art%3A10.1007%2Fs11277-012-0661-z

Wireless Pers Commun (2013) 69:1749–1772DOI 10.1007/s11277-012-0661-z

Spatial Spectrum Reuse for Opportunistic SpectrumAccess in Infrastructure-Based Systems

Dimitris Tsolkas · Nikos Passas · Lazaros Merakos

Published online: 13 May 2012© Springer Science+Business Media, LLC. 2012

Abstract Opportunistic spectrum access (OSA) receives a constantly growing interest dueto its potential to mitigate spectrum scarcity and meet the increasing communication needsof mobile users. OSA refers to identifying and exploiting spatiotemporal unused portions oflicensed spectrum to allow communication among unlicensed–secondary users (SUs) withoutadverse impact to the licensees (primary users—PUs). Key parameters in OSA are the spec-trum opportunities detection method used by the SUs, and the interference level perceivedby the PUs. A spatial spectrum reuse framework is proposed, where broadcast messagesof an infrastructure-based primary system are exploited and combined with location-awaremethods to detect spectrum opportunities and establish interference-free secondary links.The study of secondary link establishment probabilities revealed a spectrum reuse of upto 25 % for omni-directional and up to 90 % for directional antennas. Moreover, increasedthroughput is achieved in both cases, with directional antennas attaining significantly betterperformance.

Keywords Cognitive radios · Opportunistic spectrum access · Spatial spectrum reuse ·Uplink opportunities · Geometric analysis

1 Introduction

Most existing wireless communication systems operate under a static spectrum assignmentpolicy, which often leads to poor spectrum utilization [1]. On the contrary, the growing

D. Tsolkas (B) · N. Passas · L. MerakosDepartment of Informatics and Telecommunications, University of Athens, 15701 Athens, Greecee-mail: [email protected]

N. Passase-mail: [email protected]

L. Merakose-mail: [email protected]

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1750 D. Tsolkas et al.

requirements for ubiquitous wireless services to support bandwidth demanding applications,call for more flexible spectrum management schemes. A promising approach to more effi-cient spectrum utilization is the opportunistic spectrum access (OSA) under the principlesof cognitive radio networks (CRNs), which attracts a fast growing attention during the lastdecade [2]. OSA users, also referred to as unlicensed or secondary users (SUs), identifyand dynamically use local and instantaneous unused spectrum portions, while keeping theinterference to primary users (PUs) below a predefined threshold [3].OSA involves two basicoperations: (i) detection of opportunities (i.e., available spectrum portions), and (ii) exploi-tation of opportunities.

Opportunities detection is commonly addressed by a spectrum sensing procedure and/ormodeling of PUs behavior. Spectrum sensing includes the sensing method adopted by theSUs at the physical layer (PHY). An interesting survey on spectrum sensing for OSA isprovided in [4]. In the case of modeling PUs behavior, the theory of partially observableMarkov decision processes is a popular approach [5]. Exploitation of opportunities includesthe spectrum access and spectrum sharing operations for the SUs, i.e., the MAC protocolfor OSA. Focusing on ad-hoc network architectures, many MAC protocols for OSA havebeen proposed. A complete classification of these proposals is presented in [6]. Most ofthe proposed solutions use a common control channel (CCC), as an easy way to broadcastinformation to the secondary network, and transfer negotiation messages between secondarytransmitters and receivers [7–10]. Other proposals, which do not require a CCC, impose strictsynchronization among the SUs [11].

Although many of the aforementioned approaches are very interesting and theoreticallyapplicable to any environment, their efficiency varies depending on the specific primarysystem. A different approach is to focus on a random access scheme where the spectrumopportunities are detected by exploiting primary system broadcast messages. As resultedfrom [12], the use of a simple random access protocol rather than an OSA MAC protocol toa mobile ad-hoc (secondary) network that coexists with a cellular (primary) one, leads to alinear relation between the transmission capacities of the coexisting networks. In the field ofspectrum opportunities detection, Tsolkas et al. [13] briefly outlines how spatial spectrumopportunities can be detected by exploiting resource allocation features of the primary sys-tem to avoid the continuous spectrum sensing procedure. Additionally, Wang and Chen [14]shows that topology informed SUs can transmit concurrently and in the same band with PUs,using a carrier sense multiple access with collision avoidance (CSMA/CA) access scheme.

In this paper, we propose an OSA scheme for direct secondary connections during the ULperiod of a primary infrastructure-based wireless communication system. Spatial spectrumopportunities are available to SUs by exploiting broadcast messages transmitted by the basestation (BS) of the primary system, combined with location-aware methods. SUs can exploitthese opportunities by properly adjusting a CSMA/CA protocol to avoid the interference bythe primary transmissions. The main contribution of this scheme is that spectrum sensingand interference to primary users are avoided, while interference to the BS is minimized.During secondary transmissions, the BS (the only primary receiver during UL period) isprotected through location estimation and power control. Both the cases of omni-directionaland directional antennas for SUs are studied, concluding in interference-free transmissionprobabilities and performance analysis, while a throughput comparison between the proposedscheme and existing sensing-based schemes is provided.

The rest of the paper is organized as follows. Section 2 describes the proposed systemmodel while Sect. 3 focuses on the SUs operation. Section 4 includes the analysis of theinterference-free conditions and Sect. 5 provides the throughput analysis of the proposedframework. Finally, Sect. 6 contains conclusions.

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2 System Model

2.1 The Main Idea

The majority of existing OSA approaches adopts a general pattern consisting of a repeatedtwo-phase procedure: spectrum sensing phase and transmission phase. Other approachesavoid spectrum sensing focusing on involving the primary system to directly provide spectrumopportunities information to SUs. The question raised is: can SUs extract this informationwithout a sensing procedure or a negotiation with the primary system?

In this paper, a framework is provided, where SUs with the ability to get synchronizedto the BS of an infrastructure-based primary system, identify spatial spectrum opportunitiesindirectly from the BS broadcast messages. If SUs know the time and frequency of the ULprimary transmissions, they can transmit in parallel by adjusting their transmission poweraccordingly to avoid interfering the BS (i.e., the unique primary receiver during UL). Asshown in Fig. 1, it is possible for the BS to receive data from PUs without noticing anyinterference, and at the same time SUs to use the same spectrum portion to communicatewith each other.

In general, taking into account the large cell radius (several kilometers) and the short oper-ating cycle duration (several milliseconds) of modern infrastructure-based systems such asworldwide interoperability for microwave access (WiMAX) and long term evolution (LTE),the spatial spectrum reuse is a very appealing approach. The decision to operate only duringthe UL period is in-line with the OSA concept that focuses on utilizing licensed spectrumonly when the primary network underutilizes it. Large traffic loads are usually transmittedon the downlink (DL, from the BS to the PUs) forcing a primary system to minimize ULallocation. On the other hand, under low traffic conditions the UL period is extended to assistnew entries, reducing the spectrum utilization. Additionally, during a DL transmission thetotal cell area is covered by the BS’s signals, while in the UL spatial spectrum reuse opportu-nities occur due to the varying locations of the primary transmitters. Finally, interference-freespatial spectrum reuse during the DL requires the knowledge of all PU locations at any time,while during the UL only the location of the unique and static BS is needed. In the proposedapproach, the DL period is used only for overhearing the BS’s broadcast messages to detectUL transmission opportunities, and calculating the maximum allowed transmission power,while all secondary transmissions occur during the UL period.

Fig. 1 System model

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2.2 Basic Principles

Assume a number of PUs and a number of SUs uniformly distributed into a cell area of a typ-ical primary infrastructure-based wireless communication system. Also, for the purpose ofanalysis, let a time division duplex (TDD) mode where time is divided into frames, and eachframe into DL and UL transmission periods. The proposed scheme can be easily extendedand applied also in a frequency division duplex (FDD) system, as explained later.

The BS is responsible for the resource allocation, i.e., for allocating parts of the DL andUL periods to PUs in its cell for receiving and transmitting data from/to the BS, respectively.The UL periods can be allocated using time, frequency or orthogonal frequency divisiontechniques (TDMA, FDMA, or OFDMA). In any case, at most one PU transmits to the BSin every frequency channel for a part of or the whole UL period. Let us refer to this part asUL opportunity.The following options are considered:

• Focus on an infrastructure-based TDD primary system, where a delegate node (BS) isresponsible for the resource allocation procedure in its area cell.

• No cooperation between the primary and secondary system or among SUs is assumed forthe exploitation of transmission opportunities.

• SUs are equipped with standard MAC/PHY layer functionalities of the target primarysystem to be able to get synchronized to the BS and interpret broadcast messages.

• Location-aware capabilities are used by the SUs to identify the BS location and achieveinterference-free conditions.

SUs can use cognitive radios to detect/select a suitable primary system and then get synchro-nized to its BS. The selected primary system can be a single-carrier or multi-carrier (e.g.,OFDM) system. In any case, both time and frequency synchronization is required. Comparedto single-carrier, the timing-synchronization requirements for OFDM systems are in factsomewhat relaxed, since the OFDM symbol structure naturally accommodates a reasonabledegree of synchronization error. On the other hand, frequency synchronization requirementsare significantly more stringent, since the orthogonality of the data symbols is reliant on theirbeing individually discernible in the frequency domain [15]. Depending on the primary sys-tem, the synchronization methods that can be used are based on either pilot symbol or blind-cyclic prefix. Giving an example, WiMAX systems use pilot symbols, while the requiredPHY and MAC layer functionalities (such as time and frequency synchronization, channelestimation, etc.) are supported via a DL preamble transmitted by the BS before the DL frame.

3 SU Operation

Under the principles described above, the SU operation is divided in two parts: the detection ofUL opportunities during the primary system’s DL period, and the exploitation of these oppor-tunities during the primary system’s UL period (Fig. 2). In short, during the DL period, an SUoverhears the BS broadcast messages to identify transmit opportunities for the UL period,and estimates the maximum transmit power that it can use without causing interference to theBS (this power is referred to as the maximum interference-free transmit power—MIFTP).

During the UL period a CSMA/CA protocol is used for sharing the UL opportunitiesamong the SUs, while each SU transmits with power up to the MIFTP to avoid interfere withthe BS. The SU operation is applicable both in TDD and FDD primary systems; however,in the case of FDD systems a variation is needed for the MIFTP estimation as described inSect. 3.2. In the following, the aforementioned operations are analyzed in detail.

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Fig. 2 SU operation flow chart

3.1 Identifying the UL Opportunities

The majority of modern infrastructure-based systems use a part of the DL period to informtheir users (i.e., the PUs) for the frequency band and time duration that they can use for trans-mitting during the UL period. For example, in OFDMA systems such as WiMAX, the DLperiod begins with a downlink preamble that includes the so-called UL-MAP and DL-MAP

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broadcast messages describing the frequency–time regions allocated to each user in the ULand the DL periods, respectively. Knowing the modulation and coding used for transmittingthese messages, the SUs can overhear the UL-MAP to identify the UL opportunities dur-ing the next UL period. Each SU can then randomly select an UL opportunity to attempttransmission. In the proposed scheme, we focus on the exploitation of a single UL opportu-nity, leaving the design of an efficient opportunity selection scheme, other than the randomselection, for our future work.

3.2 Estimating BS Location and MIFTP

After synchronizing with the BS, an SU must estimate the MIFTP. This estimation takes placeduring the DL period using one of many existing approaches as described in the following.The only difference in the case of an FDD primary system is that a two-step estimation mustbe used, because the measurements in the DL band cannot be used for the UL band. Thus, inthe first step, the location of the BS is estimated using the DL band, and then, based on theBS location, the MIFTP is calculated for the UL band.

The majority of the localization schemes (e.g., [16–19]) are based on one or more ofthe following signal metrics: angle of arrival (AOA), time of arrival (TOA), time differenceof arrival (TDOA), and received signal strength (RSS). AOA measures the angles of signalarrivals to estimate their locations, while TOA and TDOA estimate the distance via the prop-agation time. In RSS techniques, either theoretical or empirical models are used to translatesignal strength into distance estimates. In [16], an approximation of the MIFTP is derivedfrom the maximum likelihood estimation (MLE) of the location of the primary transmitter,based on signal strength measurements and the associated Cramer–Rao bound (CRB) on theerror of the estimator. Among others, Mark and Nasif [16] provides collaborative MIFTPestimation when the primary transmitter’s power level is unknown. Also, kin et al. [17] pro-poses a linear, but suboptimal, method to estimate transmission power and location withoutprior information on the transmission power. Porretta et al. [18] provides a technique to esti-mate the location of a mobile terminal in a cell area using a single BS and a triangulationmethod supported by some minimal information about the environment in the BS neighbor-hood. Focusing on RSS techniques, Leu et al. [19] provides a framework to determine themaximum power level at which SUs can transmit without causing harmful interference tothe primary receiver based on a listen-before-talk (LBT) scheme.

SUs can use similar techniques to acquire the BS’s relative or absolute location coupledor not with global localization systems (such as the global positioning system—GPS). Dueto the large cell area and the small operation cycle of modern wireless communication sys-tems, the RSS technique is more suitable compared to time-based. In the proposed scheme,the BS transmission power is unknown, both for omni-directional and directional antennas,and, thus, an approach similar to [16] can be adopted for estimating the BS location andcalculating the MIFTP.

Ambiguous knowledge of the BS’s location, leads the SU to assume that the BS is inside anarea relative to its real location. Considering the worst case, the SU considers the closest pointof this area as the estimated BS’s location. This option results in a decreased transmissionrange for the SU, however, the main requirement for not interfering the BS is fulfilled.

3.3 UL Opportunity Exploitation

Assume that the MIFTPs have been estimated during the DL period and the UL opportunitieshave been identified from broadcast messages. Focusing on one UL opportunity allocated to

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Fig. 3 Applying DCF in the proposed system model

a PU, SUs that are not interfered by this PU can transmit to each other. However, a spectrumsharing mechanism has to take place to resolve SU access conflicts in this opportunity.

The proposed spectrum sharing mechanism is based on the distributed coordination func-tion (DCF) described in the IEEE 802.11 standard [20]. According to the standard, eachstation monitors the channel activity before a transmission attempt. If the channel is idle for apredefined period of time, a four-way handshake technique, known as request-to-send/clear-to-send (RTS/CTS), takes place [21,22]. As an important side effect, the RTS/CTS schemecan also handle the so-called hidden terminal problem, which occurs when pairs of mobilestations cannot hear each other.

If SUi wants to send data to SU j , it monitors the UL opportunity looking for an idle periodequal to DCF interframe space (DIFS). Then, SUi waits for a random back-off time and sendsan RTS message. On receipt of a CTS message from SU j , SUi can start transmitting for therest of the UL opportunity (Fig. 3). As the SUs are synchronized through the primary system,the DIFS idle period at the beginning of the UL opportunity allows them to recognize theexistence (or not) of PU activity. In the case that a PU transmission is detected, the attemptis postponed for an UL opportunity in the next UL frame. However, during the UL period,the BS, which is the only receiver during this time, must be protected against secondarytransmissions. This is achieved by allowing SUs to transmit with power up to the MIFTP.Taking into account that the SUs communicate by applying the DCF procedure during anUL opportunity, only the RTS/CTS messages need to be exchanged with the MIFTP. Thesemessages can be enriched with extra information including SUs’ locations to allow them touse the minimum required power for data exchanging. The analysis of ensuring interference-free conditions during secondary transmissions is given in the Sect. 4 while the performanceanalysis in terms of normalized throughput is included in Sect. 5.

4 Interference-Free Conditions Analysis

4.1 Interference-Free Area

Assume that SUi wants to take advantage of an UL opportunity to transmit to SU j . To avoidinterference from the transmitting PU, both SUs must be located outside its transmissionrange. Let the inverted function g(Ra) describe the path loss model, where a denotes thepath loss exponent and R the distance between transmitter and receiver. Due to the path loss

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effect, the PU’s transmit power is reduced traveling to the BS, thus an extra power margin(denoted by PM) is necessary to result in the required signal-to-noise ratio (SNR) at theBS. Taking into account this power margin, the primary signal travels some more distancebehind the BS reducing to a predefined non-interference threshold. This distance is denotedby D(PM) and calculated as in Eq. (1) as follows:

D(PM) = (g−1(PM))1/a (1)

SUs must be located outside the PU transmission range, denoted here by R(PU), to avoidthe interference caused by the PU transmission. Denoting by d(PU, SUi ) the distance of SUi

from the PU, the probability of this event is referred to as P(d(PU, SUi ) ≥ R(PU)). Addi-tionally, due to the synchronization with the BS, they must be into the cell region. Denotingby d(BS, SUi ) the distance of SUi from the BS, and r the cell radius, the probability of thisevent is referred to as P(d(BS, SUi ) ≤ r).

Assuming that the PU can be at any location into the cell region, the probability for SUi

to be into the interference-free area (IFA) is defined as in Eq. (2):

PIFA(PU, SUi ) ≡ P(d(PU, SUi ) ≥ R(PU)) · P(d(BS, SUi ) ≤ r) (2)

Figure 4 depicts the (IFA), where an SU can be located in, in two different cases: R(PU) ≤r+D(P M)

2 (Fig. 4a) and R(PU) >r+D(P M)

2 (Fig. 4b). “Appendix A” provides an estimationof this probability using Euclidean geometry, and curve (a) in Fig. 5 depicts this estimationfor D(P M) equal to 10 % of the cell radius.

The probability of both SUi and SU j being inside the IFA at the same time is calculatedby multiplying the two probabilities PIFA(PU, SUi ) and PIFA(PU, SU j ). This probabilityis depicted by curve (b) in Fig. 5. Note that this probability also represents the maximumpercentage of the cell region where the spectrum can be reused for secondary point-to-pointcommunications.

Fig. 4 IFA in case a R(PU) ≤ r+D(P M)2 and b R(PU) >

r+D(P M)2

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Fig. 5 No interference probability for D(P M) up to 10 % of the cell radius

4.2 Interference-Free Secondary Link with Omni-directional Antennas

Assume that SUi and SU j are equipped with omni-directional antennas and they can estimateMIFTP using a localization scheme. The estimated MIFTP for a secondary transmitter is anupper bound that delimits the region in which a link between this transmitter and a secondaryreceiver can be established, with no interference perceived by the BS. The maximum allow-able transmission range for SUi , denoted here by R(SUi ), is in practice equal to the distanceto the BS, and it is calculated using the MIFTP of SUi [i.e., MIFTP(SUi )] as in Eq. (3) asfollows:

R(SUi ) = (g−1(MIFTP(SUi ))

)1/a(3)

Thus, the area of maximum communication region is calculated as in Eq. (4) as follows:

A(SUi ) = π · R(SUi )2 (4)

The distance between SUi and SU j , referred to as d(SUi , SU j ), must be less or equal thanthe minimum of R(SUi ) and R(SU j ), as shown in Eq. (5).

d(SUi , SU j ) ≤ min{

R(SUi ), R(SU j )}

(5)

Assume, with no loss of generality, that R(SU j ) < R(SUi ). Due to the circular transmissionof the omni-directional antennas, SU j cannot be closer to the BS than to SUi . Thus, it musthold that the distance between BS and SU j , referred to as d(BS, SU j ), must be more or equalthan the half of R(SUi ), as depicted by Eq. (6).

d(BS, SU j ) ≥ R(SUi )

2. (6)

Also, SUs must be inside the cell region satisfying Eq. (7).

d(BS, SU j ) ≤ r (7)

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Fig. 6 Ci j region in the case a R(SUi ) ≤ r2 and b R(SUi ) > r

2

Assuming a fixed location for SUi , the probabilities of satisfying EqS. (5), (6) and (7) aredenoted by P(d(SUi , SU j ) ≤ R(SUi )), P(d(BS, SU j ) ≥ R(SUi )

2 ), and P(d(BS, SU j ) ≤ r),respectively. Thus, the link establishment probability (LEP) is defined as in Eq. (8):

Pomni (SUi , SU j ) ≡ P(d(SUi , SU j ) ≤ R(SUi )

)

·P(

d(BS, SU j ) ≥ R(SUi )

2

)· P

(d(BS, SU j ) ≤ r

)(8)

Let Ci j denote the region that SU j can be located in while Fig. 6 shows Ci j in two differentcases: (a) for R(SUi ) ≤ r

2 (Fig. 6a) and (b) for R(SUi ) > r2 (Fig. 6b). By definition, Ci j is

the maximum available region where SUi and SU j can communicate due to the fact that itis calculated using both the MIFTPs and the assumption that no PU interferes with them inthis area.

To estimate Pomni (SUi , SU j ), the relation between Ci j (Fig. 6) and the cell region isdetermined. “Appendix B” provides this analysis, while Fig. 7 depicts how Pomni (SUi , SU j )

varies with the distance between SUi and the BS.The need to transmit signals in both directions (e.g., RTS, CTS) requires the commu-

nicating SUs to be outside the PU’s interference area [i.e., satisfy Eq. (2)] and SU j to belocated inside the Ci j region [i.e., satisfy Eq. (8)]. Thus, the probability of establishing aninterference-free link (IFLEP) is defined as in Eq. (9).

Pomni (SUi , SU j , PU) ≡ PIFA(PU, SUi ) · PIFA(PU, SU j ) · Pomni (SUi , SU j ) (9)

As shown in Fig. 8, IFLEP increases as the distances of PU and SUi from the BS are decreas-ing and increasing, respectively. Also, the maximum IFLEP is achieved for the maximumLEP, i.e., when SUi is located at 70 % of the cell radius away from the BS. As the SUi movescloser to the cell boundaries, large part of its transmitting area is located outside the cellregion, leading to slightly decreased IFLEP.

4.3 Interference-Free Secondary Link with Directional Antennas

Assume now that SUi and SU j are equipped with directional antennas, and again SUi wantsto transmit data to SU j during an UL opportunity. The procedure starts by estimating theMIFTP according to a localization scheme for every possible direction. As already

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Fig. 7 Link establishment probability with omni-directional antennas

Fig. 8 Interference-free link establishment probability with omni-directional antennas

mentioned, the MIFTP for a secondary transmitter is an upper bound that delimits the regionin which a link between secondary transmitter and receiver can be established with no inter-ference perceived by the BS. In contrast to the omni-directional case, the SUs must be awareof the BS’s relevant location into the cell and not only the distance to the BS. The MIFTPfor SUi depends on the angle A between its antenna direction and the imaginary line thatconnects it with the BS [i.e., MIFTP(SUi , A)]; thus, the transmission range R(SUi ) is givenby Eq. (10).

R(SUi ) = (g−1(MIFTP(SUi , A))

)1/a(10)

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Fig. 9 Spatial spectrum reuse region for different distances between SUi and BS

The angle parameter A makes the MIFTP calculation more difficult, and also requires the sec-ondary transmitter’s antenna pattern to include the secondary receiver and vice-versa. Takingthese into account, the only feasible solution for SUs is to be located in fixed positions intothe cell, to allow calculation of the communication parameters in advance.

However, using directional antennas the link establishment probability increases due tothe flexibility to avoid the interference to the BS. For example, an SU can be very close tothe BS and turn its antenna to the opposite direction. Figure 9 depicts the spatial spectrumreuse region for different distances between SUi and BS. As shown in Fig. 9, a protectedarea around the BS must be clear due to the existence of undesirable pattern lobes behindthe SU’s antenna. The LEP in this case is denoted by Pdirect (SUi , SU j ), and is determinedin “Appendix C”. Figure 10 depicts this probability for different distances between SUi andBS.

Including the PUs activity in the calculation, an interference-free link establishmentrequires each SU to be out of PU’s interference area [satisfy (2)] and SU j to be locatedinto the appropriate region denoted as Ci j in Fig. 8. Thus, the probability of an interference-free link establishment (IFLEP) in this case is defined as in Eq. (11).

Pdirect (SUi , SU j , PU) ≡ PIFA(PU, SUi ) · PIFA(PU, SU j ) · Pdirect (SUi , SU j ) (11)

As shown in Fig. 11, the IFLEP increases as the PU is located closer to the BS. Also, themaximum IFLEP is achieved when SUi is located at the cell boundaries. Compared to omni-directional antennas, IFLEP is how much higher due to the flexibility to transmit directly tothe target SU and, thus, affect a much smaller part of the cell.

4.4 Selecting Antennas for SUs

According to the analysis presented above, the probability of establishing an interference-freesecondary link is much higher in the case of directional antennas (up to 90 % when the PU isvery close to BS and SUi is at the cell boundaries). However, directional antennas require theknowledge of the secondary destination’s location. Additionally, mobility is hard to supportbecause of the location reconfiguration that must take place before communication. On theother hand, SUs with omni-directional antennas can reuse up to 25 % of the cell region with

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Fig. 10 Link establishment probability with directional antennas

Fig. 11 Interference-free link establishment probability with directional antennas

no direction reconfiguration. Using the above analysis, the link establishment probabilitiesare calculated under a single-channel (single UL opportunity) primary system. Assume that,in a multichannel primary system (multiple UL opportunities), SUs can independently selectone of the channels to communicate. For S channels (UL opportunities) in the system, eachSU has S communication opportunities, each one calculated by Eqs. (9) and (11) for omni-directional and directional antennas, respectively. Assume that SUs and PUs are distributedin a circle around the BS with radius half of the cell’s radius

( r2

); Fig. 12 shows how the prob-

ability of establishing a secondary link increases with the number of channels. As depicted

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Fig. 12 Link establishment probability for different number of channels

in Fig. 12, directional antennas in a single channel primary system attain the same IFLEP asomni-directional antennas in a four-channel primary system.

5 Throughput Analysis

Let the normalized throughput of the secondary system be defined as the fraction of timethat the UL opportunity is used for successful transmission of payload bits. The SUs adopta contention-based access mechanism similar to IEEE 802.11 DCF mechanism, [21,22].According to [21] and [22], the normalized throughput S(n) for contention based access isgiven by Eq. (12).

S(n) = Ps(n) · Ptr · T [data](1 − Ptr ) · σ + Ps(n) · Ptr · Ts + (1 − Ps(n)) · Ptr · Tc

(12)

where,

• n is the number of contending users in the system,• Ps(n) is the successful transmission probability,• Ptr is the probability that there is at least one transmission in a specific timeslot,• T [data] is the payload duration,• σ is the time interval between two consecutive back-off time counter decrements,• Ts is the successful transmission duration, and• Tc is the collision duration.

It must be noted that the number of contending users in the proposed scheme is the numberof SUs that have data to transmit and, also, are not interfered by the PU activity. A UL oppor-tunity starts with a DIFS period allowing SUs to check for the existence of PU transmission.If PU activity is detected, the secondary transmission is postponed for a UL opportunity inthe next UL period.

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Assume that for SUi the PU transmission is detected and, thus, it is blocked for the currentUL opportunity. The blocking probability is given by Eq. (13).

Pblock(PU, SUi ) = 1 − PIFA(PU, SUi ) (13)

where PIFA(PU, SUi ) is as in Eq. (2). If the PU can be at any location inside the cell with thesame probability, then all the SUs have the same blocking probability, which will be denotedby Pblock . Assuming that the total number of SUs is denoted by m the number of SUs thatare blocked by PU activity is referred to as B(m) and calculated by Eq. (14).

B(m) = Pblock · m (14)

Taking into account Eq. (14), the number of SUs involved in the contention at the beginningof the UL opportunity is n = m − B(m).

Let now the DCF procedure applied during the UL opportunity follow a binary expo-nential back-off scheme with minimum and maximum back-off window sizes W and 2bW ,respectively. Assuming that n users are contending for the UL opportunity, the probabilitythat a station transmits in a specific timeslot, denoted by τ , depends on the conditional col-lision probability p, which is also dependent on the number of users n. Adopting the DCFmodeling in [21,22], the probability τ is given by Eq. (15).

τ = 2 · (1 − 2 · p)

(1 − 2 · p) · (W + 1) + p · W · (1 − (2 · p)b)(15)

where p denotes the probability that a transmitted packet encounters a collision. By default,p is also the probability that at least one of the remaining n − 1 users transmits in the sametimeslot as depicted by Eq. (16).

p = 1 − (1 − τ)n−1 (16)

The solution of the nonlinear system of Eqs. (15) and (16) provides the probabilities τ andp for a specific number of contending users.

Given τ, p,, and n, the probability of a successful transmission is the probability thatonly one user transmits given that at least one transmission occurs; the probability Ptr thatat least one transmission occurs is given by Ptr = 1 − (1 − τ)n , as in [21,22]. Also, sincein the proposed scheme the opportunistic transmitter has no knowledge of the opportunisticreceiver location, in the definition of the successful transmission probability the probabilitythat the opportunistic receiver is located inside the opportunistic transmitter range must beconsidered. Let Ps(n) denote the probability of a successful transmission from SUi to SU j .The Ps(n) probability is given by Eqs. (17) and (18) for omni-directional and directionalantennas, respectively.

Ps(n) = n · τ · (1 − τ)n−1

Ptr· Pomni (SUi , SU j ) (17)

Ps(n) = 7n · τ · (1 − τ)n−1

Ptr· Pdirect (SUi , SU j ) (18)

The payload duration T [data], the successful transmission duration Ts and the collisionduration Tc, involved in the throughput expression in Eq. (12), are strongly dependent onthe spectrum access protocol. For the protocol proposed here, it can be shown that theseparameters satisfy Eqs. (19), (20), and (21).

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Table 1 Evaluation parameters Parameter Value

RTS 300 bitCTS 300 bitUL opportunity 5, 000 µsDIFS 50 µsSIFS 10 µsSlot 20 µsPropagation duration 1 µsMin cont. window 5 slotsMax back off stage 32 (25)

Channel bit rate 1 Mb/s

T [data] = ULsi ze − (DIFS + C(p) · σ + RTSsi ze + CTSsi ze

+ 3 · SIFS + AC Ksize) (19)

Ts = ULsi ze (20)

Tc = RTSsi ze + 2 · SIFS + CTSsi ze (21)

where ULsi ze denotes the UL opportunity duration, and C(p) the expected number σ oftime intervals that must be counted down before a transmission occurs. Using the analysisprovided in [21], C(p) is given by Eq. (22):

C(p) = W ·(

(1 − p) − p · (2 · p)b

1 − 2 · p− 1

)(22)

For the evaluation of the proposed framework, the definitions provided above and the param-eters depicted in Table 1 are used.

We assume a simple TDD primary system with time frames of 10 ms equally dividedto DL and UL periods, while each UL period is allocated to one PU. Also, let m SUs beuniformly distributed around the BS into a circular zone with width 10 % of the cell radius.

The normalized throughput for omni-directional and directional antennas is depicted inFigs. 13 and 14, respectively. As shown in Fig. 12, in the case of omni-directional antennas,the throughput curve is very similar to that of the LEP in Fig. 7. The correlation between thesuccessful transmission probability and the LEP, shown in Eq. (17), affects the total through-put performance. Also, the parameters that affect the LEP indirectly affect the throughputperformance. Focusing on the effect of SU locations, we note that as the circular zone movesaway from the BS, higher MIFTP is possible and, thus, larger interference-free area is avail-able and higher throughput performance is achieved. For zones farther than 45 % of thecell radius away from the BS, normalized throughput can be up to 55–60 %. The maximumthroughput value is achieved for the zone centered around 70 % of the cell radius away fromthe BS where the LEP is also maximized. For zones farther than that, a large part of thetransmitting areas is located outside the cell region, leading to slightly decreased throughput.

Similarly, in the case of directional antennas (Fig. 13), the throughput performance isaffected by the LEP. In this case, the LEP linearly increases as the secondary transmittermoves away from the BS (see Fig. 9). This linear increment is also observed in the through-put curve shown in Fig. 13. However, due to the flexibility of adjusting the transmissiondirection towards the secondary receiver, there is a weak correlation between throughputand SUs’ distance to BS. In general, the normalized throughput ranges from 70 % for SUs

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Fig. 13 Normalized throughput for SUs with omni-directional antennas

Fig. 14 Normalized throughput for SUs with directional antennas

located near the BS, to 80 % for SUs located near the cell boundaries, while there is a slightlydecrement as the number of SUs increases.

The proposed scheme is designed to be applicable in primary infrastructure-based wirelesscommunication systems with very short operation cycle. For this reason, it is based on higherlevel detection of the opportunities (see Sect. 3.1). Most of the approaches in the literaturefollow a generic pattern that allocates probabilistic periods of time for sensing and trans-mitting [6–11]. Assume a single channel primary system and a UL opportunity that occursduring the UL transmission. According to our scheme, the only part of the UL opportunitythat is not exploited for secondary transmission is the contention part at the beginning of theopportunity. This part is used for sharing the opportunity among SUs.

To compare our scheme with existing approaches in the literature, we assume two alter-native schemes: (i) one (referred to as Sense/Contend scheme) where the SUs sense the

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Fig. 15 Normalized throughput comparison

channel to detect an opportunity and then contend for sharing this opportunity, and (ii)another (referred to as Sense/CCC scheme) where the SUs sense the channel to detect theopportunity and use a CCC to share it. The required sensing period depends on the channelbandwidth, the SINR acceptable thresholds and the sensitivity of the detector, and in most ofthe cases some milliseconds are required [23]. For primary systems with fast operation cycleallowing 5–10 ms maximum available time for a secondary transmission, an energy detectoris the most suitable choice due to the low sensing time (at least 0.7 ms according to the fastin-band sensing of the IEEE 802.22 standard) [24].

For both the Sense/Contend and Sense/CCC schemes, sensing can start at any instance oftime with the same probability and, thus, the average case is in the middle of the opportunity’sduration. This means that less than half of the opportunity remains for the data transmission,depending on the sensing duration.

Assuming a 5 ms opportunity and an energy detector requiring 1 millisecond for sensing,the normalized throughput of the proposed and alternative schemes is illustrated in Fig. 15. Asshown in this figure, in the cases that the spectrum sharing is resolved using resources of theopportunity (proposed and Sense/Contend), the throughput value decreases for an increasingnumber of SUs, due to the increased number of collisions. Also, the Sense/Contend approachcannot be practically used for more than 20 SUs because the throughput value is close tozero. In the general case, for both the sensing-based approaches the throughput is up to 20and 35 % for omni-directional and directional antennas, respectively, way below 50 and 70 %that can be attained with the proposed scheme.

6 Conclusions

In this paper, a spatial spectrum reuse framework for OSA in an infrastructure-based TDDprimary system has been proposed. SUs exploit the primary system’s broadcast messagesand location-aware techniques to (i) identify spatial spectrum reuse opportunities for the UL

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period, (ii) avoid interference from PUs transmissions, and (iii) protect the BS from theirtransmissions. The probability of establishing a secondary link using omni-directional ordirectional antennas was studied. The secondary link during the UL opportunity, were per-formed in accordance with a variation of the CSMA/CA protocol. The analysis confirms thatthe spectrum can be efficiently reused with no interference to the primary network and noneed for a continuous spectrum sensing procedure. The main restrictions of the proposedscheme are the need of SUs to stay synchronized to the BS and a decreased transmissionpower when they have ambiguous knowledge of the BS’s location, leading to decreased, butstill sufficient link establishment probability. In any case, the use of directional antennas leadsto substantially better performance than that of omni-directional ones. Future work includesthe extension to exploiting in parallel multiple UL opportunities.

Appendices

Appendix A

The IFA in the case that R(PU) ≤ r+D(P M)2 can be easily calculated using the difference

between the cell area π · r2 and the PU transmission area π · R(PU)2 as shown in Eq. (A1).

IFA = π · r2 − π · R(PU)2 (A1)

However, in the case where R(PU) >r+D(P M)

2 the calculation is more complex and includesthe determination of the S area shown in Fig. 16. The S area is the part of the transmitting area(circle 2) that is not included in the cell area (circle 1) and it is determined via the differencebetween the circular segments ADC and ABC.

Using Euclidean geometry for the circular segment ABC it holds that:

ABC� = r2

2(θ − sin θ) . (A2)

where θ = 2 · cos−1( x

r

)and x is the distance between the center of the circle 1 and the line

segment AC.

Fig. 16 Reference figurefor “Appendix A”

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Also, for the circular segment ADC it holds:

ADC� = R(PU)2

2· (ϕ − sin ϕ) (A3)

where ϕ = 2 · cos−1(

x−d(BS,PU)r

).

Thus, the S area is given by Eq. (A4).

S = R(PU)2

2(ϕ − sin ϕ) − r2

2(θ − sin θ) (A4)

Assumption that a PU is located in any place inside the cell with the same probability, theprobability for an SU to be located inside the interference-free area is: PIFA = IFA

π ·r2 wherethe IFA is given by Eq. (A5).

IFA = π · r2 − π · R(PU)2 + S. (A5)

Appendix B

The Ci j region in the case where R(SUi ) ≤ r2 is calculated using the difference between the

transmitting area π · R(SUi )2 of SUi and the circular segment ABC as shown in Fig. 17a.

Using Euclidean geometry it holds that:

Ci j = π · R(SUi )2 − R(SUi )

2

2(ϕ − sin ϕ) (B1)

where φ = 34 · π due to the fact that the AC line is in the middle of the distance between BS

and SUi (see Fig. 17a).In the case that R(SUi ) > r

2 , the extra calculation of the S area (see Fig. 17b) is required.Using the analysis of “Appendix A” for the circular segments DFE and DGE in Fig. 17b, itholds that

Fig. 17 Reference figure for “Appendix B”

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S = R(SUi )2

2(ϕ − sin ϕ) − r2

2(θ − sin θ) (B2)

and

Ci j = π · R(SUi )2 − R(SUi )

2

2(ϕ − sin ϕ) − S (B3)

The link establishment probability is the probability for SU j to be located in Ci j region, or

Pomni (SUi , SU j ) = Ci j

π ·r2 .

Appendix C

As shown in Fig. 17, the Ci j region for directional antennas can be calculated as in Eq. (C1)as follows:

Ci j = π · r2 − �C AD − �E AF −�AE D −�AFC (C1)

where π · r2 is the cell region.Assume p is the radius of the protected area. It holds that ω = 90◦ (see Fig. 18), thus,

using the Pythagorean Theorem it holds that: E D = FC = √r2 − p2. Also,

�AE D = �AFC = DE · p

2(C2)

�C AD = r2

2· 2 · θ (C3)

and

�E AF = p2

2· � F AE (C4)

where θ = cos−1( x

r

), x is the distance between the center of the cell area (point A) and the

line segment CD, and � F AE = 2 · (π − θ − cos−1( p

r

)). The link establishment probability

Fig. 18 Reference figurefor “Appendix C”

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(LEP) is the probability for SU j to be located in Ci j region and, thus, Pdirect (SUi , SU j ) =Ci j

π ·r2 .

Acknowledgments This research has been co-financed by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of theNational Strategic Reference Framework (NSRF)—Research Funding Program: “Heracleitus II—Investingin knowledge society through the European Social Fund”.

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Author Biographies

Dimitris Tsolkas received his B.Sc. in Computer Science in 2007(ranked 1st) and his M.Sc. in Communications Systems and Networksin 2009 at the Department of Informatics and Telecommunications atthe University of Athens, Greece. He is currently Ph.D. student, andmember of the Green, Adaptive and Intelligent Networking (GAIN)Group, within the Communication Networks Laboratory (CNL) of theDepartment of Informatics and Telecommunications at University ofAthens, Athens, Greece. His research interests are focused on mediumaccess control, radio resource management in heterogeneous networksand green communications.

Nikos Passas received his Diploma (honors) from the Departmentof Computer Engineering, University of Patras, Greece, and his Ph.D.degree from the Department of Informatics and Telecommunications,University of Athens, Greece, in 1992 and 1997, respectively. From1992 to 1995 he was a research engineer at the Greek NationalResearch Center “Demokritos”. Since 1995, he has been with the Com-munication Networks Laboratory of the University of Athens, workingas a sessional lecturer and senior researcher in a number of national andEuropean research projects. He has also served as a guest editor andtechnical program committee member in prestigious magazines andconferences, such as IEEE Wireless Communications Magazine, Wire-less Communications and Mobile Computing Journal, IEEE VehicularTechnology Conference, IEEE PIMRC, IEEE Globecom, etc. Dr. Pas-sas has published more than 80 papers in peer-reviewed journals andinternational conferences and has also published 1 book and 7 bookchapters. His research interests are in the area of mobile network archi-

tectures and protocols. He is particularly interested in QoS for wireless networks, medium access control,and mobility management. Dr. Passas is a member of the IEEE and a member of the Technical Chamber ofGreece.

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Lazaros Merakos received the Diploma in Electrical and MechanicalEngineering from the National Technical University of Athens, Athens,Greece, in 1978, and the M.S. and Ph.D. degrees in Electrical Engineer-ing from the State University of New York, Buffalo, in 1981 and 1984,respectively. From 1983 to 1986, he was on the faculty of the Elec-trical Engineering and Computer Science Department, University ofConnecticut, Storrs. From 1986 to 1994, he was on the faculty of theElectrical and Computer Engineering Department, Northeastern Uni-versity, Boston, MA. During the period 1993–1994, he served as Direc-tor of the Communications and Digital Processing Research Center,Northeastern University. During the summers of 1990 and 1991, he wasa Visiting Scientist at the IBM T. J. Watson Research Center, YorktownHeights, NY. In 1994, he joined the faculty of the University of Athens,Athens, Greece, where he is presently a Professor in the Departmentof Informatics and Telecommunications, and Scientific Director of theNetworks Operations and Management Center. His research interests

are in the design and performance analysis of communication networks, and wireless/mobile communicationsystems and services. He has authored more than 200 papers in the above areas. He has served as the scien-tific director of the Communication Networks Laboratory of the University of Athens in numerous researchprojects, including the projects RAINBOW, WAND, MOBIVAS, WINE, EURO-CITI, POLOS, ANWIRE,E2R, E2RII, E3, Self-NET funded by the European Union. Dr. Merakos is chairman of the board of theGreek Schools Network, and member of the board of the National Research Network of Greece. In 1994,he received the Guanella Award for the Best Paper presented at the International Zurich Seminar on MobileCommunications.

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