Politecnico di Milano Advanced Network Technologies Laboratory. Radio Frequency Identification
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1 Politecnico di Milano Advanced Network Technologies Laboratory Radio Frequency Identification
2 RFID in Nutshell o To Enhance the concept of bar-codes for faster identification of assets (goods, people, animals) o Ingredients: n Transition to electronic bar codes with wireless communication capabilities n Transition form optical to wireless readers 2
3 RFID History o First Bar code patents 930s o H. Stockman Paper (948) Communication by means of reflected power o First RFID Patent o Auto-ID center founded at MIT 999 n Standardization effort taken over by EPC Global (Electronic Product Code) 3
4 RFID Building Blocks o Two Basic Devices: Reader Tag RF Module Memory Processing Unit Control Logic/Collision Arbitration Mechanism Battery or Power Supply Other Interfaces (Ethernet, WiFi) RF Module Battery Scavenging circuitry (active or passive) E2PROM to store ID Control Logic/Collision Arbitration Mechanism (sensors) (processing unit) 4
5 Types of Tags n Passive o Operational power scavenged o from reader radiated power n Semi-passive o Operational power provided by battery n Active o Operational power provided by battery - transmitter built into tag 5
6 The Tags o Tags can be attached to anything: n pallets or cases of product n vehicles n company assets or personnel n People or animals n Electronic appliances 6
7 Generic Tag Architecture Write Path Receiver Antenna D S G Memory Protocol Engine 7
8 Electronic Product Code Header - Tag version number EPC Manager - Manufacturer ID Object class - Manufacturer s product ID Serial Number - Unit ID With 96 bit code, 268 million companies can each categorize 6 million different products where each product category contains up to 687 billion individual units 8
9 TAG Implementation Challenges o Effective Energy Scavenging o Miniaturization/customization o Cost 9
10 Possible Reader Software Stack Network Interface Network management Custom Custom Application/ Protocol Reader Protocol Application RFID Reader API Library Platform API Libraries O/S High-Level Interfaces Low-Level Interfaces File Systems Network Protocols Hardware 0
11 Reader Implementation Challenges o Reader must deliver enough power from RF field to power the tag o Reader must discriminate backscatter modulation in presence of carrier at same frequency o High magnitude difference between transmitted and received signals o Integration with enterprise solutions
12 RFID Backend o Middleware solutions to: n manage high data volume produced by readers n filter the data produced by the readers (remove redundancy, eliminate unwanted data, etc.) n Store the data in a way that is meaningful for the specific application n Let different readers be interoperable 2
13 Usage Models Dock Door Conveyor Belt Forklift Printers Handheld Smart Shelves Point of Sale 3
14 RFID: Spectrum Snapshot LF HF VHF UHF SHF 23/34 khz 3.56 MHz 420/460 MHz 869/928 MHz 2.35/2.45 GHz 5.8/5.9 GHz 24. GHz 0 khz 00 khz MHz 0 MHz 00 MHz GHz 0 GHz 00 GHz Magnetic Coupling Electromagnetic Coupling 4
15 RFID: Physical Communication o Near Field Model (HF) Model (UHF) Far Field Inductive Coupling (25kHz MHz): better at lower frequencies (<0MHz) for the required antenna dimensions Electromagnetic coupling 868MHz, 2.4GHz, 5GHz: better at higher frequencies for the required antenna dimensions 5
16 RFID HF o Inductive Coupling between two antennas (reader and tag) o Frequency Range 25kHz o 3,56 MHz o Reading range comparable to coil diameter Duplex (concurrent charging and transmission) or sequential (charging and transmission decoupled) operation mode 6
17 RFID UHF o o o o Electromagnetic coupling Transmission happens by modulating the impedence (ASK, FSK o PSK) Tens of meter of read range Bipolar antennas (few centimeters) What about higher frequencies? 2.45, 5.8 GHz Mini Antennas but lower read range 7
18 Politecnico di Milano Advanced Network Technologies Laboratory RFID Collision Arbitration 8
19 General Problem: Tag Identification tag reader Interrogation 9
20 Conflicts in the Responses tag reader Multiple Answers: Arbitration Required 20
21 Tag Arbitration Peculiarities o Similar to Classical Access Control but: n Fixed unknown population size n Tags cannot implement complex protocols o E.g., carrier sense is out n Often reader-driven algorithms 2
22 Collision Arbitration Mechanisms: A Classification o Vertical Classification n ALOHA-like access mechanism o Slotted ALOHA o Dynamic Frame ALOHA n Tree-based access mechanisms o Binary Tree o Horizontal Classification n Centralized/Distributed n Type of Channel Feedback (S,C,0) 22
23 Tag Arbitration Efficiency o The efficiency is commonly defined as the tag population size, N, over the length of the arbitration period L(N) Efficiency = N L N 23
24 Slotted ALOHA Protocol (Abramson, 969) o No channel feedback required, only the ACK o Time is slotted o Protocol: n The first packet in the transmission queue is transmitted in the first available slot n If the ACK does not come, the transmission is reattempted after a random number of slots X 24
25 Slotted ALOHA: retransmissions Random delays Collision t Node A Node B 25
26 Slotted ALOHA performances S in TX buffer G collisions channel S out G-S out o S in incoming traffic o S out outgoing traffic o G traffic on the channel: transmissions + retrasmissions o S out <=G 26
27 Slotted ALOHA performances S in TX buffer G collisioni canale S out G-S out o Assumptions: n Stationarity: S in =S out n Traffic G distributed according to Poisson process o Packet arrivals is a poisson point process with parameter l o Transmissions last T o G=T x l T 27
28 Slotted ALOHA performances o The probability P s for a packet transmission to be successful is the probability that no other packet arrives in the previous slot. t-t t t+t t P = P[ N( t T, t) = 0] = s e G o The throughput is: S = Ge G S / e S-aloha S-aloha 0. 0 G
29 The Frame ALOHA o Extension of the ALOHA protocol where nodes are allowed to transmit once every frame n Frame composed of r slots n Every tag chooses a slot in the frame n If transmission is failed, retry at next frame 29
30 Frame ALOHA: Single Frame o The average throughput is: E[ S] = n r n o Thus, the efficiency is: = E[ S] r = n r r n o Which is maximum for: r=n 0,6 0,5 0,4 M ( n ) = n n eff max 0,3 0,2 0, n 30
31 Frame Aloha: Multiple frames o The FA efficiency depends on the initial tag population (N), the current backlog (n) and the frame size (r). o Current Frame size r is dynamically set to the current backlog n -> Dynamic Frame Aloha 3
32 Frame ALOHA: Multiple Frames Efficiency = N L N The average tag resolution process can be recursively calculated as: L n = r + n i= 0 P( S = i ) L n i which leads to: L n r + n i= = P( S = i )L P( S = 0 ) n i 32
33 o Find out the efficiency in case N=2, and r=2. Example ) ( ) ( 2 ) ( 0) ( 2 ) ( = = = = + = = + = + = = + = = S P S P L L S P L S P L i S P L i i
34 Problem o Initial population N and backlogs n are not known o Tag arbitration is actually composed of two modules: n Backlog Estimation Module: to provide and estimate of the backlog n est n Collision Resolution: run Frame Aloha with r= n est Tag Responses Backlog Estimate Reader Actions DF- Aloha 34
35 Schoute Estimate o Assume that any procedure is able to keep the frame size r equal to the current backlog n o Under this assumption, the number of terminals transmitting in a slot is approximated by a Poisson process with intensity [terminal/slot] o The average number of terminals in a collided slot can be consequently calculated as: H=(-e - )/(-2e - )=2.39 o The backlog is estimated as: n est =round(hc), being c the number of collided slots. 35
36 Schoute Estimate Proof () o Assumptions: n the frame size r is equal to the current backlog n, n the number of terminals transmitting in a slot is well approximated by a Poisson process with intensity [terminal/slot] o we have to prove that the average number of terminals in a collided slot is: H=(-e - )/(-2e - )=
37 Schoute Estimate Proof (2) o The discrete probability distribution of the number of terminals, X, transmitting in a collided slot is given by: P (X = i/x 2) = P (X 2/X = i)p (X = i) P (X 2) o where: P (X 2/X = i) = P (X = i) = i i! e P (X 2) = 2e if i 2 0 otherwise
38 Schoute Estimate Proof (3) o The average number of terminals transmitting in a collided slot is given by: E[X/X 2] = o where: X i=0 ip (X = i/x 2) E[X/X 2] = 2e P i=2 i i i! e = e 2e QDE
39 The Binary-Tree o Random Numbers are used to partition the set of colliding tags
40 The Binary Tree Implementation o Tags have counters set to o The reader broadcasts n Trigger command: sent at the beginning and after successful/empty slots o tags decrease their counter and transmit if counter is 0 n Split commands: sent after collided slots o tags with counter equal to 0 randomly choose a new counter value in [0,] o Tags with counter greater than 0 increase their counter 40
41 The Binary Tree T S S T S T T A: ->0 0->0 0-> ->0 0-> ->0 Res B: ->0 0->0 0-> ->0 0->0 Res Res C: ->0 0-> ->2 2-> ->2 2-> ->0 Res ABC 2 AB 7 C AB 5 6 B A 4
42 Binary Tree: Optimizations o More refined feedbacks can be used to steer the splitting o Leverage tag population estimates to steer splitting o In some slots collisions are certain, use Split command other than Trigger one 2 AB ABC 7 C AB 5 6 B A Certain Collison 42
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