Analytical study of frame aggregation in error-prone channels

1. 2014 YU-ANTL Lab Seminar Analytical study of frame aggregation in error-prone channels May 29,2014 Shinnazar Seytnazarov Advanced Networking Technology Lab. (YU-ANTL) Dept. of Information & Comm. Eng, Graduate School, Yeungnam University, KOREA (Tel : +82-53-810-3940; Fax : +82-53-810-4742 http://antl.yu.ac.kr/; E-mail : seytnazarovsho@ynu.ac.kr)

2. OUTLINE • Introduction • Overview of 802.11n MAC enhancements • Frame Aggregation • Block Acknowledgment • The analytical model • Model assumptions • Model description • Analytical results • Frame size dynamic adaptation • Conclusion • References

3. Introduction • Motivation • Frame aggregation mechanism can increase the efficiency of MAC layer under ideal channel conditions • However, under high Bit Error Rate (BER) sub-frame failures increases consequently can greatly affect the performance due to their retransmission cost • So, there is a need to examine the effect of frame aggregation feature on the performance under different channel error conditions • Contribution of this paper • Authors derive an analytical model to study the impact of the frame aggregation on the saturation throughput and access delay under lossychannels • Based on numerical results, they propose an algorithm which can dynamically adjust the MPDU sub-frame size based on the maximum FER tolerable by frame's access category

4. Overview of 802.11n MAC enhancements:Frame Aggregation • Frame aggregation mechanisms • Block ACK

5. The analytical model • A. Model Assumptions • To study the performance of frame aggregation under different channel conditions, we extend Bianchi’s model [4] to be suitable with 802.11n enhancements. • Stations competing to access to the medium and operating in saturated conditions. Each station always has a traffic available for transmission. • RTS/CTS access scheme • Only A-MPDU aggregation

6. Model description

7. Model description (1) • Model description • The probability  that a station transmits in a randomly chosen time slot can be expressed as: where pis referred to unsuccessful transmission probability, caused by collisions and errors transmission [4], [11]. • If we have transmitted frame in a time slot, a conditional collision can occur with the probability  when at least one of the remaining n - 1 stations transmit. • If at least 1 bit of frame with FS bits is received with error, the error is applied to hole frame

8. Model description (2) • and given  and , we derive the  as: • Using the equations (2) and (3) we can deduct the probability of unsuccessful transmission caused by either collisions or transmission errors • Let us first consider the probability that a time slot is empty. • The probability that at least one station transmits in a chosen time slot • The probability for having a transmission without collisions is • The probability for having an erroneous transmission (without collisions): • Finally, the probability that a successful transmission occurs without collisions and errors is:

9. Model description (3) • 1) The Saturation Throughput • The network's saturation throughput is calculated as the ratio of the average number of bits being successfully transmitted in a time slot and the expected average length of a time slot • Expected length of slot time: • In the case of an RTS/CTS access mechanism (Fig. 2), they are determined as follows:

10. Model description (4) • Let us examine what happens when we have an A-MPDU aggregated data frame • We consider that is the probability that a subframe is erroneous. Assuming independent errors, the number of erroneous subframesfollows a binomial distribution , where denotes the total number of subframes in an A-MPDU aggregated frame. The probability that k of  are erroneous is given by • Therefore the average number of erroneous subframes in A-MPDU is • In this case the variable number of bits successfully transmitted  can be expressed as • where the total size of each subframes header (MAC header, delimiter, and FCS).

11. Model description (5) • 2) The Access Delay • The average access delay which is defined as the required time for an aggregated frame to reach the receivers MAC. • Using the network saturation throughput S, each A-MPDU frame takes an average of  to be transmitted. • Since, we have n stations competing for the channel we can derive the average access delay as

12. Analytical results (1)

13. Analytical results (2)

14. Analytical results (3)

15. Analytical results (4)

16. Frame size dynamic adaptation (1) • QoS requirements for some ACs according to paper • VolP traffics are delay-sensitive and they should tolerate less than 1–2% packet loss with delays greater than 30ms • Streaming video traffic is sensitive to the loss rate less than 5% and more tolerable to the delay where the latency should be no more than 4 to 5 seconds. • Station runs Algorithm 1 upon receiving Block ACK frame • STA measures frame error rate (mFER) • Then it can obtain bit error rate (mBER) • After that, it compares the mFER with the maximum FER tolerable by the corresponding frame access category FERmax_AC

17. Frame size dynamic adaptation (2)

18. Frame size dynamic adaptation (3) • If mFER ≥ FERmax_AC , STA has to use smaller frame aggregation size to meet the AC QoS requirements. Thus the subframe size is reduced using the following equation • Else,it can increase the subframe size to enhance the throughput. However, the step size X_AC of this increase is variable corresponding to the access category parameters. For example we can not use large size for voice traffics. That's authors we have fixed a maximum subframe size for each AC (FSmax_AC).

19. Conclusion • In this paper • Authors derived an analytical model capturing the effect of frame aggregation on the saturation throughput and the access delay under different channels conditions. • The results showed that the network performance depends significantly on the sub-frame size. • Authors designed an adaptive frame aggregation size algorithm. • In this algorithm, the MPDU subframe size is dynamically adjusted according to the measured FER value from the block acknowledgement frame. • In low FER channels, larger frame size is used to increase the throughput. • And in error-prone channels smaller frame aggregation size is used to meet applications QoS requirements.

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