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QoS-Aware Resource Allocation for Slowly Time-Varying Channels

QoS-Aware Resource Allocation for Slowly Time-Varying Channels. InfoCom Department - University of Rome La Sapienza giancola@infocom.uniroma1.it lucadn@newyork.ing.uniroma1.it gaby@acts.ing.uniroma1.it.

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QoS-Aware Resource Allocation for Slowly Time-Varying Channels

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  1. QoS-Aware Resource Allocation forSlowly Time-Varying Channels InfoCom Department - University of Rome La Sapienza giancola@infocom.uniroma1.it lucadn@newyork.ing.uniroma1.it gaby@acts.ing.uniroma1.it Presented at the 58th IEEE Vehicular Technology Conference, Orlando, U.S.A., October 2003

  2. Reference Scenario High level application • Two basic problems in the design of a MAC protocol are: • the efficient management of the resource • the need for fulfilling QoS requirements despite the unpredictable behaviour of the channel Data (packets) MAC Medium Access Control We propose an analytical approach for resource allocation at the MAC level. The resulting algorithm maximizes transmis-sion efficiency by adapting error protection to both channel status and required QoS. Physical Channel

  3. Model Assumptions Traffic sources are characterized by two sets of parameters: Tspecs – collects parameters describing source traffic activity Qspecs – defines QoS requirements Dmaxmaximum tolerable end-to-end delay Fminimum tolerable percen-tage of packets delivered within Dmax ppeak rate rmean rate M max packet size b token buffer Qspecs Tspecs The MAC protocol works with fixed-size MAC Protocol Data Units (MACPDUs) payload header effective payload FEC size

  4. system delay Capacity function Delay function Resource Allocation (1/4) Two functions are introduced in order to express in analytical terms the trade-off which exists between reserved capacity C and the delay D. SOURCE BUFFER Maximum number of retransmissions Round Trip Time Minimum capacity Required capacity in bps

  5. Resource Allocation (2/4) In order to evaluate the effect of segmentation on required capacity, the MAC must evaluate the size of required overhead on each MACPDU. Effective Capacity FEC size can be evaluated by taking into account the QoS parameter F. FEC Effective Payload MACPDUs

  6. Resource Allocation (3/4) Target packet loss probability on each MACPDU Given the required QoS, it depends on NRand on LEFF It depends on channel status, i.e. on the BER value pb Corrective capability on each MACPDU The value of kdetemines the FEC size We obtain a new LFEC which can affect the size of the effective payload LEFF We propose an iterative algorithm based on successive approximations. This algorithm is computationally efficient and returns the FEC size which is necessary on each MACPDU.

  7. Resource Allocation (4/4) Effective Capacity Required capacity in terms of the number of MACPDUs per frame which are necessary for the application. DF is the frame duration DNARQ is a corrective term due to the ARQ Transmission efficiency is maximized by selecting the NRvalue leading to the minimum number of MACPDUs per frame.

  8. 20 800 600 20 1 Number of MACPDUs per frame Number of MACPDUs per frame 10 400 Number of retransmissions Number of retransmissions 0 200 0 0 0 - - 3 3 - - 2 2 - - 1 1 - - 4 4 - - 3 3 - - 2 2 - - 1 1 10 10 10 10 10 10 10 10 10 10 10 10 10 10 BER BER Number of MACPDU per frame vs. BER (solid line) and optimum number of retransmissions (dotted line) for a typical real-time source. Number of MACPDU per frame vs. BER (solid line) and optimum number of retransmissions (dotted line) for a typical non-real-time source. Performance in static channels

  9. 100 percentage of packets delivered to destination 90 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 speed of the receiver [m/s] Percentage of source packets delivered to destination as a function of the receiver speed for a real-time source (circles) and a non-real-time source (crosses). Performance in slowly time-varying channels Performance of the proposed algorithm was verified in the case of a slowly time-varying channel. The Jakes channel model was used for characterizing multipath propagation in a generic indoor environment. Performance degradation is observed when the channel coherence time is comparable to the maximum end-to-end delay. In a scenario with high mobility, QoS cannot be guaranteed for real-time applications only.

  10. This work was supported by the European Union under Project No. IST-2000-25197 "Whyless.com - The Open Mobile Access Networks" Special thanks to all the people in the ACTS lab their contribution in both technical and not-technical issues. And finally… Acknowledgements …special thanks to John Silver for providing the PDF conversion of the poster.

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