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Adaptive Permission Reservation Protocol for Wireless Communications

The paper discusses shortcomings of existing PRMA protocols and proposes an adaptive PRMA scheme for efficient MAC in wireless communications. It introduces APR and ARP, which dynamically adjust the sending probability based on observed contention traffic. The simulation results show the effectiveness of the proposed scheme compared to other models.

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Adaptive Permission Reservation Protocol for Wireless Communications

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  1. The Adaptive Permission Reservation Protocolfor Wireless Communications In IEEE IPCCC’97, pp. 483-489, by L.-S. Koh and M.-T. Liu

  2. Introduction • More and more portable devices (e.g., handset and PDA) will proliferate in the near future. • MAC (multiple-access control) must effectively use the wireless bandwidth. • TDMA/FDMA/CDMA • PRMA (packet reservation multiple access) • based on TDMA, easy to implement • This paper observes some weakness of PRMA and proposes a modified adaptive PRMA scheme.

  3. Background: Cellular System • Cell structure: • radius < 1km • downlink: from BS to terminals • used only by BS • uplink: from terminals to BS • shared by voice terminals, through MAC protocol

  4. Speech Pattern: principal talking spurt mini-spurt mini-gap listening state To detect speech activity, it is suggested to use a “Speech Activity Detector”: slow detector: can detect principal talk spurt can reduce traffic by 43% fast detector: can detect mini-spurt can further reduce traffic to 36% Background: Voice Characteristic

  5. Background: FP-PRMA • FP = fixed probability • Intuition: contending a time slot with a fixed probability. • Time is slotted. • A number of slots are organized as a frame. • After each slot, a voice terminal can listen to the feedback from the BS regarding the state of the slot (busy/idle). • To begin a new talk: • find an empty slot i • in the next frame, compute a random number x • if (x > pre-defined fixed probability P), • then send in slot i and listen to the feedback • if succeed, all subsequent slot i are reserved for this call.

  6. When BS finds nothing is sent in slot i in frame k, • declare it as empty • other talks can contend for slot i in the frame k+1. • For voice transmission: • A packet is dropped if it is not sent within 32 ms. • Voice quality must be maintained at a certain level. • Problem: • How to select P? • No flexibility with the pre-defined probability P

  7. An Example of PRMA (a) 6,8 contending (b) 8 contending (c) 8 succeeds, R1 drops (d) 6’s random # too small (e) 6 contending (f) 6 succeeds ** How to dynamically adjust the value of sending probability P?

  8. Disadvantage of FP-PRMA • When there are many contending senders, a large P (e.g., 0.8) cannot solve the contending problem. • When there are few contending senders, a low sending probability (e.g., 0.2) will waste the bandwidth. • Goal: APR (Adaptive Permission Reservation Protocol) • to estimate and adjust the sending probability • by observing the contending traffic • as there are typically little change on the contending calls • factors to affect contention • newly arrival calls • dropping from the contending calls

  9. ARP (Adaptive Reservation Protocol) • Similar to FP-PRMA, but will estimate the number of contending voice terminals. • Estimation Scheme: • BS will broadcast the state of each slot through downlink. • A terminal can monitor the downlink for a period of time for the following slot status: • slot[i] = EMPTY/OCCUPIED • ack[i] = SUCCESS/COLLIDE/EMPTY

  10. Basic idea: • net-collision = (# of collisions) - (# of successful calls) • Approach: • if ACK[i] = SUCCESS, then num_collision -- • if num_collision < 0, then num_collision = 0; • if ACK[i] = COLLIDE, then num_collision ++ • if num_collision = 1, then num_collision = 2; • if ACK[i] = EMPTY, then num_collision -- • if num_collision < 0, then num_collision = 0; • Selection of P: • P = 1/num_collision

  11. slow speech activity model fast speech activity model Simulation Model

  12. Other Models to Be Compared • Ideal PRMA: • a hypothetical model • assuming a perfect centralized queue • a packet is scheduled in a FIFO manner • Thus, there is NO contention problem at all. • OP-PRMA: • The exact number of contending terminals, k, can somehow be known. • sending probability = 1/k • (also hypothetical)

  13. Simulation Parameters • System Parameters: • frame length = 20 or 40 slots • Voice Traffic: • Mean Principle Talk Spurt Duration = 1.0 sec • Mean Principle Silent Gap = 1.35 sec • Mean Minitalk Spurt Duration = 0.275 sec • Mean Mini-silent Gap = 0.05 sec • Max Tolerable Speech Delay = 0.032 sec

  14. Simulation Results:Slow Speech Activity • Ideal PRMA < OP-PRMA < Adaptive PRMA < FP-PRMA (with P=0.3)

  15. Simulation Results:Fast Speech Activity • Similar Trend: Ideal PRMA < OP-PRMA < Adaptive PRMA < FP-PRMA (with P=0.3)

  16. Conclusions • Fixed probability v.s. Dynamic probability • proposing a good estimating heuristic for the current number of contenders • performance simulation shows the scheme works close to ideal PRMA models (ideal PRMA and OP-PRMA)

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