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 Algorithms

Round 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 γ th 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 > γ th If no user CNR > CNR selected γ th  selected User with greatest  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.