Joint Spectrum and Power Allocation for Inter-CellSpectrum Sharing in Cognitive Radio Networks

Won-Yeol Lee and Ian F. AkyildizBroadband Wireless Networking Laboratory

School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlanta, Georgia 30332–0250

Email: {wylee, ian}@ece.gatech.edu

Abstract—Cognitive radio (CR) networking achieves high uti-lization of the scarce spectrum resources without causing any per-formance degradation to the licensed users. Since the spectrumavailability varies over time and space, the infrastructure-basedCR networks are required to have a dynamic inter-cell spectrumsharing capability. This allows fair resource allocation as wellas capacity maximization and avoids the starvation problemsseen in the classical spectrum sharing approaches. In this paper,a joint spectrum and power allocation framework is proposedthat addresses these concerns by (i) opportunistically negotiatingadditional spectrum based on the licensed user activity (exclusiveallocation), and (ii) having a share of reserved spectrum foreach cell (common use sharing). Our algorithm accounts forthe maximum cell capacity, minimizes the interference causedto neighboring cells, and protects the licensed users through asophisticated power allocation method. Simulation results revealthat the proposed inter-cell spectrum sharing framework achievesbetter fairness and higher network capacity than the conventionalspectrum sharing methods.

I. INTRODUCTION

Today’s wireless networks are characterized as a staticspectrum assignment policy. Recently, due to the increase inspectrum demand, this policy is faced with spectrum scarcityat particular spectrum bands. On the contrary, a large portionof the assigned spectrum is still used sporadically leading tounder-utilization of the significant amount of spectrum [1].Hence, dynamic spectrum access techniques are recently pro-posed to solve these spectrum inefficiency problems.

The key enabling technology for dynamic spectrum accesstechniques is the cognitive radio (CR) networking that al-lows intelligent spectrum-aware devices to opportunisticallyuse licensed frequency bands for transmission. In order toshare wireless spectrums with the licensed (primary) users,the unlicensed (cognitive radio) users need to continuouslymonitor the spectrum for the presence of the primary usersand reconfigure the RF front-end according to the demandsand requirements of the higher layers. These capabilities canbe realized by designing the following spectrum managementfunctions [2]: (1) Determine the portions of the spectrumcurrently available (spectrum sensing), (2) select the bestavailable channel (spectrum decision), (3) coordinate accesswith other users for this channel (spectrum sharing), and (4)effectively vacate the channel when a primary user is detected(spectrum mobility).

Among the above spectrum management functions, thespectrum sharing plays an important role in determiningthe performance of the CR network. Especially in theinfrastructure-based CR networks, the total network capacitymainly depends on the spectrum allocation among base-stations, called inter-cell spectrum sharing. Recent research onspectrum sharing has explored two different sharing models:exclusive allocation and common use. The exclusive allocationallows the CR user to use the spectrum exclusively to itsneighbor users. Although the exclusive approach is known tobe optimal [3], it has unfair resource allocation, especially inCR networks where the spectrum availability varies signifi-cantly over time and location. On the contrary, the commonuse approach enables each CR user to share the same spectrumwith its neighbors, mainly focusing on a sophisticated powerallocation method [3], [4]. Although this method can mitigatethe unfairness in resource allocation, it achieves lower totalcapacity than the exclusive allocation due to the existenceof higher inter-user interference. Since most of the researchon spectrum sharing has focused on only one sharing model(either exclusive or common use models), spectrum and powerallocations have not been considered together to date. With ei-ther of these approaches, the infrastructure-based CR networkcannot achieve its objectives, high spectrum utilization and fairresource allocation with interference avoidance.

To address these challenges, we propose an inter-cell spec-trum sharing framework for infrastructure-based CR networksin this paper. More specifically, in this framework, each cellcan exploit the exclusive and common use approaches dy-namically according to the spectrum utilization in its vicinity.In the exclusive allocation, the base-station determines thespectrum band having the highest expected cell capacity. Thisis characterized by the permissible transmission power basedon the primary user activities. If there is no spectrum availablefor the exclusive allocation, our framework switches to thecommon use approach where spectrum selection is based onthe interference and primary user activities in the neighborcells. This helps to realize 1) maximum cell capacity, 2) lessinfluence to neighbor cells, and 3) interference-free uplinktransmission. Furthermore, in order to protect the transmissionof primary networks, the inter-cell spectrum sharing neces-sitates the sophisticated power allocation in both exclusive

978-1-4244-2017-9/08/$25.00 ©2008 IEEE 1

and common use methods. To this end, we propose a jointspectrum and power allocation method where transmissionpower can be determined so as to maximize the cell capacityas well as to avoid interference to primary networks throughtransmission power constraints.

The rest of the paper is organized as follows: In Section II,we describe the limitations of conventional spectrum sharingmethods and motivate the joint spectrum and power allocationapproach. Sections III and IV present the network architectureand our proposed framework for inter-cell spectrum sharing,respectively. In Sections V and VI, we propose the spectrumallocation methods for exclusive and common use models,respectively. In Section VII, we explain the proposed jointspectrum and power allocation method. Performance evalu-ation and simulation results are presented in Section VIII.Finally, conclusions are presented in Section IX.

II. MOTIVATION

In this section we present conventional spectrum sharingmethods, and describe the practical considerations for inter-cell spectrum sharing which are the motivations of our pro-posed work.

A. Related Work

Spectrum sharing has been considered as the main function-ality to determine the total capacity of CR networks [2]. Thereare two different classical approaches in spectrum sharing:spectrum allocation for the exclusive model and the powerallocation for the common use model, which will be explainedin the following subsections.

1) Exclusive Allocation Approach: The spectrum resourcecan be assigned to only one user to avoid interference toother neighbor users. In [5], a graph coloring based collabo-rative spectrum access scheme is proposed, where a topology-optimized allocation algorithm is used for the fixed topology.In mobile networks, however, the network topology changesdue to the node mobility. Using this global optimizationapproach, the network needs to completely recompute spec-trum assignments for all users after each change, resultingin a high computational and communication overhead. Thus,a distributed spectrum allocation based on local bargainingis proposed in [6], where CR users negotiate spectrum as-signment within local self-organized groups. For the resourceconstrained networks such as sensor and ad hoc networks, arule-based device centric spectrum management is proposed,where CR users access the spectrum independently accordingto both local observation and predetermined rules, leading tominimizing the communication overhead [7].

2) Common Use Approach: This solution allows multipleusers to access the same spectrum at the same time. Thus,in this approach, power allocation is the most important partto increase the capacity with less interference to other users.Game theory has been exploited to determine the transmis-sion power of each user [3], [8]. Although this approachcan achieve the Nash equilibrium, it cannot guarantee thePareto optimum, leading to lower network capacity compared

to the exclusive allocation model. In [3], orthogonal powerallocation, i.e., exclusive allocation, is shown to be optimal tomaximize the entire network capacity. However, the commonuse model achieves more fair resource allocation, especiallyin networks with few available spectrums. In [4], a centralizedpower allocation method is proposed that uses a spectrumserver to coordinate the transmissions of a group of linkssharing a common spectrum. In [9], both single channeland multi-channel asynchronous distributed pricing (SC/MC-ADP) schemes are proposed, where each node announcesits interference price to other nodes. Using this informationfrom its neighbors, the node can first allocate a channel andin case there exist users in that channel, then, determine itstransmit power. While both methods consider the spectrumand power allocation at the same time, they do not addressthe heterogeneous spectrum availability which is a uniquecharacteristic in CR networks.

B. Considerations in Infrastructure-based CR Networks

Recent work on spectrum sharing has mainly focused onthe distributed ad-hoc networks. However, the infrastructure-based CR networks have unique challenges which have beenunexplored so far. Since infrastructure-based networks consistof multiple cells, we need to consider not only spectrumsharing inside one cell, i.e., among users, called intra-cellspectrum sharing but also spectrum sharing among multiplecells, called inter-cell spectrum sharing. Furthermore, theinfrastructure-based networks require more strict fairness inresource allocation so as to provide communication channelsto their users with the guaranteed service quality. Here areseveral practical issues we need to consider for the inter-cellspectrum sharing.

1) Heterogeneous Resource Availability: The main differ-ence between conventional wireless networks and CR net-works lies in the primary user activities. Since CR networksdo not have spectrum license, they exploit the spectrumopportunistically and vacate the spectrum immediately whena primary user appears. According to the time and location,each cell experiences different primary user activities, leadingto the heterogeneous resource availability. Also the number ofneighbor cells influences the performance of spectrum sharing.Figure 1 shows the number of available spectrum bands ateach cell in the network topology used for our simulations inSection VIII. The spectrum band is available only when allprimary user activity regions in the cell are idle. Thus, theexpected number of available spectrum bands at a cell j canbe expressed as

∑Ni=1[

∏k∈Ki(j)

P offi (k)] where N is the total

number of spectrum bands, P offi (k) is the probability that the

spectrum i is idle at the primary activity region k, and Ki(j) isa set of primary activity regions in the cell j at spectrum i. Thisshows the spectrum availability of the common use approach.If the exclusive approach is used for spectrum sharing, thenumber of neighbor cells competing for the same spectrumsshould be considered as well. In [6], the lower bound of avail-able spectrum resource, the so-called poverty line, is derivedas [

∑Ni=1(

∏k∈Ki(j)

P offi (k))]/(L+1) where L is the number

2

of neighbor cells. As shown in Figure 1, according to the celllocations, the spectrum availability varies significantly. Fur-thermore, it shows different patterns in both common use andexclusive approaches. For the efficient spectrum utilization, weneed to mitigate this heterogeneous spectrum availability byexploiting common use and exclusive approaches dynamically,i.e., in the limited spectrum environment, the common useapproach helps to increase fairness in user capacity while theexclusive approach is much advantageous in the environmentwith sufficient spectrum resources.

2) Inter-Cell Interference: Since the interference range isgenerally larger than the transmission range [10], the transmis-sion in the current cell influences its neighbor cells. For thisreason, although the current cell does not detect any primaryuser activity in its transmission range, its transmission maycause interference in the neighbor cell detecting primary useractivities. The simplest way to avoid this problem is not touse the spectrum where neighbor cells detect the transmissionof primary networks. If we consider this constraint in theexclusive model, the available spectrum resources becomelower as shown in Figure 1. Therefore, while the exclusivemodel is theoretically optimal, it shows an inefficient spectrumutilization in CR networks. In order to avoid this problemwhile satisfying interference condition, the exclusive allocationis also required to have a power allocation method adaptive tospatial and temporal characteristics of primary user activities.

3) Imperfect Knowledge of Neighbor Cells: Most of thepower allocation schemes based on the common use approachassume that every CR user or a central network entity isaware of all radio information such as the channel gains ofall possible links and all interference information in the net-works [4], [9]. However, in the infrastructure-based networks,it is impossible to obtain all necessary information for powerallocation since there is no direct communication channelamong CR users located in different cells. In order to getthe information of neighbor cells, inter-cell spectrum sharingrequires a cooperation mechanism among the cells. In addition,for a more practical spectrum sharing method, we need the cellcapacity estimation with the minimum amount of informationexchanged with neighbor cells.

III. SYSTEM MODEL

A. CR Network Architecture

In this paper, we consider the infrastructure-based CRnetwork which has centralized network entities such as a base-station in cellular networks or an access point in wirelessLANs1. CR base-stations form a cell and have their own userswhich are uniformly distributed in their coverage. In orderto detect the transmission of primary networks, all CR usersobserve their local radio information and report them to theirbase-station. Based on these local measurements, CR base-stations determine the spectrum availability and allocate thespectrum resource to CR users [11].

1In the remainder of the paper we will use the term base-station to refer tothe central network entity

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

2

4

6

8

10

12

14

Cell id

Exp

ecte

d #

of a

vaila

ble

spec

trum

s

Common useExclusive allocationExclisive allocationwith interference avoidance

Fig. 1. Available spectrum bands at different locations

Figure 2 shows the network model we consider in this paperwhere each base-station j has its transmission range withradius R(j). Here the transmission range (or cell coverage) isdefined as the range within which a transmitted signal shouldbe successfully received [10]. Each cell considers the cells inits interference range as its neighbors. The interference rangeis the area within which other unrelated users will be interferedby the transmission of the current cell [10]. In this architecture,each base-station is assumed to be aware of the informationof its neighbors (radius, location of the base-station, etc) andcapable of communicating with its neighbor base-stations.

For the bi-directional communication, we assume CR net-works use time-division duplex (TDD) which has been adoptedin an IEEE 802.22 [12]. Thus, CR networks have separatetime frames for uplink and downlink transmissions in the samespectrum band. Furthermore, each base-station j has the trans-mission power budget P tot(j) which can be allocated over itsspectrum bands. Another important architectural issue in CRnetworks is how to establish a control channel. The controlchannel plays an important role in exchanging informationregarding sensing and resource allocation. Several methods arepresented in [13], one of which is assumed to be used as thecommon control channel in our proposed method.

B. Primary Network Model

All spectrum bands CR networks can access are assumedto be licensed to different primary networks. We assume thatthe PU activity of spectrum i at PU activity region k can bemodeled as a two state birth-death process with death rateαi(k) and birth rate βi(k). An ON (Busy) state representsthe period used by PUs and an OFF (Idle) state representsthe unused period [11], [14], [15], [16]. Since each userarrival is independent, each transition follows the Poissonarrival process. Thus, the length of ON and OFF periods areexponentially distributed [17]. Based on this model, busy andidle probabilities of the spectrum i can be obtained as follows:

P oni (k) =

βi(k)αi(k) + βi(k)

, P offi (k) =

αi(k)αi(k) + βi(k)

(1)

3

Primary Network Area 2

Primary NetworkArea 1

Primary Network Area 3

Transmission Range (Cell Coverage)

Base-station

Broadcast message

CR user

Interference Range

),( *jjD

)( *jR

* Cell j

)( jR

j Cell

Primary Network Area 2

Primary NetworkArea 1

Primary Network Area 3

Transmission Range (Cell Coverage)

Base-station

Broadcast message

CR user

Interference Range

),( *jjD

)( *jR

* Cell j

)( jR

j Cell

Fig. 2. Network Architecture

Here we assume that the CR network has M available licensedbands and is already aware of PU activities. Furthermore, eachspectrum band can have multiple PU activities according to thelocation as illustrated in Figure 2.

IV. INTER-CELL SPECTRUM SHARING FRAMEWORK

A. Overview

As explained in Section II-B, infrastructure-based CR net-works are required to provide two different types of spectrumsharing schemes: intra-spectrum sharing and inter-spectrumsharing. In order to share spectrum efficiently, CR networksnecessitate a unified framework to support cooperation amonginter- and intra-cell spectrum sharing schemes and otherspectrum management functions. Figure 3 shows the proposedframework for spectrum sharing in infrastructure-based CRnetworks, which consists of inter-cell spectrum sharing, intra-cell spectrum sharing, and event monitoring.

1) Event Monitoring: The event monitoring has two differ-ent functionalities. One is to detect the PU activities, calledspectrum sensing. Here we assume periodic sensing whichhas separate time slots for sensing and transmission [11]. Inaddition, CR users monitor the quality-of-service (QoS) oftheir transmission. According to the detected event type, thebase-station determines the spectrum sharing strategies andallocates the spectrums to each user adaptively based on theradio environments.

2) Intra-Cell Spectrum Sharing: The intra-cell spectrumsharing enables the base-station to avoid the interference tothe primary networks as well as to maintain the QoS of itsCR users by allocating spectrum adaptively based on the eventdetected inside its coverage area. If a new CR user appears inthis cell, the base-station determines its acceptance and selectsthe best available spectrum band if it is admitted. Furthermore,when some of its CR users cannot maintain the guaranteedQoS or lose their connections due to the PU activities, thebase-station should re-allocate the spectrum resource to themimmediately. Also a CR MAC protocol is required to allow

Spectrum Allocation Power AllocationIntra-Cell

Spectrum Sharing(BS-User)

Transmission

Quality Monitoring

Inter-Cell (BS-BS) Spectrum Sharing

Intra-Cell (BS-User) Spectrum Sharing

Event Monitoring

Spectrum Sensing

Cell Capacity Degradation

User CapacityDegradationPrimary User

Appearance

Spectrum Allocation Power AllocationIntra-Cell

Spectrum Sharing(BS-User)

Transmission

Quality Monitoring

Inter-Cell (BS-BS) Spectrum Sharing

Intra-Cell (BS-User) Spectrum Sharing

Event Monitoring

Spectrum Sensing

Cell Capacity Degradation

User CapacityDegradationPrimary User

Appearance

Fig. 3. Inter-cell spectrum sharing framework

multiple CR users to access to the same spectrum band. Theintra-cell spectrum sharing has been widely investigated before[15], [12], [16], [18], [19] and is out of the scope in this paper.

3) Inter-Cell Spectrum Sharing: In CR networks, the avail-able spectrum bands vary over time and space which makesit difficult to provide reliable spectrum allocation. In theinfrastructure-based CR networks, the inter-cell interferencealso needs to be considered in spectrum sharing so as tomaximize the network capacity. In the proposed framework,the inter-cell spectrum sharing is comprised of two sub-functionalities: spectrum allocation and power allocation.When the service quality of the cell becomes worse or isbelow the guaranteed level, the base-station initiates the inter-cell spectrum sharing and adjusts its spectrum allocation.In the spectrum allocation, the base-station determines itsspectrum bands by considering the geographical informationof primary networks and current radio activities. Here theinter-cell spectrum sharing exploits both exclusive allocationand common use approaches adaptively based on time-varyingradio environment. After that, in the power allocation, thebase-station determines the transmission power of its assignedspectrum bands so as to maximize the cell capacity withoutinterference to the primary network. In this paper, we mainlyfocus on the inter-cell spectrum sharing among all functional-ities described here.

B. Distributed Sharing Method

Since each cell has a base-station, intra-cell spectrum shar-ing can be implemented in a centralized manner. However, itis not practical to develop the inter-cell spectrum sharing asa centralized method due to the scalability problem. Further-more, an additional network entity is required to coordinateresource allocation over the entire network. Instead, we intro-duce a distributed method for the inter-cell spectrum sharing.

For distributed sharing, each cell should be aware of theexact information of its neighbor cells. As mentioned inSection II-B, however, it is not feasible for the CR user toobtain all the necessary information from other users locatedin the other cells. Instead, in the proposed method, the base-station exchanges local cell information with its neighbor base-stations through the broadcast messages, called the distributedspectrum sharing messages (DSSMs). This message is as-sumed to be transmitted through the dedicated control channel.

Each base-station broadcasts the DSSM to its neighbor cells

4

periodically. Any conventional distributed MAC protocols canbe used for the transmission of DSSMs. The DSSM can beused not only to exchange sensing and interference informa-tion but also to announce the initiation of spectrum sharing.Once receiving the DSSM with spectrum sharing initiation,the cell prohibits itself and its neighbors from initiating an-other spectrum sharing procedure until it receives the sharingcompletion message, which enables the conflict-free sharingin the multi-cell environment. The following information areconveyed through the DSSMs:

• Spectrum availability: The base-station determines theavailability of all spectrum bands in its transmissionrange by considering the sensing information of its usersand broadcasts this availability to its neighbor base-stations. Furthermore, the base-station needs to announceits current spectrum utilization to its neighbor cells, whichcan be considered for their spectrum allocation.

• Minimum busy interference Imini (j): Local information

measured in the neighbor cells is essential to estimate theinfluence on the neighbor cells when a current cell uses acertain spectrum. However, it is not practical to exchangeall local information with its neighbors. To reduce thecommunication overhead, we use a single representativeinformation among all sensing results. When the PUactivity is detected in spectrum i, the base-station j sendsthe minimum signal strength among all sensing dataobserved in its users, which represents the primary signalstrength plus interference at the border of the PU activity.

• Maximum idle interference Imaxi (j): If no PU activity

is detected at spectrum i, the base station j sends themaximum value among the interference measured in itsusers. Unlike Imin

i (j), this value is observed during thetransmission period, instead of the sensing period, andhence mainly comprised of the interference from otherCR neighbors and noise. Since there is no interferencesource within its transmission range, the maximum idleinterference is likely to be measured at the border of itscoverage.

Above information are used for spectrum and power alloca-tions which will be explained in Sections V, VI, and VII.

V. SPECTRUM ALLOCATION FOR AN EXCLUSIVE MODEL

In wireless communications, the interference range is knownto be larger than the transmission range [10]. Thus, for theinterference-free communications, spectrum band needs to beallocated exclusively to each cell not to be overlapped with thespectrums of its neighbors, which is the traditional approach toavoid interference in cellular networks. However, as describedin Section II, the traditional exclusive approach is not suitableto CR networks, leading to inefficient and unfair spectrumutilization. To solve these problems, we propose a novelspectrum allocation to improve the spectrum availability in theexclusive model by considering the permissible transmissionpower derived from spatio-temporal characteristics of the PUactivity. To simplify the representation, the important symbolsused in the subsequent discussion are summarized in Table I.

TABLE ISYMBOLS USED FOR THE ANALYTICAL MODELING

Symbols Descriptions

N Total number of spectrum bandsWi Bandwidth of spectrum i

P tot(j) Total transmission power budget of CR cell jPmax

i (j) Maximum permissible transmission power of CR cell cell j at spectrum iPpu

i (j, k) PU restricted power of CR cell cell j at spectrum i and region kPi(j) Transmission power assigned to spectrum i in cell jR(j) Radius of CR cell j

P offi (k) Idle probability of spectrum i at region k

Ptemp Interference temperature of spectrum iImax

i (j) Maximum idle interference measured at spectrum i of cell jImin

i (j) Minimum busy interference measured at spectrum i of cell jD(j, j∗) Distance between base-stations of cell j and j∗

Primary Network Area 3

Primary Network Area 2 Primary Network Area 1

Type I

Type III

Type II

Interference range

Border cell

Normal cell

Primary Network Area 3

Primary Network Area 2 Primary Network Area 1

Type I

Type III

Type II

Interference range

Border cell

Normal cell

Interference range

Border cell

Normal cell

Fig. 4. Cell characterization

A. Cell Characterization

As we explained in Section II, even in the same spectrumband, PU activities show different characteristics accordingto the location. Based on this spatial characteristic of PUactivities, the cells in CR networks can be classified as anormal cell and a border cell. While the normal cell hasthe same PU activity region inside its transmission range, theborder cell is placed at the border of the PU activity region,and hence has multiple PU activities as shown in Figure 4.In the proposed method, according to the types of cells in theinterference range, we classify three different scenarios forexclusive spectrum allocation as shown in Figure 4.Type I. No border cell in the interference range: In this case,all cells in the interference range are placed in the same PUactivity region, i.e., the spectrum availability is identical overall cells. If no primary user is detected in a type I cell j, thebase-station can transmit on spectrum i with the maximumpower Pmax

i (j). Otherwise the transmission power is zero.Thus, the probabilities Pr(·) of both cases can be derived asfollows:

Pr(Pmaxi (j)) = P off

i (k′)

Pr(0) = 1 − P offi (k′)

(2)

where k′ is the PU activity region in the interference range.

5

Type II. Border cells in the interference range: Someof the neighbors are border cells, which can restrict thetransmission power of the current cell even though no PUactivities are detected in its transmission range. If the cellj has n PU activity regions in its interference range, it canhave n different permissible transmission powers includingone maximum transmission power Pmax

i (j) and n−1 powersP pu

i (j, k) restricted by a region k.Let K be the set of PU activity regions in its interference

range, and k′ be the region in the transmission range. Inthe type II, its transmission power can be Pmax

i (j) when allPU activity regions in K are idle. If multiple PU activitiesare detected in the interference range at the same time, thetransmission power is determined by the region which allowsthe cell to use the smallest transmission power so as notto violate the interference constraint of other regions (Moredetails are explained in Section V-B). Here we define thedominant regions K∗

k as the set of PU activity regions whichallow smaller transmission power than the region k whenprimary users are detected in all regions. Please note that k′ isnot included in K∗

k. Then the probabilities of each permissibletransmission power can be determined as follows:

Pr(Pmaxi (j)) =

∏

k∈KP off

i (k)

Pr(P pui (j, k)) = P off

i (k′) ·∏

k∗∈K∗k

P offi (k∗)

· (1 − P offi (k)) k ∈ K, k �= k′

Pr(0) = 1 − P offi (k′)

(3)

As explained in Eq. (3), if all regions in K∗k are idle, the

region k can determine the transmission power P pui (j, k). In

this case, the state of non-dominant regions does not affect thetransmission power.Type III. Border cell in the transmission range : The cellis placed at the border of region with multiple PU activities.The probability of Pmax

i (j) is the same as that of Type II.Let the set of PU activity regions in its transmission range beK′. Then the probabilities of P pu

i (j, k) and zero power can bederived as follows:

Pr(P pui (j, k)) =

∏

k′∈K′P off

i (k′) ·∏

k∗∈K∗k

P offi (k∗)

· (1 − P offi (k)) k ∈ K −K′

Pr(0) = 1 −∏

k∈K′P off

i (k′)

(4)

In this case, the CR network can use the spectrum only whenall regions in the transmission range are idle.

In the following subsection, we present how to determinethe permissible transmission power explained above.

B. Permissible Transmission Power

For efficient spectrum allocation, the CR base-station shouldbe aware of the permissible transmission power at eachspectrum preventing the interference to primary networks.This permissible power can be estimated by considering the

idle interference Imaxi (j∗) and the busy interference Imin

i (j∗)conveyed in the DSSMs.

When no PU activity is detected in any neighbors of the cellj at spectrum i, the maximum transmission power Pmax

i (j)can be used in the cell. Let the power propagation functionbe F(.) which is the function of transmission power andthe distance between a transmitter and a receiver. Then themaximum transmission power Pmax

i (j) can be obtained asfollows:

IΔ(j∗) = PtempWi − Imaxi (j∗), j∗ ∈ N (j) (5)

Pmaxi (j, j∗) = F−1(IΔ(j∗),D(j, j∗) + R(j∗)) (6)

Pmaxi (j) = min

j∗∈N (j)Pmax

i (j, j∗) (7)

where IΔ(j∗) is the available power for CR users at a neighborcell j∗, Pmax

i (j, j∗) is the possible transmission power of cellj derived from IΔ(j∗), and N (j) is the set of neighbors ofthe cell j. In the PU activity region, the total interferenceshould be less than Ptemp. From this constraint, we can obtainthe interference margin, PtempWi − Imax

i (j∗) available to CRnetworks. Since the current cell does not use the spectrumi currently, this interference margin is highly probable tobe measured at the farthest border of the neighbor cell j∗.D(j, j∗) + R(j∗) from the current base-station. From this,the maximum possible power Pmax

i (j, j∗) can be derived asEq (6). In order to satisfy the interference condition in allneighbor cells, the base-station chooses the minimum trans-mission power among all Pmax

i (j, j∗) as shown in Eq. (7).If some neighbors are border cells, the permissible trans-

mission power can be determined according to the location ofPU activity regions. In neighbor cells currently busy, Imax

i (·)is not available. In order to estimate IΔ(j∗), we insteaduse Imin

i (j∗), which includes the primary signal strengthand interference components. Assume the primary networkmaintains the minimum SINR γ at its border in the presenceof interference Ptemp. The interference at the border of theneighbor cell Imax

i (j∗) can be estimated as the differencebetween the measured signal strength and the pure primarysignal strength, Imin

i (j∗) − γ · Ptemp · Wi. Then the availablepower can be obtained using Eq. (5).

In this case, the border of the PU activity can be consideredas the nearest border of the neighbor cell j∗ from the currentbase-station. Therefore the permissible transmission power canbe determined so that the received power at the border ofneighbor cell, i.e., D(j, j∗)−Rj∗ from the base-station, doesnot exceed IΔ(j∗). Thus, the restricted transmission powercan be obtained as follows:

P pui (j, k) = min

j∗∈Ni(j,k)F−1(IΔ(j, j∗),D(j, j∗) − Rj∗) (8)

where Ni(j, k) is the set of neighbors of the cell j locatedat region k of spectrum i. Similar to Pmax

i (j) in Eq. (7), theminimum transmission power needs to be chosen for P pu

i (j, k)not to violate the interference constraint in any neighbor cells.

6

PU Idle Region

PU Busy Region

)(1 jiθ

PU Idle Region

PU Busy Region

)(2 jiθ

)}(),({ 21 jj ii θθ=Θ)}(),(max{)( 21max jjj iii θθθ =

PU Idle Region

PU Busy Region

)(1 jiθ

PU Idle Region

PU Busy Region

)(2 jiθ

)}(),({ 21 jj ii θθ=Θ)}(),(max{)( 21max jjj iii θθθ =

Fig. 5. Busy and idle regions based on primary user activities

C. Spectrum Selection

Based on the cell characterization and the permissiblepower, the capacity of each spectrum band can be estimated forspectrum selection, referred to as opportunistic cell capacity.The opportunistic cell capacity Ci(j) is defined as the capacityof spectrum i at the boundary of the transmission range of cellj, which represents the minimum capacity to be provided bythe base-station. According to the cell type, the opportunisticcapacity can be derived as follows:Type I:

Ci(j) = Wi log2(1 +F(Pmax(j), R(j))

Imaxi (j)

)P offi (9)

Type II & III:

Ci(j) = Wi[log2(1 +F(Pmax

i (j), R(j))Imaxi (j)

) · Pr(Pmaxi (j))

+∑

k∈K−K′log2(1 +

F(Pmaxi (j), R(j))Imaxi (j)

) · Pr(P pui (j, k)]

(10)

If the base-station has multiple available spectrum bands forthe exclusive allocation, it selects the one with the highestopportunistic capacity.

VI. SPECTRUM ALLOCATION FOR COMMON USE MODEL

Although the exclusive sharing is known to be optimal intotal network capacity, it is not suitable to CR networks due tothe unfair resource allocation as explained in Section II. In thecommon use approach, the cell can share the same spectrumwith its neighbor cells, which improves fairness but causescapacity degradation due to the inter-cell interference. Tomitigate this effect, the following issues should be consideredin the common use approach:

• Cell capacity maximization: The common use approachaims at finding a spectrum to enable the cell capacity tobe maximized by exploiting spectrum bands adaptivelyto the PU activities.

• Less inter-cell interference: To avoid the capacity degra-dation due to the inter-cell interference, CR networks

need to find the spectrum to cause less influence onneighbor cells.

• Uplink transmission: Unlike the downlink (from base-station to CR users), the uplink shows the differentinterference range according to the location of the users.Since the interference range of the uplink is extendedmuch farther than that of downlink, the uplink trans-mission causes higher interference to the neighbor cells.Furthermore, the uplink transmission is highly probableto interfere with the PU activity detected in its neighborcells.

To address these issues, we propose a two-step spectrumsharing for the common use model, which is explained in thefollowing subsections.

A. Angle-Based Allocation for Uplink Transmission

As explained above, the uplink transmission can cause moresignificant interference to the PU activities at its neighbor cells.Figure 5 shows PU idle and busy regions based on the locationof its neighbors who detect PU activities. When CR usersin the busy region begin to transmit, they interfere with thetransmission of primary networks in its neighbor cells. Thebest way to reduce interference in uplink transmission is touse the spectrum which does not have any PU activities inneighbor cells. If the base-station cannot find this spectrum,alternatively it can exploit the multiple spectrum bands toallow all directions to be covered with their idle regions,referred to as angle-based allocation.

Let Θi(j) be the range of angles for PU idle regions atcell j in spectrum i. Then, to avoid the resource shortage ofuplink transmission, the cell should satisfy the following anglecondition:

Θi(j) = {θ|no PU activity in the direction θ} (11)

∪i∈S(j)

Θi(j) = {θ|0 ≤ θ ≤ 2π} (12)

where S(j) is the set of spectrums assigned to a cell j. Theangle of the idle region can be estimated by the base-station,which is aware of the location information of its neighbors.

If the cell does not satisfy the angle condition for uplinktransmission, the base-station initiates the inter-cell spectrumsharing immediately and finds the proper spectrum band tosatisfy the condition in Eq. (12).

B. Interference-Based Spectrum Allocation

If current spectrum allocation already meets the conditionin Eq. (12), the CR network should consider the capacitymaximization both in terms of the cell and the total networkas explained in the beginning of this section.

The principle of the allocation is as follows: First, for themaximum cell capacity, the cell should find the spectrum withthe lowest interference in its transmission range. However,in order to maximize the total network capacity, the cellneeds to consider the influence on the neighbor cells whenit determines a certain spectrum band. Optimally, we canallocate the spectrum to maximize the total network capacity

7

Used

PUOccupied

Idle Unassigned

Assigned spectrum

Used

PUOccupied

Idle Unassigned

Assigned spectrum

(a)

Event Monitoring

Event Type?

Exclusive Allocation(for assigned spectrums)

Assigned spectrum for exclusive

allocation?

Unassigned spectrum for exclusive

allocation?Uplink

shortage?

Common Use SharingAngle-based

Common Use Sharing Interference-based

Power Allocation

Yes

PU activity

Exclusive Allocation(for unassigned spectrums)

Capacity degradationor Uplink shortage

Yes

No

Yes

No

Event Monitoring

Event Type?

Exclusive Allocation(for assigned spectrums)

Assigned spectrum for exclusive

allocation?

Unassigned spectrum for exclusive

allocation?Uplink

shortage?

Common Use SharingAngle-based

Common Use Sharing Interference-based

Power Allocation

Yes

PU activity

Exclusive Allocation(for unassigned spectrums)

Capacity degradationor Uplink shortage

Yes

No

Yes

No

(b)

Fig. 6. Joint spectrum and power allocation: (a) spectrum status diagram, and (b) flow chart.

if each cell is aware of the channel gain of all possiblelinks to the users both in neighbor and current cells as wellas the interference at those users, which is not practical inthe infrastructure-based networks. Instead we propose a morepractical and intuitive approach. Usually the cell with higherinterference shows less influence on its capacity comparedto the cells with lower interference. When new interferenceis added to the spectrum having low interference, it causeshigh capacity degradation. On the other hand, in case of thecell having higher interference, the degradation of capacityis relatively small even though additional interference is ap-plied. If the capacity becomes below the threshold due tothe additional interference, the base-station will initiate theinter-cell spectrum sharing procedure, and finally release thespectrum with low capacity, which helps to increase fairnessin resource allocation as well as total network capacity. Thus,the cell needs to choose the spectrum bands with the highestinterference in its neighbors. From these observations, wedevise the selection criterion to consider both cell capacity andtotal network capacity together where the base-station choosesthe spectrum so as to maximize the ratio of the interferencein its neighbors Imax

i (j∗) to its own interference Imaxi (j).

Even though the cell satisfies the condition for uplinktransmission in Eq. (12), it is highly probable that primaryusers will re-appear in the assigned spectrum which mayviolate the condition for uplink transmission. Thus, it is muchadvantageous for the cell to choose the spectrum with thewidest idle angle range. By combining this idea with theabove criterion, we can derive the following selection principlefor the common use approach, called an interference-basedspectrum allocation:

i∗ = arg maxi∈S(j)

θmaxi (j)2π

·min

j∗∈N (j)Imaxi (j∗)

Imaxi (j)

(13)

where θmaxi (j) is the maximum idle angle in spectrum i at cell

j as shown in Figure 5. S(j) is the set of available spectrumbands at base-station j. Here, in order to consider the effecton all neighbors, the lowest Imax

i (j∗) is chosen among theinterference measured in neighbors. If the neighbor cell is in

the active region, we can use Imini (j∗)−γ ·Ptemp ·Wi instead

of Imaxi (j∗) as explained in Section V-B.

VII. JOINT SPECTRUM AND POWER ALLOCATION FOR

INTER-CELL SPECTRUM SHARING

In the previous section, we introduced two different spec-trum allocation methods. Once the spectrum is allocated,the transmission power needs to be determined to maximizethe cell capacity. In power allocation, CR networks shouldconsider the interference constraint to protect the primary net-works. Furthermore, in order to maintain the fairness with lesscapacity degradation, inter-cell spectrum sharing is required toallocate the transmission power cooperating with both spec-trum allocations for exclusive and common use approaches.In this section, we describe the power allocation combiningwith the spectrum allocation presented in the previous sectionsand propose a joint spectrum and power allocation method forinter-cell spectrum sharing.

A. Power Allocation

Once the spectrum is selected, the base-station determinesits transmission power over all currently used spectrum bands.Generally a water filling is used to optimally allocate thepower in the presence of noise where capacity is maximizedwhen the sum of transmission power and interference are sameover all frequencies in the spectrum band [20]. However, un-like the general water filling method, in the inter-cell spectrumsharing, each spectrum has an upper power limit according tothe PU activities and spectrum utilization in the vicinity of thecurrent cell. The upper limit can be obtained as follows:

First, if there is no activity of either primary or CR users inthe neighbor cell j∗, the upper power limit P up

i (j, j∗) is thesame as Eq. (6). Second, if a neighbor cell j∗ has a PU activity,P up

i (j, j∗) can be obtained as F−1(IΔ(j∗),D(j, j∗) − Rj∗),which is explained in Eq. (8). Last, if the neighbor cellj∗ currently uses the spectrum i, we need to consider thetransmission of the cell j∗ since Imax

i (j∗) does not containits own signal strength. In this case, we can assume thatthe most portion of maximum interference Imax

i (j) measuredin the current cell comes from the cell j∗. From this, the

8

transmission power of the neighbor cell can be estimated asF−1(Imax

i (j),D(j, j∗)−Rj). Then, the total interference canbe expressed as the sum of the interferences from outside cells,Imaxi (j∗), and interference from its own transmission. From

this, the available power at the farthest border of the cell j∗

from the base-station j can be obtained as follows:

IΔ(j∗) =Ptemp · Wi − [Imaxi (j∗)+

F(F−1(Imaxi (j),D(j, j∗) − Rj), Rj∗)]

(14)

Then P upi (j, j∗) can be derived using Eq. (6). Among all

P upi (j, j∗) obtained above, the base-station j chooses the

minimum as an upper power limit of spectrum i, P upi (j).

Based on the constraints of all assigned spectrums in S(j),we introduce the constrained water filling method for powerallocation as shown in Algorithm VII-A. Here Sr(j) and P r(j)represent the set of remaining spectrums and remaining power,respectively. Sc(j) and P c(j) are candidate spectrums and theexpected power for current water filling procedure.

Algorithm 1 Constrained Water Filling MethodP r = P tot(j), Sr(j) = S(j), Pi(j) = 0, ∀i ∈ S(j)while P r > 0 and Sr(j) �= ∅ do

i∗ = arg mini∈Sr(j)

[(Pupi (j) + Imax

i (j))/Wi + N0]

Sc(j) = {i|Imaxi (j)/Wi < (Pup

i∗ (j) + Imaxi∗ (j))/Wi∗ , i ∈ Sr(j)}

P c(j) = (Pupi∗ (j) + Imax

i∗ (j))/Wi ∗∑

Wii∈Sc(j)

−∑[(Pi(j)+i∈Sc(j)

Imaxi (j)]

if P c(j) > P r(j) thenfor ∀i ∈ Sc(j) do

Pi(j) = Pi(j) + (P c(j) − P r(j)) ∗ Wi/∑

Wii∈Sc(j)

end forP r(j) = 0

elsefor ∀i ∈ Sc(j) do

Pi(j) = (Pupi∗ (j) + Imax

i∗ (j)) ∗ Wi/∑

Wii∈Sc(j)

end forSr(j) = Sr(j) − {i∗}, P r(j) = P r(j) − P c(j)

end ifend while

In the constrained water filling method, the sum of theallocated power and interference cannot exceed the upperlimit of the transmission power, which enables interferenceavoidance with primary networks while maximizing the cellcapacity.

B. Spectrum Sharing Procedures

In the spectrum sharing, it is desirable that the spectrumallocation in the current cell has less influence on the trans-mission of other cells. In the worst case, spectrum allocationcauses the capacity degradation due to the frequent interrup-tion with the transmission of neighbors. Therefore, inter-cellspectrum sharing necessitates a coordination mechanism toreduce unnecessary influence on the entire networks.

To this end, we classify the spectrum as the assignedspectrum and unassigned spectrum. Figure 6 (a) shows thestate-diagram for inter-cell spectrum sharing. The assignedspectrum bands are allowed to be accessed by the current cellwhile the unassigned bands are assigned to other neighbor

cells. The assigned spectrum can have three sub-states, used,PU occupied, and idle according to its utilization. In usedand PU occupied states, the spectrum is currently used bythe current cell and by the primary network, respectively.Spectrum in idle state is assigned to the cell but is not currentlyused. The assigned spectrum can be released to the unassignedonly when it is currently idle and is requested by the neighborcells for their exclusive allocation. In the exclusive allocation,the base-station first considers its assigned spectrum bands.If it cannot find a proper one, it extends its search to theunassigned spectrum bands. If there is no idle spectrum bandavailable for the exclusive use, it switches to the commonuse sharing. In this case, the base-station can choose anyavailable spectrum regardless of its state. Instead, the proposedcommon use allocation provides the capability to select theless influencing spectrum band as explained in Section VI.Through this coordination, each cell has a priority in utilizingits assigned spectrum, which can reduce the unnecessaryspectrum allocation.

Figure 6 (b) describes the flowchart of the proposed jointspectrum and power allocation method. Each cell continuouslymonitors the network status and radio environment throughthe local observations of its users. If one of the followingevents is detected, the base-station initiates the spectrumsharing procedure: 1) capacity degradation, 2) primary userappearance, and 3) resource shortage of uplink transmission.If the detected event is related only to the PU activities, thebase-station turns off its transmission power on that spectrum.If the base-station detects the quality degradation or resourceshortage, it performs the exclusive allocation for the assignedspectrum and then for the unassigned spectrum if necessary.If it cannot find the proper spectrum bands, it turns to thecommon use sharing. If the event is a resource shortagefor uplink transmission, it selects the spectrum having theproper idle angle through the angle-based allocation. If theevent is related only to capacity degradation, it performsthe interference-based allocation. Once spectrum is allocated,each base-station allocates the transmission power over theassigned spectrum bands by considering the total power budgetand transmission power constraints derived from spectrumallocation.

VIII. PERFORMANCE EVALUATION

In this section, we present simulation results on the perfor-mance of the proposed inter-cell spectrum sharing method.

A. Simulation Setup

In order to evaluate the performance of the proposed sharingmethod, we implement the network simulator to support thenetwork topology consisting of multiple cells in 10km x 10kmarea. Figure 7 shows the network topology used in the simu-lation. Here we assume 20 cells which have different numberof users from 20 to 40. The transmission range of each cell isuniformly distributed from 1 to 1.5km. The interference rangeis set to twice larger than the transmission range. Furthermore,we consider 20 10MHz licensed spectrum bands with different

9

−5 −4 −3 −2 −1 0 1 2 3 4 5−5

−4

−3

−2

−1

0

1

2

3

4

5

Km

Km

DSSM exchange

1

2

3

4

18

8

11

19

13

12

6

15

9

14

1017

20

7

5

16

x CR userCR base−station

Cell coverage

Fig. 7. Network topology for simulation

PU activities, αi and βi, which are uniformly distributed in[0.1, 0.5]. Each spectrum band has 2-5 PU activity regions.For the simplicity, each PU activity region on spectrum i isassumed to have the same αi and βi.

In this simulation, we use the free space power attenuationmodel where the channel gain is set to -31.54dB, the referencedistance is 1m, and the path loss coefficient is 3.5. The base-station has 3000mwatt transmission power in total and canallocate up to 600mwatt to each spectrum. The transmissionpower of the CR user is set to 125mwatt. Noise power inthe receiver is -174dBm/Hz. For the protection of primarynetworks, we set the interference temperature to 6dB greaterthan the noise power. The CR network uses the TDD withthe same length of uplink and down link time slots. Whilebase-stations can use the multiple spectrum bands at the sametime, CR users can use only one spectrum for uplink anddown link transmissions, respectively. For the intra-spectrumsharing, we use the proportional fairness principle, i.e., onceusers are assigned to the spectrum, each user is assumed toshare the time slot fairly with other assigned users. Here theminimum QoS requirement for each user is set to 8Mbps.

To evaluate the proposed method, we use three differentexisting spectrum sharing methods as follows:

• Fixed spectrum allocation: Spectrum allocation can beobtained by the coloring method with a maximum propor-tional fairness criterion [5]. Here, each cell is assigned tothe pre-determined spectrum bands and does not changethem regardless of time-varying spectrum availability.Instead, this method considers the number of neighborcells and PU activities.

• Dynamic spectrum allocation: This method is also basedon the same coloring method used in the fixed allocation.However, in this method, spectrum allocation is dynami-cally updated over the entire network whenever spectrum

availability changes, which leads to optimal performancein spectrum sharing.

• Local bargaining: In this method, each cell can negotiatewith its neighbor to obtain spectrum bands when itscapacity is below a threshold [6].

Here we do not consider existing common use sharing methodssince they are not suitable for the infrastructure-based net-works as explained in Section II-B.

B. Total Capacity

First we compare the proposed method with three existingmethods mentioned in the Section VIII-A. Figure 8 shows totalnetwork capacity for both uplink and downlink transmissions.The dynamic allocation uses the graph-based optimizationwith global topology knowledge which leads to the highestcapacity. While the fixed allocation does not require frequentoptimization, it shows lower total capacity due to the lack ofthe channel adaptation. In the bargaining method, each celltakes the spectrum band from other neighbor cells if it cannotsatisfy the QoS. However, since each cell cannot perform thespectrum allocation if its neighbors are currently involvingin other bargaining process, the spectrum utilization becomeslowest than the others. Since the proposed method exploitsthe exclusive and common use model adaptively dependenton the network environments, it achieves a higher downlinkcapacity than the fixed allocation and bargaining schemes, andthe same or slightly lower capacity compared to the dynamic(optimal) spectrum allocation while requiring less computa-tional overhead as shown in Figure 8. One the contrary, theproposed method achieves the same total capacity as the uplinkto the fixed allocation scheme due to the interference constraintimposed by Eq. (12).

C. Fairness and QoS

Here we investigate the capacity fairness, which is also animportant objective in inter-cell spectrum sharing. As shownin Figure 9, existing methods show high fluctuation in theircapacity, especially cells #12-#20 achieve significantly lowercapacities than the other cells. However, the proposed methodmaintains better fairness in capacity over all cells than theother methods. Figure 10 depicts the dynamic adaptationbetween exclusive and common use modes according to thediverse QoS requirements. If the required capacity is rela-tively low, most of spectrum bands are used as the exclusivemode. As the required user capacity increases, the numberof spectrums in common use mode increases. Through thisdynamic adaptation between both modes, the proposed methodcan maintain fairness in capacity. In Figure 11, we observethe QoS violation ratio of each cell, which is defined asthe fraction of time when the QoS of the cell is belowthe minimum requirement. The dynamic and fixed spectrumallocations do not have any QoS guarantee mechanism andjust aim at maximizing total capacity and fairness underthe exclusive sharing mode. On the contrary, the proposedmethod performs the spectrum sharing by considering the QoScondition of each cell. Figure 11 shows that the proposed

10

0 20 40 60 80 100 1200

2

4

6

8

10

12

Simulation time (sec)

Tot

al n

etw

ork

capa

city

(G

bps)

Coloring−based (Dynamic)

Coloring−based (Fixed)

Bargaining (8Mbps)

Proposed (8Mbps)

Proposed

Bargaining (8Mbps) Coloring−based (Fixed)

Coloring−based (Dynamic) User QoS requirement: 8Mbps

(a)

0 20 40 60 80 100 1200

2

4

6

8

10

12

Simulation time (sec)

Tot

al n

etw

ork

capa

city

(G

bps)

Graph−based (Dynamic)

Graph−based (Fixed)

Bargaining (8Mbps)

Proposed (8Mbps)

Proposed

Coloring−based (Dynamic)

User QoS requirement: 8MbpsColoring−based (Fixed)Bargaining (8Mbps)

(b)

Fig. 8. Performance comparison in total capacity: (a) downlink, and (b) uplink.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

10

20

30

40

50

60

70

80

90

Cell id

Ave

rage

use

r ca

paci

ty (

Mbp

s)

Graph−based (Dynamic)Graph−based (Fixed)Bargaining (8Mbps)Proposed (8Mbps)

(a)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

10

20

30

40

50

60

Cell id

Ave

rage

use

r ca

paci

ty (

Mbp

s)

Graph−based (Dynamic)Graph−based (Fixed)Bargaining (8Mbps)Proposed (8Mbps)

(b)

Fig. 9. Performance comparison in capacity fairness: (a) downlink, and (b) uplink.

8 10 12 14 16 18 20 22 24 26 28 300.2

0.3

0.4

0.5

0.6

0.7

0.8

User QoS requirement (Mbps)

Ave

rage

rat

io o

f eac

h sp

ectr

um ty

pe

Exclusive allocation

Common use

Fig. 10. Sharing modes under different QoS requirements

method shows better performance in QoS guarantee. In cell#5, the proposed method shows higher QoS violation ratiothan the other methods but achieves the same or slightly loweruser capacity as shown in Figure 9. Even though the bargainingmethod provides QoS guarantees, it is based on the classicalspectrum allocation and does not consider adaptive powerallocation, which may lead to low spectrum utilization, andhence high QoS violation.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Cell id

QoS

vio

latio

n ra

tio

Graph−based (Dynamic)

Graph−based (Fixed)

Bargaining (8Mbps)

Proposed (8Mbps)

Fig. 11. Performance comparison in QoS violation ratio

D. Interference Avoidance

Another important issue in CR networks is the interferenceavoidance with primary networks which has not been ad-dressed in previous methods. Figure 12 shows the interferenceratio under different sharing schemes, which is defined as theratio of the area violating the interference temperature limitto total area occupied by primary networks. As shown inFigure 12, our proposed method shows similar interferenceratio to other existing methods. In order to protect the primarynetworks, previous methods are assumed to adopt the same

11

0 0.005 0.01 0.015 0.02 0.025 0.030

1

2

3

4

5

6

7

Interference violation ratio

Inte

rfer

ence

vio

latio

n pe

riod

(sec

)

Proposed

Average violation ratio: 1.21%

(a)

0 0.005 0.01 0.015 0.02 0.025 0.030

1

2

3

4

5

6

7

Interference violation ratio

Inte

rfer

ence

vio

latio

n pe

riod

(sec

)

Coloring−based (Dynamic)Average violation ratio: 1.20%

(b)

0 0.005 0.01 0.015 0.02 0.025 0.030

1

2

3

4

5

6

7

Interference violation ratio

Inte

rfer

ence

vio

latio

n pe

riod

(sec

)

Coloring−based (Fixed)Average violation ratio: 1.19%

(c)

0 0.005 0.01 0.015 0.02 0.025 0.030

1

2

3

4

5

6

7

Interference violation ratio

Inte

rfer

ence

vio

latio

n pe

riod

(sec

)

BargainingAverage violation ratio: 1.18%

(d)

Fig. 12. Histogram for interference violation ratio: (a) proposed method, (b) dynamic allocation, (c) fixed allocation, and (d) local bargaining.

strategy used to avoid the inter-cell interference, i.e., CR cellscannot use the spectrum band on which some of their neighborcells detect the PU activities, leading to inefficient spectrumutilization. However, since the proposed method determinesthe transmission power not to exceed the interference tem-perature, it achieves both higher capacity and better fairnesswhile maintaining similar interference avoidance performanceto other previous methods.

IX. CONCLUSIONS

In the paper we present a joint spectrum and power al-location method for inter-cell spectrum sharing in cognitiveradio networks. Although the exclusive method theoreticallyachieves optimal capacity, this approach cannot guaranteethe fair resource allocation which is also an important issuein inter-cell spectrum sharing. Furthermore, for the optimalallocation, it requires spectrum utilization and topology in-formation of the entire network, which causes tremendousoverhead and computational complexity. In order solve theseproblems, first, we proposed a novel spectrum allocation meth-ods for both exclusive and common use models. To exploit theproposed exclusive and common use methods dynamically, wepropose a joint spectrum and power allocation method wherespectrum sharing mode and transmission power are determinedaccording to the QoS requirements, primary user activities andcurrent spectrum utilization. The simulation experiments showthat the proposed sharing method achieves better performancein terms of both network capacity and fairness.

ACKNOWLEDGMENT

This material is based upon work supported by the USNational Science Foundation under Grant No. CNS-07251580.

REFERENCES

[1] FCC, “Et docket no 02-135,” Spectrum Poicy Take Force (SPTF) Report,November 2002.

[2] I. F. Akyildiz, W. Y. Lee, M. C. Vuran, and S. Mohanty, “Next generation/ dynamic spectrum access / cognitive radio wireless networks: asurvey,” Computer Networks Journal (Elsevier), vol. 50, pp. 2127–2159,September 2006.

[3] R. Etkin, A. Parekh, and D. Tse, “Spectrum sharing for unlicensedbands,” IEEE Journal on Selected Areas in Communications, vol. 25,no. 3, pp. 517–526, April 2007.

[4] C. Raman, R. D. Yates, and N. B. Mandayam, “Scheduling variable ratelinks via a spectrum server,” in Proc. IEEE DySPAN 2005, pp. 110–118,2005.

[5] C. Peng, H. Zheng, and B. Y. Zhao, “Utilization and fairness in spectrumassignment for opportunistic spectrum access,” ACM Mobile Networksand Applications (MONET), 2006.

[6] L. Cao and H. Zheng, “Distributed spectrum allocation via local bargain-ing,” In Proc. IEEE Sensor and Ad Hoc Communications and Networks(SECON), pp. 475–486, September 2005.

[7] ——, “Distributed rule-regulated spectrum sharing.pdf,” IEEE JournalOn Selected Areas In Communications, vol. 26, no. 1, pp. 130–145,January 2008.

[8] Z. Ji and K. J. R. Liu, “Dynamic spectrum sharing: A game theoreticaloverview,” IEEE Communications Magazine, vol. 45, no. 5, pp. 88–94,May 2007.

[9] J. Huang, R. A. Berry, and M. L. Honig, “Spectrum sharing withdistributed interference compensation,” in Proc. IEEE DySPAN 2005,no. November, pp. 88–93, 2005.

[10] M. G. K. Xu and S. Bae, “How effective is the IEEE 802.11 RTS/CTShandshake in ad hoc networks?” in Proc. IEEE Global Telecommunica-tions Conferebce (Globecom) 2002, pp. 72–76, November 2002.

[11] W. Y. Lee and I. F. Akyildiz, “Optimal spectrum sensing framework forcognitive radio networks,” IEEE Transactions on Wireless Communica-tions, vol. 7, no. 9, September 2008.

[12] IEEE 802.22 WG, “Draft standard for wireless regional area networkspart 22: Cognitive wireless RAN medium access control (MAC) andphysical layer (PHY) specifications: Policies and procedures for opera-tion in the TV bands,” IEEE P802.22/D0.3.8.1, September 2007.

[13] D. Cabric, S. M. Mishra, D. Willkomm, R. Brodersen, and A. Wolisz,“A cognitive radio approach for usage of virtual unlicensed spectrum,”in Proc. 14th IST Mobile and Wireless Communications Summit, June2005.

[14] C. Chou, S. Shankar, H. Kim, and K. G. Shin, “What and how muchto gain by spectrum agility?” IEEE Journal on Selected Areas inCommunications, vol. 25, no. 3, pp. 576–588, April 2007.

[15] W. Y. Lee and I. F. Akyildiz, “A spectrum decision framework forcognitive radio networks,” submitted for publication, 2008.

[16] Q. Zhao, L. Tong, A. Swami, and Y. Chen, “Decentrallized cognitivemac opportunistic spectrum access in ad hoc networks: A pomdp frame-work,” IEEE Journal on Selected Areas in Communications, vol. 25,no. 3, pp. 589–600, April 2007.

[17] K. Sriram and W. Whitt, “Characterizing superposition arrival processesin packet multiplexers for voice and data,” IEEE Journal of SelectedAreas in Communications, vol. SAC-4, pp. 833–846, September 1986.

[18] T. Chen, H. Zhang, G. M. Maggio, and I. Chlamtac, “CogMesh: acluster-based cognitive radio network,” in Proc. IEEE DySPAN 2007,pp. 168–178, April 2007.

[19] J. Tanga, S. Misrab, and G. Xueb, “Joint spectrum allocation andscheduling for fair spectrum sharing in cognitive radio wireless net-works,” Computer Networks Journal (Elsevier), vol. 52, no. 11, pp.2148–2158, August 2008.

[20] C. E. Shannon, “Communication in the presence of noise,” Proceedingsof the IEEE, vol. 72, pp. 1192–1201, September 1984.

12