545 research outputs found

    Hybrid Spectrum Sharing in mmWave Cellular Networks

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    While spectrum at millimeter wave (mmWave) frequencies is less scarce than at traditional frequencies below 6 GHz, still it is not unlimited, in particular if we consider the requirements from other services using the same band and the need to license mmWave bands to multiple mobile operators. Therefore, an efficient spectrum access scheme is critical to harvest the maximum benefit from emerging mmWave technologies. In this paper, we introduce a new hybrid spectrum access scheme for mmWave networks, where data is aggregated through two mmWave carriers with different characteristics. In particular, we consider the case of a hybrid spectrum scheme between a mmWave band with exclusive access and a mmWave band where spectrum is pooled between multiple operators. To the best of our knowledge, this is the first study proposing hybrid spectrum access for mmWave networks and providing a quantitative assessment of its benefits. Our results show that this approach provides major advantages with respect to traditional fully licensed or fully unlicensed spectrum access schemes, though further work is needed to achieve a more complete understanding of both technical and non technical implications

    Enabling RAN Slicing Through Carrier Aggregation in mmWave Cellular Networks

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    The ever increasing number of connected devices and of new and heterogeneous mobile use cases implies that 5G cellular systems will face demanding technical challenges. For example, Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) scenarios present orthogonal Quality of Service (QoS) requirements that 5G aims to satisfy with a unified Radio Access Network (RAN) design. Network slicing and mmWave communications have been identified as possible enablers for 5G. They provide, respectively, the necessary scalability and flexibility to adapt the network to each specific use case environment, and low latency and multi-gigabit-per-second wireless links, which tap into a vast, currently unused portion of the spectrum. The optimization and integration of these technologies is still an open research challenge, which requires innovations at different layers of the protocol stack. This paper proposes to combine them in a RAN slicing framework for mmWaves, based on carrier aggregation. Notably, we introduce MilliSlice, a cross-carrier scheduling policy that exploits the diversity of the carriers and maximizes their utilization, thus simultaneously guaranteeing high throughput for the eMBB slices and low latency and high reliability for the URLLC flows.Comment: 8 pages, 8 figures. Proc. of the 18th Mediterranean Communication and Computer Networking Conference (MedComNet 2020), Arona, Italy, 202

    ๋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

    Survey of Spectrum Sharing for Inter-Technology Coexistence

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    Increasing capacity demands in emerging wireless technologies are expected to be met by network densification and spectrum bands open to multiple technologies. These will, in turn, increase the level of interference and also result in more complex inter-technology interactions, which will need to be managed through spectrum sharing mechanisms. Consequently, novel spectrum sharing mechanisms should be designed to allow spectrum access for multiple technologies, while efficiently utilizing the spectrum resources overall. Importantly, it is not trivial to design such efficient mechanisms, not only due to technical aspects, but also due to regulatory and business model constraints. In this survey we address spectrum sharing mechanisms for wireless inter-technology coexistence by means of a technology circle that incorporates in a unified, system-level view the technical and non-technical aspects. We thus systematically explore the spectrum sharing design space consisting of parameters at different layers. Using this framework, we present a literature review on inter-technology coexistence with a focus on wireless technologies with equal spectrum access rights, i.e. (i) primary/primary, (ii) secondary/secondary, and (iii) technologies operating in a spectrum commons. Moreover, we reflect on our literature review to identify possible spectrum sharing design solutions and performance evaluation approaches useful for future coexistence cases. Finally, we discuss spectrum sharing design challenges and suggest future research directions

    Measurement and Optimization of LTE Performance

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    4G Long Term Evolution (LTE) mobile system is the fourth generation communication system adopted worldwide to provide high-speed data connections and high-quality voice calls. Given the recent deployment by mobile service providers, unlike GSM and UMTS, LTE can be still considered to be in its early stages and therefore many topics still raise great interest among the international scientific research community: network performance assessment, network optimization, selective scheduling, interference management and coexistence with other communication systems in the unlicensed band, methods to evaluate human exposure to electromagnetic radiation are, as a matter of fact, still open issues. In this work techniques adopted to increase LTE radio performances are investigated. One of the most wide-spread solutions proposed by the standard is to implement MIMO techniques and within a few years, to overcome the scarcity of spectrum, LTE network operators will offload data traffic by accessing the unlicensed 5 GHz frequency. Our Research deals with an evaluation of 3GPP standard in a real test best scenario to evaluate network behavior and performance
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