93 research outputs found
๋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
Millimeter Wave Cellular Networks: A MAC Layer Perspective
The millimeter wave (mmWave) frequency band is seen as a key enabler of
multi-gigabit wireless access in future cellular networks. In order to overcome
the propagation challenges, mmWave systems use a large number of antenna
elements both at the base station and at the user equipment, which lead to high
directivity gains, fully-directional communications, and possible noise-limited
operations. The fundamental differences between mmWave networks and traditional
ones challenge the classical design constraints, objectives, and available
degrees of freedom. This paper addresses the implications that highly
directional communication has on the design of an efficient medium access
control (MAC) layer. The paper discusses key MAC layer issues, such as
synchronization, random access, handover, channelization, interference
management, scheduling, and association. The paper provides an integrated view
on MAC layer issues for cellular networks, identifies new challenges and
tradeoffs, and provides novel insights and solution approaches.Comment: 21 pages, 9 figures, 2 tables, to appear in IEEE Transactions on
Communication
Enabling Technologies for Ultra-Reliable and Low Latency Communications: From PHY and MAC Layer Perspectives
ยฉ 1998-2012 IEEE. Future 5th generation networks are expected to enable three key services-enhanced mobile broadband, massive machine type communications and ultra-reliable and low latency communications (URLLC). As per the 3rd generation partnership project URLLC requirements, it is expected that the reliability of one transmission of a 32 byte packet will be at least 99.999% and the latency will be at most 1 ms. This unprecedented level of reliability and latency will yield various new applications, such as smart grids, industrial automation and intelligent transport systems. In this survey we present potential future URLLC applications, and summarize the corresponding reliability and latency requirements. We provide a comprehensive discussion on physical (PHY) and medium access control (MAC) layer techniques that enable URLLC, addressing both licensed and unlicensed bands. This paper evaluates the relevant PHY and MAC techniques for their ability to improve the reliability and reduce the latency. We identify that enabling long-term evolution to coexist in the unlicensed spectrum is also a potential enabler of URLLC in the unlicensed band, and provide numerical evaluations. Lastly, this paper discusses the potential future research directions and challenges in achieving the URLLC requirements
Analysis of a contention-based approach over 5G NR for Federated Learning in an Industrial Internet of Things scenario
The growing interest in new applications involving co-located heterogeneous
requirements, such as the Industrial Internet of Things (IIoT) paradigm, poses
unprecedented challenges to the uplink wireless transmissions. Dedicated
scheduling has been the fundamental approach used by mobile radio systems for
uplink transmissions, where the network assigns contention-free resources to
users based on buffer-related information. The usage of contention-based
transmissions was discussed by the 3rd Generation Partnership Project (3GPP) as
an alternative approach for reducing the uplink latency characterizing
dedicated scheduling. Nevertheless, the contention-based approach was not
considered for standardization in LTE due to limited performance gains.
However, 5G NR introduced a different radio frame which could change the
performance achievable with a contention-based framework, although this has not
yet been evaluated. This paper aims to fill this gap. We present a
contention-based design introduced for uplink transmissions in a 5G NR IIoT
scenario. We provide an up-to-date analysis via near-product 3GPP-compliant
network simulations of the achievable application-level performance with
simultaneous Ultra-Reliable Low Latency Communications (URLLC) and Federated
Learning (FL) traffic, where the contention-based scheme is applied to the FL
traffic. The investigation also involves two separate mechanisms for handling
retransmissions of lost or collided transmissions. Numerical results show that,
under some conditions, the proposed contention-based design provides benefits
over dedicated scheduling when considering FL upload/download times, and does
not significantly degrade the performance of URLLC
Enhancing Radio Access Network Performance over LTE-A for Machine-to-Machine Communications under Massive Access
The expected tremendous growth of machine-to-machine (M2M) devices will require solutions to improve random access channel (RACH) performance. Recent studies have shown that radio access network (RAN) performance is degraded under the high density of devices. In this paper, we propose three methods to enhance RAN performance for M2M communications over the LTE-A standard. The first method employs a different value for the physical RACH configuration index to increase random access opportunities. The second method addresses a heterogeneous network by using a number of picocells to increase resources and offload control traffic from the macro base station. The third method involves aggregation points and addresses their effect on RAN performance. Based on evaluation results, our methods improved RACH performance in terms of the access success probability and average access delay
Priority-based initial access for URLLC traffic in massive IoT networks: Schemes and performance analysis
At a density of one million devices per square kilometer, the10โs of billions of devices, objects, and machines
that form a massive Internet of things (mIoT) require ubiquitous connectivity. Among a massive number of
IoT devices, a portion of them require ultra-reliable low latency communication (URLLC) provided via fifth
generation (5G) networks, bringing many new challenges due to the stringent service requirements. Albeit a surge
of research efforts on URLLC and mIoT, access mechanisms which include both URLLC and massive machine
type communications (mMTC) have not yet been investigated in-depth. In this paper, we propose three novel
schemes to facilitate priority-based initial access for mIoT/mMTC devices that require URLLC services while also
considering the requirements of other mIoT/mMTC devices. Based on a long term evolution-advanced (LTEA) or 5G new radio frame structure, the proposed schemes enable device grouping based on device vicinity
or/and their URLLC requirements and allocate dedicated preambles for grouped devices supported by flexible
slot allocation for random access. These schemes are able not only to increase the reliability and minimize the
delay of URLLC devices but also to improve the performance of all involved mIoT devices. Furthermore, we
evaluate the performance of the proposed schemes through mathematical analysis as well as simulations and
compare the results with the performance of both the legacy LTE-A based initial access scheme and a grant-free
transmission scheme.acceptedVersio
Enabling Fairness and QoS for LTE/Wi-Fi Coexistence in Unlicensed Spectrum
The increase of the number of interconnected devices, the Internet of Things (IoT) and new types of services have led to the development of new techniques to improve data transmission and new commercial opportunities in the telecommunications world.
A possible solution that has attracted many telecom companies is the ability to expand their business by exploring new frequency bands, in particular the unlicensed spectrum.
Licensed Assisted Access (LAA) is an LTE based technology that leverages the 5GHz unlicensed band along with licensed spectrum to deliver a performance boost for mobile device users.
A key aspect of LAA is how to regulate access to the communication channel in order to maintain fairness between LTE and other technologies already present in this spectrum section.
Listen Before Talk (LBT) is a technique used in radiocommunications whereby radio transmitters first sense its radio environment before it starts a transmission. However, the aggressive character of LTE is not always correctly managed by LBT.
Based on this observation, we have tried to develop a new channel access method that makes LTE less invasive on the unlicensed spectrum, providing high performance services.
The results obtained show that our algorithm is able to better balance resource sharing by ensuring that all technologies within the frequency band have good coexistence and high performance
- โฆ