295 research outputs found

    Multi-Cell Uplink Radio Resource Management. A LTE Case Study

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    5G URLLC๋ฅผ ์œ„ํ•œ ์ €์ง€์—ฐ ํ†ต์‹  ํ”„๋กœํ† ์ฝœ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2020. 2. ์‹ฌ๋ณ‘ํšจ.2020๋…„ IMT ๋น„์ „์— ๋”ฐ๋ฅด๋ฉด 5 ์„ธ๋Œ€ (5G) ์ด๋™ ํ†ต์‹  ์„œ๋น„์Šค๋Š” eMBB (Enhanced Mobile Broadband), mMTC (Massive Machine Type Communication) ๋ฐ URLLC (Ultra Reliability and Low Latency Communication)์˜ ์„ธ ๊ฐ€์ง€ ์„œ๋น„์Šค๋กœ ๋ถ„๋ฅ˜๋œ๋‹ค. ๋‚ฎ์€ ์ง€์—ฐ ์‹œ๊ฐ„๊ณผ ๋†’์€ ์‹ ๋ขฐ๋„๋ฅผ ๋™์‹œ์— ๋ณด์žฅํ•˜๋Š” ๊ฒƒ์€ ์‹ค์‹œ๊ฐ„ ์„œ๋น„์Šค ๋ฐ ์‘์šฉ ํ”„๋กœ๊ทธ๋žจ์˜ ์ƒ์šฉํ™”๋ฅผ ์œ„ํ•˜์—ฌ ํ•„์š”ํ•œ ํ•ต์‹ฌ ๊ธฐ์ˆ ์ด๊ณ , 3 ๊ฐœ์˜ 5G ์„œ๋น„์Šค ์ค‘ URLLC๋Š” ๊ฐ€์žฅ ์–ด๋ ค์šด ์‹œ๋‚˜๋ฆฌ์˜ค๋กœ ์—ฌ๊ฒจ์ง€๊ณ  ์žˆ๋‹ค. ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์—์„œ๋Š” URLLC ์„œ๋น„์Šค๋ฅผ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์Œ๊ณผ ๊ฐ™์€ 3๊ฐ€์ง€ ์ €์ง€์—ฐ ํ†ต์‹  ํ”„๋กœํ† ์ฝœ์„ ์ œ์•ˆํ•œ๋‹ค: (i) 2-way ํ•ธ๋“œ์‰์ดํฌ ๊ธฐ๋ฐ˜ ๋žœ๋ค ์•ก์„ธ์Šค, (ii) Fast Grant Multiple Access ๋ฐ (iii) UE๊ฐ€ ์‹œ์ž‘ํ•˜๋Š” ํ•ธ๋“œ ์˜ค๋ฒ„ ๋ฐฉ์‹. ์ฒซ์งธ, 5G์—์„œ ๋ชฉํ‘œ๋กœ ํ•˜๋Š” ์„ฑ๋Šฅ ์ง€ํ‘œ๋Š” ๋ฐ์ดํ„ฐ ์ „์†ก๋ฅ ์˜ ์ฆ๊ฐ€๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ง€์—ฐ ์‹œ๊ฐ„์„ ๊ฐ์†Œ์‹œํ‚ค๋Š” ๊ฒƒ๋„ ํฌํ•จํ•˜๊ณ  ์žˆ๋‹ค. ํ˜„์žฌ LTE-Advanced ์‹œ์Šคํ…œ์€ ๋žœ๋ค ์•ก์„ธ์Šค ๋ฐ ์ƒํ–ฅ ๋งํฌ ์ „์†ก ์ ˆ์ฐจ์—์„œ 4๊ฐœ์˜ ๋ฉ”์‹œ์ง€ ๊ตํ™˜์„ ํ•„์š”๋กœํ•˜๊ณ , ์ด๋Š” ๋†’์€ ์ง€์—ฐ ์‹œ๊ฐ„์„ ์•ผ๊ธฐํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ์ง€์—ฐ ์‹œ๊ฐ„์„ ํšจ๊ณผ์ ์œผ๋กœ ์ค„์ด๊ธฐ ์œ„ํ•˜์—ฌ 2-way ๋žœ๋ค ์•ก์„ธ์Šค ๋ฐฉ์‹์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆํ•œ 2-way ๋žœ๋ค ์•ก์„ธ์Šค ๊ธฐ์ˆ ์€ ํ”„๋ฆฌ์•ฐ๋ธ”์˜ ์ˆ˜๋ฅผ ์ฆ๊ฐ€์‹œํ‚ด์œผ๋กœ์จ ํ•ด๋‹น ์ ˆ์ฐจ๋ฅผ ์™„๋ฃŒํ•˜๋Š”๋ฐ ๋‹จ 2๊ฐœ์˜ ๋ฉ”์‹œ์ง€ ๋งŒ ํ•„์š”ํ•˜๋‹ค. ์šฐ๋ฆฌ๋Š” ์ด๋Ÿฌํ•œ ํ”„๋ฆฌ์•ฐ๋ธ”์„ ์ƒ์„ฑํ•˜๊ณ  ํ™œ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์—ฐ๊ตฌํ–ˆ๊ณ , ๋‹ค์–‘ํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•˜์—ฌ ์ œ์•ˆํ•œ ๋žœ๋ค ์•ก์„ธ์Šค ๋ฐฉ์‹์ด ๊ธฐ์กด ๊ธฐ์ˆ ๊ณผ ๋น„๊ตํ•˜์—ฌ ์ง€์—ฐ ์‹œ๊ฐ„์„ ์ตœ๋Œ€ 43% ์ค„์ด๋Š” ๊ฒƒ ์„ ํ™•์ธํ–ˆ๋‹ค. ๋˜ํ•œ ์ œ์•ˆํ•œ ๋žœ๋ค ์•ก์„ธ์Šค๋Š” ๊ณ„์‚ฐ ๋ณต์žก๋„๊ฐ€ ์•ฝ๊ฐ„ ์ฆ๊ฐ€ํ•˜์ง€๋งŒ, ๋„คํŠธ์›Œํฌ ๋กœ๋“œ๋Š” ๊ธฐ์กด ๊ธฐ์ˆ ์— ๋น„ํ•ด ์ ˆ๋ฐ˜ ์ด์ƒ ๊ฐ์†Œํ•œ๋‹ค. ๋‘˜์งธ,์›๊ฒฉ ๋™์ž‘,์ž์œจ ์ฃผํ–‰,๋ชฐ์ž…ํ˜• ๊ฐ€์ƒ ํ˜„์‹ค ๋“ฑ๊ณผ ๊ฐ™์€ ๋‹ค์–‘ํ•œ ๋ฏธ์…˜ ํฌ๋ฆฌํ‹ฐ์ปฌ ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜์ด ๋“ฑ์žฅํ•˜๊ณ  ์žˆ๋‹ค. ๋‹ค์–‘ํ•œ URLLC ํŠธ๋ž˜ํ”ฝ์€ ๋‹ค์–‘ํ•œ ์ง€์—ฐ ์‹œ๊ฐ„ ๋ฐ ์‹ ๋ขฐ๋„ ์ˆ˜์ค€์„ ์š”๊ตฌ ์‚ฌํ•ญ์œผ๋กœ ๊ฐ€์ง€๊ณ  ์žˆ๊ณ , ์ด์™€ ํ•จ๊ป˜ ํ•„์š”ํ•œ ๋ฐ์ดํ„ฐ ํฌ๊ธฐ ๋ฐ ํŒจํ‚ท์˜ ๋ฐœ์ƒ์œจ ๋“ฑ์˜ ์ธก๋ฉด์—์„œ ๋‹ค์–‘ํ•œ ํŠน์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ๋ฏธ์…˜ ํฌ๋ฆฌํ‹ฐ์ปฌ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์˜ ๋‹ค์–‘ํ•œ ์š”๊ตฌ ์‚ฌํ•ญ์„ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•ด ์ƒํ–ฅ ๋งํฌ ์ „์†ก์— ์ค‘์ ์„ ๋‘” FGMA(Fast Grant Multiple Access)๋ฅผ ์ œ์•ˆํ–ˆ๋‹ค. FGMA๋Š” ์Šน์ธ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜, ๋™์  ํ”„๋ฆฌ์•ฐ๋ธ” ๊ตฌ์กฐ, ์ƒํ–ฅ ๋งํฌ ์Šค์ผ€์ค„๋ง ๋ฐ ์ ์‘์  ๋Œ€์—ญํญ ์กฐ์ ˆ์˜ ๋„ค ๊ฐ€์ง€ ๋ถ€๋ถ„์œผ๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. FGMA์—์„œ๋Š” ์ง€์—ฐ ์‹œ๊ฐ„์„ ์ตœ์†Œํ™” ํ•˜๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ์ž์› ํ• ๋‹น์„ ํ•œ๋‹ค. ์ด ๋ฐฉ๋ฒ•์„ ํ™œ์šฉํ•˜๋ฉด ์ ์‘์  ๋Œ€์—ญํญ ์กฐ์ ˆ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ†ตํ•ด ์ง€์—ฐ ์‹œ๊ฐ„ ์š”๊ตฌ ์‚ฌํ•ญ์ด ๋‹ค๋ฅธ ํŠธ๋ž˜ํ”ฝ์˜ ๋ถˆ๊ท ํ˜•์„ ์™„ํ™” ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ์Šน์ธ ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ†ตํ•ด FGMA ์‹œ์Šคํ…œ์— ์ด๋ฏธ ์Šน์ธ๋œ ๋ชจ๋“  UE๋“ค์— ๋Œ€ํ•œ ์š”๊ตฌ ์‚ฌํ•ญ์„ ํ•ญ์ƒ ๋ณด์žฅํ•œ๋‹ค. FGMA๋Š” ์‹œ๊ฐ„์— ๋”ฐ๋ผ ๋ณ€ํ•˜๋Š” ํ™˜๊ฒฝ์—์„œ๋„ UE์˜ QoS ์š”๊ตฌ ์‚ฌํ•ญ์„ ํšจ์œจ์ ์œผ๋กœ ๋ณด์žฅํ•œ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ์†Œํ˜• ์…€์€ ์…€๋ฃฐ๋Ÿฌ ์„œ๋น„์Šค ๋ฒ”์œ„๋ฅผ ๊ฐœ์„ ํ•˜๊ณ  ์‹œ์Šคํ…œ ์šฉ๋Ÿ‰์„ ํ–ฅ์ƒ ์‹œ ํ‚ค๊ณ , ๋งŽ์€ ์ˆ˜์˜ ๋ฌด์„  ๋‹จ๋ง์„ ์ง€์›ํ•˜๋Š” ํ•ต์‹ฌ ๊ธฐ์ˆ ๋กœ ๋– ์˜ค๋ฅด๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ์…€์˜ ์„œ๋น„์Šค ๋ฒ”์œ„์˜ ๊ฐ์†Œ๋Š” ๋นˆ๋ฒˆํ•œ ํ•ธ๋“œ์˜ค๋ฒ„๋ฅผ ์œ ๋„ํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ํšจ๊ณผ์ ์ธ ํ•ธ๋“œ์˜ค๋ฒ„ ๋ฐฉ์‹์ดURLLC ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์„ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•ด์„œ ํ•„์š”ํ•˜๋‹ค. ๋”ฐ๋ผ์„œ, URLLC์„œ๋น„์Šค๋ฅผ ์š”๊ตฌํ•˜๋Š” ์ด๋™์„ฑ์ด ์žˆ๋Š” UE๋ฅผ ์„œ๋น„์Šคํ•˜๊ธฐ ์œ„ํ•ด ์ ์‘์  ํ•ธ๋“œ์˜ค๋ฒ„ ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์„ ํƒ ๋ฐ ๋‹จ๋ง์˜ ๋™์ž‘์„ ๋ฏธ๋ฆฌ ์ค€๋น„ํ•ด ๋†“๋Š” ๋ฐฉ์‹์„ ์ ์šฉํ•œ ๋‹จ๋ง์ด ์‹œ์ž‘ํ•˜๋Š” ํ•ธ๋“œ์˜ค๋ฒ„ ๋ฐฉ์‹์„ ์ œ์•ˆํ•œ๋‹ค. ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋Š” ์ œ์•ˆํ•œ ํ•ธ๋“œ์˜ค๋ฒ„๊ฐ€ ์ˆ˜์œจ์„ ํ–ฅ์ƒ์‹œํ‚ด๊ณผ ๋™์‹œ์— ์ €์ง€์—ฐ์„ ๋‹ฌ์„ฑํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ชฌ์„ ๊ฐ„๋žตํžˆ ์š”์•ฝํ•˜๋ฉด ์ง€์—ฐ ์‹œ๊ฐ„์˜ ์ข…๋ฅ˜๋ฅผ ๋žœ๋ค ์•ก์„ธ์Šค ์ง€์—ฐ ์‹œ๊ฐ„, ์ƒํ–ฅ ๋งํฌ ๋ฐ์ดํ„ฐ ์ „์†ก ์ง€์—ฐ ์‹œ๊ฐ„ ๋ฐ ํ•ธ๋“œ์˜ค๋ฒ„ ์ง€์—ฐ ์‹œ๊ฐ„๊ณผ ๊ฐ™์ด 3๊ฐ€์ง€๋กœ ๊ตฌ๋ถ„ํ•˜์˜€๋‹ค. 3๊ฐ€์ง€ ์ข…๋ฅ˜์˜ ์ง€์—ฐ ์‹œ๊ฐ„์— ๋Œ€ํ•ด์„œ ๊ฐ๊ฐ ์ €์ง€์—ฐ์„ ๋‹ฌ์„ฑ ํ•  ์ˆ˜ ์žˆ๋Š” ํ”„๋กœํ† ์ฝœ๊ณผ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•˜์˜€๋‹ค.According to IMT vision for 2020, the fifth generation (5G) wireless services are classified into three categories, namely, Enhanced Mobile Broadband (eMBB), Massive Machine Type Communication (mMTC), and Ultra Reliable and Low Latency Communication (URLLC). Among three 5G service categories, URLLC is considered as the most challenging scenario. Thus, ensuring the latency and reliability is a key to the success of real-time services and applications. In this dissertation, we propose the following three latency reduction protocols to support the URLLC services: (i)2-way handshake-based random access, (ii) Fast grant multiple access, and (iii) UE-initiated handover scheme. First, the performance target includes not only increasing data rate, but also reducing latency in 5G cellular networks. The current LTE-Advanced systems require four message exchanges in the random access and uplink transmission procedure, thus inducing high latency. We propose a 2-way random access scheme which effectively reduces the latency. The proposed 2-way random access requires only two messages to complete the procedure at the cost of increased number of preambles. We study how to generate such preambles and how to utilize them. According to extensive simulation results, the proposed random access scheme significantly outperforms conventional schemes by reducing latency by up to 43%. We also demonstrate that computational complexity slightly increases in the proposed scheme, while network load is reduced more than a half compared to the conventional schemes. Second, various mission-critical applications are emerging such as teleoperation, autonomous driving, immersive virtual reality, and so on. A variety of URLLC traffic has various characteristics in terms of required data sizes and arrival rates with a variety of requirements of latency and reliability. To support the various requirements of the mission-critical applications, We propose a fast grant multiple access (FGMA) focusing on the uplink transmission. FGMA consists of four important parts, namely, admission control, dynamic preamble structure, the uplink scheduling, and bandwidth adaptation. The latency minimization scheduling policy is adopted in FGMA. Taking advantage of this method, the bandwidth adaptation algorithm makes even for the imbalanced arrival of the traffic requiring different latency requirements. With the proposed admission control, FGMA guarantee the requirements to all admitted UEs in the systems. We observe that the proposed FGMA efficiently guarantee the QoS requirements of the UEs even with the dynamic time-varying environment. Finally, small cells are considered a promising solution for improving cellular coverage, enhancing system capacity and supporting the massive number of things. Reduction of the cell coverage induced the frequent handover, so that the effective handover scheme is of importance in the presence of the URLLC applications. Thus, we propose a UE-initiated handover to deal with the mobile UEs requiring URLLC services taking into account the adaptive handover parameter selection and the logic of preparing in advance. The simulation results show that the proposed handover enhances the throughput performance as well as achieving low latency. In summary, we identify interesting problem in terms of latency. We classify three latency, random access latency, data transmission latency, and handover latency. With compelling protocols and algorithms, we resolve the above three problems.1 Introduction 1 1.1 Motivation 1 1.2 Main Contributions 2 1.2.1 Low Latency Random Access for Small Cell Toward Future Cellular Networks 2 1.2.2 Fast Grant Multiple Access in Large-Scale Antenna Systems for URLLC Services 3 1.2.3 UE-initiated Handover for Low Latency Communications 4 1.3 Organization of the Dissertation 4 2 Low Latency Random Access for Small Cell Toward Future Cellular Networks 6 2.1 Introduction 6 2.2 Related Work 9 2.3 Random Access and Uplink Transmission Procedure in LTE-A 11 2.3.1 Random Access in LTE-A 12 2.3.2 Uplink Transmission Procedure 14 2.3.3 Latency Issue in LTE-A 15 2.4 Proposed Random Access 16 2.4.1 Key Idea . 17 2.4.2 Proposed Preamble and Categorization 18 2.5 Preamble Sequence Analysis 23 2.5.1 Preamble Sequence Generation in LTE-A 23 2.5.2 Proposed Preamble Sequence Generation 25 2.5.3 Proposed Preamble Detection 26 2.6 Performance Evaluation 31 2.6.1 Network Latency 32 2.6.2 One-way Latency 33 2.6.3 Network Load 36 2.6.4 Computational Complexity 37 2.7 Conclusion 39 3 Fast Grant Multiple Access in Large-Scale Antenna Systems for URLLC Services 40 3.1 Introduction 40 3.2 Related Work 43 3.3 System Model 44 3.3.1 QoS Information and Service Category 45 3.3.2 Channel Structure 47 3.3.3 Frame Structure 48 3.4 Fast Grant Multiple Access 49 3.4.1 The Uplink Scheduling Policy 51 3.4.2 Dynamic Preamble Structure 53 3.4.3 Admission Control 54 3.4.4 Bandwidth Adaptation 55 3.5 Performance Evaluation 57 3.5.1 Impact of admission control 59 3.5.2 Impact of bandwidth adaptation 61 3.5.3 FGMA performance 62 3.6 Conclusion 64 4 UE-initiated Handover for Low Latency Communications 67 4.1 Introduction 67 4.2 Background and Motivation 69 4.2.1 Handover Decision Principle 69 4.2.2 Handover Procedure 70 4.2.3 Summary of the latency issues 72 4.3 UE-initiated Handover 73 4.3.1 The proposed handover design principles 73 4.3.2 The proposed handover procedure 75 4.4 Performance Evaluation 77 4.4.1 Low mobility environment 77 4.4.2 Low mobility environment 78 4.4.3 High mobility environment 80 4.5 Conclusion 82 5 ConcludingRemarks 84 5.1 Research Contributions 84 Abstract (InKorean) 92Docto

    Software Defined Radio for NB-IoT

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    The next generation of mobile radio systems is expected to providing wireless connectivity for a wide range of new applications and services involving not only people but also machines and objects. Within few years, billions of low-cost and low-complexity devices and sensors will be connected to the Internet, forming a converged ecosystem called Internet of Things (IoT). As a result, in 2016, 3GPP standardizes NB-IoT, the new narrowband radio technology developed for the IoT market. Massive connectivity, reduced UE complexity, coverage extension and deployment flexibility are the targets for this new radio interface, which also ensures harmonious coexistence with current GSM, GPRS and LTE systems. In parallel, the rise of open-source software combined with Software Defined Radio (SDR) solutions has completely changed radio systems engineering in the late years. This thesis focuses on developing the NB-IoTโ€™s protocol stack on the EURECOMโ€™s open-source software platform OpenAirInterface (OAI). First part of this work aims to implement NB-IoTโ€™s Radio Resource Control functionalities on OAI. After an introduction to the platform architecture, a new RRC layer code structure and related interfaces are defined, along with a new approach for Signalling Radio Bearers management. A deep analysis on System Information scheduling is conducted and a subframe-based transmission scheme is then proposed. The last part of this thesis addresses the implementation of a multi-vendor platform interface based on Small Cell Forumโ€™s Functional Application Platform Interface (FAPI) standard. A configurable and dynamically loadable Interface Module (IF-Module) is designed between OAIโ€™s MAC and PHY layers. Primitives and related code structures are presented as well as corresponding Data and Configurationโ€™s procedures. Finally, the convergence of both NB-IoT and FAPI requirements lead to re-design PHY layer mechanisms for which a downlink transmission scheme is proposed

    Cyber security vulnerabilities during long term evolution power-saving discontinuous reception protocol

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    Long Term Evolution (LTE) is a wireless access communications network that consists of base stations called eNodeBs (eNBs), which allow connectivity between the mobile device or user equipment (UE) and the core network. To save battery power, the UE can turn off its radio transceiver circuitry, based on various parameters exchanged during the attach procedure with its serving eNB, using a protocol called discontinuous reception (DRX). During the DRX period, the UE is still connected to the network and its receiver is turned on periodically to determine if the eNB has sent any packets to it. This thesis develops the concepts of using simulation to demonstrate if a denial of service attack during the long DRX period, as hypothesized by some researchers, can be realized. Requirements for experimentation were identified and current simulation tools were evaluated as potential candidates. The tools applied were the LTE standards, the open source ns-3 network simulator and analysis of actual LTE packet traces. Follow-on studies will be required in order to address issues due to the incompleteness of the ns-3 LTE model and the incompatibility of the file format for LTE traces with that required by the Wireshark network protocol analyzer. Essentially, neither tool contains the DRX algorithm.http://archive.org/details/cybersecurityvul1094542650Civilian, Department of Homeland SecurityApproved for public release; distribution is unlimited

    Optimization and Performance Analysis of High Speed Mobile Access Networks

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    The end-to-end performance evaluation of high speed broadband mobile access networks is the main focus of this work. Novel transport network adaptive flow control and enhanced congestion control algorithms are proposed, implemented, tested and validated using a comprehensive High speed packet Access (HSPA) system simulator. The simulation analysis confirms that the aforementioned algorithms are able to provide reliable and guaranteed services for both network operators and end users cost-effectively. Further, two novel analytical models one for congestion control and the other for the combined flow control and congestion control which are based on Markov chains are designed and developed to perform the aforementioned analysis efficiently compared to time consuming detailed system simulations. In addition, the effects of the Long Term Evolution (LTE) transport network (S1and X2 interfaces) on the end user performance are investigated and analysed by introducing a novel comprehensive MAC scheduling scheme and a novel transport service differentiation model

    Techniques for Efficient Spectrum Usage for Next Generation Mobile Communication Networks. An LTE and LTE-A Case Study

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    Self-Optimization of Coverage and Capacity in LTE using Adaptive Antenna Systems

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    In cellular radio networks, the selection of antenna parameters and techniques for antennas plays a key role for capacity and coverage area. Not only network performance is affected by suboptimal network planning but also it is affected by the dynamic radio environment. Therefore, antenna parameters should be adjusted adaptively. Since reacting to the changed situation manually is very expensive and time consuming, The Third Generation Partnership Project (3GPP) introduced the Coverage and Capacity Optimization (CCO) use case for Long Term Evolution (LTE) under the topic of Self-Organizing Network (SON). This thesis work provides a detailed analysis of the optimization space of antenna parameters and compares different tilt techniques as well as discusses vertical sectorization as a novel capacity optimization approach. The work continues by further focusing on the self optimization of coverage and capacity using Adaptive Antenna Systems (AAS) on the basis of findings in the previous simulations on antenna parameters. Evaluations are performed by mapping link-level simulation results into a system level LTE simulator that models antennas in details and propagation in three dimensions
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