Lucent1xDiversityScheduling

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Title: Effects of Scheduling on Transmit Diversity Performance in 1xEV-DV.5

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Abstract: This contribution is presented as supporting information to Lucents71xEVDV proposal.8

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Source: Achilles Kogiantis, Niranjan Joshi, and Oguz Sunay10

Lucent Technologies11973 386-439912[achilles, nsjoshi, sunay] @lucent.com13

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Date: December 07, 200015

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Recommendation: Review and Discuss17

Notice

2000 Lucent Technologies. All rights reserved.

The information contained in this contribution is provided for the sole purpose of promoting discussion withinthe 3GPP2 and its Organization Partners and is not binding on the contributor. The contributor reserves the

right to add to, amend, or withdraw the statements contained herein.

The contributor grants a free, irrevocable license to 3GPP2 and its Organization Partners to incorporate text or

other copyrightable material contained in the contribution and any modifications thereof in the creation of TIAor 3GPP2 publications; to copyright and sell in Organizational Partners name any Organizational Partners

standards publication even though it may include portions of the contribution; and at the Organization Partners

sole discretion to permit others to reproduce in whole or in part such contributions or the resulting

Organizational Partners standards publication


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1

1 INTRODUCTION2The submitted proposals for the 1xEVDV standard give an important role to a fast packet-3

switching downlink channel with scheduling among the users queued packets. The4

scheduling operation interacts with the physical layer processes, unlike in the majority of5

the previously studied, and implemented, wireless systems that were designed for6

optimizing multiple access circuit-switched links. This interaction of the physical with the7

Medium Access Control (MAC), and higher, layers is evident in the case of scheduling since8

the scheduler operation is heavily dependent on feedback information from the physical9

layer. Particularly, the interaction of the scheduling process with that of the physical layer10

transmit diversity schemes is analyzed. Transmit diversity has been introduced in the11

physical layer to improve the downlink per-user performance and consequently to improve12

the overall capacity of the system. In the later sections, it will be shown that the combined13

performance of scheduling and transmit diversity does not lead to the same conclusions as14

a physical layer only study of the transmit diversity. A similar study leading to the same15

conclusions was conducted in [3].16

2 TRANSMIT DIVERSITY TECHNIQUES FOR DOWNLINK TRANSMISSION17For the purpose of this study, two transmit antennas are considered at the base station for18

downlink transmission for the forward packet data channel in Lucents 1xEV-DV proposal.19

Also, two transmit diversity techniques for the forward link are considered, namely, Space-20

Time-Spreading (STS) and Selection Transmit Diversity (STD). The no diversity (single Tx21

antenna) transmission is considered also as a reference case. The signals that may be22

transmitted from the two antennas experience multipath fading and propagation losses by23

the scattering environment. The cumulative vector channel effects seen at the mobile's24

receiver, can be lumped into two variables that describe the two complex channel25

responses, one for each transmit antenna, namely 1h and 2h .26

Space-Time-Spreading, [2], is an open loop scheme and guarantees second-order diversity27

for each transmitted symbol. In this scenario, the mobile receiver observes a post-28

combining channel gain2

h for each symbol equal to: ( )222

1

2

2

1hhh += , which is the29

average of the channel gains of the two paths.30

Selection Transmit Diversity is a closed loop scheme with binary feedback sent by the31

mobile. In this case, assuming error-free feedback with no delays, the observed channel32

gain at the mobile receiver is the better of the two paths: (2

2

2

1

2

,max hhh = . The33

feedback bit and the consequent antenna selection is performed every slot.34

In the following, the assumption of independent channel responses from each transmit35

antenna is made.36


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3 SCHEDULING ALGORITHMS1In conjuction with the trasnmit diversity schemes that were defined previously, three2

different scheduling algorithms for downlink transmission are considered for the analysis:3

Maximum C/I Scheduler (max C/I). This scheduler essentially ranks all the users4

according to their instantaneous carrier-to-interference (C/I) ratios. This scheduler5

is optimal in obtaining the maximum network throughput [1].6

Proportional Fair Scheduler (PF). This algorithm is described in detail in [4]. In7

short, the scheduler computes the ratio of the current supportable rate Current8

ratei(t), for each user i to the average throughput each user has received so far Ri(t).9

A user with the largest ratio gets priority in receiving data. The average throughput10

is updated as, Ri(t+1)=(1-1/tc)Ri(t) + transmission ratei, where tc is a constant. A user11

that does not receive service has 0 for his transmission ratei.12

Random Scheduler. As the name suggests, users are picked randomly. Essentially13

the performance of this scheduler is equivalent to the Round Robin scheduler that14

offers no advantage to users with favorable channel conditions15

4 SIMULATION RESULTS16The Forward Packet Data Channel of Lucents 1xEVDV proposal is used as a platform for17

our study. The assumption of data only loading (no voice users present) is made. The link18

level performance is abstracted in the form of the mapping between the data rate and C/I19

values for an AWGN channel as shown in Table 1, and [5]. A users' initial C/I is drawn from20

the distribution shown in Fig. 1.21

Data Rate (Kbps) C/I (dB)

38.4 -12.5

76.8 -9.5

102.6 -8.5

153.6 -6.5

204.8 -5.7

307.2 -4.0

614.4 -1.0

921.6 1.3

1228.8 3.0

1843.2 7.2

2457.6 9.5

Table 1. Data Rate to C/I Mapping22

This distribution is the result of a multicell simulation, with lognormal shadowing, pathloss23

and antenna pattern gains. A correlated Rayleigh Jakes fading process is generated for24


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each diversity path around the initial C/I. At the system level, a simplifying assumption of1

single slot transmission (1.25ms) for all data rates, as opposed to the rate-dependent2

varying slot transmission, is made. The base station is assumed to have all user queues3

always full so as to transmit data continuously. Thus, no traffic model assumption is made.4

For a different set of number of users, fading rates, and scheduling schemes, multiple trials5

are performed. Each trial runs for 13 seconds.6

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0.1

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Mobile Station Received C/I (dB)

CDF

C/I Distribution in a Multi-Cell Environment

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Figure 1. Cumulative Distribution of downlink received C/I based on a 19-cell8

scenario with lognormal shadowning and pathloss modeling.9

4.1 Results10 The performance of various transmit diversity schemes in conjunction with the various11

scheduling algorithms is measured in terms of the mean sector/network throughput. A12users received signal strength distribution, which includes shadowing and fading, will13

contribute significantly to the sector throughput. This received C/I distribution, is also14

influenced by the employed transmit diversity scheme. This is evident from the pdf curves15

representing random scheduler (i.e. no scheduler) in Fig. 2. The STD scheme clearly16

displays the highest mean C/I. The STS, as expected, shows a smaller variance and has a17

higher mean compared to the single antenna case. In Fig. 2 it is shown how the scheduler18

utilizes this C/I information. It is evident from Figs. 3 and 4 that, for the random and max19

C/I scheduler the performance of STD is superior to the other schemes. Moreover, the STS20

performs slightly better that the single antenna case. For the PF scheduler, which accounts21

for more than just C/I information, the single antenna performance is superior to the STS22

scheme. From all the figures, it is evident that an efficient scheduler exploits more23

efficiently the tails of the per user C/I distribution, as shaped with the use of STD. This is24

not the case though, for the STS scheme that suppresses the distribution tails, while25

increasing its mean.26

Fig. 3 shows that for all schemes the mean sector throughput increases with increased cell27

loading. Moreover the throughput curve saturates quickly either due to the assumption of28

rate set limitation to 2457.6 kbps as well as the scheduler behavior. The throughput29


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remains insensitive to the increase of fading rates, as shown in Fig. 4. Only the PF1

scheduler shows a measurable reduction in the network throughput for low to medium2

fading rates. For all sector/network loadings and all fading rates, STD is uniformly superior3

in throughput achieved, by at least 5% versus the single transmit antenna case.4

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0.01

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Scheduler Output C/I (dB)

PDF

Scheduler output C/I distr ibution. Fading rate=3Hz, 16 users

1Tx max C/I

STS max C/ I

STD max C/I

1Tx Random

STS Random

STD Random

1Tx PF

STS PF

STD PF

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Figure 2. Scheduler Output distribution for various cases of transmit diversity and6

scheduling algorithms.7

10 20 30 40 50 60 7060 0

80 0

1000

1200

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1600

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2000

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2400

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Number of users

MeanThroughput(Kbps)

Mean Throughput vs. Cell Loading for 3Hz fading rate

1Tx max C/I

STS max C/I

1Tx Random

STS Random

STD max C/I

STD Random

1Tx PF

STS PF

STD PF

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Figure 3. Combined transmit diversity and scheduling performance as a function of9

the number of active users for fading rate of 3Hz.10


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0 10 20 30 40 50 60 70 80 90 100

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

Fading Rate (Hz)

MeanThroughput(Kbps)

Mean Throughput vs. fading rate for 16 users

1Tx max C/ISTS max C/I

1Tx Random

STS Random

STD max C/I

STD Random

1Tx PF

STS PF

STD PF

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Figure 4. Combined transmit diversity and scheduling performance as a function of2

the fading rate for a fixed sector loading of 16 active users.3

5 CONCLUSIONS4A study on the interaction of three scheduling algorithms with three different transmission5

configurations (with and without transmit diversity) on a data only case for the 1xEVDV6

system was conducted. The simulation results indicate that without transmit diversity (i.e.7

only one transmit antenna) the resulting network throughput is equivalent to the one with8

the most efficient open loop two-branch transmit diversity scheme, STS. On the other hand,9the closed loop STD is shown to offer distinct advantages in conjunction with the10

scheduling operation. For low to medium cell loading, the network throughput can be 5-11

10% higher when STD is deployed. The performance differences among the diversity12

schemes are dependent on the resulting per-user C/I distribution profiles. The greedy13

schedulers take advantage of the high-value tails of the per-user C/I distributions while14

STS attempts to shrink these tails. Also, it was shown that the network throughput is not15

affected by the Doppler rate, except for the case of the PF scheduler that is more sensitive16

in the low to medium speeds.17

6 REFERENCES:181. D. Tse, and S. Hanly, ``Multiaccess Fading Channels-Part I: Polymatroid Structure,19

Optimal Resource Allocation and Throughput Capacities,'' IEEE Transactions on20

Information Theory, Vol. 44, No. 7, November 1998.21

2. Lucent Technologies Inc., ``Down Link Improvement through Space Time Spreading,''22

Standards Contribution 3GPP2-C30-19990817-014.23


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3. H. Huang, H. Viswanathan, A. Blanksby, and M. Haleem, ``Multiple Antenna1

Enhancements to High Rate Packet Data CDMA System,'' submitted to the Journal of2

VLSI Signal Processing, September 2000.3

4. A. Jalali, R. Padovani, and R. Pankaj, ``Data Throughput of CDMA-HDR: A High4

Efficiency-High Data Rate Personal Communication Wireless System,'' IEEE Vehicular5

Technology Conference, Tokyo, Japan, May 2000.6

5. P. Bender, P. Black, M. Grob, and R. Padovani, ``CDMA/HDR: A Bandwith-Efficient7

High-Speed Wireless Data Service for Nomadic Users,'' IEEE Communications Magazine,8

July 2000.9

6. N. Joshi, S. Kadaba, S. Patel, and G. Sundaram, Downlink Scheduling in CDMA Data10

Networks,Mobicom 2000 Conference, Boston, MA, August 2000.11

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