opportunistic scheduling in wireless networks mohammed eltayeb obaid khattak
TRANSCRIPT
Opportunistic Scheduling in Wireless Networks
Mohammed Eltayeb
Obaid Khattak
Project Outline This report gives an overview of different scheduling
algorithms, from the simple round robin algorithm, to opportunistic scheduling algorithms considering QoS, with simulation of system capacity feedback load and fairness.
We divided the algorithms into fair, semi-fair and greedy algorithms.
All simulations are done with Matlab 7.0 with an average SNR of 15dB and 1000 Ts for 30 users.
Back Ground Theory
A scheduling system is implemented both in the mobile station (MS) and in the base station (BS).
The BS uses a TDMA scheme and during one time slot, only one user can receive or transmit, and this user is selected by the scheduler.
Fair AlgorithmsRound Robin
• The RR scheduler is the simplest scheduling algorithm, and it is not opportunistic. • When a user connects to the base station (BS), it is given a position in the queue of users, and the scheduler will iterate through the queue.
Fair Algorithms - RR
Fair Algorithms - RR
Fair Algorithms
Opportunistic Round Robin (ORR)
• The ORR algorithm is a Round Robin scheduler.• Channel conditions are taken into account.• The scheduler iterates the list of users, and every time the best user is selected and removed from the list.
Fair Algorithm - ORR
Fair Algorithm - ORR
SEMI-FAIR SCHEDULING ALGORITHMS
EXAMPLES AND PERFORMANCE
Semi-Fairness
Middle ground between Fair & Greedy Provide Fairness in terms of scheduling
outage Feedback load not zero but not rate optimal
either
Example: Switched Diversity Scheduling (SDS)
SDS
Family of algorithms based on multi-antenna systems schemes
Specific Threshold γth is set Scans users to find CNR > γth If user found, selected At each time slot, sequence may be randomized or
organized in special way Examples
Selection Combining Transmission (SCT) SET with Post-Selection (SETps)
SCT
Checks ALL users, selects user with highest CNR
Fair if all users are i.i.d Advantage
Only form of SDS which is rate optimal Disadvantage
Normalized feedback load (NFL) unity
MASSE Performance of SCT
Throughput Fairness in SCT
SETps
Extension of Switch-and-Examine Transmission (SET)
First scanned user with CNR > γth selected
If no user CNR > γth User with greatest CNR selected Combats scheduling outage
At each time slot, list randomized Provides level of fairness
MASSE of SETps
Throughput Fairness of SETps
Time-slot Fairness of SETps
NFL of SETps
GREEDY SCHEDULING ALGORITHMS
EXAMPLES AND PERFORMANCE
Greedy Algorithms
More concerned with maximizing system throughput, not fairness to individual users
Do provide fairness when all users have i.i.d. channel conditions
Rate optimal, MASSE values equal Examples
Maximum CNR Scheduling (MCS) Optimal Rate, Reduced Feedback (ORRF)
MCS
All users report their CNR to BS
User with best channel selected Rate optimal
Large overhead in reporting CNR values Normalized feedback load (NFL) unity
Poor throughput and time-slot fairness Same as SCT
MASSE of optimal schedulers
Optimal Rate, Reduced Feedback (ORRF) Scheduler decides threshold CNR
Distributed to all users Users with CNR > Threshold reply Best user selected If no user replies
Scheduler requests full feedback Every user returns CSI (Channel State Information)
After full feedback or without it, best user selected
NFL of ORRF
Time-slot Fairness of ORRF
Throughput Fairness
MASSE-based Comparison
NFL-based Comparison
References
[1] P. Viswanath, D. N. C. Tse, and R. Laroia, _Opportunistic beamforming using dumb antennas,_ IEEE Trans. Inform. Theory, vol. 48, pp. 1277_ 1294, June 2002. [2] A. J. Goldsmith and P. P. Varaiya, _Capacity of fading channels with channel side information,_ IEEE Trans. Inform. Theory, vol. IT-43, pp. 1896_ 1992, Nov. 1997. [3] D. Gesbert and M.-S. Alouini, _How much feedback is multi-user diversity really worth?,_ in IEEE Int. Conf. on Communications (ICC'04), (Paris, France), pp. 234_238, June 2004. [4] V. Hassel, M.-S. Alouini, G. E. Øien, and D. Gesbert, _Rate-optimal multiuser scheduling with reduced feedback load and analysis of delay effects._ Submitted to IEEE Int. Conf. on Comm. (ICC'05), (Seoul, South Korea), May 2005. [5] M. Johansson, _Issues in multiuser diversity._ http://www.signal.uu.se/Research/PCCWIP/Visbyrefs/Johansson_Visby04.pdf. Presentation at WIP/BEATS/CUBAN workshop Wisby, Sweden, Aug. 2004. [6] R. Knopp and P. A. Humblet, _Information capacity and power control in single cell multiuser communications,_ in IEEE Int. Conf. on Communications (ICC'95), (Seattle, WA), pp. 331_335, June 1995. [7] B. Holter, M.-S. Alouini, G. E. Øien, and H.-C. Yang, _Multiuser switched diversity transmission._ Accepted for IEEE Veh. Tech. Conf. (VTC'04- spring), (Los Angeles, CA), Sept. 2004.