Maximum utility principle access control for beyond 3G mobile system

WIRELESS COMMUNICATIONS AND MOBILE COMPUTINGWirel. Commun. Mob. Comput. 2007; 7:951–959Published online 15 May 2007 in Wiley InterScience(www.interscience.wiley.com) DOI: 10.1002/wcm.491

Maximum utility principle access control for beyond3G mobile system

Xiaodong Xu1*,y, Chunli Wu1, Xiaofeng Tao1,2, Ying Wang1,2 and Ping Zhang1,2

1Wireless Technology Innovation Institute (WTI), Beijing University of Posts and Telecommunications (BUPT),

Beijing 100876, China2Key Laboratory of Universal Wireless Communication, Beijing University of Posts and Telecommunications,

Ministry of Education, Beijing 100876, China

Summary

With current research focusing on beyond 3G (B3G)/4G mobile systems, many advanced techniques are

investigated by world-wide research institutes and standard organization, such as multi input multi output

(MIMO), orthogonal frequency division multiplex (OFDM), and multi-antenna distributed cellular network

architecture. Based on these novel techniques, the radio resource management (RRM) strategies, such as access

control, also need to be developed. This paper proposes the maximum utility principle access control (MUPAC)

basing on Dijkstra’s Shortest Path Algorithm for multi-antenna cellular network architectures. In the accessing

process of the proposed algorithm, the shortest path in Dijkstra’s Algorithm is replaced by the cost of accessing

process, which is represented by utility function. Taking Generalized Distributed Cellular Architecture—Group

Cell as an example, MUPAC is described in details with the utility function, maximum utility principle, flow chart

of accessing process. Performance evaluation and analyses verify the merits of MUPAC algorithm in improving

system capacity, accessing success probability, and efficiency of system resources usage. Copyright # 2007 John

Wiley & Sons, Ltd.

KEY WORDS: access control; maximum utility principle; Dijkstra’s Shortest Path Algorithm; Group Cell

1. Introduction

With the commercialization of 3G mobile commu-

nication systems, the ability to provide diversiform

data services, including asymmetrical services, are

enhanced further than that of 2G systems. But at the

same time, users still have higher requirement for high

data rate and high quality of service (QoS) mobile

services. Therefore, the research and development of

new-generation mobile telecommunication system are

brought forward.

The objective of the enhanced 3G (E3G), B3G/4G

has been anticipated to provide users after the year

2010 with the data rate up to 100 Mbps or 1 Gbps in

mobility environments [1]. Numerous research plans

and projects towards B3G/4G have been initiated in

*Correspondence to: Xiaodong Xu, Wireless Technology Innovation Institute (WTI), Beijing University of Posts andTelecommunications (BUPT), Beijing, 100876, China.yE-mail: [email protected]

Copyright # 2007 John Wiley & Sons, Ltd.

Europe, East Asia, and North America, such as the

International Telecommunication Union (ITU), Wire-

less World Research Forum (WWRF), Korea’s Next

Generation Mobile Committee (NGMC), Japan’s mo-

bile IT Forum (mITF), and China 863 beyond 3G

(B3G) Future Technologies for Universal Radio En-

vironment (FuTURE), etc. Many international stan-

dardization organizations, such as 3GPP Long Term

Evolution (LTE) [2] and 3GPP2 Air Interface Evolu-

tion (AIE) [3], also have begun the research and

standardization of E3G systems.

The B3G/4G research in China started in 2001 in

the FuTURE project [4], which is being supported by

national 863 high-tech program. There are two re-

search branches in FuTURE. One is time division

duplex (TDD) branch and the other is frequency

division duplex (FDD) branch. Both of them are

investigating and demonstrating advanced techniques

for B3G systems to meet the application requirements

around the year 2010. Important advancements have

been achieved in the research and development of

B3G radio transmission technologies and multi-an-

tenna distributed cellular architectures.

With the research and development for B3G/4G

systems, a lot of advanced physical layer technologies

show their merits to be applied in future mobile

telecommunication systems. Among these techniques,

the multi-antenna techniques, such as multi input

multi output (MIMO) [5], space time code (STC)

[6], and orthogonal frequency division multiplexing

(OFDM), show their merits in improving system

capacity and coverage area. OFDM and MIMO tech-

niques have been standardized in 3GPP LTE as key

techniques of E3G physical layer. Accordingly with

the evolution of physical layer techniques, the Media

Access Control (MAC) and radio resource manage-

ment (RRM) techniques are all facing the require-

ments for evolution. Furthermore, current cellular

structure cannot fully take advantages of multi-an-

tenna techniques and full IP architecture. Therefore,

how to evolve the current cellular architecture and

effectively use advanced physical layer techniques in

future mobile systems also becomes the focus of

research.

On the other hand, due to the crowded situation

around 2 GHz spectrum resources, future mobile sys-

tems will use higher carrier frequency. The higher

carrier frequency has higher wireless signal attenua-

tion that would make the radius of cell reduce further.

If future mobile systems still use current cellular

structure and handover strategy [7,8], the handover

between cells will be more frequent than that of

today’s system and this will deteriorate the system

performance dramatically.

According to the reasons mentioned above, current

mobile cellular network is faced with new requirements

for further development. The cellular network archi-

tecture for future mobile telecommunication system

must adapt to advanced physical layer multi-antenna

techniques and cope with the frequent handover

problems. The constructions methods of cellular net-

work and the strategy of handover need to be broken

through. Many researchers have been dedicated to

novel cellular constructive methods and there have

been some contributions that focus on the novel cellular

structure, such as Generalized Distributed Cellular

Architecture—Group Cell [1,9], Distributed Wireless

Communication System (DWCS) [10], and Virtual Cell

Network (VCN) [11]. The overview of the China

beyond 3G project and the basic concepts of the Group

Cell are introduced in Reference [1]. The system

capacity and handover performance of Group Cell

architecture are analyzed in Reference [9]. The con-

cepts of DWCS and VCN are provided in References

[10] and [11], respectively.

Most of these contributions are based on distributed

cellular architecture with multi-antenna techniques,

which can enlarge the coverage and employ the

advantages of multi-antenna techniques. Among these

contributions, Generalized Distributed Cellular Archi-

tecture—Group Cell can fully combine the advan-

tages of MIMO, enlarge the coverage, and has flat

network architecture for full IP services. These merits

ensure Group Cell implemented in China B3G Fu-

TURE TDD systems, both in theoretical research and

B3G/4G hardware demo system, with physical layer

techniques of OFDMA, MIMO, and STC, etc.

Based on these novel cellular architectures, the

traditional RRM strategies need to be evolved either.

The Access Control algorithm used in 2G/3G systems

[12,13] cannot accommodate the features of multi-

antenna distributed cellular architecture, especially

for users served by multiple antennas. Therefore,

this paper investigates the Access Control method

for Generalized Distributed Cellular Architecture—

Group Cell as an example of novel multi-antenna

distributed cellular architecture. maximum utility

principle access control (MUPAC) method is pro-

posed, which can maximize the usage of limited

system resources with guaranteeing access users’

QoS requirements. Furthermore, through this method,

the interference caused by access users can also be

mitigated maximally and the accessing success prob-

ability can also be improved.

952 X. XU ET AL.

Copyright # 2007 John Wiley & Sons, Ltd. Wirel. Commun. Mob. Comput. 2007; 7:951–959

DOI: 10.1002/wcm

In Section 2, the definition and construction

method of Generalized Distributed Cellular Archi-

tecture—Group Cell is briefly introduced. In

Section 3, based on Dijkstra’s Shortest Path Algo-

rithm, the MUPAC method is discussed in details,

including the utility function and the flow chart of

access control. The performance evaluation and

simulation results are stated in Section 4. Finally,

there comes the conclusion.

2. Generalized Distributed CellularArchitecture—Group Cell

Based on multi-antenna transmission techniques,

Group Cell is characterized by several adjacent cells

which use the same resources (such as frequency,

code, time slot, etc.) to communicate with a specific

mobile terminals (MT) and use different resources to

communicate with different MTs [9].

Including access point (AP) and MT, the Group

Cell architecture is plotted in Figure 1, which indi-

cates the typical configuration in urban and highway

environments. The cells connected to an AP can form

one or several Group Cells. The structure, size, and

topology of the Group Cell are flexible to accommo-

date different application environments.

In a typical Group Cell-based wireless communica-

tion system, each AP has several separated antenna

elements (AEs). The AE can be single antenna or

antenna array. The function of signal processing is

accomplished at the AP. In Figure 1, AP1 has six AEs.

If the AEs in the area are indexed by 1�6 and the size

of the Group Cell is 3, we can find there are two Group

Cells connected with AP1 in this area, which are

Group Cell 1 of AE 1, AE 2, AE 3 and Group Cell

2 of AE 4, AE 5, AE 6. This is a fixed Group Cell

structure and the AEs of each Group Cell are fixed.

With the movement of the MT, different fixed Group

Cell will be selected.

Another construction method of Group Cell is

called slide Group Cell, which can be viewed as the

process of sliding windows. Considering the situation

in AP2, with the movement of MT3, the AEs of the

Group Cell that serves the MT3 can also move

correspondingly with it. As shown in Figure 1, AE

11, AE 12, AE 13 of AP2 are used for MT3 in timeslot

1. With the movement of the MT3, in timeslot 2, AE

12, AE 13, AE 14 will be selected by AP2 for MT3.

The construction of the Group Cell is dynamically

changed instead of fixed. This is the slide Group Cell

structure. This handover process is Slide Handover

[9], by which the users are always staying in the center

of Group Cell and the cell-edge effect can be elimi-

nated. The performance of the Group Cell architecture

with Slide Handover will be improved further.

The signals in Group Cell architecture could be

transmitted and received by all the AEs of the Group

Cell by the techniques such as MIMO, STC, and

OFDMA. Therefore, the system’s ability to resist

interference could be improved. Furthermore, because

the signal sources of the same Group Cell are iden-

tical, the MT does not need handover in intra-Group

Cell. Only if the MT moves out the coverage of

current Group Cell, the handover between the Group

Cells and Group Handover occurs, this can greatly

decrease the handover and improve the system capa-

city.

3. MaximumUtility Principle Access Control

Based on the Generalized Distributed Cellular Archi-

tecture—Group Cell, the users in the system are

served by more than one AE (Group Cell). The access

control method in the Group Cell architecture needs to

solve the problem of how to choose multiple AEs to

form the serving Group Cell, and allocate appropriate

resources to communicate with users. As Section 2

describes, the size of Group Cell can be adjustable for

users by their QoS requirements. Therefore, by adding

AEs with maximum utility to user’s current serving

Group Cell step by step to fulfill the users’ QoS

requirements can solve this problem. This solutionFig. 1. Group cell architecture in urban and highwayenvironments.

MAXIMUM UTILITY PRINCIPLE ACCESS CONTROL 953


DOI: 10.1002/wcm

can maximize the usage of limited system resources

with guaranteeing access users’ QoS requirements.

Furthermore, the interference, caused by new users

can also be mitigated maximally and the accessing

success probability can also be improved.

The steps of adding AEs with maximum utility can

be accomplished, based on Dijkstra’s Shortest Path

Algorithm [14] in Graph Theory. The Maximum

Utility Principle is proposed in details and the flow

chart of the MUPAC algorithm is described in the

following parts.

3.1. Dijkstra’s Shortest Path Algorithm

Dijkstra’s Shortest Path Algorithm is used to solve the

single-source shortest-paths problem on a weighted,

directed graph for the case in which all edge weights

are nonnegative, which was proposed by E. W. Dijk-

stra in 1959.

Based on Dijkstra’s Shortest Path Algorithm, when

there are new users initiating their access attempts in

Group Cell architecture, the shortest path in the

Dijkstra’s Algorithm can be replaced by the minimal

cost of accessing process. The cost of accessing

process includes the interference to other users and

occupying system resources (AEs, channels, and other

resources). Furthermore, the cost can be represented

by the utility functions, including the gains for the

access user and deterioration to other users. There-

fore, the seeking for shortest path in Dijkstra’s Algo-

rithm can be transferred to seeking the AEs or

resources with maximum utility. The Maximum Uti-

lity Principle can improve the system capacity and

load ability. By the Dijkstra’s Shortest Path Algorithm

and the Maximum Utility Principle, the user accessing

in multi-antenna distributed Group Cell architecture

can be effectively accomplished.

3.2. Utility Function in Maximum Utility Principle

In the MUPAC method, the utility function is con-

structed with considering current system load, re-

source occupying, and so on. The utility function

has two objectives. One is used to add AEs to current

serving Group Cell (or form the serving Group Cell

with the first AE) with Maximum Utility Principle and

the other is to select system resources, allocated to the

access users with Maximum Utility Principle.

The utility function has two aspects, including the

gain of new AE added in current serving Group Cell

(or resources allocated to the access user) and the

deterioration for other users existed in the system.

The utility function is written as Equation (1).

Uði; . . . ; j; kÞ ¼ �Ck½GCði; . . . ; j; kÞ � ICði; . . . ; j; kÞ�þ �ð1 � �CkÞmax

M 6¼C�Mi � . . . �Mj � �Mk½GMði; . . . ; j; kÞ

��IMði; . . . ; j; kÞ�g

ð1Þ

where Uði; . . . ; j; kÞ denotes the utility of adding AE k

to current serving Group Cell formed by AEs i; . . . ; j.C and M denote the resources and C is the current

resource used by serving Group Cell. �Ck is an

indicator function, which indicates the occupying

information of resource C in AE k.

�Ck ¼0; ResourceC occupied in AE k

1; ResourceC available in AE k

�ð2Þ

where, GCði; . . . ; j; kÞ denotes the gain achieved by

adding AE k to current Group Cell with resource C.

ICði; . . . ; j; kÞ denotes the interference to other users

by adding AE k to current serving Group Cell with C.

� is a constant between 0 and 1 to introducing the

penalty for coordinating current resource C and dif-

ferent resource (resource C0) for the new serving

Group Cell. � can be set according to the current

system load condition. The choice of C0 to replace C

can also be achieved by Maximum Utility Principle

with the utility function, which is:

C0 ¼ arg maxM 6¼C

�Mi � . . . �Mj � �Mk½GMði; . . . ; j; kÞ�

�IMði; . . . ; j; kÞ�gð3Þ

Specifically, when choosing the first AE to form the

serving Group Cell, the utility for choosing the first

AE can be written as:

UðkÞ ¼ maxM

�Mk½GMðkÞ � IMðkÞ�f g ð4Þ

when�Ck, GCði; . . . ; j; kÞ, and ICði; . . . ; j; kÞ in Equa-

tion (1) do not exist before serving Group Cell is

formed. Correspondingly, the method for choosing

system resource for the new Group Cell by Maximum

Utility Principle can be written as:

C ¼ arg maxM

�Mk½GMðkÞ � IMðkÞ�f g ð5Þ

Considering the actual mobile systems, the gain

and interference in utility function are usually

954 X. XU ET AL.


DOI: 10.1002/wcm

represented by SINR. Therefore, Equation (1) can be

revised to:

And Equation (4) can also be revised to:

UðkÞ ¼

arg maxC

�Cklgk;kP

n 6¼k

ð1��CnÞ lgn;k�Xn 6¼k

ð1��CnÞlgn;n

lgk;n

264

375

8><>:

9>=>;

ð7Þ

where lgn;k denotes the path gain between AE n to the

access user who is currently served by AE k. The

power for each user in Equations (6) and (7) are

equally allocated.

3.3. Flow Chart of Maximum UtilityPrinciple Access Control

With the Dijkstra’s Shortest Path Algorithm and

utility function proposed in Sections 3.1 and 3.2, the

flow chart of MUPAC can be presented in Figure 2.

All the AEs belong to the same AP in user-access

process so that the AP can get the users’ receiving

SINR of each AE. AP can obtain each AE’s pilot

strength received by access user by two approaches.

One approach is the user feedback the pilot strength

and AE id to AP by channel quality indicator (CQI)

and so on. The other approach is AP calculates the

downlink pilot strength by estimating the uplink

signal strength, which is especially effective in TDD

systems with symmetrical uplink and downlink.

Based on the flow chart, the detailed implementa-

tion steps of MUPAC are shown as follows.

(1) Access user initiates access attempt.

(2) AP obtains the users’ receiving pilot strength of

each AE.

(3) Based on the information in step (2), AP calcu-

lates the utility of each AE and available resource

by utility function and chooses the first AE and

resource with the Maximum Utility Principle to

form the serving Group Cell. If all the AEs

detected by access user have no resource avail-

able, the access user will be transferred to the

accessing waiting list.

(4) AP obtains the users’ receiving SINR of serving

Group and compares it with user’s QoS require-

ment. If current serving Group can provide

Uði; . . . ; j; kÞ ¼ �Cklgk;iP

n 6¼i;j:::;k

ð1 � �CnÞ lgn;i�

Xn6¼i;...;j;k

ð1 � �CnÞlgn;n

lgk;n

264

375

þ �ð1 � �CkÞ arg maxM 6¼C

�Mi�Mj:::�Mk

lgk;iPn 6¼i;...;j;k

ð1��MnÞ lgn;i�

Pn 6¼i;...;j;k

ð1 � �MnÞlgn;nlgk;n

24

35

8>><>>:

9>>=>>;

ð6Þ

Start

MT initiatesAccess

Requirement

AP obtains the pilotstrength of each AE

Select AE and resourceaccording to maximum

utility principle

Calculate currentreceiving SINR of

MT

SINR<TargetSINR?

Access success

End

No

YesNcurrent<Nmax?

Yes

Access denied, putMT into access

waiting list

No

Fig. 2. Flow chart of maximum utility principle accesscontrol.



DOI: 10.1002/wcm

adequate QoS to the user, the access process

accomplishes successfully. Vice versa, the access

user needs more AEs added to the current serving

Group.

(5) AP obtains the users’ receiving SINR of AEs,

excluding current serving Group and chooses the

AE with maximum utility to add it to the serving

Group Cell. This step needs to guarantee the new

AE and current serving Group Cell to use the

same resource. The utility function includes the

penalty of resource changing. Then, goes to step (4).

4. Performance Evaluation and Analyses

Comparing with fixed Group Cell size access control

algorithm, MUPAC can get flexibility in forming

serving Group Cell for cell-center users with less

AEs, which can improve the efficiency of system

resource usage. For cell-edge users or poor channel

quality users, the proposed algorithm can choose more

AEs to guarantee the target QoS requirement of access

users, and improve the accessing success probability.

Furthermore, the proposed algorithm also gives the

resource allocation method, based on Maximum Uti-

lity Principle, which can use the system resource more

efficiently.

For the performance evaluation and analyses, two

other access control algorithms are taken for compar-

ing. Algorithm 1 fixes the Group Cell size to 3 and

always chooses three AEs with maximal path-gain for

access users to form the serving Group Cell. The

resource for the serving Group Cell is randomly

allocated from the common available resources in

each AE. Algorithm 2 fixes the Group Cell size to 3

and chooses three AEs with maximum path-gain too,

but the resource allocation method is to choose the

resource that maximizes the receiving SINR by three

AEs. MUPAC chooses the AEs and allocates re-

sources, according to the Maximum Utility Principle.

The Group Cell size of MUPAC method is limited to

4. System-level simulation is adopted to evaluate

these three access control algorithms by comparing

the successfully accessed user numbers with different

system load (total access user number generated in

simulation) and different QoS requirement (Target

SINR for different mobile services). The average

serving Group Cell sizes are calculated for different

algorithms to compare the system resource usage

efficiency. The power allocation for these three algo-

rithms is the same as fixed power allocation scheme.

The simulation parameters and setting are shown in

Table I.

The simulation results are shown in Figures 3–6.

Figure 3 indicates the accessed user number versus

different target SINR with different total generated

users.

As shown in Figure 3(a), even though the system

load is relatively low, algorithms 1 and 2 still have

Table I. Simulation Parameters and Setting.

Parameters Setting

Cell radius 250 mAEs connected by AP 27Total channel number 4Total transmission power of AP 43 dBmMaximum size of Group Cell 4Carrier frequency 5.3 GHz Urban [15]Thermal noise density �174 dBm/Hz� 0.9

0 2 4 6 8 10 1280

100

120

140

160

180

200

220

Target SINR (dB)

Use

r N

um

ber

Proposed AlgorithmAlgorithm 2Algorithm 1

User Generated = 211

(a)

0 2 4 6 8 10 120

200

400

600

800

1000

1200

Target SINR (dB)

Acc

esse

d U

ser

Nu

mb

er



(b)

Fig. 3. Successfully accessed user number versus targetSINR with different total generated users.

956 X. XU ET AL.


DOI: 10.1002/wcm

some blocked users, while proposed algorithm can

almost accommodate all generated users. The advan-

tages of proposed algorithm versus Algorithm 1 lie in

the resource allocation mechanism. Algorithm 2 ob-

tains some gain to Algorithm 1 for the same reason.

But comparing to proposed algorithm, Algorithm 2

does not consider the interference to existing users

caused by accessing users, which can make other

users in the system outage. Furthermore, the Group

Cell size of Algorithms 1 and 2 is fixed, which limits

the flexible use of system resources. While in pro-

posed algorithm, the Group Cell size can be adjustable

to meet the QoS requirement of the accessing user.

In Figure 3(b), when the system load is heavy, the

proposed algorithm obtains obvious gain with low-

target SINR that can be accomplished with less AEs,

and system resource are saved for other users. With

211 361 511 661 811 961 1111 12610

200

400

600

800

1000

1200

Generated User Number

Use

r N

um

ber


Target SINR = 0dB

(a)

211 361 511 661 811 961 1111 126150

100

150

200

250

300

350


Acc

esse

d U

ser

Nu

mb

er


Target SINR = 12dB

(b)

Fig. 4. Successfully accessed user number versus totalgenerated users with different target SINR.

0

5

10

361661

9611261

200

400

600

800

1000

Target SINR (dB)Generated User Number

Acc

esse

dU

serN

um

ber


Fig. 5. Performance of proposed algorithm versus Algo-rithms 1, 2.

211 361 511 661 811 961 1111 12611

1.5

2

2.5


Ava

rag

e G

rou

p S

ize

Target SINR = 0dB

Target SINR = 5dB

Target SINR = 12 dB

(a)

0 2 4 6 8 10 121

1.5

2

2.5

Target SINR (dB)

Ava

rag

e G

rou

p S

ize




(b)

Fig. 6. Average serving Group Cell size versus total access user number or target SINR of MUPAC.



DOI: 10.1002/wcm

the increment of target SINR, the serving group size

will get larger to guarantee the QoS requirement of

accessing users.

Figures 4(a) and 4(b) indicate the successfully

accessed user number versus total generated users

with different target SINR as 0 and 12 dB, respec-

tively. The MUPAC algorithm shows its merits in

heavy system load.

Integrating these two aspects shown by Figures 3

and 4, Figure 5 is plotted to lend further credence to

the performance gain, brought by proposed algorithm

with a three-dimension figure. From Figure 5, the

merits of proposed algorithm are obvious, especially in

the areas of low-target SINR and heavy system load.

Moreover, to study the resource usage efficiency of

proposed algorithm, the average serving Group Cell

size is analyzed. Figure 6(a) plots the average serving

Group Cell size of MUPAC algorithm versus total

generated users with different target SINR, which

indicates the tendency of larger serving Group Cell

size with larger target SINR. Figure 6(b) shows the

variation of average serving Group Cell size with

different system loads. But both these serving Group

Cell sizes are smaller than Algorithms 1 and 2, which

is fixed to 3. The proposed algorithm can fully use the

limited system resources and accommodate more users

with guaranteeing the access users’ QoS requirements.

5. Conclusion

Currently, the research and development of E3G,

B3G/4G have been the focus of all over the world.

Many worldwide research and standard institutes,

such as ITU, WWRF, 3GPP, 3GPP2, mITF, NCMC,

and FuTURE, have deployed a lot of researches about

future mobile telecommunication systems. China Fu-

TURE project investigates both TDD and FDD archi-

tectures for B3G systems. Important advancements

have been achieved in the research and development

of hardware B3G demo systems. In B3G TDD demo

system, 100 Mbps data rate is provided and General-

ized Distributed Cellular Architecture—Group Cell is

implemented with physical layer techniques of

OFDMA, MIMO, and STC, etc.

This paper proposes the MUPAC basing on Dijk-

stra’s Shortest Path Algorithm for multi-antenna dis-

tributed cellular network architectures. In the

accessing process of proposed algorithm, the shortest

path in Dijkstra’s Algorithm can be replaced by the

cost of accessing process, which is represented by

utility function. Taken Generalized Distributed Cel-

lular Architecture—Group Cell as example, the MU-

PAC algorithm is described in details with the utility

function, Maximum Utility Principle, flow chart of

accessing process. Performance evaluation and ana-

lyses verify the merits of MUPAC algorithm in

improving system capacity, accessing success prob-

ability and efficiency of system resources usage.

Acknowledgements

This work was supported by the projects of National

Natural Science Foundation of China under Grant

numbers 60496312 and 60302024.

References

1. Zhang P, Tao X, Zhang J, Wang Y, Li L, Wang Yong. Thevisions from FuTURE beyond 3G TDD. IEEE Communica-tions Magazine 2005; 43(1): 38–44.

2. 3GPP. TR25.913, Requirements for Evolved UTRA (E-UTRA)and Evolved UTRAN (E-UTRAN), 2005.

3. 3GPP2. cdma2000 Enhanced Packet Data Air Interface Sys-tem-System Requirements Document, 2005.

4. Yu X, Chen G, Chen M, Gao X. The FuTURE project in China.IEEE Communications Magazine 2005; 43(1): 70–75.

5. Foschini GJ, Gans MJ. On limits of wireless communicationsin a fading environment when using multiple antennas.Wireless Personal Communication 1998; 6(3): 311–335.

6. Foschini GJ. Layered space-time architecture for wirelesscommunication in a fading environment when using multi-element antennas. Bell Labs Technical Journal 1996; 1(2): 41–59.

7. Bell Lab. High-Capacity Mobile Telephone System TechnicalReport, 1971.

8. Harold W. The competitive potential of cellular mobile tele-communications. IEEE Communications Magazine 1983;21(8): 16–23.

9. Tao X, Dai Z, Tang C, Zhang P. Generalized cellular networkinfrastructure and handover mode-group cell and group hand-over. Acta Electronic Sinica 2004; 32(12A): 114–117.

10. Zhou S, Zhao M, Xu X, Wang J, Yao Y. Distributed wirelesscommunication system: a new architecture for future publicwireless access. IEEE Communications Magazine 2003; 41(3):108–113.

11. Cayirci E, Ersoy C. Application of 3G PCS technologies torapidly deployable mobile networks. IEEE Network 2002;16(5): 20–27.

12. Rao RM, Comaniciu C, Lakshman TV, Poor HV. An overviewof CAC principles in DS-CDMA networks—call admissioncontrol in wireless multimedia networks. IEEE Signal Proces-sing Magazine 2004; 21(5): 51–58.

13. Bambos N, Chen SC, Pottie GJ. Channel access algorithmswith active link protection for wireless communication net-works with power control. IEEE/ACM Transaction Networking2000; 8(5): 583–597.

14. Dijkstra EW. A note on two problems in connexion with graphs.Numerische Mathematik, 1959:269–271.

15. Zhao X, Kivinen J, Vainikainen P, Skog K. Propagationcharacteristics for wideband outdoor mobile communicationsat 5.3 GHz. IEEE Journal on Selected Areas in Communica-tions 2002; 20(3): 507–514.

958 X. XU ET AL.


DOI: 10.1002/wcm

Authors’ Biographies

Xiaodong Xu is a Ph.D. candidate ofCircuit and System in Beijing Univer-sity of Posts and Telecommunications.He received his Master’s Degree inCommunication and Information Sys-tem from Shandong University in July2004. His research direction is advancedmobile communication systems and thekey technologies, including Generalized

Distributed Network Architecture, Radio Resource Manage-ment for B3G/4G, and standardization of Enhanced 3Gsystems.

Chunli Wu is pursuing her Master’sdegree at WTI of Beijing University ofPosts and Telecommunications. Herresearch direction is advanced mobilecommunication systems and key tech-niques, multi-antenna distributed cellu-lar architecture, Radio ResourceManagement strategies, and standardi-zation of Enhanced 3G systems.

Xiaofeng Tao, (M’00), received hisB.S. degree in Electrical Engineeringfrom Xi’an Jiaotong University, China,in 1993, and M.S.E.E. and Ph.D. inTelecommunication Engineering fromBeijing University of Posts and Tele-communications in 1999 and 2002,respectively. He was a Research Engi-neer working in the Posts and Telecom-

munications Industry Company of China (PTIC) from 1993to 1996. He is currently an Associate Professor and the ViceDirector of WTI of BUPT and a group leader of the TDDSpecial Working Group of China 863 FuTURE Program.

His research interests cover techniques for B3G, such asspace-time coding, MIMO, novel cell structures, and intel-ligent group handover mode.

Ying Wang (SM’02-M’04) receivedher B.S. and M.S. degrees in Electro-nics Engineering from NorthwesternPolytechnical University in 1998 and2000, respectively, and her Ph.D. incircuits and systems from Beijing Uni-versity of Posts and Telecommunica-tions in 2003. From January 2004 toMarch 2004, she was invited to work as

a visiting researcher in Communications Research Labora-tory (renamed NiCT from April 2004), Yokosuka, Japan.And in 2005, she worked as a Research Associate in HongKong University. Now she is an Associate Professor ofBUPT and a Researcher of Wireless Technology InnovationInstitute. Her research interests are in the area of thecooperative relaying system, radio resource management,and performance analysis in the beyond 3G and 3G systems.

Ping Zhang (M’04), received his M.S.degree from Northwestern Polytechni-cal University, Xi’an, China, in 1986and his Ph.D. from Beijing Universityof Posts and Telecommunications, Beij-ing, China, in 1990, both in ElectronicsEngineering. From 1994 to 1995, hewas a Post-Doctoral Researcher in thePCS Department, Korea Telecom Wire-less System Development Center. Now

he is the Professor of BUPT, Director of Wireless Technol-ogy Innovation Labs, member of the China 3G and B3Ggroup, Senior Consultant of NTT DoCoMo, member ofWWRF vision committee. His research interests cover thekey techniques of the beyond 3G and 3G systems, especiallyin the multiple access technique, modulation, and channelcoding.



DOI: 10.1002/wcm

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