M‑IRSA: Multi‑Packets Transmitted Irregular Repetition Slotted Aloha

doi:10.12142/ZTECOM.202004009

ZTE Communications ›› 2020, Vol. 18 ›› Issue (4): 62-68.DOI: 10.12142/ZTECOM.202004009

• Special Topic • Previous Articles Next Articles

M‑IRSA: Multi‑Packets Transmitted Irregular Repetition Slotted Aloha

SUN Jingyun(), LIU Zhen, WU Yang

Hiwing Satellite Operation Division of China Aerospace Science and Industry Corporation, Bejing 100070, China

Received:2020-10-11 Online:2020-12-25 Published:2021-01-13
About author:SUN Jingyun (sunjingyun@satcloud.com.cn) received the B.E. and Ph.D. degrees in electronic engineering from Beihang University, China in 2013 and 2020, respectively. She now works with the Hiwing Satellite Operation Division of China Aerospace Science and Industry Corporation (CASIC), China. Her research interests are wireless communications and coded random access schemes.|LIU Zhen received the M.S. degree in communication and information system from Harbin Engineering University (HEU), China in 2014. He is currently a senior system engineer with the Hiwing Satellite Operation Division of CASIC, China. His research interests include satellite telemetry, tracking, and control (TT&C) and wireless communications.|WU Yang received the M.S. degree in information technology from University of New South Wales, Australia in 2018. He is currently a system engineer with the Hiwing Satellite Operation Division of CASIC, China. His research interests include AI and wireless communications.

Abstract

Abstract:

The design of random media access control (MAC) protocol has been attracting great attention for satellite communication networks, where the propagation delay is long and the traffic load is varying. Advanced coded random access schemes tend to provide resource allocation strategies for massive uncoordinated devices, where multiple packet replicas from each user are transmitted in random slots of the frame and successive interference cancellation (SIC) iterations are tracked to recover collided packets at the receiver. It is assumed that each active user just has a single information packet to be transmitted. In this paper, an MAC layer random access scheme named Multi-Packets Transmitted Irregular Repetition Slotted Aloha (M-IRSA) is proposed. Different from the existing advanced random access schemes, the M-IRSA scheme supports various number of packet transmission per user by using pre-coding procedure. Joint decoding combined with SIC iterations and local decoding is analyzed. The simulation results show that the proposed scheme is more efficient compared with the IRSA scheme without packet loss rate (PLR) loss.

Key words: Aloha, coded random access, MAC, satellite network, successive interference cancellation

SUN Jingyun, LIU Zhen, WU Yang. M‑IRSA: Multi‑Packets Transmitted Irregular Repetition Slotted Aloha[J]. ZTE Communications, 2020, 18(4): 62-68.

Figures/Tables 5

Figure 1 IRSA scheme and SIC procedure.

Figure 2 An Multi-Packets Transmitted Irregular Repetition Slotted Aloha (M-IRSA) example with frame size m=6 slots and 2 active users. The first user u1 contains 3 information packets and generates 5 coded packets. The user u2 contains 2 information packets and generates 3 coded packets. Slots s1 and s2 suffer from collisions.

Figure 3 Expected pre-coding rate versus the normalized packet data size.

Figure 4 PLR performance comparison between M-IRSA and IRSA schemes.

Figure 5 Throughput performance comparison between M-IRSA and IRSA schemes.

References 12

1	LAYA A, KALALAS C, VAZQUEZ⁃GALLEG F, et al. Goodbye, ALOHA! [J]. IEEE access, 2016, 4(7): 2029–2044
2	LE⁃NGOC T, JAHANGIR I M. Performance analysis of CFDAMA⁃PB protocol for packet satellite communications [J]. IEEE transactions on communications, 1998, 46(9): 1206–1214. DOI: 10.1109/26.718562 DOI
3	CASINI E, DE GAUDENZI R, HERRERO O R. Contention resolution diversity slotted ALOHA (CRDSA): an enhanced random access schemefor satellite access packet networks [J]. IEEE transactions on wireless communications, 2007, 6(4): 1408–1419. DOI: 10.1109/twc.2007.348337 DOI
4	LIVA G. Graph⁃based analysis and optimization of contention resolution diversity slotted ALOHA [J]. IEEE transactions on communications, 2011, 59(2): 477–487. DOI: 10.1109/tcomm.2010.120710.100054 DOI
5	PAOLINI E, LIVA G, CHIANI M. Coded slotted ALOHA: a graph⁃based method for uncoordinated multiple access [J]. IEEE transactions on information theory, 2015, 61(12): 6815–6832. DOI: 10.1109/tit.2015.2492579 DOI
6	ALVI S, DURRANI S, ZHOU X Y. Enhancing CRDSA with transmit power diversity for machine⁃type communication [J]. IEEE transactions on vehicular technology, 2018, 67(8): 7790–7794. DOI: 10.1109/tvt.2018.2831926 DOI
7	GRAELL I, AMAT A G I, LIVA G. Finite⁃length analysis of irregular repetition slotted ALOHA in the waterfall region [J]. IEEE communications letters, 2018, 22(5): 886–889. DOI: 10.1109/lcomm.2018.2812845 DOI
8	SANDGREN E, AMAT A G I, BRANNSTROM F. On frame asynchronous coded slotted ALOHA: asymptotic, finite length, and delay analysis [J]. IEEE transactions on communications, 2017, 65(2): 691–704. DOI: 10.1109/tcomm.2016.2633468 DOI
9	DE GAUDENZI R, HERRERO O D R, GALLINARO G, et al. Random access schemes for satellite networks, from VSAT to M2M: a survey [J]. International journal of satellite communications and networking, 2018, 36(1): 66–107. DOI: 10.1002/sat.1204 DOI
10	TAGHAVI A, VEM A, CHAMBERLAND J F. On the design of universal schemes for massive uncoordinated multiple access [C]//IEEE International Symposium on Information Theory. Barcelona, Spain: IEEE, 2016: 345–349. DOI: 10.1109/ISIT.2016.7541318 DOI
11	LEE M, LEE J K, LEE J J, et al. R⁃CRDSA: reservation⁃contention resolution diversity slotted ALOHA for satellite networks [J]. IEEE communications letters, 2012, 16(10): 1576–1579. DOI: 10.1109/lcomm.2012.082012.120573 DOI
12	LEE Y, LEE J, LIM J, et al. MR⁃CRDSA: multiple reservation contention resolution diversity slotted ALOHA for battle⁃field communication [C]//IEEE Military Communications Conference. Tampa, USA: IEEE, 2015. DOI: 10.1109/MILCOM.2015.7357423 DOI

[1]	XIE Xinyu, WU Yongpeng, YUAN Zhifeng, MA Yihua. Massive Unsourced Random Access Under Carrier Frequency Offset [J]. ZTE Communications, 2023, 21(3): 45-53.
[2]	CHEN Jiajun, GAO Yin, LIU Zhuang, LI Dapeng. Future Vision on Artificial Intelligence Assisted Green Energy Efficiency Network [J]. ZTE Communications, 2023, 21(2): 34-39.
[3]	AWADA Uchechukwu, ZHANG Jiankang, CHEN Sheng, LI Shuangzhi, YANG Shouyi. Machine Learning Driven Latency Optimization for Internet of Things Applications in Edge Computing [J]. ZTE Communications, 2023, 21(2): 40-52.
[4]	LI Zhongya, CHEN Rui, HUANG Xingang, ZHANG Junwen, NIU Wenqing, LU Qiuyi, CHI Nan. SVM for Constellation Shaped 8QAM PON System [J]. ZTE Communications, 2022, 20(S1): 64-71.
[5]	ZHAO Zipiao, ZHAO Yongli, YAN Boyuan, WANG Dajiang. Auxiliary Fault Location on Commercial Equipment Based on Supervised Machine Learning [J]. ZTE Communications, 2022, 20(S1): 7-15.
[6]	NAN Yucen, FANG Minghao, ZOU Xiaojing, DOU Yutao, Albert Y. ZOMAYA. A Collaborative Medical Diagnosis System Without Sharing Patient Data [J]. ZTE Communications, 2022, 20(3): 3-16.
[7]	LIU Zhuang, GAO Yin, LI Dapeng, CHEN Jiajun, HAN Jiren. Enabling Energy Efficiency in 5G Network [J]. ZTE Communications, 2021, 19(1): 20-29.
[8]	DENG Xu, ZHU Lidong. Resource Allocation Strategy Based on Matching Game [J]. ZTE Communications, 2020, 18(4): 10-17.
[9]	Julian AHRENS, Lia AHRENS, Hans D. SCHOTTEN. A Machine Learning Method for Prediction of Multipath Channels [J]. ZTE Communications, 2019, 17(4): 12-18.
[10]	LIU Jianwei, YUAN Yifei, HAN Jing. A Case Study on Intelligent Operation System for Wireless Networks [J]. ZTE Communications, 2019, 17(4): 19-26.
[11]	HAN Bin, Hans D. SCHOTTEN. Machine Learning for Network Slicing Resource Management:A Comprehensive Survey [J]. ZTE Communications, 2019, 17(4): 27-32.
[12]	XUE Songyan, LI Ang, WANG Jinfei, YI Na, MA Yi, Rahim TAFAZOLLI, Terence DODGSON. To Learn or Not to Learn:Deep Learning Assisted Wireless Modem Design [J]. ZTE Communications, 2019, 17(4): 3-11.
[13]	Mohammed SEID, Stephen ANOKYE, SUN Guolin. Machine Learning Based Unmanned Aerial Vehicle Enabled Fog-Radio Aerial Vehicle Enabled Fog-Radio Access Network and Edge Computing [J]. ZTE Communications, 2019, 17(4): 33-45.
[14]	Zöchmann Erich. A Framework for Active Learning of Beam Alignment in Vehicular Millimeter Wave Communications by Onboard Sensors [J]. ZTE Communications, 2019, 17(2): 2-9.
[15]	JIN Yichao, WEN Yonggang. When Machine Learning Meets Media Cloud: Architecture, Application and Outlook [J]. ZTE Communications, 2018, 16(3): 30-39.

M‑IRSA: Multi‑Packets Transmitted Irregular Repetition Slotted Aloha

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 5

References 12

Related Articles 15

Recommended Articles

Metrics