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Jianwei Zhang, Huawei
Guard intervals for extra quiet period in TDD WRAN system
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Synchronous Quiet Period
a period in which all WRAN devices stop transmission in all
channels available in the system
used for sensing the signals in all channels of the system without
interfering the system itself
useful to enhance awareness to the surrounding radio
environment
Can the sensing accuracy be further enhanced?
Jianwei Zhang, Huawei
Guard Intervals
– When using OFDMA at the physical layer, guard intervals should be
inserted at the switching points of transmission
OFDM symbols of different users can be synchronized at BS.
– We can use these guard intervals as extra quiet periods for
sensing!
1
Related Work by I2R (Singapore)
All CPE should have a mandatory quiet period with fixed length at
the switching point from downlink (DL) to uplink (UL).
DL Subframe
Disadvantages
– Guard intervals from uplink to downlink have not been
utilized.
– Since a quiet period of fixed length is inserted to all CPEs
(regardless of their distances to base station), for the CPEs at
the edge of the cell in which guard intervals are usually not
required, the uplink transmission of these CPEs will be deferred
not effective
1
– TDD (time division duplex) deployment
– OFDMA (orthogonal frequency domain multiplexing access) is used
in both uplink and downlink
Main Features
Feature: Adaptive Guard Interval Control
Conventionally, CPE1 should wait for CPE2 during the uplink
transmission such that their first uplink symbols are synchronized
at BS.
We relax the above constraint:
* CPE2’s first UL symbol is synchronized with CPE1’s second UL
symbol
1
Advantages of Adaptive GI Control
For those CPEs being close to BS: they can start transmission in
advance
(1) Length of guard intervals from DL to UL can be shortened
(2) More OFDM symbols can be transmitted
For those CPEs being far away from BS
(1) Uplink transmission will no longer be deferred
(2) Number of transmitted OFDM symbols remains unchanged
If considering some practical limitations such as the hardware
limitation or the delay spread of the multi-path channel, a gap
should be guaranteed between the DL and UL sub-frame when operating
the adaptive GI control.
1
CPE3 (0<d<R)
Feature: Asynchronous Quiet Period
Guard intervals from UL to DL can also be used as extra quiet
period for
channel sensing.
Depending on the demand for sensing accuracy, some OFDM
symbols
can be replaced by the sensing period
– Flexibility is ensured
– BS notifies the assignment of such sensing periods to the CPEs
by
using the proposed Sensing Period Assignment (SPA) message.
1
CPE3 (0<d<R)
Connection ID
Start Time
Indicates the start time of the sensing period, in unit of OFDM
symbols
Duration
}
Adaptive Guard Interval Control
For CPEs being close to BS, more OFDM symbols can be
transmitted
Guard intervals from DL to UL can be shortened
For CPEs being far away from BS, their uplink transmission will no
longer be deferred
Performance Gain: Assume cell size is 33km and frame length is 5ms,
the round-trip delay is 0.22ms 4.4% of bandwidth can be used!
Asynchronous Quiet Period
Guard intervals from UL to DL can also be used for channel
sensing
Flexibility: some OFDM symbols can be replaced by sensing
period
Sensing Period Assignment (SPA) message: one kind of MAC management
message
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Background
The WRAN system needs to detect the presence of incumbent systems
and avoid the interference to the incumbent system
Detection of Incumbents
The subband needs to be vacated in the whole cell/sector
Lower spatial efficiency
Detect the locations of the incumbents
When the operation range of incumbent is small, the subband may be
used without interfering to the incumbent.
Higher spatial efficiency
Complexity grows exponentially with the number of targets
Many previous work requires: knowledge of number of targets,
knowledge of signatures, and detection of time of arrivals,
etc.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
For each region, decide whether some incumbents exist
Higher spatial efficiency
The number of targets need not be known a priori
Complexity does not exponentially grow with the number of
targets
Control overhead
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
and Cij = Cost of deciding Hi(), given Hj() is true
The decision rule of the Bayesian method is
where is a subset of PIT region iff i*() = 1.
Cost matrix example:
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
The Bayesian Method (3)
We assume the detection process of a sensor is modeled by Bernoulli
trials.
Each IT within its detection region is an i.i.d. trial.
The probability of detecting a particular IT is independent of its
position.
Flag di = 1, iff at least one IT is detected.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Compute Protection Region
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Detection radius = 10 grids (Grid space = 50m)
5km by 5km square region
y (grid point)
y (grid point)
CPE density (#CPE/km2)
CPE density (#CPE/km2)
Probability of miss
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
CPE density (#CPE/km2)
CPE density (#CPE/km2)
Probability of miss
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
PF,i = 0.1 (per CPE per subband)
Actual average number of IT per km2 = 0.16 IT/km2
Ratio of areas of PIT region
Expected number of IT per km2
Probability of miss
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Estimate of
Black curve
March 2006
Downlink System
Ideal antenna with 120-degree beam-width and front-to-back ratio
GFB of 13dB.
Uniform gain within main beam and constant attenuation of 13dB
outside.
Cell radius is 33km; path loss exponent in a cell, pl = 3.
10 circular clusters of CPEs, with radius of 3km, center uniformly
distributed
For every cluster, 100 CPEs are uniformly distributed within
it.
Pth = Maximum WRAN signal power allowed in the protection
region
PRmin = Minimum required receiving power of a CPE: Pth + 3dB
Drr = The radius of the receivable region
Dpro = The minimum distance between BS and protection region,
Dpro.
Region-based Algorithm: Transceivable Region
FDD
TDD
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
March 2006
Complexity Comparison
At a reasonable CPE density, the complexity of the region-based
algorithm is about 10 times of the union algorithm and its
complexity will converge to less than 14 times of the union
algorithm.
Complexity Ratio of Region-based to Union Algorithm
CPE density (#CPE/km2)
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
CPEs inside the receivable region can use the channel
Noticeable gain in the number of usable channels per cell
Compared with union algorithm:
Small increase in probability of miss
The tradeoff can be controlled by the cost matrix
Moderate Computation Complexity
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Proposal
Design of MAC Management Messages for channel sensing of the
CPE’s
Our proposed RF sensing algorithm suggests the following
information is sufficient for satisfactory performance in sensing
report of CPE’s
Incumbent type
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Jianwei Zhang, Huawei
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Flexible
Design Criteria: Reduce control overhead
Interval-basis Channel List
Incremental Measurement Report
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Part 1: Channel Sensing
Pilot design for channel estimation and interference detection in
WRAN system
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
The subcarrier spacing is about several KHz
To facilitate the interference detection
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
The subcarrier spacing is about several KHz
Subband-based OFDMA
March 2006
Interference Detection
Left graphs stands for the constellation of pilots on the same
subcarriers of different OFDM blocks
Right graphs stands for the constellation of corresponding received
signals
Interference symmetric structure of the constellation will be
destroyed
No matter the interference varies or not
No matter what constellation size used
Channel
Pk,i: Pilot on the k-th subcarrier of i-th OFDM block.
Pk,i = - Pk,i+1
Hypothesis test:
H0: |Yk,i + Yk,i+1|2 = |Pk,i*Hk + nk,i + Pk,i+1*Hk + nk,i+1|2
= |nk,i + nk,i+1|2
H1: |Yk,i + Yk,i+1|2 = |Pk,i*Hk + Ik,i + nk,i + Pk,i+1*Hk + Ik,i+1
+ nk,i+1|2
= |Ik,i + Ik,i+1 + nk,i + nk,i+1|2
P(|Yk,i+Yk,i+1|2 > threshold | H0) = Palarm
|Yk,i + Yk,i+1|2 given H0 χ2 distribution.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Simulation Model and Parameters
Interference generated in time domain more close to the real
situation
Interference on one subcarrier of different OFDM blocks
varies
False alarm probability is set to 0.01
Noise power is known a prior
AWGN
Filter
Remove
CP
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Interference detection
No matter the interference is varying or not
No matter the constellation size used
Performance only depends on interference to noise ratio
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Existence of Narrowband Interference in WRAN
Avoids Transmission in Interference Jammed Subcarriers
Transmitter may not know the existence of interference due to
bursty nature of interference
Receiver Detect Interference
Pilot based approaches
Data based approaches
Based on estimated data
Based on correlation of channel fading in frequency and time
domain
Existing Decoders Require Interference Knowledge
Performance determined by the accuracy of the interference
detection
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Require noise and interference statistics (position and
power)
Conventional Decoding
Ignore (erase) interference jammed symbols
Decoding metric is Euclidean distance (Optimal metric for
AWGN)
Undetected interference corrupts decoder because of metric
mismatch
all require interference detector
Joint Erasure Decoding
Given the number of erasures, search all possible codewords x with
all possible erasure positions e
Determine the number of erasures
Apply sufficiency criteria
Achievable performance
Maximum Likelihood decoding with the exact knowledge of the noise
and interference statistics
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Error Checking Code Based
Output the first candidate codeword that passes error checking and
terminate decoding
Path Metric Difference Based
Metric difference is decreasing
Metric difference is small after all interference are erased
If the metric difference is less than a threshold , then output the
candidate codeword & terminate decoding
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Demodulator marks symbol erasures
Erase the symbol if any of the corresponding bit is marked as an
erasure by decoder
Erase the symbol based on the channel output
detectable
Rate-½ 64-state convolutional code
16QAM with Gray mapping
Fixed SIR or number of jammed subcarriers
Sufficiency criterion: path metric difference based
Demodulator does not mark erasure based on channel output
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
The proposed decoder
(3) is insensitive to interference power
Simulations – Fixed SIR or Jams
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
SIR=0dB, SNR=20dB 5 Jams, SNR=20dB
Optimal threshold of the path metric difference based sufficiency
criterion is
almost independent of number of jammed subcarriers
almost independent of interference power
Threshold can be determined offline
Simulations – Fixed SIR or Jams
Jianwei Zhang, Huawei
Interference detection
Sufficiency criterion: path metric difference based
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Great gain over conventional decoder for BER and PER
Complexity increase by 1.5 times for PER=0.1 relative to
conventional
(2) With interference detector (blue)
Smaller gain for BER but significant gain for PER
Complexity increase by 15% for PER=0.1 relative to
conventional
(3) Proposed decoder performs similarly with or without
interference detector
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Random interference for each carrier with probability 0.04
SIR uniformly distributed in [-20dB,10dB]
2 OFDM pilot symbols for frequency domain LS channel
estimation
Each codeword is transmitted through 200 carriers and 10 OFDM
symbols
Each convolutional codeword is encoded by CRC
Demodulator marks erasures
CRC generator polynomial is 435(octal )
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
(1) Without channel estimation error (solid)
Joint erasure marking and decoding Performs closely to optimal
decoder
Complexity increase by 50% for WER=0.01 relative to conventional
decoder
(2) With channel estimation error (dashed)
Joint erasure marking and decoding is less sensitive to channel
estimation error than separate erasure marking and decoding using
demodulator only
Complexity increases by twice for WER=0.01 relative to conventional
decoder
Gain of joint over separate
(separate)
(joint)
(separate)
(joint)
The proposed decoding scheme almost achieves the optimal decoder
performance without knowing the interference statistics
Threshold of sufficiency criterion does not depend on interference
characteristics and can be determined offline
Complexity increase is reasonably small especially for high SNR or
with an interference detector
Performance loss due to channel estimation error is much smaller
than that of conventional decoding scheme
Therefore, it is robust and effective to combat unknown
interference in practical situations
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Part 2: Radio Resource Allocation
Effective and flexible structure for CPE CSIT collection at base
station for TDD/FDD OFDMA architecture
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Design good resource allocation algorithm to fully utilize the
resource
Radio resource is very scarce
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Using the reciprocity of the uplink and downlink channel
CSIT of the excited subchannels of those currently uplink-active
CPEs of TDD system
Using feedback
CSIT of the un-excited subchannels of those currently uplink-active
CPEs of a TDD system
CSIT of the currently uplink-inactive CPEs of TDD system
CSIT of all the CPEs of FDD system
Very important to design a good CSIT collection mechanism
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Features of Downlink WRAN System
BS knows the QoS requirements and queueing states of all the
CPEs
BS can determine which CPEs have higher priority and are more
urgent
Maximum Doppler frequency is very small
The CSIT can be updated rather infrequently
Variation of Doppler frequency among CPEs is limited
The CSIT update frequencies of CPEs are similar
Polling-based CSIT feedback mechanism
Centralized polling at the BS
BS decides which CPEs to poll based on QoS requirements, queueing
states, etc.
BS decides for each selected CPE which subband to estimate based on
power mask, history, etc.
BS decides for each selected CPE through which subchannels to
convey CSIT
Placement of the polling information
For currently active CPEs, the polling information is contained in
the UL-MAP
For currently inactive CPEs, the polling information is contained
in some broadcast channel
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
CSIT_Collection_Request for active CPEs (to be cont’d)
Syntax
for i = 1: N_DL_RCID {
UL_RCID_flag
1
0: no selected CPE is uplink-active-only 1: there are selected CPEs
that are uplink-active-only
If {UL_RCID_flag == 1}{
N_UL_RCID
8
N_UL_RCID is the number of selected uplink-active-only CPEs that
are in this subband
for i = 1: N_UL_RCID {
CSIT_Collection_Request for active CPEs (Cont’d)
CID_flag
1
If {CID_flag == 1}{
N_CID
8
N_CID is the number of selected CPEs that are switched to this
subband
for i = 1: N_CID {
Syntax
Remarks
Feedback_Control() {
Subband_change_flag
1
0: estimate the downlink CSI of this subband 1: in the next frame
estimate the downlink CSI of the subband specified by Subband
Index
If{Subband_ change_flag==1}{
}
Else{
Quantization_level_flag
1
0: use default quantization level, L=a 1: use specified
quantization level
If{ Quantization_level_flag ==1}{
}
Feedback_ch_constraint_flag
1
0: use default number of subchannels, N=c 1: use specified number
of subchannels
If{ Feedback_ch_constraint_flag==1}{
6
}
Feedback_symb_constraint_flag
1
0: use default number of OFDM symbols, M=e 1: use specified number
of OFDM symbols
If{Feedback_symb_constraint_flag==1}{
2
}
CSIT_Collection_Request for inactive CPEs (to be cont’d)
Syntax
for i = 1:N_CID{
Quantization_level_flag
1
0: use default quantization level, L=a 1: use specified
quantization level
If{ Quantization_level_flag ==1}{
}
Feedback_ch_constraint_flag
1
0: use default number of subchannels, N=c 1: use specified number
of sub-channels
If{ Feedback_ch_constraint_flag==1}{
6
}
CSIT_Collection_Request for inactive CPEs (Cont’d)
Feedback_symb_constraint_flag
1
0: use default number of OFDM symbols, M=e 1: use specified number
of OFDM symbols
If{Feedback_symb_constraint_flag==1}{
2
}
Overhead reduction
For currently active CPEs, 8-bit RCID is used instead of the 16-bit
CID to identify CPEs
Flexibility
Default constraint on the number of subchannels and the number of
OFDM symbols that a CPE should use to do feedback is known to both
the BS and the CPEs
BS has the option to allocate more or less subchannels and/or OFDM
symbols for each CPE to do feedback, depend on the QoS requirement
or the urgency of the downlink traffic
Default CSIT quantization level is known to both BS and CPEs
BS has the option to increase or decrease the quantization level to
adjust the precision of the feedback
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Main Features of Our Proposed Structure
CPEs decide which subchannel CSIT to feedback based on the channel
condition
Using predefined modulation and coding scheme, given the number of
subchannels, OFDM symbols that are used to convey CSIT, and the
CSIT quantization level, each CPE knows it can feedback the CSIT of
say c number of subchannels
For FDD system, the CPE should choose c number of subchannels with
the largest gains
For TDD system, the CPE should choose c number of un-excited
subchannels with the largest gains
CSIT_Feedback_Format
CSIT_Feedback_Format() {
Remarks
Downlink multiuser resource allocation algorithm for OFDMA-based
QoS-enabled WRAN system
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
(1) Interference Avoidance to Incumbent Users (IU)
– No cooperation possible between incumbent & WRAN
systems
Preventive measures should be chosen at the WRAN transmitter
– Unknown BS-IU channels & incompatible system structure
Isotropic transmission reduces the effective cell coverage
Transmit-side interference pre-cancellation is impossible
(2) Broad available spectrum for each cell: (~180MHz, 30 TV
channels)
– covered by multiple OFDM symbols instead of one
– max. one subband per each CPE
Simultaneous multi-band channel estimation is not possible
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Paper
[Wong99] C. Y. Wong, R. S. Cheng, K. B. Letaief, and R. Murch,
“Multiuser OFDM with adaptive subcarrier, bit and power
allocation,” IEEE Journal on Selected Areas of Communications, vol.
17, no. 10, pp. 1747-1758, Oct. 1999.
US Patent
[Li05] X. Li, H. Liu, K. Li, and W. Zhang, “OFDMA with Adaptive
Subcarrier-Cluster Configuration and Selective Loading,” US Patent,
US6947748 B2, Sep-20 2005.
US Patent Application
[Cho05] Y.-O. Cho, et al, “Method for Allocating Subchannels in an
OFDMA Mobile Communication System,” US Patent Application,
US2005/0180354 A1, Aug-18, 2005.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
– Peak power constraint, namely power mask, for every
subband.
– Sectored antenna adopted for reducing the performance sensitivity
to any nearby incumbent users (from a cell to only a sector).
for (2) Broad available spectrum for each cell: (~180MHz, 30 TV
channels)
– Two-layer resource allocation algorithm:
avoid over-congestion of subbands.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Layer-1 Allocation
Subband Assignment
Layer-2 Allocation
In-subband Subchannel, Power and Rate Allocation
Knowledge of transmit power mask on every subband in every
sector
Knowledge of channel gain of the assigned subband
Dynamic Frequency Selection Block
Intuition: Subband with smaller allowed maximum transmit power
should handle less CPEs
Step 1: For each sector, eliminate those unserviceable subbands,
defined as those subbands with the power mask value smaller than a
threshold.
Step 2: Define Pmm,b,c as the average power mask per subchannel of
subband b, i.e. the peak possible transmit power per subchannel, in
sector c. Let Kc be the total number of users in sector c. For each
sector c, the number of users allocated to subband b, represented
by Kb,c, is done according to the following equation:
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Layer-1: Subband Assignment
Step 2: (cont’d) where Nb is the number of serviceable subbands and
L is the number of sectors.
Both and should be non-decreasing functions of .
Example functions:
If the objective is to maximize the minimum average user data rate,
we can use:
(i)
where b can be set to the average channel power gain to noise
ratio.
(ii)
- (i) approximates the rate of each subchannel in subband b of
sector c.
- (ii) reflects the relative number of possible subchannel
allocation across different sectors for that subband b.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Layer-1: Subband Assignment
Step 3: Randomly select Kb,c users for subband b in sector c.
Remarks: Step 3 is indeed up to the vendors. e.g. Assignment can be
done based on user classes so that users of higher class may be
distributed to a subband with larger power mask.
Example: Advantages of exploiting one-dimensional (within sector)
and two-dimensional (across sector & subband) power mask
against equal user allocation.
Objective:
System Settings:
3 sectors, 2 subbands, 40 subchannels per subband, 60 users per
sector.
(i) 1-D (Single-sector) allocation
(ii) 2-D (Multi-sector) allocation
March 2006
Layer-1: Performance
Subchannel allocation and subchannel data rate for the Layer-1
algorithm example with 40 subchannels per subband:
Sector
March 2006
Layer-1: Performance
Effect of different user allocation algorithms on the subband data
rate per user with 60 users per sector: (Differences are
highlighted)
Sector
- realized in Sector 3:
min. average rate per user increases from 0 to 1.4287.
Advantage of 2-D allocation over its 1-D counterpart (also Equal
Allocation):
- realized in Sector 1:
min. average rate per user increases from 1.1713 to 2.0429.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
– Maximize subband throughput by subchannel (a group of
pre-selected subcarriers) and power allocation.
– Support differentiated-QoS service.
– Allow flexible tradeoff between max. throughput and fairness
among users.
Problem Formulation:
(i) individual subcarrier power gain is known.
(ii) average channel power gain is known,
– The proposed algorithm is optimal for case (i), and almost
optimal for case (ii) if every subchannel is within the coherence
bandwidth.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
priority control (lQoS_Class(k) 0)
Power mask
where
is a factor bridging the gap between ideal minimum power required
(using mutual information) and actual required transmission power
(using practical modulation schemes for a given rate)
is the noise power,
is the average channel power gain of subcarrier n(i) in subchannel
i, and
with
Proposed algorithm
- by relaxing to , the problem becomes convex and method of
Lagrangian can be applied to obtain the optimal solutions.
Algorithm Details:
Initialize .
Step 2: Select the optimal CPE for each subcarrier for a given
value of Ω
CPE k is selected ( ) for subcarrier i according to the following
criterion:
where
Layer-2: In-subband Allocation
with defined as
Step 3: Compute the optimal allocated power for each CPE for a
given value of
The optimal average power for user k on subchannel i is:
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
If ( ),
If ( ),
Else
End
Else
If ( ),
End
End
While ( ) for some predefined tolerance level ,
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
If ( ),
Elseif ( ),
End
End
and ,
where
so that on average the total power constraint is satisfied.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Layer-2: Channel Quantization
In our numerical results, the following simple channel quantization
algorithm is used:
Quantization lookup table construction:
Acquire the channel power gain distribution.
Identify the range of the channel power with a desirable
probability of occurrence, say 90%.
Equally partition the corresponding range in the logarithm
domain.
Set up the thresholds as the middle points of each interval in the
logarithm domain.
Transform the thresholds into their corresponding thresholds in the
original domain.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Layer-2: Rho Quantization
When time-sharing cannot be implemented, the following two
algorithms can be used:
Algorithm 1:
Step 1: Select the assignment profile closest to the Total Power
Constraint.
Step 2: Perform optimal power allocation for that assignment
set.
Algorithm 2: (shown good enough through numerical evaluation)
Select the assignment profile with the total power smaller than the
Total Power Constraint. In practice, perfect channel information
feedback may not be possible but limited number of bits is used
instead.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
March 2006
Layer-2: Performance
Sum rate comparison of (i) optimal SPA, (ii) random SA &
optimal PA and (iii)random SA & equal PA with effects of
channel quantization:
Legend:
Perfect
March 2006
Layer-2: Performance
Percentage loss of sum rate for the optimal subchannel and power
allocation due to channel quantization:
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
3-bit Channel Quantization is sufficiently good (~ 1% loss).
1-bit Channel Quantization is fairly good (~ 9% loss).
Random Subchannel Assignment with Optimal/Equal Power
Allocation:
Even 1-bit Channel Quantization gives apparently the same
performance.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Number of iterations required for convergence with 3-bit channel
quantization and power constraint accuracy of 99.999998%:
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
(Number of users)*(Number of subcarriers or subchannels2)
*(Number of iterations3)
(i) Number of operations1 required:
(Number of subcarriers or subchannels2)*(Number of
iterations3)
Random Subchannel Assignment with Equal Power Allocation:
Two steps: random subchannel assignment + peak power clipping
according to the Power Mask values.
Remarks:
1. includes mainly the calculation of power and rate.
2. when the same channel gain and power mask are used in a
subchannel.
3. fairly independent of the total number of users, of order
O(log(FFT Size)) assuming same #subchannels for all FFT
sizes.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
March 2006
Layer-2: Performance
Percentage of the occurrence of subchannel sharing with the
application of 3-bit channel quantization.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
March 2006
Layer-2: Performance
Percentage loss of sum rate among the cases of subchannel sharing
with sharing factor quantization for the optimal subchannel and
power allocation:
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
- Sharing rarely occurs (~2%).
- Actual loss due to rho-quantization in total data rate is
negligible
(~0.01% loss with rho-quantization Algorithm 2 among
scenarios
with time-sharing).
Conclusion
Developed a two-layer resource allocation algorithm for the
downlink IEEE 802.22 WRAN Systems, featuring
– interference avoidance to incumbent users
– user pre-distribution over subbands in a cell, avoiding
over-congestion of subbands in a way that subband with a larger
power mask (max. transmit power possible) should handle more
CPEs
– efficient in-subband subchannel and power allocation for:
(i) maximizing subband throughput at affordable complexity,
(ii) allowing QoS to be guaranteed,
(iii) allowing prioritized transmission and flexible tradeoff
between maximum throughput and fairness among users.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Part 2: Radio Resource Allocation
Joint dynamic frequency selection and power control with user
specific transmit power mask constraints in uplink WRAN system
using OFDMA scheme
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Principles of WARN systems
shares the VHF/UHF TV bands between 47MHz-910MHz which are being
used by the licensed operators and other license-exempt (LE)
devices.
a main constraint is to avoid interference to incumbent services
such as TV broadcasting (analog and digital) and Public Safety
systems.
Role of Dynamic Frequency Selection
performs multiple-access control to provide QoS-guaranteed services
required in the WRAN standard while not disturbing the service
quality of the licensed users.
involves user selection, rate adaptation as well as transmit power
control (TPC).
Jianwei Zhang, Huawei
Role of Dynamic Frequency Selection (Cont’)
The spectrum occupation information, called geographical spectrum
state information (GSSI), is obtained by data fusion and acts as
the input information for dynamic frequency selection (DFS).
– Usually full GSSI may not be easy to obtain.
– Instead of full GSSI, one possible form of partial GSSI is
transmit power masks imposed on all WRAN transmitters.
nb: Index of subbands
nc: Index of subchannels
March 2006
Related Works
· In patent US2005180354 “Method for allocating subchannels in an
OFDMA mobile communication system”, Cho et al. proposed resource
allocation algorithms to maximum the transmission rates of all
users by allocating subchannels and bits.
· The scheme introduced an adaptive modulation using linear
programming into an existing scheme for a system including a single
kind of users, thereby enabling simultaneous execution of the
adaptive modulation for all users in a system including two kinds
of users.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
March 2006
Related Works
· In paper “Multiuser OFDM with adaptive subcarrier, bit and power
allocation,” Wong et al. considered a subcarrier, bit and power
allocation problem in OFDM system.
· The objective is to the minimize the total transmitted power,
given the minimum data rate requirement of each user.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Drawbacks of the Related Work
For the patent US2005180354, the problem considered here is
actually a rate adaptive problem which maximizes a lower bound of
all users’ throughput with respect to a transmit power
budget.
Delay constraints and users’ priorities were not considered in this
invention.
It cannot be applied in WRAN systems since it does not employ any
technique to guarantee free interference to the incumbent
users.
Subband allocation among multiple OFDM symbols was not
investigated.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
In-subband Subchannel, Power and Rate Allocation
Knowledge of transmit power mask on every subband in every
sector
Knowledge of channel gain of the assigned subband
Dynamic Frequency Selection Block
Layer 1 (Subband Allocation)
Method 1: (Sum-Rate-Max Strategy)
Step 1: For each 6-MHz subband b, create a list of CPEs in
descending order of
their transmit power mask values. CPEs with power mask values
smaller than a
serviceable threshold predefined a priori are eliminated.
Step 2: Create a list of CPEs in descending order of their maximum
power
mask values across subbands. Define as the normalized power mask
per
subchannel of user k on subband b.
For k = to where ,
(i)
(ii) Remove CPE k from for all b’s except bk.
End
functions. For example,
where b can be set to the average channel gain to noise
ratio.
Step 3 (Optional): Perform subband re-assignment starting from the
CPE with the
minimum .
Layer 1 (Subband Allocation)
Method 2: (Round-Robin-Max Strategy)
Step 1: For each 6-MHz subband b, create a list of CPEs in
descending order
of the transmit power mask values. CPEs with power mask values
smaller than a
serviceable threshold predefined a priori are eliminated.
Step 2: Sort the subbands in descending order of their maximum
power mask.
Starting from index 1, i.e. the subband with the largest maximum
power mask,
each subband takes turn to pick up one CPE with the maximum
transmit power
mask. Any CPE selected in the previous subband will be subtracted
from the list of
the latter subbands. Repeat Step 2 until the lists of all the
subbands are empty.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
Subchannel Power Masks and the Approximated Subchannel Data
Rate
CPE
CPE Assignment and Corresponding Subchannel Data Rates
Sum-Rate-Max
Round-Robin-Max
CPE-Max
Subchannel Allocation and Corresponding Subchannel Data Rates
Sum-Rate-Max
Round-Robin-Max
CPE-Max
Objective
maximize the weighted system capacity given the QoS requirements
and power constraints
Problem Formulation
subject to
Proposed Algorithm (1)
Our proposed algorithm to solve Layer-2 problem is described a
follows:
Step 1: Initialize all the Lagrangian multipliers to be zeros and
set .
Step 2: Selection of temporarily optimal CPE for each subchannel
given the values of .
For every subchannel and every CPE, compute
where
Then for each subchannel, we select the CPE such that
and accordingly set
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
For each CPE in each subchannel, compute
Step 4: Examine whether the total power limitation for each CPE is
satisfied or not.
Given the temporarily optimal values of and .
If has been satisfied for each CPE, stop.
The optimal solutions have been obtained.
Else, go to Step 5.
Step 5: Adjust the values of to satisfy the total power
limitations.
Denote as the precision of the power allocation within a tolerance
error.
Jianwei Zhang, Huawei
doc.: IEEE 802.22-06/0050r0
While haven’t been satisfied for all the CPE’s,
Choose the CPE that exceeds the most the total power
limitation.
Set that the lower bound to be the current value and the upper
bound to
be , where
If ,
set ;
Elseif ,
set .
March 2006
Channel Quantization
· In practice, perfect channel information feedback may not be
possible but limited number of bits is used instead.
· A simple channel quantization algorithm is provided where the
index of a quantization table based on the estimated channel power
gain is used as the channel feedback.
Quantization lookup table construction:
Step 1: Acquire the channel power gain distribution.
Step 2: Identify the range of the channel power with a desirable
probability of
occurrence, say 90%.
Step 3: Equally partition the corresponding range in the logarithm
domain.
Step 4: Set up the thresholds as the middle points of each interval
in the
logarithm domain.
Step 5: Transform the thresholds into their corresponding
thresholds in the
original domain.
Linjun Lu Huawei Technologies Shenzhen, China 0086-755-28973119
[email protected]
Soo-Young Chang Huawei Technologies Davis, CA, U.S. 1-916 278 6568
[email protected]
Jianwei Zhang Huawei Technologies Shanghai, China 86-21-68644808
[email protected]
Lai Qian Huawei Technologies Shenzhen, China 86-755-28973118
[email protected]
Jianhuan Wen Huawei Technologies Shenzhen, China 86-755-28973121
[email protected]
Vincent K. N. Lau HKUST Hong Kong, China 852-2358-7066
[email protected]
Roger S. Cheng HKUST Hong Kong, China 852-2358-7072
[email protected]
Ross D. Murch HKUST Hong Kong, China 852-2358-7044
[email protected]
Wai Ho Mow HKUST Hong Kong, China 852-2358-7070
[email protected]
Khaled Ben Letaief HKUST Hong Kong, China 852-2358-7064
[email protected]
AWGN
Interference
Fading
Enc
IL
Mod
Dem
DIL
Dec
Edward K. S. Au HKUST Hong Kong, China 852-2358-7086
[email protected]
Peter W. C. Chan HKUST Hong Kong, China 852-2358-7086
[email protected]
Ernest S. Lo HKUST Hong Kong, China 852-2358-7086
[email protected]
Lingfan Weng HKUST Hong Kong, China 852-2358-7086
[email protected]
Zhou Wu Huawei Technologies Shenzhen, China 86-755-28979499
[email protected]
Jun Rong Huawei Technologies Shenzhen, China 86-755-28979499
[email protected]
Jian Jiao Huawei Technologies Beijing, China 86-10-82882751
[email protected]
Meiwei Jie Huawei Technologies Shenzhen, China 86-755-28972660
[email protected]
Syntax
Size
Notes
channel measurement request for
System Type
8 bits
measured. See Table 2. If this field is 0, the
CPE should sense all incumbent system
s
in
fra
me
1: Request full
(Carrier Interference
channel of each incumbent type
.
measure
should
measure
Number of Channels
8 bits
incumbent system.
(units in
e incumbent
incumbent system.
8 bits
current incumbent system.
measurement (units in
0
10
20
30
40
50
60
70
80
90
100
0
10
20
30
40
50
60
70
80
90
100
0
2
4
6
8
10
12
14
16
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
2
lambda used in the algorithm (#estimated IT/km
2
q
Î
100
200
300
400
500
600
700
800
900
1000
-100
-90
-80
-70
-60
-50
-40
-30
-20
-10
0
k
th
subcarrier
10
|H|
01002003004005006007008009001000
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
A cluster
CPE Transceivable Region
Blue star: IT