Presentazione Laurea Triennale in Ingegneria Elettronica e Informatica

1. Extended Summary of “Coded
Slotted ALOHA: A Graph-Based
Method for Uncoordinated Multiple
Access”
Enrico Paolini, Gianluigi Liva, and Marco Chiani. Coded slotted aloha: A
graph-based method for uncoordinated multiple access. IEEE Transactions
on Information Theory, 61(12):6815–6832, 2015.
Student: Marco Parentin - IN0500912
Supervisor: Prof. Fulvio Babich
Academic Year: 2022-2023

2. MASSIVE MULTIPLE ACCESS (MMA)
q Multiple access (MA): organize
trasmissions from many independent
users to a common receiver
q Massive scenario:
Ø Huge population size
Ø Random and sporadic activity
Ø Short packets
q Traditional schemes are not suitable
for MMA due to low efficiency
Image: https://hdl.handle.net/11580/98575
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3. TOWARDS 6G’s IoT
q Billions of machine-type users (massive
Machine-type Communication)
q Sporadic transmission of few packets (e.g.
alarm, GPS position, …)
q Highly unpredictable number of active users
Ø Need for a scalable scheme
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4. RANDOM MULTIPLE ACCESS (RMA)
q Traditional solution: Slotted ALOHA (SA)
Ø Time divided in slots
Ø Users transmit in first available slot whenever they have a packet
Ø No coordination: collisions and idle slots ⇒ Low efficiency
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5. RANDOM MULTIPLE ACCESS (RMA)
q Traditional solution: Slotted ALOHA (SA)
Ø Time divided in slots
Ø Users transmit in first available slot whenever they have a packet
Ø No coordination: collisions and idle slots ⇒ Low efficiency
q Modern solutions: Successive Interference Cancellation (SIC)
Ø Remove contribution of correctly received packet in colliding slot
Ø Repetition schemes: CRDSA (2007), IRSA (2011)
Ø Packet-coding scheme: CODED SLOTTED ALOHA (CSA, 2015)
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6. CSA ENCODING PROCESS
Ø User Activation
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7. CSA ENCODING PROCESS
Ø User Activation
Ø Segmentation
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8. CSA ENCODING PROCESS
Ø User Activation
Ø Segmentation
Ø Packet-Level Encoding
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9. CSA ENCODING PROCESS
Ø User Activation
Ø Segmentation
Ø Packet-Level Encoding
Ø Random slice selection
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10. CSA ENCODING PROCESS
Ø User Activation
Ø Segmentation
Ø Packet-Level Encoding
Ø Random slice selection
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11. CSA ENCODING PROCESS
Ø User Activation
Ø Segmentation
Ø Packet-Level Encoding
Ø Random slice selection
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12. CSA DECODING PROCESS
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13. CSA DECODING PROCESS
Ø Clean segments received
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14. CSA DECODING PROCESS
Ø Clean segments received
Ø Local erasure decoding
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15. CSA DECODING PROCESS
Ø Clean segments received
Ø Local erasure decoding
Ø SIC
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16. CSA DECODING PROCESS
Ø Clean segments received
Ø Local erasure decoding
Ø SIC
Ø Iterate
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17. CSA DECODING PROCESS
Ø Clean segments received
Ø Local erasure decoding
Ø SIC
Ø Iterate
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18. PERFORMANCE ANALYSIS (I)
q Key idea: exploit analogy with decoding of LDPC codes on graphs
⇕
q SIC ≡ Message
passing through
graph’s edges
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19. PERFORMANCE ANALYSIS (II)
q Important parameters:
Ø Load 𝑮: avarage packets per slot
Ø Throughput 𝑺: expected successful
transmissions per slot
qAsymptotic analysis of iterative decoding:
Ø Threshold behavior
∃ 𝐺!"# ∶ %
𝑆 = 𝐺 ∀ 𝐺 < 𝐺!"#
𝑆 = 0 ∀ 𝐺 > 𝐺!"#
Ø No retransmission for 𝐺 < 𝐺!"#
Image: From 5G to 6G: Has the Time for Modern Random Access Come?
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20. WEAK POINTS and FUTURE
q Main issue: SIC requires synchronization
Ø Ok for satellites
Ø Difficult in terrestrial distributed systems
SATELLITE
NOMA
(Capture)
IRSA / CSA
(SIC)
5G 8

21. WEAK POINTS and FUTURE
q Main issue: SIC requires synchronization
Ø Ok for satellites
Ø Difficult in terrestrial distributed systems
NOMA
(Capture)
IRSA / CSA
(SIC)
6G? 8

22. q In CSA segmentation, code diversity and SIC enable to approach 1
packet/slot of throughput without retransmissions
q Higher energy efficiency with respect to IRSA
q Several commonalities with LDPC codes on graphs
q The scheme is promising for 6G
CONCLUSIONS
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23. THANK YOU FOR YOUR ATTENTION
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