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 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

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 selected If no user CNR > γ th  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

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