False Positive Detection

Assignment AMAP False Detection Analysis
Document Number: IEEE S802.16m-10/0314
Date Submitted: 2010-3-5
Source:
Yi Hsuan
Hujun Yin
[email protected]
Intel Corporation
Re:
Venue:
Category: AWD-Comments / Area: Chapter 16.3.6 (DL physical structure)
“Comments on AWD 16.3.6 DL physical structure”
IEEE Session#66, Orlando
Purpose: Discussion and Adoption by TGm
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1
Assignment AMAP Design Decisions in TGm
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Various AMAPs are separately coded for different users.
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MLRU is the minimum resource unit for assignment AMAP. MLRU is
formed from distributed LRUs in the time first manner.
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Two MCS levels can be used for assignment AMAPs in an AMAP
region. The two MCS levels can be either QPSK (½, ¼), or
QPSK(½, 1/8), depending on configuration.
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¼ TBCC is used to code assignment AMAP
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Non-user specific information indicates the number of assignment
AMAP in an assignment AMAP group.
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CRC in Assignment AMAP IE is masked by station ID.
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Blind detection using station ID is needed.
False Positive Detection
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False positive detection happens when CRC check passes by mistake for a
detection trial. This is caused by certain decoding errors such that error bits
in the AMAP IE and CRC are aligned to allow CRC check to pass. Such
decoding errors can be caused by
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•
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Channel impairment or RF impairment. This factor cannot be avoided in any
blind detection scheme.
Rate matching or repetition mismatch. While present in LTE, this cause of false
positive is eliminated in the current structure using only 1 AMAP IE size.
Because encoded assignment AMAP is not scrambled with any user
specific sequence, each MS can decode assignment AMAP for other MS if
the channel is ideal. However CRC check would fail because it’s scrambled
by STID. With this in mind, false detection is less likely to happen for MS
with good geometry and more likely to happens for cell edge users.
AMAP false positive detection can interrupt both DL an UL traffic, especially
for UL persistent scheduling. LTE has many contributions on the analysis of
the false activation frequency of semi-persistent scheduling (SPS).
A-A-MAP Decoding Errors
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•
•
•
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From SINR distribution of EMD baseline cell, 50% of users can receive
QPSK ½ correctly.
Assume the rest of the users can receive QPSK 1/8 correctly.
50% of users with good geometry can decode all A-A-MAPs correctly so
there is no false detection for those users.
The rest of the users can decode A-A-MAPs of QPSK 1/8 correctly but fails
to decode A-A-MAPs of QPSK ½ correctly.
Assume half of the A-A-MAPs use QPSK ½ and the other half uses QPSK
1/8.
Given 32 A-A-MAPs per subframe, on average there is 8 decoding errors
per users.
False Positive Probability
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Assume the worst case scenarios in terms of false detection:
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20 MHz bandwidth TDD (4:4).
Fully loaded VoIP traffic.
32 A-A-MAPs and detection trials
8 A-A-MAP decoding errors per MS on average
Suppose an MS tries to decode all A-A-MAPs in each DL subframe, a false
positive detection can happen every 216/(8*4*200)=10.24 seconds.
Because there are 16 A-A-MAP IE types and each type has equal
probability of false detection, false detection duration of a UL IE (UL basic
and UL persistent IEs) is 10.24 * 8 = 81.92 seconds.
False Detection Impact
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When A-A-MAP false detection generates a false DL A-MAP IE, MS would
try to decode a false DL burst and send a Nack in UL at a arbitrary HARQ
feedback channel.
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If the UL HARQ feedback channel is used by another MS, the worst case is that the Nack
transmission wipes out an Ack transmission of the other MS. This makes BS performs a
redundant retransmission. The system impact of this effect is small.
When A-A-MAP false detection generates a false UL A-MAP IE, MS can
transmit an invalid data burst which can collide with other UL transmission.
The collision can cause a failure of an HARQ process.
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Further analysis is needed to see how much impact the false detection can affect the failure
rate of the system HARQ process. The failure rate of HARQ process is designed to be
between 10-3 to 10-4.
UL HARQ Failure Rate Due to False Detection (1)
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The following scenario is used to analyze the impact of false detection on
UL HARQ processes.
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20 MHz 4:4 TDD
Full VoIP capacity traffic
32 A-A-MAPs and detection trials per DL subframe
From the evaluation results submitted to IMT-Advanced, 16m VoIP capacity
is about 80 users/effective MHz per link. In the considered scenario, it
means 800 active VoIP users in the system.
Given 800 VoIP users, one UL IE false detection can happen once every
81.92/800 = 102.4ms.
Given 800 VoIP users, there are 400 UL HARQ processes in 20 ms (one
VoIP packet every 20 ms per user and 50% VoIP activity factor) or 2000 UL
HARQ processes in 100 ms.
UL HARQ Failure Rate Due to False Detection (2)
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Assume that a false UL A-A-MAP detection causes
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A invalid UL data burst transmission. Subsequent transmission due to synchronous HARQ
and persistent scheduling is stopped due to detection of invalid DL HARQ feedback.
Collision with another one UL burst (a little optimistic)
HARQ process associated the collided UL burst fails due to the collision (a little pessimistic)
The HARQ process failure rate due to UL A-A-MAP false detection is
therefore 1/2000 = 5∙10-4.
With the target failure rate of HARQ to be between 10-3 to 10-4, the HARQ
failure rate caused by UL A-A-MAP false detection should be reduced.
UL A-A-MAP IE Reserved Bits
IE Type
IE parameters
Reserved bits
with 4 Tx ant.
Reserved bits
with 2 Tx ant.
UL Basic IE
SU-PMI=0,
CSM=0,
MEF=0
6
7
SU-PMI=0,
CSM=0,
MEF=1
5
6
SU-PMI=0,
CSM=1
2
3
SU-PMI=1
2
5
TNS=Mt (SUMIMO)
3
3
TNS >Mt (MUMIMO)
2
2
UL Persistent IE
A-A-MAP IE Sanity Check Based on Reserved
Bits
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As shown in the previous slide, UL A-A-MAPs have different numbers of
reserved bits depending on the IE type and some parameters in the IE.
MS should perform IE sanity check after A-A-MAPs are successfully
decoded. If the decoded A-A-MAP is from a false detection, MS may detect
invalid reserved bit value and identify false detection.
Given n reserved bits, sanity check can reduce false detection probability by
1/2n if A-A-MAP IE randomization is applied.
A-A-MAP IE Sanity Check Based on Resource
Allocation
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When false detection happens, the resource allocation may be invalid such
as allocation overlapping with UL control region and allocation occupying
different types of resources.
For VoIP based traffic, MS expects small resource allocation. For example,
a 12.2 kbps VoIP burst contains no more than 40 bytes.
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Given the burst size signaling design in 16m, the burst size index (IB) is the sum of allocation
size index (IA), defined as the product of LRU number and rank, and five bit MCS (IMCS) in
assignment AMAP, i.e., IB=IA+IMCS.
For no more than 40 bytes burst sizes, IB is from 1 to 16. Therefore IA can be from 1 to 16 as
well. For each given IA, IMCS can be from 0 to 16-IA. The total number of valid combination of
burst allocation size, MCS, and rank is (16+1)*16/2=136.
There are 8+5+2=15 bits in UL persistent scheduling IE used for resource allocation, MCS,
and rank respectively.
By sanity check, MS can reduce the probability of false detection by a factor of
136/215=0.00415.
Sleep Mode
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•
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Implementation of power saving modes like sleep or idle modes effectively
reduces the need to decode assignment AMAP constantly and therefore
reduces the probability of false detection as well.
For VoIP traffic, there is one packet every 20ms. MS only needs to wake up
one subframe every 4 frames to decode assignment AMAP for allocation or
de-allocation of persistent scheduling.
The probability of false detection can therefore be reduced by a factor of
1/16.