Cooperative Spectrum Allocation with QoS Support in ... - IEEE Xplore

5 downloads 17 Views 3MB Size Report
Cognitive Cooperative Vehicular Ad Hoc Networks ... 2 The State Key Laboratory ofTntegrated Services Networks, Xidian University, China ... Institute, China United Network Communications Corporation Limited, Beijing, 100048, P.R.China.

VEHICULAR NETWORKING

Cooperative Spectrum Allocation with QoS Support in Cognitive Cooperative Vehicular Ad Hoc Networks ZHANG Lep,2,\ LUO Tao!,2, LIU Wei4, ZHU Siting\ LI Jianfeng! 1

Beijing University of P osts and Telecommunications, Beijing, 100876, P.R.China. The State Key Laboratory ofTntegrated Services Networks, Xidian University, China 3 Network Technology Research Institute, China United Network Communications Corporation Limited, Beijing, 100048, P.R.China. 4The 20th Research Institute of CET C, Xi'an, 710086, China 2

Abstract:

To solve the contradiction between

the increasing demand of diverse vehicular wireless applications and the shortage

enhance the communication reliability of safety service considerably in CC-VANET. Keywords:

VANET; spectrum sensing;

of spectrum resource, a novel cognitive

resource allocation; asymmetric; generalized

cooperative vehicular ad-hoc network (CC­

nash bargaining solution

VANET) framework is proposed in this paper. Firstly, we develop an adaptive cognitive spectrum sensing (ACSS) mechanism which can help to trigger and adjust the spectrum

49

I. IN TRODUCTION

The vehicular ad-hoc network (VANET)

sensing window according to network traffic

is a comprehensive network, which can ex­

load status and communication quality. And

change the safety and non-safety information

then, Generalized Nash Bargaining Solution

among vehicles or between vehicles and fixed

(GNBS), which can achieve a good tradeoff

road side unit (RSU). It can support various

between efficiency and weighted fairness, is

intelligent transportation system (ITS) ap­

proposed to formulate the asymmetric inter­

plications over the wireless links. In 1999,

cell resource allocation. Finally, GNBS­

Federal Communication Commission (FCC)

Safety (GNBS-S) scheme is developed to

assigned 75MHz spectrum at 5. 9GHz for

enhance the Quality of Service (QoS) of

vehicular communication. However, recent

safety applications, especially in the heavy

studies indicate that the channel bandwidth

load status, where the bandwidth demanded

might be inadequate to support the severe dif­

and supplied cannot be matched well.

ferent quality of service (QoS) requirements

Furthermore, the primary user activity (PUA)

of safety-service in peak hours of traffic [1-3].

which can cause rate loss to secondary users,

Thus, with the increasing communication de­

is also considered to alleviate its influence to

mand of diverse applications and severe QoS

fairness. Simulation results indicate that the

requirements, the limited and static spectrum

proposed CC-VANET scheme can greatly

resource can result in severe message access

improve the spectrum efficiency and reduce

delay and packet loss rate.

the transmission delay and packet loss rate

Recently, cognitive radio (CR) has been

on the heavy contention status. And GNBS

considered as an effective technique to im­

spectrum allocation scheme outperforms both

prove the efficiency of spectrum utilization by

the Max-min and Max-rate schemes, and can

allowing cognitive users to share the wireless China Communications· October 2014

channel with primary users in an opportunis­

The remainder of this paper is organized

tic manner. And cooperative communication

as follows: related works are firstly reviewed

I n t h i s p a p er, w e

which can increase link capacity by exploiting

in Section 2. Then, Section 3 describes the

propose a novel cen­

spatial diversity has also attracted a lot of

proposed CC- VANET architecture, and the

tralized CC-VANET

attention in recent years. For this purpose,

ACSS scheme is developed in section 4.

framework to solve the contradiction be­

we propose a novel cognitive cooperative

After that, the basic theory for the proposed

VANET (CC-VANET) to solve the contradic­

bargaining solutions and a two-band partition

d e m a n d of d i v e r s e

tion between the increasing demand of diverse

algorithm for inter-cell spectrum allocation are

vehicular services and

vehicular services and the spectrum scarcity

given in section 5. Finally, the performance

the shortage of spec­

of vehicular communication in this paper.

evaluation results are described in section 6

trum resource.

The CC-VANET system enables VANET to

and conclusions are drawn in section 7.

tween the increasing

use additional spectrum opportunities outside the standard 5.9GHz band, and it can greatly enhance the QoS performance of various ITS

II. RELATED WORKS

applications. Besides, through cooperative

In order to extend the channel capacity,

spectrum sharing strategies between

researchers attempt to identify spectrum holes

heterogeneous cognitive networks as in liter­

of TV band on the road with the character of

ature [4], the primary users might offer some

predictable vehicle mobility in literature [2].

spectrum access opportunities to cognitive

And a fuzzy VANET system is developed in

users, and both the whole system efficiency

[5] to dynamically assign additional spectrum

and fairness can be improved greatly.

from ISM band to a control channel. How­

Though cognitive radio and cooperative

ever, it has never considered when and how

communication have made great achievements

to trigger the cognitive mechanism and the

respectively, the research of their applications

contradiction between the cognitive gains of

in CC-VANET is still at a preliminary stage.

additional spectrum and the overhead of spec­

Due to the dynamic spectrum sharing of CR,

trum sensing. In this paper, we will address

resource allocation in CC-VANET becomes

the issues mentioned above and develop a

more complicated than the traditional vehicular

novel ACSS mechanism. In [3], a cooperative

networks. The notable primary user activity,

sensing framework with a stationary BS

asymmetric spectrum requirements between

which provides coordination instructions

multi-cells and severe QoS requirements of

to the passing vehicles is proposed. The

safety service should be considered in CC­

literature [6] points out the problem with a

VANET. In addition, when and how to trigger

centralized fusion center, and proposes a belief

the cognitive spectrum sensing mechanism

propagation spectrum sensing method which

and the relationship between cognitive

requires each vehicle to send its respective

overhead and performance gains are also of

belief of the presence of primary user. To

great importance to be deeply researched.

guarantee the QoS of vehicular applications,

Considering these factors, we define a

the authors in [7] develop a novel spectrum

communication load metric to evaluate the

management framework including shared

network traffic status, and develop an adaptive

channel, exclusive-use channel and cluster

cognitive spectrum sensing (ACSS) scheme

size control, with the theory of constrained

to trigger and adjust the sensing window

Markov decision process (CMDP). Howev­

according to the network traffic load status.

er, the achievements mentioned above have

Then, Generalized Nash Bargaining Solution

never addressed the asymmetric spectrum

(GNBS), which can achieve a good tradeoff

requirements between multi-cells in vehicular

between efficiency and weighted fairness, is

environments. For this purpose, we will model

proposed to formulate the asymmetric inter­

the asymmetric resource allocation problem

cell resource allocation.

with GNBS to favor the hot cells in severe

China Communications· October 2014

50

contention status. Game theory which includes cooperative and

the road side unit (RSU) based on CR (CR­

non-cooperative methods is widely regarded

RSU) and local information processing unit

as an efficient theory to analyze the resource

(LIPU). In general, we suppose the whole

allocation problem in wireless networks. The

network can be divided into different cognitive

non-cooperative game theory, in which each

subsystems each with several cognitive cells

player is self-interested and the Nash equilib­

(CCs). As shown in Fig.l, the system works

rium is often inefficient, has been studied in

as follows: Firstly, the CRVs take the task of

[8] for multi-cell OFDM A resource allocation.

local load estimation and spectrum sensing,

With the aim to minimize the users' transmis­

and then periodically report related results

sion power under the constraints of minimal

to the corresponding CR-RSU. Then, the

rate and maximal power, it is used to allocate

CR-RSU is responsible for data fusion and

the subchannels and power to the uplink users.

resource allocation in a single cognitive cell.

The cooperative game approach which empha­

Finally, LIPU will calculate and predict the

sizes collective rationality and fairness is also

network load metric of the subsystem and

used to model the spectrum sharing strategy in

then decide when and how to trigger the

[9, 10]. In [9], Nash Bargaining Solution (NBS)

ACSS mechanism. In addition, LIPU is also

is studied in the resource allocation scenario of

in charge of inter-cell resource allocation with

power, rate, and subchannels for a single-cell

cooperative game theory and maintaining the

OFDMA system, and it can obtain more fair

cognitive spectrum pool.

and efficient performance than traditional

As in Fig. 2 , a c o g n i t i v e s u b s y s t e m

allocation algorithms. In order to favor some

composed o f four rectangle cognitive cells is

players, different bargaining powers for users

considered. Assume the density of cognitive

are introduced to NBS for interference channel

vehicles and the bandwidth requirements of

in [10]. In this paper, GNBS is introduced to model

each cell can be obtained by the LIPU. As­ sume a serious road traffic jam has happened

the inter-cell spectrum allocation problem. For

in cognitive cell-l (CC-l) and it will result in

asymmetric cognitive cells with different load

heavy communication load and QoS degrada­

levels and bandwidth requirements, GBNS

tion. However, there may be residual spectrum

scheme can achieve a good tradeoff between

in other adjacent cognitive cells. Thus, the

the weighted fairness and overall achiev­

asymmetric traffic statuses and bandwidth

able rate. And then the scheme is extended

requirements among multi-cells should be

to the spectrum starvation case in which the

addressed in CC-VANET. Suppose the avail­

QoS support of safety applications should be

able subchannels can be obtained accurately

given high priority. Afterwards, a novel two­

by cooperative spectrum sensing technique.

band partition allocation scheme is developed

In addition, the cells in a cognitive subsystem

for different communication load status.

cannot select the same subchannels because

Furthermore, the primary user activity (PUA)

of co-channel interference. The channel state

is also considered to alleviate the degradation

information for each vehicle over different

of fairness.

channels is assumed to be perfectly estimated.

III. PROPOSED SYSTEM 3.1 The proposed CC-VANET

51

tities, i.e., the vehicle based on CR (CRV ),

3.2 System model

In this paper, a two-step scheme is developed for the spectrum resource allocation in CC­ VANET. Firstly, LIPU is responsible for

architecture

allocating subchannels to each cell fairly

In this paper, we propose a centralized CC­

and efficiently, which is named inter-cell

VANET architecture composed of three en-

allocation. Then, RSU will allocate the availChina Communications· October 2014

able subchannels among different CRV s in each CC, which is called intra-cell allocation. Assume each CRY can access the licensed spectrum in an overlay manner. we mainly focus on the asymmetric inter-cell spectrum allocation problem in CC-VANET. Consider a subsystem composed of N CCs, and Nn on-board units (OBUs) are randomly distributed in each cell. Suppose there are

K

available subchannels with equal bandwidth

WHz in the cognitive spectrum pool. The total

achievable rate for a cell can be expressed as

R"

=

I��l a:�kr:

(I)

r: respectively represent the

where a: and

llSL

n m

n m

RS[

Data Pusion Tntra-ce 11 A 11oCiltion

Data fusion Tntril-ce11 Allocation Bruadcast

llepOrT

toopcrclLivc spccLrur

channel indication, and the average utility of the k-th subchannel allocated to the CCn, and /;k denotes a discount factor of the achievable rate. It is assumed that no any subchannel can support transmission for more than one cell, �N Vk, with the definition i.e., L...J " �1 a�

a�

=

{I; ;

=

I,

channel 0th

0

.

k is assigned to CCn,

erwlse.

(2)

The discount factor of the achievable rate /;k=l-Pk, where Pk denotes the probability that the k-th subchannel is reoccupied by the primary users. The average utility of the k-th subchannel is defined as

r:

r;

=

=

(ljN,,)

I,:>:;

Wlog2 (I +

n

E {I, 2, ... ,N}

Fig.1 Framework of the proposed CC-VANET

(3a)

(p;h;)jcr); i E {I, 2, ... ,Nn}

(3b)

r; is the achievable transmission rate of CRY i, h; and p; represent the subchannel gain and transmit power for CRY i in the k-th

where

Licensed User

(3) �f�; � � [":CC----1 � �

....-. .,. ....,.-�

:

-----

11 :

·----

�.-- j � --b.l i .CC �

!

A: �-� �--- A -�-----L ----

-�1 :; I'� :- - - �- -�- - A�- -�T-- - - � I

....

:

;



-- -- �

... I

t. fl

� -

----

:

� .



:

....

-t��-��- � �----- . "� . I.

:

I

i i

..

----

.....

: -F

1



--

fl.:

!1 I

---

.

: I

-

� ---�--T------L �� i -

4.'. -�/ I

-

______

:

I

_

i

Fig.2 Illustrative scenario of a su bsystem in CC-VANET

subchannel, respectively. It is averaged by Nn because there are Nn OBUs. The noise power for all subchannels is assumed to be the same, and equals to

(j2.

we define a communication load metric CJt) to represent the network contention level of the subsystem. As described in (4), the packet

IV. ADAPTIVE COGNITIVE SPECTRUM

loss rate and message delay are considered as

SEN SIN G SCHEME

the most important QoS parameters to eval­

In order to guarantee the QoS of safety service,

The message delay can be considered as the

China Communications· October 2014

uate the performance of vehicular services. sum of queuing delay, contention delay due 52

to other vehicles and the transmission delay. Each CRY will compare its obtained packet loss rate

DJt) and message delay PJt) with

the corresponding service-related thresholds.

The basic theories of GNBS and its

If the estimated packet loss rate or message

application in asymmetric spectrum resource

delay exceeds the threshold, the load level will

allocation are given in this section. And we

be added 1. Thus, it is obvious that the local

also propose a simplified two-band partition

load metric for each CRY can only be one

allocation algorithm, and generalize it to the

integer, i.e., C,,(t)

E {O, 1, 2}. C,,(t) ST" . [(D"(t) > D:h) + (p"(t) > P;h)] +(1 - ST,,) . [(D"(t) > D�D + (P n(t) > P�:) ] (4) =

Where STn represents the message type that CRY is transmitting. And its definition as

{0, non

following ST n

=

1,

- safety related service

safety related service

(5)

applications. 5.1 General nash bargaining

solution

As mentioned above, LIPU is considered as inter-cell spectrum allocation, and the CR­ RSU is supposed as the bargaining player of

information from the CRV s within its communication range, the communication load status for a cognitive cell will be obtained by averaging the measurements using (6). The RSUs send the information to LIPU periodically, and then LIPU will calculate CUPu(t) which represents the average network

contention level of the subsystem. NOJiU C�BU(t) CHSU(t) _1 _ NOllU n

heavy load status to enhance the QoS of safety

the central controller which is in charge of

When an RSU receives the contention

Vn E N }

each cell. Define a nonempty bounded set

{R" E S IR" � R�'i",

, which represents

the set of feasible utilities that each player can obtain if they cooperate after satisfying its minimum utility.R"ll"

=

(R7"ll, ... R�"ll) is

considered as the disagreement point (e.g., minimum rate requirement in this paper).

And f(S, Rmin ) is the outcome of an N-person

bargaining problem and NBS can provide a

L =l

(6)

L C:SU(t)

(7)

come can be solved via optimization problem

We can infer that CRSU(t) and CUPu(t) must

to further generalize the NBS to allow each

=

CLlPU(t)

=

_1_

I'iRSU

NHSU 11=1

be any number between 0 and 2 because

C�BU(t) E {O, I, 2}. Obviously, the larger it is, the more additional spectrum is needed. Con­ sidering the contradiction between the gains of cognitive spectrum and the overhead of spectrum sensing, we proposed a novel ACSS scheme as in (8).

Ws (t)

=

(W;J2) . C1PU (t)

(8)

W, (t) represents the spectrum sensing window and Wp is the whole bandwidth of where

cognitive spectrum pool. Obviously, the proposed ACSS mechanism can adjust the sensing window according to network traffic load and communication quality.

53

v. COOPERATIVE SPECTRUM

ALLOCATION STRATEGY

unique and fair Pareto optimal operation point under the axioms in [9]. To ensure fairness and efficiency, the out­ in Nash bargaining model. And it is worthy CC to have different bargaining powers. The GBNS can be expressed as

f(S, Rmi" )

=

where (01,

arg

• • •

RET-�'lli' n�=, (R n - R�i")""

,0,,)

0

E [ , U"

L�=l 0"

=

(9)

1, and

en represents the bargaining power for CCn. Without loss of generality, en can be propor­ tional to the communication load level or the minimum requirements. And it is defined as equation (10). On �

(Rmin_s + RlllillJlS) (R::u,,-, + R"UllJ 0::
'" a;

:c



fairness between multi-cells. JF!

=

(Rj

+

R2)2 /(2R� + 2R;)

(20)

R" represents the average rate for each CRY, and R" RJN,,, nE{I,;2}, JFIE[0.5,1]. where

8

=

It can be observed that the proposed scheme

6

can achieve strict fairness for each CRY under different bargaining powers. However, the

4

differences between the cells in a subsystem

2

cause communication outage for the hot cells

are not considered in Max-min scheme, it may with terrible road traffic conditions. o

2

Consider a scenario that a serious traffic

3

jam or an accident has happened in CC-l. Set

Fig.7 Achieva ble rate for cognitive cells with dife f rent inter-cell allocation schemes

Nj=200, N]=80, there are 160 and 30 CRYs which are requesting for safety applications respectively in CC-l and CC-2. The number of available subchannels in the cognitive

x1� 14ri---,---,---,,---,---,---,----,---,---,---,

spectrum pool ranges from 50 to 80, while they are not enough to support the whole safety applications. And then the outage prob­ ability for safety applications is evaluated in Fig.) 0. As GNBS-S scheme gives high priority

"' 1 0 :;:,

to the safety applications, it outperforms the

(J)

traditional allocation schemes and can reduce

e ro

0: (J) :0 '" > (J) :E ()

«

the outage probability to a great extent. VII. CON CLUSION

4

In this paper, we propose a novel centralized

2

CC-VANET framework to solve the contra­ 0.1

0.2

0.3

0.6 0.5 0.4 Bargainng power of CC-1

0.7

0.8

0.9

diction between the increasing demand of diverse vehicular services and the shortage of spectrum resource. Firstly, the ACCS mechanism is developed to adjust the sensing

Fig.8 Achieva ble rate with GNBS allocation scheme

81 can be seen in an intuitive sense. [t is shown

that the cognitive cell with larger bargaining power can obtain more spectrum resource using GNBS scheme. And it can achieve com­ parable fairness with Max-min scheme when the requirements of both cells are similar. The results demonstrate that the generalized bargaining schemes can allocate the resource 57

window according to communication traffic load level and link quality. And then a cooperative bargaining spectrum allocation based on GNBS is proposed to formulate the inter-cell resource allocation in CC­ VANET. With the introduction of bargaining power, the generalized scheme considering PUA can allocate the spectrum resource in a weighted fair manner and favor the hot cells with severe traffic jams or emergency

China Communications· October 2014

- -- - -- - - -- - -- ,

incidences. In addition, an improved scheme

1.1 "

with QoS support for safety service is also developed especially for the heavy load allocation algorithm is proposed for the Simulation results demonstrate that the ACSS mechanism can offer additional spectrum for vehicular communication and reduce the message delay and packet rate loss greatly. And the proposed GNBS scheme can improve the communication reliability considerably

,--

1�·

cases. Furthermore, a practical two-partition two cell scenario in different load statuses.

--;-

>

Suggest Documents