Scheduling and Optimization

Criteria and Algorithms for Scheduling of Packet

Data over Wireless Channels

Nilo Casimiro Ericsson, Signals & Systems, Uppsala University

Outline

Introduction, backgroundScheduling for spectral efficiency

Latest scheduling insightsNo need for complex optimization

Provide an average throughputAdaptive criteria – simulation results

Conclusion

Packet data over fading channels

Avoid fading dips!

Scheduling of OFDM bins

time

freq

user

4

53

2

1Perform scheduling

based on predicted average SNR in time-frequency bins

For each bin let the

“best” user transmit; use adaptive modulation and ARQ

What the scheduler does:

Scheduling algorithms

• Simple “linear” maximization– Best First– Maximum Allocation– Robin Hood

• “Exact” buffer-matching– Controlled Steepest Descent– Exhaustive search

Complexity (25 bins)

one-step

one-step + swap

two-step

But, is the criterion right at all?

• Buffer content minimimization at each scheduling instant seems short-sighted– Search algorithms allocate resources to

match buffer content as exactly as possible

• Sum-of-squares criteria• Uncertain predictions…

– ”Academic” interest, off course

• Instead: Maintain a (constant?) average (over time) throughput for each active stream– Based on maximized “linear” criteria– If necessary: re-allocations from over-

provisioned streams

Traffic adaptive criteria

• Previously in Robin Hood (Coarse adaptivity)– Three features compared in some order:

• Modulation, Priority, SNR

– If two have equal Modulation => compare Priority, etc…

– Can change order to (adaptation to traffic situation)Priority, Modulation, SNR

• New: Quantize features into (e.g.)Modulation 3 bits m1,m2,m3Priority 2 bits p1,p2SNR 2 bits s1,s2 (explain!)

– The new feature: m1,m2,m3,p1,p2,s1,s2• But also: m1,p1,p2,m2,m3,s1,s2

Adaptive criteria example

User 1:M = 6 (64QAM),

mmm = 1102

P = 1 (medium low), pp = 012

A) mmmpp = 110012 = 2510

B) mppmm = 101012

= 1910

User 2:M = 5 (32QAM),

mmm = 1012

P = 2 (medium high),pp = 102

A) mmmpp = 101102 = 2210

B) mppmm = 110012

= 2510

3 bits for Modulation (0-7)2 bits for Priority (0-3)0 bits for SNR (omitted)

>

<

A) mmmppB) mppmm

Simulation of scheduler

• 25 OFDM bins per schedule– 5 MHz carrier @ 1900 MHz– Time-frequency bin size: 0.667 ms x 200 kHz– 108 payload symbols per bin

• 12 users• 8 modulation levels (3 bits)

– 0-7 (“quiet”-128QAM)– SNR thresholds: [ 6.5 10 14 18 22.5 26 30 ]

dB– (why not 1-8?)

• 4 priority levels (2 bits)– 0-3

• Random SNR for each user and bin• 100 schedule simulations per criteria setup

Simulation 1:

12 users, 4 priorities: 3 users of each prioritySame SNR distribution for all: N(10,10)Maximum modulation: 7 (128QAM)

Criteria:mmppm

Criteria:mmmpp

Criteria:mppmm

Criteria:ppmmm

Criteria:mmpmp

Criteria:mpmpm

Criteria:pmpmm

Criteria:mpmmp

Criteria:pmmpm

Criteria:pmmmp

(A) (B)

Thr

ough

put p

er u

ser

Tot

al th

roug

hput

Simulation 2:

12 users, 4 priorities: 3 users of each priority4 different SNR distributions: N({15,12,9,6},5)Highest priority for worst SNR

Criteria:mmppm

Criteria:mmmpp

Criteria:mppmm

Criteria:ppmmm

Criteria:mmpmp

Criteria:mpmpm

Criteria:pmpmm

Criteria:mpmmp

Criteria:pmmpm

Criteria:pmmmp

(A) (B)

Thr

ough

put p

er u

ser

Tot

al th

roug

hput

Conclusion

• For practical scheduler: abandon complex search algorithms– Too many uncertainties (channel prediction,

buffer usage)

• Scheduling can handle also distant users with worse conditions than near users– Work with “priorities”– Upgrade the importance of “priority”

• Probably, average throughput target will also help distant users– Over-provisioned near users will give

resources to under-provisioned distant users

Simulation 3:

12 users, 4 priorities: 3 users of each priority3 different SNR distributions: N({5,10,15},5)Maximum modulation: 7 (128QAM)

Criteria:mmppm

Criteria:mmmpp

Criteria:mppmm

Criteria:ppmmm

Criteria:mmpmp

Criteria:mpmpm

Criteria:pmpmm

Criteria:mpmmp

Criteria:pmmpm

Criteria:pmmmp

(A) (B)

Thr

ough

put p

er u

ser

Tot

al th

roug

hput