Uplink Open Loop Power Control Recommendations for IEEE 802.16m Amendment
IEEE 802.16 Presentation Submission Template (Rev. 9)
Document Number: IEEE S802.16m-09/0703
Date Submitted:
2009-03-07
Source:
Rongzhen Yang, Ali T. Koc, Papathanassiou Apostolos, Wei Guan,
Hujun Yin, Nageen Himayat, Yang-seok Choi, Shilpa Talwar
Intel Corporation
E-mail: [email protected]
[email protected]
Venue:.
Re: IEEE 802.16m-09/0012, “Call for Contributions on Project 802.16m Amendment Working Document (AWD) Content”.
Target topic: “Power Control”
Base Contribution: IEEE C802.16m-09_0546
Purpose:
To discuss and adopt the proposed text of IEEE C802.16m-09_0546 in the next revision of the 802.16m Amendment.
Notice:
This document does not represent the agreed views of the IEEE 802.16 Working Group or any of its subgroups. It represents only the views of the participants listed in
the “Source(s)” field above. It is offered as a basis for discussion. It is not binding on the contributor(s), who reserve(s) the right to add, amend or withdraw material
contained herein.
Release:
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Uplink Power Control Review
IEEE 802.16m system requirements from SRD
•
•
Average User Throughput
Cell edge Throughput
IEEE 802.16m description at SDD:
• Open Loop Power Control (OLPC)
–
–
•
Closed Loop Power Control (CLPC)
–
–
•
Tradeoff between overall system throughput and cell edge performance
Interference controlled by the information broadcasted from ABS
Fast power control
Limit the overhead of the signaling
Coupling of CLPC and OLPC
–
Provides high efficiency with reduced signaling overhead
Interference Control for uplink MIMO
Maximum Sector Throughput Method
SINR Target Method:


SINRMIN
1 
 
SINROpt  10 log 10 max 10^ (
),   SIRDL 
10
Nr  


( Detail derivation shown in backup)
SINRMIN:
is the SINR requirement for the minimum rate expected by ABS, is set by
the power control message.
 :
is the fairness and IoT control factor, decided by ABS.
Nr :
is the number of receive antennas at ABS.
SIRDL:
is the ratio of downlink signal vs. interference power at one AMS receive
antenna, measured by AMS
Multi-Modes OLPC for Legacy and
Enhancement Support
Tx Power calculation for per Tx-antenna per subcarrier:
P( dBm )  L  SINRT arg et  NI  Offset _ AMS perAMS  Offset _ ABS perAMS
•
SINRT arg et is
the target uplink SINR using different methods:
– Mode 1 (Legacy Mode) & Mode 2 (Enhanced Mode):
 C / N  10 log 10( R),
SINRt arg et  
SINROPT ,
mod e 1
mod e 2
• Mode selection, control factors and system information are
indicated at power control message
Uplink SLS Evaluation for Enhanced Mode
Gamma value
Sector throughput (in Mbps)
Cell-edge throughput (in
Kbps)
Sector SE
Cell-Edge SE
0.2
1.3865
104
0.8146
0.0611
0.4
1.5655
95.6
0.9198
0.0562
0.6
1.7056
77.2
1.002
0.0454
0.8
1.7895
58.8
1.0514
0.0345
1.0
1.8619
41.2
1.0939
0.0242
CDF of Throughput
CDF of User Throughput, Enhanced mode
1
0.95
0.9
0.85
0.8
0.75
0.7
0.65
0.6
0.55
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0
• 6 uplink data symbols (one
subframe) per frame
• 25% control overhead is
assumed for SE calculation
• Detailed settings in appendix
gamma=0.2
gamma=0.4
gamma=0.6
gamma=0.8
gamma=1.0
500
Throughput(kbps)
Performance Curve and IoT Control
Performance curve
CDF of Sector IoT, Enhanced mode
0.065
1
0.06
0.9
0.055
0.8
0.7
CDF of IoT
Cell-edge SE
0.05
0.045
0.04
0.035
0.5
0.4
0.3
0.03
gamma=0.2
gamma=0.4
gamma=0.6
gamma=0.8
gamma=1.0
0.2
0.025
0.02
0.8
0.6
0.1
0.85
0.9
0.95
Sector SE
1
1.05
1.1
0
0
5
10
15
20
IoT(dB)
• IoT (Interference) can be stably controlled by gamma value
• Tradeoff between overall system throughput and cell edge performance can
be decided by gamma value
25
Recommendations
• Legacy OLPC is extended to multi-modes to
support both optimum power setting method
and legacy method
• Proposed enhancement method is selected to
support:
– Interference Control
– Tradeoff between overall system throughput and
cell edge performance
Appendix
• Parameters for UL SLS Evaluation
• Full Tx power performance comparison
• Maximum Sector Throughput Method
Derivation
SLS Simulation settings
Parameter
Value
Parameter
Value
Carrier frequency (GHz)
2.5 GHz
Site to site distance (m)
500m
System bandwidth (MHz)
10 MHz
Channel
eITU-Ped B, 3km/h
Reuse factor
1
Max power in MS (dBm)
23dBm
Frame duration
(Preamble+DL+UL)
5ms
Antenna Config
1x2 SIMO
Number of OFDM
symbols in UL Frame
6
HARQ
On (Max retrans: 4/Sync)
FFT size (tone)
1024
Target PER
0.2
Useful tone
864
Link to system mapping
RBIR
Number of LRU
48
Scheduler type
PF
LRU type
CRU
Resource Assignment
Block
4 LRU
Number of users
per sector
10
Penetration loss (dB)
20dB
CMIMO support
no
Control Overhead
25%
Algorithm Simulation Settings
Parameter

Value
(0.2, 0.4, 0.6, 0.8, 1.0)
 N CLHome 


 i 1 CL

Neighbor
,
i


SIRDL Simulation
SINRMIN
Notes:
SIRDL  PDL,H / PDL, I
1
0dB
 N CLHome 


 i 1 CL

Neighbor,i 

1
- PDL,H  PT / CLHome is the received signal power of downlink preamble, CLHome
is the channel loss to the home cell. (only slow fading is considered)
N
- PDL,Neighbor   PT / CLNeighbor,i is the downlink received interference signal power
i 1
from N (N=8) strongest neighbor cells. CLNeighbor,i is the channel loss to the ith
neighbor cell. (only slow fading is considered)
Full Tx Power Comparison
Gamma value
Sector throughput (in Mbps)
Cell-edge throughput (in
Kbps)
Sector SE
Cell-Edge SE
0.2
1.39
108.9024
0.8166
0.064
0.4
1.5915
97.9968
0.935
0.0576
0.6
1.7364
84.1728
1.0202
0.0495
0.8
1.8034
66.048
1.0595
0.0388
1.0
1.8669
49.6128
1.0968
0.0291
Full Power
0.943
6.144
0.554
0.0036
CDF of User Throughput
CDF of Sector IoT
1
1
0.95
0.9
0.9
0.85
0.8
0.8
0.75
0.7
0.6
CDF of IoT
CDF of Throughput
0.7
0.65
0.55
0.5
0.45
0.6
0.5
0.4
0.4
0.35
0.3
gamma=0.2
0.25
gamma=0.4
0.2
gamma=0.6
0.15
gamma=0.8
0.1
gamma=1
0.05
Full power
gamma=0.2
0.3
gamma=0.4
gamma=0.6
0.2
gamma=0.8
gamma=1
0.1
Full power
0
0
0
500
0
10
20
30
40
50
IoT(dB)
Throughput(kbps)
All settings are same except the power control schemes
60
70
80
90
Maximum Sector Throughput Method Derivation (1)
Initial Modeling
For one MS:
• Channel Loss: the channel loss (include pathloss and fading) form MS to strong BSs
can be measured by preamble signal strength, top N: CL0, CL1, CL2, .. CLN, CL0 is
the channel loss to home sector.
• NI (Noise plus Interference): Home and neighbor sectors information are modeled as
(NI0, NI1, NI2, …, NIN)
When one MS increases Tx PSD, it will bring SE gain and cause SE loss to neighbor
sectors (SU-SISO):
SEgain  log( 1  SINRNew )  log( 1  SINROrig )
SEloss (i )  log( 1  SINR(i )Orig )  log( 1  SINR(i ) New )
1  SINRNew
 log(
)
1  SINROrig
Si
1  SINR(i )Orig
NIi
 log(
)  log(
)
Si
1  SINR(i ) New
1
NIi  I i
SINROrig 
1
PSD0 / CL0
, PSDNew  PSD0  PSD
NI0
PSD
CL0
SE gain  log( 1 
)
PSD0
NI0 
CL0
 log( 1 
I i
I i
)  log( 1 
)
NIi
Si  NIi
Then, total SE loss is:
N
SEloss   SEloss (i )
i 1
In theory, the Maximum Sector Throughput will be got when
SE gain  SEloss, PSD  0
I i 
P
CLi
Maximum Sector Throughput Method Derivation (2)
Simplification Assumptions
• One virtual neighbor sector: the channel loss to all neighbor sectors are
difficult to be accurately measured in real environment, we assume one
virtual neighbor sector that accounts for accumulated downlink
interferences
PDL,I
P
P
 T ,Pr eamble   T ,Pr eamble
CLI
CLi
i 1~ N
SIRDL 
PDL,H
PDL,I

1 

CLI   
CL
 i 1~ N i 
SIRDL 
1
CLI
CLH
Then, we can get the Maximum Sector Throughput derivation for SU-SISO system:
SINRT arg et 
NI I 
1
 1 
NI H  SINRI

  SIRDL  1

SINRT arg et    SIRDL  1
Gamma is used as the control factor to control the interference to other sectors
Maximum Sector Throughput Method Derivation (3)
SU-MIMO Consideration
Nr receive antenna for ABS:
 1  SINRNew, MRC 
SEGain  log 

 1  SINR
Orig , MRC 

N r  ( PSDtx  PSDtx ) 

N r  PSDtx

1


CLH  NI H , Ant
CLH
  log 1 
 log 
N r  PSDtx
N  PSDtx



1
NI H , Ant  r



CLH  NI H , Ant
CLH



I
SE  SEGain  SE Loss

 1  SINR
I
SELoss
 log 
 1  SINR I
New , MRC

I
Orig , MRC






N  SNRI , Ant  PNoise , Ant

1 r


NI I , Ant
  log 

N r  SNRI , Ant  PNoise , Ant

 1 
NI I , Ant  PSDtx / CLI



PSDtx


CL

NI
N

SNR

P
I
I , Ant
r
I , Ant
Noise , Ant 
 log  1 

N r  SNRI , Ant  PNoise , Ant  NI I , Ant  PSDtx / CLI  
 1 

NI I , Ant  PSDtx / CLI


PSDtx, Ant
N r * PSDtx, Ant
CLI * NI I , Ant
N r * SNRI , Ant * PNoise, Ant
CLH
 0( PSDtx, Ant  0) 

N r * PSDtx, Ant
N r * SNRI , Ant * PNoise, Ant NI I , Ant  PSDtx, Ant / CLI
NI H , Ant 
1
CLH
NI I , Ant  PSDtx, Ant / CLI
SINRI , Ant
N * PSDtx, Ant
NI I , Ant
1
CLH / CLI
CL

 NI H , Ant  r
 1  N r * SINRI , Ant  * I *
N r * PSDtx, Ant 1  N r * SINRI , Ant NI I , Ant
CLH
CLH SINRI , Ant
NI H , Ant 
CLH

 CL
NI I , Ant
CL
 PSDtx, Ant  1  N r * SINRI , Ant * I *
 NI H , Ant  * H
CLH SINRI , Ant

 Nr
 CL * NI I , Ant * 1  N r * SINRI , Ant 

* I
 NI H , Ant * CLH 
SINRI , Ant


 PSDtx, Ant 
1
Nr
 SINRH , Ant 
PSDtx, Ant
1

CLH * NI H , Ant N r

 CL * NI I , Ant * 1  N r * SINRI , Ant  
* I
 1
SINRI , Ant * CLH * NI H , Ant



NI I , Ant 
1
1
 * SIRDL 
* 1 

NI H , Ant 
N r * SINRI , Ant 
Nr
SINRT arg et    SIRDL 






1
Nr
Gamma is used as control factor to control the interference to other sectors
Maximum Sector Throughput Method Derivation (4)
MU-MIMO Consideration
Four study cases for consideration:
• Home sector SU and virtual neighbor sector SU
(already done for SU-MIMO)
• Home sector MU and virtual neighbor sector SU
• Home sector SU and virtual neighbor sector MU
• Home sector MU and virtual neighbor sector MU
Maximum Sector Throughput Method Derivation (5)
Home sector MU and virtual neighbor sector SU
 1  SINRNew ,MRC 
 1  SINRNew ,MRC 
  log 

SEGain  2 * log 
 1  SINR

 1  SINR

Orig, MRC 
Orig, MRC 


N r * PSDtx, Ant


CLH
 log 1 
N * PSDtx, Ant

NI H , Ant  r

CLH

2
N * PSDtx, Ant


2* r


CLH
  log 1 
N * PSDtx, Ant


NI H , Ant  r


CLH


2
I
SELoss






N * SNRI , Ant * PNoise, Ant 

 1 r

I
 1  SINROrig

NI I , Ant
, MRC



 log 

log
I



N
*
SNR
*
P
1

SINR
r
I , Ant
Noise, Ant
New , MRC 

1

NI I , Ant  2 * PSDtx, Ant / CLI 

2 * PSDtx, Ant


CLI * NI I , Ant
N r * SNRI , Ant * PNoise, Ant
 log 1 

N r * SNRI , Ant * PNoise, Ant
NI I , Ant  2 * PSDtx, Ant / CLI
 1
NI I , Ant  2 * PSDtx, Ant / CLI

I
SE  SEGain  SE Loss
 0( PSDtx, Ant  0)
2 * PSDtx, Ant
N r * PSDtx, Ant
CLI * NI I , Ant
N r * SNRI , Ant * PNoise, Ant
CLH


N * PSDtx, Ant
N r * SNRI , Ant * PNoise, Ant
NI I , Ant  2 * PSDtx, Ant / CLI
NI H , Ant  r
1
CLH
NI I , Ant  2 * PSDtx, Ant / CLI
2*

SINRI , Ant
1
CLH / CLI

N * PSDtx, Ant 1  N r * SINRI , Ant NI I , Ant
NI H , Ant  r
CLH

 CL
NI I , Ant
CL
 PSDtx, Ant  1  N r * SINRI , Ant  * I *
 NI H , Ant  * H
CLH SINRI , Ant

 Nr
 SINRH , Ant 

NI I , Ant 
1
1
 * SIRDL 
* 1 

NI H , Ant 
N r * SINRI , Ant 
Nr






Maximum Sector Throughput Method Derivation (6)
Home sector SU and virtual neighbor sector MU
 1  SINRNew ,MRC 
 1  SINRNew ,MRC 
  log 

SEGain  log 
 1  SINR

 1  SINR

Orig, MRC 
Orig, MRC 


N r * PSDtx, Ant




CLH


 log 1 
N r * PSDtx, Ant 

NI H , Ant 


CLH


I
SELoss
PSDtx, Ant


I
 1  SINROrig,MRC 
CLI * NI I , Ant
N r * SNRI , Ant * PNoise, Ant
  log 1 
 2 * log 
I


N
*
SNR
*
P
NI I , Ant  PSDtx, Ant / CLI
r
I , Ant
Noise, Ant
 1  SINRNew ,MRC 
 1
NI


PSD
/
CL
I , Ant
tx, Ant
I

PSDtx, Ant


2*


CLI * NI I , Ant
N r * SNRI , Ant * PNoise, Ant 

 log 1 

N r * SNRI , Ant * PNoise, Ant NI I , Ant  PSDtx, Ant / CLI 
 1

NI I , Ant  PSDtx, Ant / CLI


I
SE  SEGain  SELoss
 0( PSDtx, Ant  0)
PSDtx, Ant
N r * PSDtx, Ant
2*
CLI * NI I , Ant
N r * SNRI , Ant * PNoise, Ant
CLH


N * PSDtx, Ant
N * SNRI , Ant * PNoise, Ant NI I , Ant  PSDtx, Ant / CLI
NI H , Ant  r
1 r
CLH
NI I , Ant  PSDtx, Ant / CLI

1
CLH / CLI / 2  SINRI , Ant

N * PSDtx, Ant 1  N r * SINRI , Ant NI I , Ant
NI H , Ant  r
CLH
Define CLI  CLI / 2 , then
* 1  N * SINR 
1  CL * NI
PSD

*
 NI
tx , Ant
Nr


I
I , Ant
r
SINRI , Ant
I , Ant
H , Ant

* CLH 

 1 CL * NI I , Ant * 1  N r * SINRI , Ant 

* * I
 NI H , Ant * CLH 
SINRI , Ant
2

 PSDtx, Ant 
1
Nr
 SINRH , Ant 

1 NI I , Ant 
1
1
 * SIRDL 
*
* 1 
2 NI H , Ant 
N r * SINRI , Ant 
Nr






2
Maximum Sector Throughput Method Derivation (7)
Home sector MU and virtual neighbor sector MU
 1  SINRNew ,MRC 
 1  SINRNew ,MRC 
  log 

SEGain  2 * log 
 1  SINR

 1  SINR

Orig, MRC 
Orig, MRC 


N r * PSDtx, Ant


CLH
 log 1 
N * PSDtx, Ant

NI H , Ant  r

CLH

2
N * PSDtx, Ant


2* r


CLH
  log 1 
N r * PSDtx, Ant


NI H , Ant 


CLH


2
I
SELoss






PSDtx, Ant

2*

I
 1  SINROrig

CL
N r * SNRI , Ant * PNoise, Ant
, MRC
I * NI I , Ant
  log 1 
 2 * log 
I


N
*
SNR
*
P
NI I , Ant  2 * PSDtx, Ant / CLI
r
I , Ant
Noise, Ant
 1  SINRNew ,MRC 
 1
NI I , Ant  2 * PSDtx, Ant / CLI

PSDtx


4*


CL
*
NI
N
*
SNR
*
P
I
I , Ant
r
I , Ant
Noise, Ant

 log 1 

N r * SNRI , Ant * PNoise, Ant NI I , Ant  2 * PSDtx, Ant / CLI 
 1

NI I , Ant  2 * PSDtx / CLI


I
SE  SEGain  SELoss
 0( PSDtx, Ant  0)
4 * PSDtx, Ant
N r * PSDtx, Ant
CLI * NI I , Ant
N r * SNRI , Ant * PNoise, Ant
CLH


N * PSDtx, Ant
N r * SNRI , Ant * PNoise, Ant
NI I , Ant  2 * PSDtx, Ant / CLI
NI H , Ant  r
1
CLH
NI I , Ant  2 * PSDtx, Ant / CLI
2*

1
CLH / CLI / 2  SINRI , Ant

N * PSDtx, Ant 1  N r * SINRI , Ant NI I , Ant
NI H , Ant  r
CLH
Define CLI  CLI / 2 , then
PSDtx, Ant 
1
Nr
 CL * NI I , Ant * 1  N r * SINRI , Ant 

* I
 NI H , Ant * CLH 
SINRI , Ant


 1 CL * NI I , Ant * 1  N r * SINRI , Ant 

* * I
 NI H , Ant * CLH 
SINRI , Ant
2

 PSDtx, Ant 
1
Nr
 SINRH , Ant 

1 NI I , Ant 
1
1
 * SIRDL 
*
* 1 

2 NI H , Ant 
N r * SINRI , Ant 
Nr






2
Maximum Sector Throughput Method Derivation (8)
MU-MIMO Study Summary
Virtual neighbor Sector SU: SINRH , Ant 

NI I , Ant 
1
1
 * SIRDL 
* 1 
NI H , Ant 
N r * SINRI , Ant 
Nr

NI I , Ant 
1
1
 * SIRDL 
* 1 
2 NI H , Ant 
N r * SINRI , Ant 
Nr
Virtual neighbor Sector MU: SINRH , Ant  1 *
Conclusions:
• For MU-MIMO, same power control formula can be applied
SINRT arg et    SIRDL 
1
Nr
• When AMS, MS perform MU/SU switching, the Tx power
should not be changed
• The gamma is used to control interference, if neighbor sectors
have higher percentage of MU selection, the gamma value can
be decreased to reduce interference