Radio Resource Allocation for Multi-radio Coexistence
IEEE 802.16 Presentation Submission Template (Rev. 9)
Document Number:
IEEE C802.16m-08/882r1
Date Submitted:
2008-09-05
Source:
Feng Seng Chu
National Taiwan University
E-mail: b8901009@ee.ntu.edu.tw
Kwang Cheng Chen
National Taiwan University
E-mail: chenkc@cc.ee.ntu.edu.tw
Neeli Prasad
Aalborg University
E-mail: np@es.aau.dk
Ramjee Prasad
Aalborg University
E-mail: prasad@kom.aau.dk
Kanchei (Ken) Loa
Institute for Information Industry
E-mail: loa@iii.org.tw
Venue:
IEEE 802.16 Interim, Session #57, Kobe, Japan
PHY aspects of Multi-Radio Coexistence; in response to the TGm Call for Contributions and Comments 802.16m-08/033 for Session 57
Purpose:
Propose radio resource allocation as collaborative and non-collaborative coexistence mechanism.
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Outline
• Multi-radio Coexistence
• Classification of Multi-radio Coexistence
– Collaborative/Non- collaborative
– Collocation/Non- collocation
•
•
•
•
Proposed Solution
Realization based 16m SDD
Example Algorithms in Function Block
Proposed Text
Multi-radio Coexistence
• In 802.16m SRD, Section “Co-deployment
with other networks” [1]
– It is anticipated that IEEE 802.16m is to be
deployed in the same (on a co-channel and nonco-channel basis) or adjacent RF bands as non
IEEE 802.16m legacy networks.
– The 802.16m standard shall provide a method
to avoid generate or suffer interference to/from
other coexisting systems.
Classification of Multi-radio
Coexistence
• Collaborative/Non-collaborative [2]
– There is information exchange among coexisting
systems.
• Collocation/Non-collocation [2]
– When two devices’ antennas are positioned less
than 0.5 meters apart.
• In this contribution we focus on
– 1. Non-collaborative non-collocation coexistence.
– 2. Collaborative non-collocation coexistence.
Proposed Solution
• 16m and non 16m systems may be deployed in
the same licensed band [section 9.3, 1], however,
interference among systems should be avoid.
• 16m shall enable the advanced RRM for efficient
utilization of radio resources [section 6.4, 1].
• Radio resource management/allocation (RRM
and RRA) can satisfy both requirements.
– Avoid interference among systems.
– Significant capacity improvement to achieve reliable
communications by efficient resource utilization.
Non-collaborative Non-collocation
Coexistence
• General operations
Feedback CSI of available sub-carriers
Spectrum Sensing
BS
MS
1. Identify available subcarriers.
RRA
Optimal allocation
or
Low-complexity
2. Estimate CSI of
available subcarriers.
Data Traffic
3. Predict available subcarriers
and their CSI in next frame.
16m Protocol Structure
Processing Flow
Radio Resource
Management
System Configuration
Management
Multi-Carrier
RRCM
MAC
Scheduling and
Resource Multiplexing
PHY Control - interference and CQI measurement
Control Signaling
Key Operations
• PHY control – interference and CQI measurement
– Identify available subcarriers.
– Estimate CSI of available subcarriers.
– Predict available subcarriers in next frame.
– Predict CSI of next frame available subcarriers.
• Radio resource management, Scheduling and
Resource Multiplexing
– Properly allocating system resource among user to
maximize system capacity while avoiding interference
Example Algorithm to
Identification of Subcarrier Status
• Generalized Likelihood Ratio test
Pp H1
  p is received power.
l p 
 , 
Pp H 0   H1 and H 0 represent availabili ty.
Other Example Algorithms in PHY
• To estimate CSI of available subcarriers
– Least-square or LMMSE [3]
• To predict available subcarriers in next frame
– Based on HMM [4]
• To predict CSI
– Linear prediction [5]
Properly Allocating System Resource
c c
c c
User 1
c c
User 2
User 3
:un-available subcarrier
:available subcarrier
After collecting above information of all user by
PHY control function block, do RRM and SRM.
Example Algorithm for
Radio resource allocation
Power allocated to subcarrier k in time slot t
T  max
ωu ,t,k,p t,k
U
T
K
 ω
u 1 t 1 k 1
u,t,k
log 2 1  pt,k CNR
Channel to noise ratio
Subcarrier allocation index for user u, time slot t
and subcarrier k
Subject to
i  Total Power Constraint (ii) Non - negative Constraint
iii  Availabili
ty Constraint
iv  Fairness Constraint
Such a multi-variable non-linear optimization is hard to be
Solved, low-complexity algorithm may be preferred.
Another Choice:
Low-complexity Algorithm
• We can divide the optimal allocation into
– 1. time-frequency subcarrier allocation.
– 2.Power allocation.
Uniformly distribute power
T  max
ωu,t,k,p t,k
U
T
K
 ω
u,t,k
u 1 t 1 k 1
log 2 1  pt,k CNR 
Allocate subcarriers
Allocate power among subcarriers
T  max
ωu,t,k,p t,k
U
T
K
 ω
u 1 t 1 k 1
u,t,k
log 2 1  pt,k CNR 
By subcarriers allocation resulted in prior step.
Numerical Result (1)
System Capacity
14
Optimal
Low Complexity Algorithm, Step 1
Low Complexity Algorithm, Step 2
Low Complexity Algorithm, Step 3
Normalized Capacity
12
10
8
6
4
2
0
0
5
10
15
20
OSNR (dB)
25
30
35
40
Numerical Result (2)
System Capacity
16
Low Complexity Algorithm, Step 1
OFDM based FDMA
OFDMA-Subcarrier-Interleaved
14
Normalized Capacity
12
10
8
6
4
2
0
0
5
10
15
20
OSNR (dB)
25
30
35
40
Numerical Result (3)
System Capacity With/Without Fairness Normalization, (OSNR,P 11) = (20 dB,0.8)
9
8
Normalized Capacity
7
6
5
4
3
Low Complexity Step 1, Without Fairness Normalization
FDMA,
Without Fairness Normalization
Interleaved,
Without Fairness Normalization
Low Complexity Step 1, With Fairness Normalization
FDMA,
With Fairness Normalization
Interleaved,
With Fairness Normalization
2
1
0
0
0.1
0.2
0.3
0.4
0.5
Probability (P 00)
0.6
0.7
0.8
0.9
Collaborative Non-collocation
Coexistence
• Since there are information exchange among
coexisting systems, we can consider a more
aggressive scheme
– Cross-Three-Layer Radio Resource Allocation by
including frequency allocation among cells.
• Inter-BS coordination function are included.
Processing Flow based on 16m SDD
Inter-BS coordination
Radio Resource
Management
System Configuration
Management
Multi-Carrier
RRCM
MAC
Scheduling and
Resource Multiplexing
PHY Control - CQI measurement
Control Signaling
Resource Management/Allocation
If we represent the total network capacity as CT ,
total capacity of each cell as Ci , and total capacity
of each system is Ci .
The maximizati on of network capacity by dynamic allocating
spectrum among cells can be formulated as
N
N
i
CT  max  Ci  max  Ci
Bi
i 1
Spectrum allocated to cell i
Bi
i 1  1
N : Number of cells.
X i : Numer of coexisting systems in cell i.
Resource Management/Allocation
• Furthermore, with different assumptions the
resulted capacity of each systems are different.
• For example, if we assume MIMO-OFDMA
systems, the system capacity can be
Depend on decoding scheme and channel assumption
1
Ci 
TNT K i

U i
T
N T K i  Bi Δf


u 1 t 1
1
i ,
i , ,u ,t
i ,



log
1

SNR
p
 u ,t , ,k
 ,k
t , , k 
k 1
U i : Number of users in system.
u : user index
NT : Numer of Tx antenna in system .  : Antenna index
Numerical Result
Network Capacity
Normalized Network Capacity
15
Cross-Three-Layer
Cross-Two-Layer
Fixed Resource Allocation
10
5
0
0
5
10
15
20
SNR (dB)
25
30
35
40
Note
• Resource should be allocated to users
according to resource allocation unit defined
in SDD [6].
• The proposed RRA algorithm can be slight
modified to fit 16m system PHY configuration.
Contributions
• We propose RRA as critical mechanism for
multi-radio coexistence.
• Both non-collaborative / collaborative noncollocation scenario were considered.
• Processing flow based on 16m SDD.
• Example algorithms for each function block.
Proposed Text
• 17.x Solutions for Co-deployment and Co-existence
– For avoiding interference to/from coexisting systems,
flexibly adjusting system usage spectrum is a critical
characteristic of coexistence mechanism. Furthermore, to
achieve reliable communication under such scenario,
efficiently utilizing system resource is also essential. Radio
resource management/allocation is a well-known
approach satisfying both the two requirements. By
properly integrating the capability of existing function
blocks in 16m
protocol structure, the proposed
mechanism can be realized effectively.
•
17.x.1 RRA for Non-Collaborative Non-collocation Multi-Radio Coexistence
– Since there is no information exchange among coexisting systems for this scenario, the
function block “PHY Control - interference measurement” is required.
– There should be at least two step in this function, (i) identify each subcarrier status of
each user. (ii) Predict each subcarrier status in next frame of each user.
– For resource allocation, the function block “PHY Control – CQI measurement/feedback”
is required.
– According to RRA algorithm adopted, the required CSI or CQI should be estimated and
predicted in this function block.
– Both the two function blocks “Radio resource management” and “Scheduling and
resource multiplexing” are required to properly avoid interference and optimize system
performance by information mentioned above.
– In order to dynamic adjust system spectrum, both the “Multi-carrier” and “system
configuration management” function blocks are required.
•
17.x.2 RRA for Collaborative Non-collocation Multi-Radio Coexistence
– Since there is information exchange among coexisting systems for this scenario,
interference measurement is not necessary and we can further improve system
performance by integrating frequency allocation among cells into resource allocation to
formulate an aggressive Cross-Three-Layer scheme.
– To realize this idea, inter-BS function block should be considered.
Reference
[1] “Project 802.16m System Requirements Document (SRD),” August, 2008.
http://www.wirelessman.org/tgm/docs/80216m-07_002r5.pdf.
[2] IEEE 802.15.2/D09, March 2003, http://myurl.com.tw/6gus.
[3] Morelli M, Mengali U, “A comparison of pilot-aided channel estimation
methods for OFDM systems,” Signal Processing, IEEE Transactions on,
Volume 49, Issue 12, page(s): 3065-3073.
[4] Akbar, I.A.; Tranter, W.H., “Dynamic spectrum allocation in cognitive
radio using hidden Markov models: Poisson distributed case,”
SoutheastCon, IEEE, March 2007 Page(s):196 – 201.
[5] Akhtman J., Hanzo L., “Channel Impulse Response Tap Prediction for
Time-Varying Wireless Channels,” IEEE Trans. on Vehicular Technology,
Vol. 56, Issue 5, Part 1, 2007 Page(s):2767 – 2769.
[6] “Draft IEEE 802.16m System Description Document ,” July, 2008,
http://wirelessman.org/tgm/docs/80216m-08_003r4.zip