-frequency representation 5.1.1 Block representation 5.1.2 Relation to Zak transform 5.2 Time-frequency spreading 5.3 Time-frequency block in LTV channel 5.3.1 Subcarrier and subsymbol numerology 5.3.2 Processing based on the time-domain signal 5.3.3 Processing based on the frequency-domain signal 5.3.4 Unified signal model 5.4 summary 6 Generalized waveforms based on time-frequency shifts 6.1 General time-frequency shift 6.1.1 Time-frequency shift design 6.1.2 Relation between the shifted pulses 6.2 Time-frequency shift in Gabor frame 6.2.1 Conventional GFDM 6.3 GFDM modulation 6.3.1 Filter bank representation 6.3.2 Block representation 6.3.3 GFDM matrix structure 6.3.4 GFDM demodulator 6.3.5 Alternative interpretation of GFDM 6.3.6 Orthogonal modulation and GFDM spreading 6.4 Summary 7 Modulation Framework: Architectures and Applications 7.1 Modem architectures 7.1.1 General modulation matrix structure 7.1.2 Run-time flexibility 7.1.3 Generic GFDM-based architecture 7.1.4 Flexible parallel multiplications architecture 7.1.5 MIMO waveform architecture 7.2 Extended GFDM framework 7.2.1 Architectures complexity and flexibility analysis 7.2.2 Number of multiplications 7.2.3 Hardware analysis 7.3 Applications of the extended GFDM framework 7.3.1 Generalized FDMA 7.3.2 Enchantment of OFDM system 7.4 Summary 7 Conclusions and Future work

    On Providing Energy-efficient Data Transmission to Mobile Devices

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    The transformation from telephony to mobile Internet has fundamentally changed the way we interact with the world by delivering ubiquitous Internet access and reasonable cost of connectivity. The mobile networks and Internet services are supportive of each other and together drive a fast development of new services and the whole ecosystem. As a result, the number of mobile subscribers has skyrocketed to a magnitude of billions, and the volume of mobile traffic has boomed up to a scale no-one has seen before with exponential growth predictions. However, the opportunities and problems are both rising. Therefore, to enable sustainable growth of the mobile Internet and continued mobile service adaption, this thesis proposes solutions to ensure that the reduction of overall environmental presence and the level of QoE are mutually addressed by providing energy-efficient data transmission to mobile devices. It is important to understand the characteristics of power consumption of mobile data transmission to find opportunities to balance the energy consumption and the growth of mobile services and the data volumes. This research started with power consumption measurements of various radio interfaces and investigations of the trade-off between computation and communication of modern mobile devices. Power consumption models, state machines and the conditions for energy-efficient mobile data transmission were proposed to guide the development of energy-saving solutions. This research has then employed the defined guideline to optimise data transmission for energy-efficient mobile web access. Proxy-based solutions are presented in this thesis, utilising several strategies: bundling-enabled traffic shaping to optimise TCP behaviour over congested wireless links and keep the radio interface in low power consumption states as much as possible, offloading HTTP-object fetching to shorten the time of DNS lookups and web content downloading, and applying selective compression on HTTP payload to further reduce energy consumption of mobile data transmission. As a result, the solutions dramatically reduce the energy consumption of mobile web access and download time, yet maintain or even increase user experience

    Exploiting Energy Awareness in Mobile Communication

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    Design of surface acoustic wave filters and applications in future communication systems

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