469 research outputs found
Data Aggregation and Packet Bundling of Uplink Small Packets for Monitoring Applications in LTE
In cellular massive Machine-Type Communications (MTC), a device can transmit
directly to the base station (BS) or through an aggregator (intermediate node).
While direct device-BS communication has recently been in the focus of 5G/3GPP
research and standardization efforts, the use of aggregators remains a less
explored topic. In this paper we analyze the deployment scenarios in which
aggregators can perform cellular access on behalf of multiple MTC devices. We
study the effect of packet bundling at the aggregator, which alleviates
overhead and resource waste when sending small packets. The aggregators give
rise to a tradeoff between access congestion and resource starvation and we
show that packet bundling can minimize resource starvation, especially for
smaller numbers of aggregators. Under the limitations of the considered model,
we investigate the optimal settings of the network parameters, in terms of
number of aggregators and packet-bundle size. Our results show that, in
general, data aggregation can benefit the uplink massive MTC in LTE, by
reducing the signalling overhead.Comment: to appear in IEEE Networ
Dynamic RACH Partition for Massive Access of Differentiated M2M Services
In machine-to-machine (M2M) networks, a key challenge is to overcome the overload problem caused by random access requests from massive machine-type communication (MTC) devices. When differentiated services coexist, such as delay-sensitive and delay-tolerant services, the problem becomes more complicated and challenging. This is because delay-sensitive services often use more aggressive policies, and thus, delay-tolerant services get much fewer chances to access the network. To conquer the problem, we propose an efficient mechanism for massive access control over differentiated M2M services, including delay-sensitive and delay-tolerant services. Specifically, based on the traffic loads of the two types of services, the proposed scheme dynamically partitions and allocates the random access channel (RACH) resource to each type of services. The RACH partition strategy is thoroughly optimized to increase the access performances of M2M networks. Analyses and
simulation demonstrate the effectiveness of our design. The proposed scheme can outperform the baseline access class barring (ACB) scheme, which ignores service types in access control, in terms of access success probability and the average access delay
๋น๋ฉดํ๋์ญ ์ ๋ฃฐ๋ผ ํต์ ์ ์ฑ๋ฅ ๋ถ์ ๋ฐ ์ฑ๋ฅ ํฅ์ ๊ธฐ๋ฒ ์ฐ๊ตฌ
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ๊ณต๊ณผ๋ํ ์ ๊ธฐยท์ ๋ณด๊ณตํ๋ถ, 2021. 2. ๋ฐ์ธ์
.3GPP๋ LAA (licensed-assisted access)๋ผ๊ณ ํ๋ 5GHz ๋น๋ฉดํ ๋์ญ
LTE๋ฅผ ๊ฐ๋ฐํ์ต๋๋ค. LAA๋ ์ถฉ๋ ๋ฐฉ์ง ๊ธฐ๋ฅ์ ์ฌ์ฉํ๊ธฐ ์ํด Wi-Fi์ CSMA /
CA (Carrier Sense Multiple Access with Collision avoidance)์ ์ ์ฌํ LBT (Listen
Before Talk) ์์
์ ์ฑํํ์ฌ ๊ฐ LAA ๋ค์ด ๋งํฌ ๋ฒ์คํธ์ ํ๋ ์ ๊ตฌ์กฐ ์ค๋ฒ ํค๋๋
๊ฐ๊ฐ์ ์ข
๋ฃ ์๊ฐ์ ๋ฐ๋ผ ๋ฌ๋ผ์ง๋๋ค. ์ด์ LBT ์์
. ์ด ๋
ผ๋ฌธ์์๋ ๋น๋ฉดํ ๋์ญ
์
๋ฃฐ๋ฌ ํต์ ์ ๋ถ์ํ๊ธฐ์ํ ์์น ๋ชจ๋ธ์ ์ ์ํ๋ค. ๋ค์์ผ๋ก, ๋น๋ฉดํ ๋์ญ ์
๋ฃฐ๋ฌ
ํต์ ์ ๋ค์ ๋ ๊ฐ์ง ํฅ์๋ ๊ธฐ๋ฅ์ ๊ณ ๋ คํฉ๋๋ค. ๋์ญ ๋
๋ฆฝํ ์
๋ฃฐ๋ฌ ํต์ . ๊ธฐ์กด WiFi ๋ถ์ ๋ชจ๋ธ๋ก๋ LAA์ ์ฑ๋ฅ์ ํ๊ฐํ ์ ์๋ค๋ ์ ์ ๊ฐ์ํ์ฌ ๋ณธ ์์ ์์๋
์ฌ๋ฌ ๊ฒฝํฉ ์งํ ๋ NodeB๋ก ๊ตฌ์ฑ๋ LAA ๋คํธ์ํฌ์ ์ฑ๋ฅ์ ๋ถ์ํ๊ธฐ์ํ ์๋ก์ด
Markov ์ฒด์ธ ๊ธฐ๋ฐ ๋ถ์ ๋ชจ๋ธ์ ์ ์ํฉ๋๋ค. LAA ํ๋ ์ ๊ตฌ์กฐ ์ค๋ฒ ํค๋์ ๋ณํ.
LTE-LAA๋ LTE์์ ์์ ๋ ์๋ ์ ์ ์๊ณ ๋ฆฌ์ฆ์ ์ํด ์ ์ ๋ณ์กฐ ๋ฐ ์ฝ๋ฉ (AMC)
์ ์ฑํํฉ๋๋ค. AMC๋ ์งํ ๋ nodeB (eNB)๊ฐ ํ์ฌ ์ ์ก์ ์ฑ๋ ํ์ง ํ์๊ธฐ ํผ๋
๋ฐฑ์ ์ฌ์ฉํ์ฌ ๋ค์ ์ ์ก์์ํ ๋ณ์กฐ ๋ฐ ์ฝ๋ฉ ๋ฐฉ์ (MCS)์ ์ ํํ๋๋ก ๋์ต๋๋ค.
๋ผ์ด์ ์ค ๋์ญ์์ ๋์ํ๋ ๊ธฐ์กด LTE์ ๊ฒฝ์ฐ ๋
ธ๋ ๊ฒฝํฉ ๋ฌธ์ ๊ฐ ์์ผ๋ฉฐ AMC ์ฑ๋ฅ
์ ๋ํ ์ฐ๊ตฌ๊ฐ ์ ์งํ๋๊ณ ์์ต๋๋ค. ๊ทธ๋ฌ๋ ๋น๋ฉดํ ๋์ญ์์ ๋์ํ๋ LTE-LAA
์ ๊ฒฝ์ฐ ์ถฉ๋ ๋ฌธ์ ๋ก ์ธํด AMC ์ฑ๋ฅ์ด ์ ๋๋ก ์ฒ๋ฆฌ๋์ง ์์์ต๋๋ค. ์ด ํธ์ง์์๋
AMC ์ด์์ ๊ณ ๋ คํ ํ์ค์ ์ธ ์ฑ๋ ๋ชจ๋ธ์์ LTELAA ์ฑ๋ฅ์ ๋ถ์ํ๊ธฐ์ํ ์๋ก
์ด Markov ์ฒด์ธ ๊ธฐ๋ฐ ๋ถ์ ๋ชจ๋ธ์ ์ ์ํฉ๋๋ค. ๋ฌด์ ๋คํธ์ํฌ ๋ถ์์ ๋๋ฆฌ ์ฌ์ฉ๋๋
Rayleigh ํ์ด๋ฉ ์ฑ๋ ๋ชจ๋ธ์ ์ฑํํ๊ณ ๋ถ์ ๊ฒฐ๊ณผ๋ฅผ ns-3 ์๋ฎฌ๋ ์ดํฐ์์ ์ป์ ๊ฒฐ๊ณผ
์ ๋น๊ตํฉ๋๋ค. ๋น๊ต ๊ฒฐ๊ณผ๋ ํ๊ท ์ ํ๋๊ฐ 99.5%๋ก ๋ถ์ ๋ชจ๋ธ์ ์ ํ๋๋ฅผ ๋ณด์ฌ์ค๋๋ค. ๋์ ๋ฐ์ดํฐ ์๋์ ๋ํ ์๊ตฌ ์ฌํญ์ผ๋ก ์ธํด 3GPP๋ LTE-LAA๋ฅผ์ํ ๋ค์ค
๋ฐ์กํ ์ด์์ ์ ๊ณตํ์ต๋๋ค. ๊ทธ๋ฌ๋ ๋ค์ค ๋ฐ์กํ ๋์์ OOBE์ ์ทจ์ฝํ๊ณ ์ ํ๋
์ ์ก ์ ๋ ฅ์ ์ฌ์ฉํ์ฌ ๋นํจ์จ์ ์ธ ์ฑ๋ ์ฌ์ฉ์ ์ด๋ํฉ๋๋ค. ๋ณธ ๋
ผ๋ฌธ์ ์ฑ๋ ํจ์จ์
๋์ด๊ธฐ์ํ ์๋ก์ด ๋ค์ค ๋ฐ์กํ ์ ๊ทผ ๋ฐฉ์์ ์ ์ํ๋ค. ์ฐ๋ฆฌ๊ฐ ์ ์ํ ๋ฐฉ์์ ์ ์ก
๋ฒ์คํธ๋ฅผ ์ฌ๋ฌ ๊ฐ๋ก ๋ถํ ํ๊ณ ์ ์ก ์ ๋ ฅ ์ ํ์ ์ถฉ์กฑํ๋ฉด์ ์งง์ ์๋ธ ํ๋ ์ ์ ์ก
์ ์ฌ์ฉํฉ๋๋ค. ๋ํ ์ฑ๋ ์ํ๋ฅผ ์ ํํ๊ฒ ํ๋จํ์ฌ OOBE ๋ฌธ์ ๋ฅผ ๊ทน๋ณต ํ ์์๋
์๋์ง ๊ฐ์ง ์๊ณ ๋ฆฌ์ฆ์ ์ ์ํฉ๋๋ค. ์ํํธ์จ์ด ์ ์ ๋ผ๋์ค๋ฅผ ์ฌ์ฉํ๋ ํ๋กํ
ํ์
์ 99% ์ด์์ ์ ํ๋๋ก ์ฑ๋ ์ํ๋ฅผ ๊ฒฐ์ ํ๋ ์๋์ง ๊ฐ์ง ์๊ณ ๋ฆฌ์ฆ์ ์คํ
๊ฐ๋ฅ์ฑ๊ณผ ์ฑ๋ฅ์ ๋ณด์ฌ์ค๋๋ค. ns-3 ์๋ฎฌ๋ ์ด์
์ ํตํด ์ ์ ๋ ๋ค์ค ๋ฐ์กํ ์ก์ธ์ค
๋ฐฉ์์ด ๊ธฐ์กด LBT ์ ํ A ๋ฐ ์ ํ B์ ๋นํด ์ฌ์ฉ์์ธ์ง ์ฒ๋ฆฌ๋์์ ๊ฐ๊ฐ ์ต๋ 59%
๋ฐ 21.5%์ ์ฑ๋ฅ ํฅ์์ ๋ฌ์ฑ ํจ์ ํ์ธํ์ต๋๋ค. ๋ ๊ฑฐ์ LAA์๋ ๋ฐฐํฌ ๋ฌธ์ ๊ฐ
์๊ธฐ ๋๋ฌธ์ 3GPP์ MulteFire ์ผ๋ผ์ด์ธ์ค๋ ๋น๋ฉดํ ๋์ญ ๋
๋ฆฝํ ์
๋ฃฐ๋ฌ ํต์ ์์ค
ํ
์ ์ ์ํ์ต๋๋ค. ๊ทธ๋ฌ๋, ์ข
๋์ ๋น๋ฉดํ ๋์ญ ๋
๋ฆฝํ ์
๋ฃฐ๋ฌ ํต์ ์์คํ
์ ์ํฅ
๋งํฌ ์ ์ด ๋ฉ์์ง์ ์ ์ก ํ๋ฅ ์ด ๋ฎ๋ค. ์ด ๋
ผ๋ฌธ์ Wi-Fi ๋ธ๋ก ACK ํ๋ ์์ ์
๋งํฌ
์ ์ด ๋ฉ์์ง๋ฅผ ๋ฃ๋ W ARQ : Wi-Fi ์ง์ HARQ๋ฅผ ์ ์ํฉ๋๋ค. ๋ํ W-ARQ์ ์ฒ
๋ฆฌ ์ฑ๋ฅ์ ํฅ์์ํค๊ธฐ ์ํด ๋ณ๋ ฌ HARQ ๋ฐ ํด๋ฌ์คํฐ๋ง ๋ Minstrel์ ์ ์ํฉ๋๋ค.
์ฐ๋ฆฌ๊ฐ ์ ์ํ ์๊ณ ๋ฆฌ์ฆ์ ๊ธฐ์กด MulteFire๊ฐ ๊ฑฐ์ ์ ๋ก ์ฒ๋ฆฌ๋ ์ฑ๋ฅ์ ๋ณด์ด๋ ๊ฒฝ์ฐ
๋์ ์ฒ๋ฆฌ๋ ์ฑ๋ฅ์ ๋ณด์ฌ์ค๋๋ค. ์์ฝํ๋ฉด ๋น๋ฉดํ ๋์ญ ์
๋ฃฐ๋ฌ ํต์ ์ ์ฑ๋ฅ์ ๋ถ์
ํฉ๋๋ค. ์ ์ ๋ ๋ชจ๋ธ์ ์ฌ์ฉํจ์ผ๋ก์จ ์ฐ๋ฆฌ๋ ๋ ๊ฑฐ์ ๋ค์ค ๋ฐ์กํ ๋์์ ์ฃผ์ฅํ๋ฉฐ
๋น๋ฉดํ ์
๋ฃฐ๋ฌ ํต์ ์ HARQ๋ ํจ์จ์ ์ด์ง ์๋ค. ์ด๋ฌํ ์ด์ ๋ก, ์ฐ๋ฆฌ๋ ์ต์ฒจ๋จ ๊ธฐ
์ ์ ๋นํด UPT ๋ฐ ์ฒ๋ฆฌ๋๊ณผ ๊ฐ์ ๋คํธ์ํฌ ์ฑ๋ฅ ํฅ์์ ๋ฌ์ฑํ๋ OOBE ์ธ์ ์ถ๊ฐ
์ก์ธ์ค ๋ฐ W-ARQ๋ฅผ ์ ์ํฉ๋๋ค.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
๊ฐ์ฌ์ ๊ธ 93Docto
Compressive Sensing-Based Grant-Free Massive Access for 6G Massive Communication
The advent of the sixth-generation (6G) of wireless communications has given
rise to the necessity to connect vast quantities of heterogeneous wireless
devices, which requires advanced system capabilities far beyond existing
network architectures. In particular, such massive communication has been
recognized as a prime driver that can empower the 6G vision of future
ubiquitous connectivity, supporting Internet of Human-Machine-Things for which
massive access is critical. This paper surveys the most recent advances toward
massive access in both academic and industry communities, focusing primarily on
the promising compressive sensing-based grant-free massive access paradigm. We
first specify the limitations of existing random access schemes and reveal that
the practical implementation of massive communication relies on a dramatically
different random access paradigm from the current ones mainly designed for
human-centric communications. Then, a compressive sensing-based grant-free
massive access roadmap is presented, where the evolutions from single-antenna
to large-scale antenna array-based base stations, from single-station to
cooperative massive multiple-input multiple-output systems, and from unsourced
to sourced random access scenarios are detailed. Finally, we discuss the key
challenges and open issues to shed light on the potential future research
directions of grant-free massive access.Comment: Accepted by IEEE IoT Journa
- โฆ