7 research outputs found

    Downlink channel access performance of NR-U: Impact of numerology and mini-slots on coexistence with Wi-Fi in the 5 GHz band

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    Coexistence between cellular systems and Wi-Fi gained the attention of the research community when LTE License Assisted Access (LAA) entered the unlicensed band. The recent introduction of NR-U as part of 5G introduces new coexistence opportunities because it implements scalable numerology (flexible subcarrier spacing and OFDM symbol lengths), and non-slot based scheduling (mini-slots), which considerably impact channel access. This paper analyzes the impact of NR-U settings on its coexistence with Wi-Fi networks and compares it with LAA operation using simulations and experiments. First, we propose a downlink channel access simulation model, which addresses the problem of the dependency and non-uniformity of transmission attempts of different nodes, as a result of the synchronization mechanism introduced by NR-U. Second, we validate the accuracy of the proposed model using FPGA-based LAA, NR-U, and Wi-Fi prototypes with over-the-air transmissions. Additionally, we show that replacing LAA with NR-U would not only allow to overcome the problem of bandwidth wastage caused by reservation signals but also, in some cases, to preserve fairness in channel access for both scheduled and random-access systems. Finally, we conclude that fair coexistence of the aforementioned systems in unlicensed bands is not guaranteed in general, and novel mechanisms are necessary for improving the sharing of resources between scheduled and contention-based technologies

    ๋น„๋ฉดํ—ˆ๋Œ€์—ญ ์…€๋ฃฐ๋ผ ํ†ต์‹ ์„ ์œ„ํ•œ ์„ฑ๋Šฅ ํ–ฅ์ƒ ๊ธฐ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2021.8. ๋ฐ•์„ธ์›….The 3rd generation partnership project (3GPP) has standardized long-term evolution (LTE) licensed-assisted access (LTE-LAA) that uses a wide unlicensed band as an alternative solution to the insufficient bandwidth problem of the existing LTE. 3GPP cellular communications in unlicensed spectrum allow transmission only after completing listen-before-talk (LBT) operation. For downlink, the LBT operation helps cellular traffic to coexist well with Wi-Fi traffic. However, cellular uplink transmission is attempted only at the time specifically determined by the base station after having a successful LBT and the user equipment (UE) may suffer transmission failure and delayed transmission due to Wi-Fi interference. As a result, cellular uplink traffic does not coexist well with Wi-Fi traffic. NR-U suffers from the collision issue because its channel access mechanism is similar to that of Wi-Fi. Wi-Fi solves the collision problem through the request-to-send/clear-to-send (RTS/CTS) mechanism. However, NR-U has no way of solving the collision problem. As a result, NR-U suffers severe performance degradation due to collisions as the number of contending nodes increases. In this dissertation, we consider the following two enhancements to cellular communication in the unlicensed spectrum: (i) Uplink channel access enhancement for solving poor uplink performance and (ii) collision minimization for efficient channel utilization. First, we mathematically analyze the problem of unfairness between cellular and Wi-Fi for uplink channel access. To address the coexistence problem in unlicensed spectrum, we propose a standard-compliant approach, termed UpChance, which allows the UE to use a minimum length of uplink reservation signal (RS) and the base station to determine the optimal timing for the UE's uplink transmission. Through ns-3 simulation, we verify that UpChance improves the performance of fairness and random access completion time by up to 88% and 99%, respectively. Second, we propose to extend an RS duration and use a split RS for reservation in NR-U that consists of front RS and rear RS and design a new collision minimization scheme, termed R-SplitC, that contains two components: new split RS operation and contention window size (CWS) control. New split RS operation helps to minimize collisions in NR-U transmissions, and CWS control works to protect the performance of other communication technologies such as Wi-Fi. We mathematically analyze and evaluate the performance of our scheme and confirm that R-SplitC improves network throughput by up to 100.6% compared to the baseline RS scheme without degrading Wi-Fi performance. In summary, we propose standard-compliant uplink channel access enhancement scheme and collision minimization scheme for cellular communication in unlicensed spectrum. Through this research, we achieve enhancements of network performance such as throughput and fairness.3์„ธ๋Œ€ ํŒŒํŠธ๋„ˆ์‹ญ ํ”„๋กœ์ ํŠธ๋Š” ๊ธฐ์กด LTE์˜ ๋ถ€์กฑํ•œ ๋Œ€์—ญํญ ๋ฌธ์ œ์— ๋Œ€ํ•œ ๋Œ€์•ˆ์œผ๋กœ ๋„“์€ ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ์„ ์‚ฌ์šฉํ•˜๋Š” ๋ผ์ด์„ ์Šค ์ง€์› ์ ‘์†์„ ํ‘œ์ค€ํ™”ํ•˜๊ณ  ์žˆ๋‹ค. ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ์—์„œ 3GPP ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹ ์€ LBT ๋™์ž‘์„ ์™„๋ฃŒํ•œ ํ›„์—๋งŒ ์ „์†ก์„ ํ—ˆ์šฉํ•œ๋‹ค. ๋‹ค์šด๋งํฌ์˜ ๊ฒฝ์šฐ LBT ์ž‘์—…์„ ํ†ตํ•ด ์…€๋ฃฐ๋Ÿฌ ํŠธ๋ž˜ํ”ฝ์ด ์™€์ดํŒŒ์ด ํŠธ๋ž˜ํ”ฝ๊ณผ ์ž˜ ๊ณต์กดํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์…€๋ฃฐ๋Ÿฌ ์—…๋งํฌ ์ „์†ก์€ LBT ์„ฑ๊ณต ํ›„ ๊ธฐ์ง€๊ตญ์— ์˜ํ•ด ํŠน๋ณ„ํžˆ ๊ฒฐ์ •๋œ ์‹œ๊ฐ„์—๋งŒ ์‹œ๋„๋˜๋ฉฐ, ์‚ฌ์šฉ์ž ์žฅ๋น„๋Š” ์™€์ดํŒŒ์ด์˜ ๊ฐ„์„ญ์œผ๋กœ ์ธํ•ด ์ „์†ก ์‹คํŒจ์™€ ์ „์†ก ์ง€์—ฐ์„ ๊ฒช์„ ํ™•๋ฅ ์ด ๋†’๋‹ค. ๋”ฐ๋ผ์„œ ์…€๋ฃฐ๋Ÿฌ ์—…๋งํฌ ํŠธ๋ž˜ํ”ฝ์ด ์™€์ดํŒŒ์ด ํŠธ๋ž˜ํ”ฝ๊ณผ ์ž˜ ๊ณต์กดํ•˜์ง€ ๋ชปํ•œ๋‹ค. ๋ผ์ด์„ ์Šค ์ง€์› ์ ‘์† ๊ธฐ์ˆ ์€ ๋˜ํ•œ ์ฑ„๋„ ์•ก์„ธ์Šค ๋ฉ”์ปค๋‹ˆ์ฆ˜์ด ์™€์ดํŒŒ์ด์˜ ์ฑ„๋„ ์•ก์„ธ์Šค ๋ฉ”์ปค๋‹ˆ์ฆ˜๊ณผ ์œ ์‚ฌํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๋™์‹œ ์ „์†ก์œผ๋กœ ์ถฉ๋Œ ๋ฌธ์ œ๋ฅผ ๊ฒช๊ณ  ์žˆ๋‹ค. ์™€์ดํŒŒ์ด๋Š” RTS/CTS ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ํ†ตํ•ด ์ถฉ๋Œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ˜„์žฌ ๋ผ์ด์„ ์Šค ์ง€์› ์ ‘์† ๊ธฐ์ˆ ์€ ์ถฉ๋Œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•  ๋ฐฉ๋ฒ•์ด ์กด์žฌํ•˜์ง€ ์•Š๋Š”๋‹ค. ๋”ฐ๋ผ์„œ ๋ผ์ด์„ ์Šค ์ง€์› ์ ‘์† ๊ธฐ์ˆ ์€ ๊ฒฝํ•ฉ ๋…ธ๋“œ ์ˆ˜๊ฐ€ ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ์ถฉ๋Œ๋กœ ์ธํ•ด ์‹ฌ๊ฐํ•œ ์„ฑ๋Šฅ ์ €ํ•˜๋ฅผ ๊ฒช๋Š”๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ์—์„œ ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹ ์— ๋Œ€ํ•œ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๋‘ ๊ฐ€์ง€ ๊ฐœ์„ ์„ ๊ณ ๋ คํ•œ๋‹ค. (i) ์—…๋งํฌ ์„ฑ๋Šฅ ์ €ํ•˜๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์—…๋งํฌ ์ฑ„๋„ ์•ก์„ธ์Šค ํ–ฅ์ƒ ๋ฐ (ii) ํšจ์œจ์ ์ธ ์ฑ„๋„ ํ™œ์šฉ์„ ์œ„ํ•œ ์ถฉ๋Œ ์ตœ์†Œํ™”. ์ฒซ์งธ, ์—…๋งํฌ ์ฑ„๋„ ์•ก์„ธ์Šค๋ฅผ ์œ„ํ•œ ์…€๋ฃฐ๋Ÿฌ์™€ ์™€์ดํŒŒ์ด ์‚ฌ์ด์˜ ๋ถˆ๊ณต์ •์„ฑ ๋ฌธ์ œ๋ฅผ ์ˆ˜ํ•™์ ์œผ๋กœ ๋ถ„์„ํ•œ๋‹ค. ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ์—์„œ์˜ ๊ณต์กด ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด, ์šฐ๋ฆฌ๋Š” ๋‹จ๋ง์ด ์ตœ์†Œ ๊ธธ์ด์˜ ์—…๋งํฌ ์˜ˆ์•ฝ ์‹ ํ˜ธ๋ฅผ ์‚ฌ์šฉํ•˜๊ณ  ๊ธฐ์ง€๊ตญ์ด ๋‹จ๋ง์˜ ์—…๋งํฌ ์ „์†ก์— ๋Œ€ํ•œ ์ตœ์ ์˜ ํƒ€์ด๋ฐ์„ ๊ฒฐ์ •ํ•  ์ˆ˜ ์žˆ๋Š” UpChance๋ผ๋Š” ํ‘œ์ค€์„ ๋งŒ์กฑํ•˜๋Š” ์ƒํ–ฅ ๋งํฌ ์ฑ„๋„ ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์•ˆํ•œ๋‹ค. ns-3 ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด UpChance๊ฐ€ ๊ณต์ •์„ฑ๊ณผ ๋žœ๋ค ์•ก์„ธ์Šค ์™„๋ฃŒ ์‹œ๊ฐ„์„ ๊ฐ๊ฐ ์ตœ๋Œ€ 88%, 99% ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๊ฒƒ์„ ๊ฒ€์ฆํ•œ๋‹ค. ๋‘˜์งธ, ์šฐ๋ฆฌ๋Š” ์ „๋ฐฉ ์˜ˆ์•ฝ์‹ ํ˜ธ์™€ ํ›„๋ฐฉ ์˜ˆ์•ฝ์‹ ํ˜ธ๋กœ ๊ตฌ์„ฑ๋œ ๋ถ„ํ•  ์˜ˆ์•ฝ ์‹ ํ˜ธ๋ฅผ ์‚ฌ์šฉํ•˜๊ณ  ๊ฒฝํ•ฉ ์ฐฝ ํฌ๊ธฐ๋ฅผ ์ถ”๊ฐ€์ ์œผ๋กœ ์ œ์–ดํ•˜๋Š” R-SplitC๋ผ๋Š” ์ƒˆ๋กœ์šด ์ถฉ๋Œ ์ตœ์†Œํ™” ์ฒด๊ณ„๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ƒˆ๋กœ์šด ๋ถ„ํ•  ์˜ˆ์•ฝ ์‹ ํ˜ธ๋Š” ๋ผ์ด์„ ์Šค ์ง€์› ์ ‘์† ๊ธฐ์ˆ ์˜ ์ „์†ก๊ฐ„์˜ ์ถฉ๋Œ์„ ์ตœ์†Œํ™”ํ•˜๋Š” ๋ฐ ๋„์›€์„ ์ฃผ๋ฉฐ, ๊ฒฝํ•ฉ ์ฐฝ ํฌ๊ธฐ ์ œ์–ด๋Š” ์™€์ดํŒŒ์ด์™€ ๊ฐ™์€ ๋‹ค๋ฅธ ํ†ต์‹  ๊ธฐ์ˆ ์˜ ์„ฑ๋Šฅ์„ ๋ณดํ˜ธํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” ์šฐ๋ฆฌ ์ฒด๊ณ„์˜ ์„ฑ๋Šฅ์„ ์ˆ˜ํ•™์ ์œผ๋กœ ๋ถ„์„ํ•˜๊ณ  ํ‰๊ฐ€ํ•˜์—ฌ R-SplitC๊ฐ€ ์™€์ดํŒŒ์ด ์„ฑ๋Šฅ์„ ์ €ํ•˜์‹œํ‚ค์ง€ ์•Š๊ณ  ๊ธฐ์กด์˜ ์˜ˆ์•ฝ ์‹ ํ˜ธ ์ฒด๊ณ„์— ๋น„ํ•ด ๋„คํŠธ์›Œํฌ ์ฒ˜๋ฆฌ๋Ÿ‰์„ ์ตœ๋Œ€ 100.6% ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•œ๋‹ค. ์š”์•ฝํ•˜๋ฉด, ์šฐ๋ฆฌ๋Š” ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ์—์„œ ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹ ์„ ์œ„ํ•œ ์—…๋งํฌ ์ฑ„๋„ ์•ก์„ธ์Šค ํ–ฅ์ƒ ๊ธฐ๋ฒ• ๋ฐ ์ถฉ๋Œ ์ตœ์†Œํ™” ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด, ์šฐ๋ฆฌ๋Š” ์ตœ์ฒจ๋‹จ ๊ธฐ์ˆ ์— ๋น„ํ•ด ์ฒ˜๋ฆฌ๋Ÿ‰ ๋ฐ ๊ณต์ •์„ฑ๊ณผ ๊ฐ™์€ ๋„คํŠธ์›Œํฌ ์„ฑ๋Šฅ์˜ ํ–ฅ์ƒ์„ ๋‹ฌ์„ฑํ•œ๋‹ค.1 Introduction 1 1.1 Motivation 1 1.2 Main Contributions 2 1.2.1 Uplink Channel Access Enhancement for Cellular Communication in Unlicensed Spectrum 2 1.2.2 R-SplitC: Collision Minimization for Cellular Communication in Unlicensed Spectrum 3 1.3 Organization of the Dissertation 4 2 Uplink Channel Access Enhancement for Cellular Communication in Unlicensed Spectrum 5 2.1 Introduction 5 2.2 Related Work and Preliminaries 7 2.2.1 Related Work 7 2.2.2 Preliminaries 8 2.3 Mathematical Analysis for Unfairness between Uplink Cellular and Wi-Fi 10 2.3.1 PRACH scenario 10 2.3.2 UL data scenario 13 2.4 Proposed Scheme 17 2.4.1 UE Operation 18 2.4.2 eNB Operation 19 2.5 Performance Evaluation 24 2.5.1 Simulation Environments 24 2.5.2 UL data transmission 25 2.5.3 Random access 27 2.6 Summary 29 3 R-SplitC: Collision Minimization for Cellular Communication in Unlicensed Spectrum 37 3.1 Introduction 37 3.2 Related Work and Preliminaries 39 3.2.1 Related Work 39 3.2.2 NR-U 40 3.2.3 listen-before-talk (LBT) 41 3.2.4 reservation signal and mini-slot 41 3.2.5 Wi-Fi 42 3.3 Proposed Scheme 44 3.3.1 New RS structure 46 3.3.2 CWS control 48 3.4 Performance Analysis 49 3.4.1 Throughput Analysis for R-Split 49 3.4.2 Throughput Analysis for R-SplitC 55 3.5 Performance Evaluation 57 3.5.1 Performance Evaluation for an NR-U only Network 58 3.5.2 Performance Evaluation for an NR-U/Wi-Fi Network 61 3.6 Summary 65 4 Concluding Remarks 67 4.1 Research Contributions 67 4.2Future Work 68 Abstract (In Korean) 75 ๊ฐ์‚ฌ์˜๊ธ€ 78๋ฐ•

    ๋น„๋ฉดํ—ˆ๋Œ€์—ญ ์…€๋ฃฐ๋ผ ํ†ต์‹ ์˜ ์„ฑ๋Šฅ ๋ถ„์„ ๋ฐ ์„ฑ๋Šฅ ํ–ฅ์ƒ ๊ธฐ๋ฒ• ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2021. 2. ๋ฐ•์„ธ์›….3GPP๋Š” LAA (licensed-assisted access)๋ผ๊ณ ํ•˜๋Š” 5GHz ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ LTE๋ฅผ ๊ฐœ๋ฐœํ–ˆ์Šต๋‹ˆ๋‹ค. LAA๋Š” ์ถฉ๋Œ ๋ฐฉ์ง€ ๊ธฐ๋Šฅ์„ ์‚ฌ์šฉํ•˜๊ธฐ ์œ„ํ•ด Wi-Fi์˜ CSMA / CA (Carrier Sense Multiple Access with Collision avoidance)์™€ ์œ ์‚ฌํ•œ LBT (Listen Before Talk) ์ž‘์—…์„ ์ฑ„ํƒํ•˜์—ฌ ๊ฐ LAA ๋‹ค์šด ๋งํฌ ๋ฒ„์ŠคํŠธ์˜ ํ”„๋ ˆ์ž„ ๊ตฌ์กฐ ์˜ค๋ฒ„ ํ—ค๋“œ๋Š” ๊ฐ๊ฐ์˜ ์ข…๋ฃŒ ์‹œ๊ฐ„์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์ง‘๋‹ˆ๋‹ค. ์ด์ „ LBT ์ž‘์—…. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹ ์„ ๋ถ„์„ํ•˜๊ธฐ์œ„ํ•œ ์ˆ˜์น˜ ๋ชจ๋ธ์„ ์ œ์•ˆํ•œ๋‹ค. ๋‹ค์Œ์œผ๋กœ, ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹ ์˜ ๋‹ค์Œ ๋‘ ๊ฐ€์ง€ ํ–ฅ์ƒ๋œ ๊ธฐ๋Šฅ์„ ๊ณ ๋ คํ•ฉ๋‹ˆ๋‹ค. ๋Œ€์—ญ ๋…๋ฆฝํ˜• ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹ . ๊ธฐ์กด WiFi ๋ถ„์„ ๋ชจ๋ธ๋กœ๋Š” LAA์˜ ์„ฑ๋Šฅ์„ ํ‰๊ฐ€ํ•  ์ˆ˜ ์—†๋‹ค๋Š” ์ ์„ ๊ฐ์•ˆํ•˜์—ฌ ๋ณธ ์„œ์‹ ์—์„œ๋Š” ์—ฌ๋Ÿฌ ๊ฒฝํ•ฉ ์ง„ํ™” ๋œ NodeB๋กœ ๊ตฌ์„ฑ๋œ LAA ๋„คํŠธ์›Œํฌ์˜ ์„ฑ๋Šฅ์„ ๋ถ„์„ํ•˜๊ธฐ์œ„ํ•œ ์ƒˆ๋กœ์šด Markov ์ฒด์ธ ๊ธฐ๋ฐ˜ ๋ถ„์„ ๋ชจ๋ธ์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. LAA ํ”„๋ ˆ์ž„ ๊ตฌ์กฐ ์˜ค๋ฒ„ ํ—ค๋“œ์˜ ๋ณ€ํ˜•. LTE-LAA๋Š” LTE์—์„œ ์ƒ์† ๋œ ์†๋„ ์ ์‘ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•ด ์ ์‘ ๋ณ€์กฐ ๋ฐ ์ฝ”๋”ฉ (AMC) ์„ ์ฑ„ํƒํ•ฉ๋‹ˆ๋‹ค. AMC๋Š” ์ง„ํ™” ๋œ nodeB (eNB)๊ฐ€ ํ˜„์žฌ ์ „์†ก์˜ ์ฑ„๋„ ํ’ˆ์งˆ ํ‘œ์‹œ๊ธฐ ํ”ผ๋“œ ๋ฐฑ์„ ์‚ฌ์šฉํ•˜์—ฌ ๋‹ค์Œ ์ „์†ก์„์œ„ํ•œ ๋ณ€์กฐ ๋ฐ ์ฝ”๋”ฉ ๋ฐฉ์‹ (MCS)์„ ์„ ํƒํ•˜๋„๋ก ๋•์Šต๋‹ˆ๋‹ค. ๋ผ์ด์„ ์Šค ๋Œ€์—ญ์—์„œ ๋™์ž‘ํ•˜๋Š” ๊ธฐ์กด LTE์˜ ๊ฒฝ์šฐ ๋…ธ๋“œ ๊ฒฝํ•ฉ ๋ฌธ์ œ๊ฐ€ ์—†์œผ๋ฉฐ AMC ์„ฑ๋Šฅ ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ž˜ ์ง„ํ–‰๋˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ์—์„œ ๋™์ž‘ํ•˜๋Š” LTE-LAA ์˜ ๊ฒฝ์šฐ ์ถฉ๋Œ ๋ฌธ์ œ๋กœ ์ธํ•ด AMC ์„ฑ๋Šฅ์ด ์ œ๋Œ€๋กœ ์ฒ˜๋ฆฌ๋˜์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. ์ด ํŽธ์ง€์—์„œ๋Š” AMC ์šด์˜์„ ๊ณ ๋ คํ•œ ํ˜„์‹ค์ ์ธ ์ฑ„๋„ ๋ชจ๋ธ์—์„œ LTELAA ์„ฑ๋Šฅ์„ ๋ถ„์„ํ•˜๊ธฐ์œ„ํ•œ ์ƒˆ๋กœ ์šด Markov ์ฒด์ธ ๊ธฐ๋ฐ˜ ๋ถ„์„ ๋ชจ๋ธ์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ๋ฌด์„  ๋„คํŠธ์›Œํฌ ๋ถ„์„์— ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๋Š” Rayleigh ํŽ˜์ด๋”ฉ ์ฑ„๋„ ๋ชจ๋ธ์„ ์ฑ„ํƒํ•˜๊ณ  ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ns-3 ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ์—์„œ ์–ป์€ ๊ฒฐ๊ณผ ์™€ ๋น„๊ตํ•ฉ๋‹ˆ๋‹ค. ๋น„๊ต ๊ฒฐ๊ณผ๋Š” ํ‰๊ท  ์ •ํ™•๋„๊ฐ€ 99.5%๋กœ ๋ถ„์„ ๋ชจ๋ธ์˜ ์ •ํ™•๋„๋ฅผ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ๋†’์€ ๋ฐ์ดํ„ฐ ์†๋„์— ๋Œ€ํ•œ ์š”๊ตฌ ์‚ฌํ•ญ์œผ๋กœ ์ธํ•ด 3GPP๋Š” LTE-LAA๋ฅผ์œ„ํ•œ ๋‹ค์ค‘ ๋ฐ˜์†กํŒŒ ์šด์˜์„ ์ œ๊ณตํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋‹ค์ค‘ ๋ฐ˜์†กํŒŒ ๋™์ž‘์€ OOBE์— ์ทจ์•ฝํ•˜๊ณ  ์ œํ•œ๋œ ์ „์†ก ์ „๋ ฅ์„ ์‚ฌ์šฉํ•˜์—ฌ ๋น„ํšจ์œจ์  ์ธ ์ฑ„๋„ ์‚ฌ์šฉ์„ ์ดˆ๋ž˜ํ•ฉ๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์ฑ„๋„ ํšจ์œจ์„ ๋†’์ด๊ธฐ์œ„ํ•œ ์ƒˆ๋กœ์šด ๋‹ค์ค‘ ๋ฐ˜์†กํŒŒ ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์•ˆํ•œ๋‹ค. ์šฐ๋ฆฌ๊ฐ€ ์ œ์•ˆํ•œ ๋ฐฉ์‹์€ ์ „์†ก ๋ฒ„์ŠคํŠธ๋ฅผ ์—ฌ๋Ÿฌ ๊ฐœ๋กœ ๋ถ„ํ• ํ•˜๊ณ  ์ „์†ก ์ „๋ ฅ ์ œํ•œ์„ ์ถฉ์กฑํ•˜๋ฉด์„œ ์งง์€ ์„œ๋ธŒ ํ”„๋ ˆ์ž„ ์ „์†ก ์„ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ ์ฑ„๋„ ์ƒํƒœ๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ํŒ๋‹จํ•˜์—ฌ OOBE ๋ฌธ์ œ๋ฅผ ๊ทน๋ณต ํ•  ์ˆ˜์žˆ๋Š” ์—๋„ˆ์ง€ ๊ฐ์ง€ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์†Œํ”„ํŠธ์›จ์–ด ์ •์˜ ๋ผ๋””์˜ค๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ํ”„๋กœํ†  ํƒ€์ž…์€ 99% ์ด์ƒ์˜ ์ •ํ™•๋„๋กœ ์ฑ„๋„ ์ƒํƒœ๋ฅผ ๊ฒฐ์ •ํ•˜๋Š” ์—๋„ˆ์ง€ ๊ฐ์ง€ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์‹คํ–‰ ๊ฐ€๋Šฅ์„ฑ๊ณผ ์„ฑ๋Šฅ์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ns-3 ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ์ œ์•ˆ ๋œ ๋‹ค์ค‘ ๋ฐ˜์†กํŒŒ ์•ก์„ธ์Šค ๋ฐฉ์‹์ด ๊ธฐ์กด LBT ์œ ํ˜• A ๋ฐ ์œ ํ˜• B์— ๋น„ํ•ด ์‚ฌ์šฉ์ž์ธ์ง€ ์ฒ˜๋ฆฌ๋Ÿ‰์—์„œ ๊ฐ๊ฐ ์ตœ๋Œ€ 59% ๋ฐ 21.5%์˜ ์„ฑ๋Šฅ ํ–ฅ์ƒ์„ ๋‹ฌ์„ฑ ํ•จ์„ ํ™•์ธํ–ˆ์Šต๋‹ˆ๋‹ค. ๋ ˆ๊ฑฐ์‹œ LAA์—๋Š” ๋ฐฐํฌ ๋ฌธ์ œ๊ฐ€ ์žˆ๊ธฐ ๋•Œ๋ฌธ์— 3GPP์™€ MulteFire ์–ผ๋ผ์ด์–ธ์Šค๋Š” ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ ๋…๋ฆฝํ˜• ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹  ์‹œ์Šค ํ…œ์„ ์ œ์•ˆํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์ข…๋ž˜์˜ ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ ๋…๋ฆฝํ˜• ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹  ์‹œ์Šคํ…œ์€ ์ƒํ–ฅ ๋งํฌ ์ œ์–ด ๋ฉ”์‹œ์ง€์˜ ์ „์†ก ํ™•๋ฅ ์ด ๋‚ฎ๋‹ค. ์ด ๋…ผ๋ฌธ์€ Wi-Fi ๋ธ”๋ก ACK ํ”„๋ ˆ์ž„์— ์—… ๋งํฌ ์ œ์–ด ๋ฉ”์‹œ์ง€๋ฅผ ๋„ฃ๋Š” W ARQ : Wi-Fi ์ง€์› HARQ๋ฅผ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ W-ARQ์˜ ์ฒ˜ ๋ฆฌ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ๋ณ‘๋ ฌ HARQ ๋ฐ ํด๋Ÿฌ์Šคํ„ฐ๋ง ๋œ Minstrel์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์šฐ๋ฆฌ๊ฐ€ ์ œ์•ˆํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ๊ธฐ์กด MulteFire๊ฐ€ ๊ฑฐ์˜ ์ œ๋กœ ์ฒ˜๋ฆฌ๋Ÿ‰ ์„ฑ๋Šฅ์„ ๋ณด์ด๋Š” ๊ฒฝ์šฐ ๋†’์€ ์ฒ˜๋ฆฌ๋Ÿ‰ ์„ฑ๋Šฅ์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ์š”์•ฝํ•˜๋ฉด ๋น„๋ฉดํ—ˆ ๋Œ€์—ญ ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹ ์˜ ์„ฑ๋Šฅ์„ ๋ถ„์„ ํ•ฉ๋‹ˆ๋‹ค. ์ œ์•ˆ ๋œ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ ์šฐ๋ฆฌ๋Š” ๋ ˆ๊ฑฐ์‹œ ๋‹ค์ค‘ ๋ฐ˜์†กํŒŒ ๋™์ž‘์„ ์ฃผ์žฅํ•˜๋ฉฐ ๋น„๋ฉดํ—ˆ ์…€๋ฃฐ๋Ÿฌ ํ†ต์‹ ์˜ HARQ๋Š” ํšจ์œจ์ ์ด์ง€ ์•Š๋‹ค. ์ด๋Ÿฌํ•œ ์ด์œ ๋กœ, ์šฐ๋ฆฌ๋Š” ์ตœ์ฒจ๋‹จ ๊ธฐ ์ˆ ์— ๋น„ํ•ด UPT ๋ฐ ์ฒ˜๋ฆฌ๋Ÿ‰๊ณผ ๊ฐ™์€ ๋„คํŠธ์›Œํฌ ์„ฑ๋Šฅ ํ–ฅ์ƒ์„ ๋‹ฌ์„ฑํ•˜๋Š” OOBE ์ธ์‹ ์ถ”๊ฐ€ ์•ก์„ธ์Šค ๋ฐ W-ARQ๋ฅผ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค.3GPP has developed 5 GHz unlicensed band LTE, referred to as licensed-assisted access (LAA). LAA adopts listen before talk (LBT) operation, resembling Wi-Fis carrier sense multiple access with collision avoidance (CSMA/CA), to enable collision avoidance capability, while the frame structure overhead of each LAA downlink burst varies with the ending time of each preceding LBT operation. In this dissertation, we propose numerical model to analyze unlicensed band cellular communication. Next, we consider the following two enhancements of unlicensed band cellular communication: (i) out-of-band emission (OOBE) aware additional carrier access, and (ii) Wi-Fi assisted hybrid automatic repeat request (H-ARQ) for unlicensed-band stand-alone cellular communication. Given that, existing analytic models of Wi-Fi cannot be used to evaluate the performance of LAA, in this letter, we propose a novel Markov chain-based analytic model to analyze the performance of LAA network composed of multiple contending evolved NodeBs by considering the variation of the LAA frame structure overhead. LTE-LAA adopts adaptive modulation and coding (AMC) for the rate adaptation algorithm inherited from LTE. AMC helps the evolved nodeB (eNB) to select a modulation and coding scheme (MCS) for the next transmission using the channel quality indicator feedback of the current transmission. For the conventional LTE operating in the licensed band, there is no node contention problem and AMC performance has been well studied. However, in the case of LTE-LAA operating in the unlicensed band, AMC performance has not been properly addressed due to the collision problem. In this letter, we propose a novel Markov chain-based analysis model for analyzing LTELAA performance under a realistic channel model considering AMC operation. We adopt Rayleigh fading channel model widely used in wireless network analysis, and compare our analysis results with the results obtained from ns-3 simulator. Comparison results show an average accuracy of 99.5%, which demonstrates the accuracy of our analysis model. Due to the requirement for a high data rate, the 3GPP has provided multi-carrier operation for LTE-LAA. However, multi-carrier operation is susceptible to OOBE and uses limited transmission power, resulting in inefficient channel usage. This paper proposes a novel multi-carrier access scheme to enhance channel efficiency. Our proposed scheme divides a transmission burst into multiple ones and uses short subframe transmission while meeting the transmission power limitation. In addition, we propose an energy detection algorithm to overcome the OOBE problem by deciding the channel status accurately. Our prototype using software-defined radio shows the feasibility and performance of the energy detection algorithm that determines the channel status with over 99% accuracy. Through ns-3 simulation, we confirm that the proposed multi-carrier access scheme achieves up to 59% and 21.5% performance gain in userperceived throughput compared with the conventional LBT type A and type B, respectively. Since the legacy LAA has deployment problem, 3GPP and MulteFire alliance proposed unlicensed band stand-alone cellular communication system. However, conventional unlicensed band stand-alone cellular communication system has low transmission probability of uplink control messages. This disertation proposes W-ARQ: Wi-Fi assisted HARQ which put uplink control messages into Wi-Fi block ACK frame. In addition we propose parallel HARQ and clustered Minstrel to enhance throughput performance of W-ARQ. Our proposed algorithm shows high throughput performance where conventional MulteFire shows almost zero throughput performance. In summary, we analyze the performance of unlicensed-band cellular communication. By using the proposed model, we insist the legacy multi-carrier operation and HARQ of unlicensed cellular communication is not efficient. By this reason, we propose OOBE aware additional access and W-ARQ which achievee enhancements of network performance such as UPT and throughput compared with state-of-the-art techniques.Abstract i Contents iv List of Tables vii List of Figures viii 1 Introduction 1 1.1 Unlicensed Band Communication System . . . . . . . . . . . . . . . 1 1.2 Overview of Existing Approaches . . . . . . . . . . . . . . . . . . . 2 1.2.1 License-assisted access . . . . . . . . . . . . . . . . . . . . . 2 1.2.2 Further LAA . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.3 Non-3GPP Unlicensed Band Cellular Communication . . . . 6 1.3 Main Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.3.1 Performance Analysis of LTE-LAA . . . . . . . . . . . . . . 6 1.3.2 Out-of-Band Emission Aware Additional Carrier Access for LTE-LAA Network . . . . . . . . . . . . . . . . . . . . . . . 7 1.3.3 W-ARQ: Wi-Fi Assisted HARQ for Unlicensed Band StandAlone Cellular Communication System . . . . . . . . . . . . 8 1.4 Organization of the Dissertation . . . . . . . . . . . . . . . . . . . . 8 2 Performance Analysis of LTE-LAA network 10 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.3 Proposed Markov-Chain Model . . . . . . . . . . . . . . . . . . . . . 14 2.3.1 Markov Property . . . . . . . . . . . . . . . . . . . . . . . . 14 2.3.2 Markov Chain Model for EPS Type Variation . . . . . . . . . 16 2.3.3 LAA Network Throughput Estimation . . . . . . . . . . . . . 18 2.4 Model Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3 Out-of-Band Emission Aware Additional Carrier Access for LTE-LAA Network 35 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2 Related work and Background . . . . . . . . . . . . . . . . . . . . . 37 3.2.1 Related work . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.2.2 Listen Before Talk . . . . . . . . . . . . . . . . . . . . . . . 38 3.2.3 Out-of-Band Emission . . . . . . . . . . . . . . . . . . . . . 39 3.3 Multi-carrier Operation of LTE-LAA . . . . . . . . . . . . . . . . . . 39 3.4 Carrier Sensing considering Out-of-Band Emission . . . . . . . . . . 47 3.4.1 Energy Detection Algorithm . . . . . . . . . . . . . . . . . . 49 3.4.2 Nominal Band Energy Detection . . . . . . . . . . . . . . . . 50 3.4.3 OOBE-Free Region Energy Detection . . . . . . . . . . . . . 51 3.5 Additional Carrier Access Scheme . . . . . . . . . . . . . . . . . . . 52 3.5.1 Basic Operation . . . . . . . . . . . . . . . . . . . . . . . . . 52 3.5.2 Transmission Power Limitation . . . . . . . . . . . . . . . . 53 3.5.3 Dividing Transmission Burst . . . . . . . . . . . . . . . . . . 54 3.5.4 Short Subframe Decision . . . . . . . . . . . . . . . . . . . . 54 3.6 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.6.1 Performance of Energy Detection considering OOBE . . . . . 57 3.6.2 Simulation Environments . . . . . . . . . . . . . . . . . . . . 57 3.6.3 Performance of Proposed Carrier Access Scheme . . . . . . . 58 3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 4 W-ARQ: Wi-Fi Assisted HARQ for Unlicensed Band Stand-Alone Cellular Communication System 66 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 4.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4.3 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.4 W-ARQ: Wi-Fi assisted HARQ for Unlicensed Band Stand-Alone Cellular Communication System . . . . . . . . . . . . . . . . . . . . . . 69 4.4.1 Parallel HARQ . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.4.2 Clustered Minstrel . . . . . . . . . . . . . . . . . . . . . . . 72 4.5 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 75 4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 5 Concluding Remarks 80 5.1 Research Contributions . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Abstract (In Korean) 90 ๊ฐ์‚ฌ์˜ ๊ธ€ 93Docto

    Energy and throughput efficient strategies for heterogeneous future communication networks

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    As a result of the proliferation of wireless-enabled user equipment and data-hungry applications, mobile data traffic has exponentially increased in recent years.This in-crease has not only forced mobile networks to compete on the scarce wireless spectrum but also to intensify their power consumption to serve an ever-increasing number of user devices. The Heterogeneous Network (HetNet) concept, where mixed types of low-power base stations coexist with large macro base stations, has emerged as a potential solution to address power consumption and spectrum scarcity challenges. However, as a consequence of their inflexible, constrained, and hardware-based configurations, HetNets have major limitations in adapting to fluctuating traffic patterns. Moreover, for large mobile networks, the number of low-power base stations (BSs) may increase dramatically leading to sever power consumption. This can easily overwhelm the benefits of the HetNet concept. This thesis exploits the adaptive nature of Software-defined Radio (SDR) technology to design novel and optimal communication strategies. These strategies have been designed to leverage the spectrum-based cell zooming technique, the long-term evolution licensed assisted access (LTE-LAA) concept, and green energy, in order to introduce a novel communication framework that endeavors to minimize overall network on-grid power consumption and to maximize aggregated throughput, which brings significant benefits for both network operators and their customers. The proposed strategies take into consideration user data demands, BS loads, BS power consumption, and available spectrum to model the research questions as optimization problems. In addition, this thesis leverages the opportunistic nature of the cognitive radio (CR) technique and the adaptive nature of the SDR to introduce a CR-based communication strategy. This proposed CR-based strategy alleviates the power consumption of the CR technique and enhances its security measures according to the confidentiality level of the data being sent. Furthermore, the introduced strategy takes into account user-related factors, such as user battery levels and user data types, and network-related factors, such as the number of unutilized bands and vulnerability level, and then models the research question as a constrained optimization problem. Considering the time complexity of the optimum solutions for the above-mentioned strategies, heuristic solutions were proposed and examined against existing solutions. The obtained results show that the proposed strategies can save energy consumption up to 18%, increase user throughput up to 23%, and achieve better spectrum utilization. Therefore, the proposed strategies offer substantial benefits for both network operators and users

    Performance Analysis of LTE-LAA Network

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