doc.: ieee 802.22-06/0048r0 submission may 2006 slide 1jianwei zhang, huawei channel sensing and...

PowerPoint PresentationChannel Sensing and Radio Resourse Allocation Algorithms for WRAN Systems
IEEE P802.22 Wireless RANs Date: 2006-03-29
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Jianwei Zhang, Huawei
PART I: CHANNEL SENSING
1. Guard intervals for extra quiet period in TDD WRAN system
2. Region-based Bayesian method for RF sensing in WRAN system
3. The MAC management message for channel sensing
4. Pilot design for channel estimation and interference detection in WRAN system
PART II: RADIO RESOURCE ALLOCATION
1. Effective and flexible structure for CPE CSIT collection at base station for TDD/FDD OFDMA architecture
2. Downlink multiuser resource allocation algorithm for OFDMA-based QoS-enabled WRAN system
3. Joint dynamic frequency selection and power control with user specific transmit power mask constraints in uplink WRAN system using OFDMA scheme
INTRODUCTION
In this contribution, some algorithms on channel sensing and radio resource allocation are suggested.
These algorithms were briefly introduced during Mar. 2006 meeting in IEEE802-06/0030r3. However detailed description on these algorithms was requested from the floor of the working group because of lack of information on them in that document. Therefore this contribution is submitted with the corresponding MS Word format contribution.
This contribution consists of two parts:
Part I: Channel Sensing
Part II: Radio Resource Allocation
The first part has four algorithms and the second has three algorithms as shown in the next slide.
PART I: CHANNEL SENSING
3. The MAC management message for channel sensing
4. Pilot design for channel estimation and interference detection
in WRAN system
May 2006
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?
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 (1)
All CPE should have a mandatory quiet period with fixed length at the switching point from downlink (DL) to uplink (UL).
DL Subframe
To be improved
– 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 can be improved
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
ADANTAGES 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)
OUR PROPOSED DESIGN (2)
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
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.
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
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:
THE BAYSIAN 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.
Compute Protection Region
Detection radius = 10 grids (Grid space = 50m)
5km by 5km square region
y (grid point)
y (grid point)
PF,i = 0.01 (per CPE per subband)
Ratio of areas of PIT region
CPE density (#CPE/km2)
Probability of miss
Probability of miss
Actual average number of IT per km2 = 0.16 IT/km2
Expected number of IT per km2
Probability of miss
Estimate of
Black curve
May 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 (1)
y (km)
x (km)
FDD
TDD
May 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
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
May 2006
PROPOSED DESIGN
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
Flexible
Design Criteria: Reduce control overhead
Interval-basis Channel List
Incremental Measurement Report
May 2006
4. Pilot design for channel estimation and interference detection in WRAN system
The subcarrier spacing is about several KHz
To facilitate the interference detection
The subcarrier spacing is about several KHz
Subband-based OFDMA
May 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 ith 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.
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
Interference detection
No matter the interference is varying or not
No matter the constellation size used
Performance only depends on interference to noise ratio
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
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
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
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
The proposed decoder
(3) is insensitive to interference power
SIMULATIONS – FIXED SIR OR JAMS (2)
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 (3)
864 subcarriers
Interference detection
Sufficiency criterion: path metric difference based
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
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 )
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
PART II: RADIO RESOURCE ALLOCATION
2. Downlink multiuser resource allocation algorithm for OFDMA-based QoS-enabled WRAN system
May 2006
Design good resource allocation algorithm to fully utilize the resource
Radio resource is very scarce
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
* CSIT: channel state information at transmitter
Very important to design a good CSIT collection mechanism
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
MAIN FEATURES OF PROPOSED STRUCTURE
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
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
FEATURES OF OUR PROPOSED STRUCTURE (2)
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
(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
– 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.
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:
LAYER-1: SUBBAND ASSIGNMENT (2)
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 .
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.
LAYER-1: SUBBAND ASSIGNMENT (3)
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

LAYER-1: PERFORMANCE (2)
Subchannel allocation and subchannel data rate for the Layer-1 algorithm example with 40 subchannels per subband:
Sector
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.
– 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.
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
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:
If ( ),
If ( ),
Else
End
Else
If ( ),
End
End
While ( ) for some predefined tolerance level ,
If ( ),
Elseif ( ),
End
End
and ,
where
so that on average the total power constraint is satisfied.
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.
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.
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
Percentage loss of sum rate for the optimal subchannel and power allocation due to channel quantization:
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.
Number of iterations required for convergence with 3-bit channel quantization and power constraint accuracy of 99.999998%:
(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.
Percentage of the occurrence of subchannel sharing with the application of 3-bit channel quantization.
Percentage loss of sum rate among the cases of subchannel sharing with sharing factor quantization for the optimal subchannel and power allocation:
- 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.
May 2006
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).
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
RELATED WORKS (1)
· 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.
RELATED WORKS (2)
· 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.
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.
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
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
(Cont’)
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
minimum .
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.
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
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.
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 .
May 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.
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.
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
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
Ross D. Murch
Wai Ho Mow
Khaled Ben Letaief
pro
pl
R
th
rr
D
P
P
D
1
min
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
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
Ross D. Murch
Wai Ho Mow
Khaled Ben Letaief

doc.: ieee 802.22-06/0048r0 submission may 2006 slide 1jianwei zhang, huawei channel sensing and...

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