Research on Threshold Adjustment Algorithm in Adaptive Modulation and Coding

THE JOURNAL OF CHINA UNIVERSITIES OF POSTS AND TELECOMMUNICATIONS Vol.13, No.2, Jun.2006

Research on Threshold Adjustment Algorithm in Adaptive Modulation and Coding FAN Chen,

CHEN Mei-ya,

SU Li-jun,

YANG Da-cheng

Sch(pl of Telecommunication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, P. R. China

Abstract: Adaptive Modulation and Coding (AMC) has gained u lot of attentions in the research of High Sped Downlink Packet Access (HSDPA) . The idea is to adapt the trunsmissivn to the fast changing channel conditions by the use o j d i f frrent Modulation and W i n g Schemes (MCS) . This paper presents an adaptive AMC algorithm und introduces u thwretical analysis model in order to to investigate its throughput and Frame Error Rate (FER) . Subject to the given FER turget, our numerical and link level simulation results both show that our algorithm outperforms other existing adapt& algorifhms . Key words: u d u p t i u mcdulation und cvding; threshold &just ; markov model ; HSDPA CLC number: TN929.5 Document code: A Article ID: 1005-8885(2006)02-0015-05

level simulation results in Refs. [ 3 - 51 show that the “thresholds” based MCS selection methods can trace the 1 Introduction variation of wireless channel. In this paper, we develAMC is one of the key techniques in HSDPA“]. oped a theoretical analysis model to analyze the FER AMC has been of interest as an efficient way to increase performance of TA algorithm and points out T A algothe throughput of 3G wireless communication systems. rithm can’t guarantee its FER target. Based on the The core idea of AMC is to dynamically change the threshold adjustment method of TA algorithm, we proMCS in subsequent frames with the objective of maxi- pose an Improved Threshold Adjustment ( ITA) algomizing the spectral efficiency of wireless transmission rithm, which can guarantee the FER of each MCS unwhile maintains a proper QoS requirement. der any channel conditions. Markov model and link level Some theoretical analyses on MCS selection with and simulation were used to investigate the FER perforwithout Hybrid Automatic Request (HARQ) have been mance of ITA and TA. Numerical and link Ievel simulapresented in Refs. [ 11 - 151. These theoretical analyses tion results both show that subjected to a given FER can deduce various sets of fixed MCS thresholds accord- target, ITA can guarantee the FER more accurately ing to various channel conditions. Since the actual wire- than TA. The outline of this paper can be seen as follows: The less channel is time varying, fixed MCS thresholds can’t trace the variation of channel and can’t guarantee the threshold adjustment algorithm and our improved algoQoS requirement of data transmission. An analysis of rithm are described in Section 2. A theoretical analysis multicode .AMC with fixed thresholds are presented in model for MCS thresholds optimization is given in Section 3, some analytical characterization of TA and ITA Ref. [ 101. In order to adaptively estimate the optimal “thresh- are also presented in Section 3 . Numerical and link level olds” to achieve the FER target, Refs. [ 3 - 5 1 propose simulation results are given in Section 4 followed by some kind of Threshold Adjustment ( T A ) algorithms, conclusion in Section 5 . which use a threshold adjustment method similar to the outer loop power control scheme that is already adopted 2 Threshold Based Adjustment Algoin R99. An independent threshold adjustment algorithm rithms was proposed in Refs. [ 4 - 51, Which adjust the up and The T A algorithms proposed in Refs. [ 3 - 5 1 are low thresholds of one MCS simultaneously. Some improved algorithms of the independent threshold adjust- somewhat similar to the outer loop power control ment algorithm are presented in Refs. [7 - 91. The link scheme that is already adopted in R99. There are two

Received date: 2005-06-28 Foundation item: The work in this paper is sponmred by QUALCOMM Inc.

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2006

T A methods proposed in Refs. [ 3 - 51, which adjust the can't guarantee its target FER. So we proposed an ITA threshold values based on the feedback Acknolwledge- algorithm, which can guarantee the target FER accument/ Non- Acknowledgement ( ACK/NACK ) informa- rately. ITA adds one additional threshold under the tion. As ACK/NACK is closely related with channel lowest MCS, that is to say there are K thresholds to be conditions, the thresholds based method can keep track adjusted for K levels of MCS. The threshold adjustment of the varying radio channels. In the thresholds based scheme the MCS switching levels are adapted to maintain a target frame error rate (PNACK). The algorithm increases the MCS switching level by AU, when a NACK is received and decreases it by ADnwnwhen an ACK is received. A suitable value is selected for AU, and ADownis then calculated so that the expected threshold adjustment is 0 when the target P N A C K is achieved, i . e.

process can be desrrihe as fellows: If kth MCS level is chosen, only the threshold of T ( k ) will be lowered if ACK is received while only T ( K - 1 ) will be increased receiving upon NACK signal.

3

The Theoretical Analysis Model

3 . 1 Frame Error Rate Analysis Model A theoretical analysis model is developed in this paper to calculate the thresholds and to study the FER and

throughput performance of thresholds mapping algorithm. The PDF of SNR is, fSNR( x ), F F E R , ( I) is the 2 . 1 Threshold Adjustment Algorithm function of FER versus SNR for ith MCS. Let r , deIf a system allows K levels of MCS, there are K - 1 notes the probability that MCS, is chose, and p , denotes thresholds to be adjusted. One might adjust all thresh- the average FER for MCS, , we get: olds by correcting only a reference threshold while fixing the gaps between the remaining thresholdsL3]. In order to improve the adaptability of TA, Refs. [ 4 - 51 investiT, f SNR ( FFERt ( ) d3. gate an independent adjustment for each threshold as

I

P,=

y.,-l

J:

(2) follows: IfSNR(x)dx If k th MCS level is chosen, the threshold of T ( k + 1) and T ( k ) will be lowered if ACK is received while Here [ T , - 1 , T , ] is the mapping thresholds for only T ( k ) will be increased receiving upon NACK sigMCS, , and To = - 03, T , = + 03 are supposed, R FER nal. is FER. Fig. 1 is the threshold adjustment process of T A . Through the above equation we can get the total FER When the received Common Pilot Channel ( CPICH ) and throughput for the threshold-based algorithm, falls into the range between T ( 3 ) and T ( 2 ) , MCS 2 is selected as the transmission MCS. When the feedback is which can be presented as: 7-1 NACK, only T ( 2 ) increase AU,. While the feedback F = r , P , = To fsNR(;Z.)FFER1(S)dz+ r=l is ACK, T ( 2 ) and T (3) both decrease. Only when MCS 3 is selected and the feedback is NACK, does (3) .-'+ fsNR(x)FFm,v(x)dX T(3) increase AU,. T,, -I

2

s"

j

L Time Fig. 1 An illustration of T A algorithm

2.2

Improved Threshold Adjustment Algorithm

Using the theoretical analysis model, which is described in Section 3, we found that independent T A

(4) 3.2

Frame Error Rate Analysis of TA and ITA

If the stable state of TA and ITA is achieved, the expected threshold adjustment is O L 4 ] . The stable state can be achieved, when the ratio of ADnwnand AU, at each

FAN Chen, et u l . : Research on Threshold Adjustment Algorithm in Adaptive Modulation and Coding

No. 2

MCS equals the predefined target

PNACK

. Here

1- PNACK

is the target FER. In TA algorithm, the probability of increasing T , is the NACK probability of MCS,, which can be represented as ( r,pI), and the probability of decreasing T I is the ACK probability sum of MCS, and MCS, - 1, which equals r , ( 1 - p , ) + r , ( 1 - p , ) . So an alternative equation of the threshold variance in stable state is AU,r,p, = AD,,,[ r, (1 - p , ) + r , - 1 ( 1 - p , - 1 ) 1. All K - 1 threshold adjustment in stable state can be represented as: PNAcK

-

17

Eqs. ( 2 ) - ( 8 ) can be used to investigate the FER and throughput of TA and ITA algorithm. We use a first order finite state Markov model proposed in Ref. [ 11] to simplify the calculation of the above formulas. The Markov based expressions can substitute the integral expression ri and p I with the sum of state stationary probability and FER. Eq. ( 2 ) can be represented as: k+l

"T

ktl

P I

T,lP,f --AD,", r , l ( l - p 7 2 )+ r n - l ( l - j % - t ) - AU,

c

Zl

1-k

, I

Here we suppose the states sJ , j = k , k + 1, k +1 fall in the region of [ T , - 1 , T , 1. Using the method in Ref. [ 111, we form a Markov model for 3 km single path Rayleigh fading channel where the average SNR corresponding to each frame is uniformly quantized with a given step size of 1 dB. The numerical simulations of T A and ITA are presented in Section 4 . * * a ,

J

I

i $2 = P N A C K [

rl

1+ -( 1 - pl r2

)]

(6)

4 Link Level and Numerical Simulation Results

rl+ r2+ + r, = 1 p , is the actual FER of each MCS, while P N A C K is the Adaptive modulation and coding technology is a key predefined FER of each MCS. Eq. ( 6 ) shows that the technique of HSDPA. Node B can choose the proper a * *

average FER of MCS, in T A algorithm is always larger ( 8 ) show that similar than P N A ~ K , while Eqs. ( 7 ) FER target can be maintained for each MCS in ITA algorithm, which are denoted as i PNACK-I, .**,

-

PNAC.K 1 . When

I P N A ~ K - I , ..*, P N A CIKare - ~set to

be the same as FER target, we can see that the average FER of each MCS exactly equals the FER target. The numerical and link level simulation in Section 4 both affirmed the conclusions presented by Eq. ( 6 ) and Eq. ( 8 ) . r71P?l

-

PNACK-~

r r I ( l- p n ) - 1 - P N A C K - ~

MCS according the channel condition of current user. In 3GPP, QPSK and 16-QAM with 1/3 turbo coding rate are considered in the current specifications. Multi code transmission is not considered in the study, and only one Spreading Factor ( S F ) is used. The table below lists the MCS schemes that are used in our study: Table 1

Modulation and coding rate

type

Turbo coding rate

Data rate /kbps

MCSl

QPSK

1/2

240

MCSz

QPSK

3/4

360

MCS,

16-QAM

1/2

480

MCSP

16-QAM

3/4

720

MCS

Modulation

~~

I + , + r2+ + r,=1 -*-

The FER of each MCS in stable state can be represented as:

We assume the channel as single Rayleigh fading channel, and the received SNR can be calculated as SNR = I a 2 I x SNR,,,, where a is the channel fading value and SNR,,, is the average transmission SNR at the BS side. The channel quality indicator ( ACK or NACK) is calculated for each frame. A summary of the link level simulation parameters is given in Table 2, other simulation parameters can be found in Refs. [ 1 21. The FER target for both numerical and link level

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simulation is set to be 14.28 % ' , which can be presented as P N A C K ( ~ - P N A C K ) - ~ = ~ / ~ .

Table 2

Simulation parameters

2006

guarantee the FER. The throughput loss of ITA is mainly because ITA convergence to a set of higher thresholds than TA as shown in Table 5 . Table 5

Parameters

Values

Propagation conditions

l-path Rayleigh

MCS

Theoretical FER of TA and ITA MCSl

MCSZ

MCS3

MCS,

3 km/h

FER ( T A ) / %

45.94

22.90

20.74

18.35

HS- DSCH Ec/ Ior

1

FER (ITA)/%

14.05

14.09

14.08

14.16

HSDPA frame length

2 ms

Th (TA)

-m

-7.6

-4.5

-1.8

Spreading faclor

16

Th (ITA)

-9.45

-5

Number of multi-cixie simulated

1

1"JIW

0 dB

Vehicle speed

--

3

0

Then, we form a first-order finite-state Markov model for 3 km single path Rayleigh fading channel which is " l1 ( 2 ms) MCS update period used to calculate the convergent thresholds of TA and Channel estimation Ideal channel estimation ITA according to Eqs. ( 4 ) - ( 1 0 ) . The same FER performance as the above link level simulation can be deFast fading model Jakes model duced from the numerical results. Here, we only list the None (only ACK/NACK is detected) H-AKQ average FER of convergent thresholds of the two algo14% FER target for all MCS Threshold adjustment rithms. The convergent thresholds of TA are approxi60 s Simulation duration mately 2 dB lower than ITA, which can account for the A link level simulator was carried out with parameters higher FER of TA. The reason of where T A has a highin Table 2 to investigate the performance of TA and er FER can be see from Eqs. ( 5 ) ( 6 ) . As shown in ITA. Tables 3 - 4 show that the average FER of each Eqs. ( 6 ) and ( S ) , the p , of TA is always larger than K ITA . is a MCS converged to the target FER in ITA, while the P N A C K while the p , of ITA equals P N ~ ~So, FER of T A algorithm exceed its target. Substitute the proper MCS selection method for QoS guaranteed data average FER of each MCS and P (MCS; ) with p ; and r; transmission in HSDPA. From the theoretical analysis in Section 3 and the link in Eqs. (3) - ( 4 ) , we can get the throughput and total FER of T A and ITA. From the total FER in level and numerical simulation results in this section, we Tables 3 - 4, we can see ITA could guarantee the target can get the conclusion that ITA is effective in tracking FER more accurately than TA although its throughput the variance of channel conditions and can guarantee the is 32.4 k less than TA, which is the same as the theo- FER for each MCS accurately. retical analysis Eqs. (7)- (8) in Section 3.

-

Table 3

5

Link level simulation results of TA

TA

MCS,

MCS2

M a 3

MC,S,

FER/ 'X,

47.25

25.10

21.72

18.55

P( MCS, )/ '%

14.5 1

12.71

20.52

52.26

Total FEK/ '&

24.20

'Throughput

436.24 kb/s ~

Table 4 __ FEW %I P( MCS,)/

q0

Link level simulation results of ITA

15.20

14.42

13.85

14.06

17.68

13.48

28.83

40.01

Total FER/%I

14.25

'Throughput

403.85 kh/s

For multimedia application and other real time services, which have tight FER requirement, ITA can guarantee the predefined FER target according to the user's QoS requirement, and T A algorithm can't

Conclusions

In this paper we focus on research of adaptive modulation and coding scheme in HSDPA. We analyze the Threshold adjustment algorithm in Refs. [ 2 - 41 and point out that TA algorithm can't guarantee the FER performance by theoretical analysis in Section 3 . Based on the threshold adjustment method, we propose an ITA algorithm, which can guarantee the FER target accurately and maintain the same FER target for each MCS. Numerical and link level simulation results both show the efficiency of ITA algorithm.

References : [ l ] 3GPP T R 25. 848. Physical layer aspects of UTRA high speed downlink packet access [ S] . 2001 . 3GPP2/TSG - C . R1002. 1xEV-DV Evaluation Methodolo[2] gy (V13)[S]. 2003. [a] 3GPP TSC, RAN1 Document R-01-0775 Further simulation results on link adaptation with threshold adjustment [PI //3GPP Meeting, Aug 27 - 31, 2001, Turin, Italy, 2001.

No. 2 -

FAN Chen, et

u1. :

Research on Threshold Adjustment Algorithm in Adaptive Modulation and Codinn

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~

[ 121

1131

[ 141

[ 151

Biography:FAN Chen, received the B. S. and M. S. degree in computer networks from Shandong University of Science and ‘I‘echnology, in 2000 and 2003. Now, he is a I’h. D. Candidate of Beijing University of Posts and Telecommunications. His research interests include AMC, HARQ, CDMA RRM, QoS support for mixed data services.