PHY layer access misbehavior in WLAN networks

1. PHY layer access misbehavior in WLAN networks Master thesis presentation Radio Communication Systems, KTH Probir Khaskel Advisor: Olav Queseth & Examiner: Prof. Jens Zander

2. Outline • Problem definition • System model • Link adaptation • Single cell system • Multi-cell system • Game theoretical analysis • Conclusion • Future work • Airport environment • Infrastructure based network • Time driven system in MATLAB • 1 time slot = 1 OFDM symbol (4μ sec ) • Ideal system performance • System response in CCA level modification • Players attitude • Dynamic strategies for stable system

3. Problem Definition • Greedy users in a single network • Modification in the PHY layer • Frequent channel access by modifying CCA threshold level • Greedy users in a single network • Modification in the PHY layer • Frequent channel access by modifying CCA threshold level • Is there any incentive to modify CCA level defined by the standard from the user’s point of view ? ?? • Does this modification have impact on the overall system performance (in terms of throughput) ?

4. Problem background Greedy channel access in the PHY layer RF signal strength Channel is Idle -62 -72 ↑ Channel is busy Threshold (dBm) -82 ~ Time

5. Propagation model • Traffic model and packet • Asynchronous and identical traffic from the upper layer • Fixed packet size (MPDU-256 bytes) • Co-channel interference • Adjacent channel interference is ignored • Single cell system with various number of nodes • Multicell system with 16 cells, re-use factor 4, 3 nodes in each cell • Fixed maximum power of +23 dBm • Noise level -95 dBm • System deployment • Transmit power and noise • Capture model • Channel interference P ( d ) rx , i i ³ G å i + P ( d ) N rx , j j ¹ j i System model • Propagation model • Traffic model and packet • System deployment • Transmit power and noise • Capture model • Channel interference

6. Mode Modulation Code Rate Data Rate C/I (dB) 1 BPSK 1/2 6 Mbps 6.02 2 BPSK 3/4 9 Mbps 7.78 3 QPSK 1/2 12 Mbps 9.03 4 QPSK 3/4 18 Mbps 10.79 5 16-QAM 1/2 24 Mbps 17.04 6 16-QAM 3/4 36 Mbps 18.80 7 64-QAM 2/3 48 Mbps 24.05 8 64-QAM 3/4 54 Mbps 24.56 IEEE 802.11a PHY and link adaptation • 8 PHY modes with data rates ranging from 6 to 54 Mbps • Link Adaptation for data transmission is realized • as MPDU-based • fast link adaptation, placed closer to the air-interface • based on the estimated C/I at the receiver • Link Adaptation for ACK transmission is realized as • receiver adopts the same PHY mode as the corresponding received data packet • 8 PHY modes with data rates ranging from 6 to 54 Mbps • Link Adaptation for data transmission is realized • as MPDU-based • fast link adaptation, placed closer to the air-interface • based on the estimated C/I at the receiver • Link Adaptation for ACK transmission is realized as • receiver adopts the same PHY mode as the corresponding received data packet

7. Single cell system

8. load vs. throughput 1.4 6 STA 11 STA 16 STA 1.2 21 STA 1 avg. throughput [Mbps] 0.8 0.6 0.4 0.2 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 avg. offered load per station [Mbps] load vs. delay 200 180 160 140 120 avg. delay [ms] 100 80 60 40 20 0 0 0.5 1 1.5 2 2.5 avg. offered load per station [Mbps] load vs. collision 200 180 160 140 120 avg. no. of collision 100 80 60 40 20 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 avg. offered load per station [Mbps] Single cell: Ideal system performance • For higher number of users, system gets saturated earlier • More number of users in the system, more throughput drops down from system capacity to saturation level • System with higher number of users is less capable to support delay bounded QoS with increasing offered load • Number of collision also gets saturated in system saturation

9. cslevel vs. throughput for various no. of nodes 1.6 1.4 (-52, 1.51) 1.2 5 nodes 10 nodes 1 15 nodes 20 nodes (-54, 0.719) avg. throughput per user [Mbps] 0.8 0.6 (-58, 0.352) 0.4 0.2 (-58, 0.206) 0 -85 -80 -75 -70 -65 -60 -55 -50 -45 -40 cslevel [dBm] Single cell: Saturation analysis • The less number of users in the system, the higher reachable CCA level

10. cslevel vs. throughput; (D|S) cslevel vs. throughput; (S|D) 0.9 0.8 G2: (-52, 0.761) G1: (-50, 0.857) 0.8 0.7 0.7 0.6 0.6 0.5 0.5 G1: (-52, 0.499) avg. throughput per user [Mbps] avg. throughput per user [Mbps] 0.4 0.4 G2: (-50, 0.466) 0.3 0.3 0.2 0.2 offered load per user:1.37 [Mbps] offered load per user:1.37 [Mbps] 0.1 0.1 G2: -82 dBm (timid) G2: increasing (greedy) G1: increasing (greedy) G1: -82 dBm (timid) 0 0 -85 -80 -75 -70 -65 -60 -55 -50 -45 -40 -85 -80 -75 -70 -65 -60 -55 -50 -45 -40 cslevel [dBm] cslevel [dBm] Single cell: Greedy vs. timid users

11. load vs. throughput 0.9 0.8 0.7 avg. throughput [Mbps] 0.6 0.5 0.4 G2: -52 dBm 0.3 G1: -50 dBm Ideal system 0.2 avg. system, (D|D) load vs. delay 200 0.1 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 180 avg. offered load per station [Mbps] 160 140 120 avg. delay [ms] 100 80 60 G2: -52 dBm 40 G1: -50 dBm Ideal system 20 avg. system, (D|D) 0 0 0.5 1 1.5 2 2.5 avg. offered load per station [Mbps] load vs. collision 1000 G2: -52 dBm 900 G1: -50 dBm 800 Ideal system avg. system, (D|D) 700 600 avg. collision 500 400 300 200 100 0 0 0.5 1 1.5 avg. offered load per station [Mbps] Single cell: Greedy vs. greedy users • System throughput decreases than that of the ideal system • Number of collision increases around eight times, however, delay performance does not deteriorate compare to throughput and collision

12. bargain domain of SSG, single cell system 1 defection by G1 single cell: 11 STA defection by G2 0.9 G1: 3 nodes G2: 7 nodes 0.8 2 (S|D ) 0.7 S: -82 dBm (S|S) (0.499,0.761) 1 (0.719,0.719) D : -50 dBm 2 0.6 2 D : -52 dBm Nash Equilibrium 1 2 0.5 payoff of G2, v (D |D ) (0.612,0.521) 1 (D |S) 0.4 (0.857,0.466) 0.3 0.2 current NE is Pareto inefficient, 0.1 (S|S) could be Pareto efficient NE 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1 payoff of G1, v Single cell: single stage game • Current Nash Equilibrium is Pareto inefficient • (S|S) would be Pareto efficient NE • Current Nash Equilibrium is Pareto inefficient • (S|S) would be Pareto efficient NE • System performance is better when users follow the standard protocol

13. Single cell: multi stage game • Discount factor, δ (delay bounded application dependent) • Anticipated payoff in stage tto player i • In an infinite game, payoff is computed as • Users prefer to defect if δ<0.563, meaning that they are more likely to defect • Dynamic strategies: TFT, GRIM ensure a stable system

14. Multi-cell system

15. cslevel vs. throughput; (C|C) 0.7 (-68, 0.665) 0.65 0.6 0.55 0.5 avg. throughput per user [Mbps] 0.45 0.4 0.35 (-82, 0.376) 0.3 offered load per user:1.0 [Mbps] 0.25 -90 -80 -70 -60 -50 -40 -30 -20 cslevel [dBm] cslevel vs. collision; (C|C) 500 (-82, 483) 450 400 350 300 avg. no. of collision 250 200 (-68, 139) 150 100 offered load per user:1 [Mbps] 50 -90 -80 -70 -60 -50 -40 -30 -20 cslevel [dBm] Multi-cell: saturation analysis • System throughput out-perform the standard by cooperative modification of the CCA threshold • Collision reduces around three and a half times compare to the ideal system

16. bargain domain of SSG; multi cell system 1 multi cell: 48 nodes defection by G1 defection by G2 G1: 16 nodes 0.9 G2: 32 nodes 0.8 C: -68 dBm D: -44 dBm 0.7 (C|C) 2 0.6 (0.665,0.665) (C|D) 0.5 payoff of 2, v Nash (0.327,0.438) Equilibrium 0.4 (D|C) (D|D) (0.727,0.398) 0.3 (0.366,0.366) 0.2 0.1 current NE is Pareto efficient 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1 payoff of 1, v Multi-cell: game analysis • SSG: Current Nash Equilibrium is Pareto efficient • MSG: TFT, GRIM dynamic strategies ensure a stable system • Users prefer to defect if δ<0.171, meaning that they are more likely to cooperate

17. Conclusion • Single cell system • It’s possible to achieve higher throughput by modifying the CCA level • Any modification results in deterioration of the system performance • Multi-cell System • Adaptive modification of the CCA level gives a noticeable system improvement • A small group gains by further modification, the overall system performance deteriorates • Users are more likely to cooperate • Operators might be interested to have a control on the CCA level modification based on the network condition and update the users to adjust in a regular fashion

18. Future work • Part of the received data of a collided packet could be recoverable by smart decoding algorithm, which in tern could increase the system throughput by avoiding to retransmit the whole packet • Transmit Power Control (TPC) could increase system capacity by minimizing co-channel interference • In general, any misbehaving activities can be detected by collision counter. However, pinpointing a misbehaving user is a crucial task • Players’ assessment of others’ strategy by observed throughput might be a pitfall for system stability

19. Question & Comments!

20. Extra slides Discount factor, δ Lower preference of future payoff, e.g. best effort type application Higher preference of future payoff, e.g. voice telephony 0.171 0.563 0 1 δ →

21. Extra slides Hidden Terminal Problem Access Point Station/Node Hidden terminal

22. Extra slides Unlicensed frequency bands Introduction • UPCS-Unlicensed Personal Communication Services [1.9GHz] • ISM-Industry, Science and Medicine [2.4-2.4835GHz] • UNII-Unlicensed National Information Infrastructure [5.15-5.825GHz] Why Unlicensed? • Promotes efficient spectrum sharing • Further experimentation and innovation • Mobility of wireless applications since no license needed in new location