a hybrid spectrum mobility and handover protocol in 3gpp...
TRANSCRIPT
A Hybrid Spectrum Mobility and HandoverProtocol in 3GPP Cognitive LTE Systems
Yuh-Shyan ChenDepartment of Computer Science
and Information Engineering,National Taipei University
Email: [email protected]
Ching-Hsiung ChoGraduate Institute of
Communications Engineering,National Taipei University
Email: [email protected]
Abstract—Many researches show that the current ap-proach of fixed spectrum allocation caused the most ofidle resources being unused by other wireless devices.Cognitive Radio (CR) is the novel system that improvesthe low utilization spectrum, with software-defined radio(SDR) devices of reconfigurable and switching spectrumresources to enhance the appropriate spectrum access andsharing. The new network technology long term evolution(LTE) systems have been proposed and this technique hashighly flexible bandwidth and spectrum agile to satisfythe CR network. For the purpose of spectrum selectionand mobility, we propose a hybrid spectrum mobility andhandover protocol that based on the Poisson distributionof spectrum resources and consider the different spectrumholes characters to compute the expected transmission timeof each spectrum hole. The minimum expected transmis-sion time makes an appropriate spectrum holes selectionto spectrum mobility and the makes the secondary userto select the adaptive base station to handover. Simulationresults have shown that the proposed protocol is able toselect spectrum holes adaptively and reduce the spectrummobility ratio.
Index Terms—Cognitive, mobility, LTE, software de-fined radio (SDR), handover.
I. INTRODUCTION
In recent years, Internet users a way to usenetwork access technology has been vigorous de-velopment of the current wireless network graduallyreplaced the limited network. Due to the wirelessnetwork bandwidth constraints can not fully takeadvantage of all of the radio spectrum resources formobile devices and power supply can not continueto use, and the free radio spectrum resources isvery frequent. According to Federal Communica-tions Commission (FCC), temporal and geograph-ical variations in the utilization of the assigned
spectrum range from 15% to 85% (2)(3). In order toimprove the utilization of the overall radio spectrum,the cognitive radio (CR) network is a solution to thislow utilization of the radio spectrum.
The concept of CR is first presented by JosephMitola III and Gerald Q. Maguire, Jo. (4). In CRnetworks, there are two types of users; one is tolicensed users (primary users, PUs), and the otheris unlicensed users (secondary user, SUs). PUscan access the wireless network resources anytimeand anywhere. Unlike the PUs, the SUs only takeadvantage of these radio spectrum resources whenPUs unused. When PUs reclaim the radio spectrumresources, the SUs must move away the currentradio spectrum resources at once and switch to otheridle radio spectrum resources.
With the development of wireless network tech-nology, the wireless mobile access has been pro-gressed by second-generation (2G) and third-generation (3G) cellular systems. In recent years,the Third Generation Partnership Project (3GPP) hasproposed a 3G long term evolution (LTE) (6)(5).LTE is based on the universal terrestrial radio access(UTRA) and high speed down-link packet access(HSDPA) and further strengthen its communicationscapacity to upload in order to enhance its qualityof service can be provided. LTE have to coexistwith 2G/3G systems, WLAN, WiMAX, etc. SinceLTE have highly flexible bandwidth and LTE ishave possible to use communication device in manydifferent bands with facility for reprogramming ifthe operator you are using communication devicewith has completely different frequency band it isbeing proposed that Software Defined Radio (SDR)
be used with LTE.
SDR is a revolutionary technology (7). SDR maychange the wireless industry, and the restrictionson mobile communication system are solved. SDRis the first research and development in order tointegrate communication capabilities between U.S.militaries. SDR can dynamic set up different net-work protocol when mobile terminal with SDRdevice in different networks. In addition to recon-figurable property, in the CR network the SUs withSDR device use the physical layer of the sensingtechnology to periodically cycle sense the currentsignal strength and the idle spectrum resources (orcalled spectrum holes). With these information, SUsdynamically select a suitable spectrum hole to usewithout interfering with PUs.
In this paper, to achieve layer two spectrum mo-bility and layer three handover selection. SUs withSDR device perform the following three phases;(1) environment observation, (2) computation andanalysis, and (3) evaluation and transmission. Inthe environment observation phase, the secondaryusers (SUs) collect the spectrum bands informationand other communication parameters by the SDRdevice. In the computation and analysis phase, thecollected information is analyzed to understand thecharacters of every spectrum hole. The charactersof each spectrum hole are prepared for the nextphase. In the evaluation an transmission phase, thesecondary users evaluate expected transmission timeof each spectrum hole for SUs service data. Thespectrum hole with minimum expected transmissiontime to complete SU service has more opportunityusage without interruption. For layer two purposes,the spectrum hole with minimum expected transmis-sion time of spectrum hole is selected to spectrummobility. The minimum expected transmission timeof spectrum hole make the layer three select theadaptive base station to handover.
The remainder of this paper is organized asfollows. In section II, related works are described.section III overviews the system architecture, andthe basic ideas of the proposed schemes. sectionIV describes the proposed hybrid spectrum mobilityand handover protocol. Performance evaluation ispresented in section V. section VI concludes thispaper.
II. RELATED WORK
In layer two solution, the dynamic spectrum allo-cation (DSA) mainly focuses on how to exploitingtemporal and spatial traffic statistics to allocate thespectrum to SUs. In recent years, DSA has beena gate of heat research because of its potentialto exploit highly under utilized wireless spectrumresource. DSA make the CR with more frequencyagility by sensing the spectrum holes and automat-ically tuning to the adaptive frequency channels.Many research of DSA has proposed based on thesystems that composed of SUs equipped with CRsystems that aim to utilize spectrum holes that arenot being used by PUs.
Ohyunet al.(8) proposed a spectrum matching al-gorithms which consider the user QoS and spectrumcharacteristics to efficiently allocate spectrum holesfor SUs in the CR base station architecture. Forminimizing the probability of spectrum handoverand satisfying the service of SUs, the spectrummatching algorithm focus on the different servicesof SUs and the spectrum hole of different sizesand holding time, according the differences thespectrum matching algorithm select the require timeof service that most closest to the spectrum holdingtime to assign spectrum hole. These spectrum beclassified by the similar holding time, each SUshould calculate the service require time itself, thenthe CR base station according to the service requiretime to select a holding time class and random aspectrum hole in the class to allocate the spectrumhole to SU.
Akbar et al.(9) proposed a Markov-based Chan-nel Prediction Algorithm (MCPA) and the channeloccupancy of PUs is assumed to be passion dis-tribution, it is based on the hidden Markov model(HMM). HMM is a finite state machine that canpredict the appearance of spectrum holes in differentspectrum bands. The first of MCPA operation needto observe channel usage patterns and update HMMparameters, then predicting channel availability andoccupation using HMM and decide whether the SUshould remain in the same spectrum or move toothers.
Hoyhtyaet al.(10) propose a simple classificationand learning of predictive channel selection method.In this method the author presents the architecture
Fig. 1. Example of inter-cell interference coordination.
for predictive CR systems for statistics of spectrumsensing results and the channel history. In order tochoose the channel with the largest idle time, theauthor classifies the network traffic pattern to fourtypes. According to the different types of trafficpattern the predicting results is different in eachtypes. The prediction of idle times with periodictraffic patterns, the history information support toexact predicts future channel idle times. The predic-tion of idle times with random traffic patterns, thepredictive idle times is calculated by the detection ofthe available idle time. For availability using the idlechannels the probability of predictive idle time mustbe greater than 50%. When the current channel usedby SU has been occupied by PU, SU utilize the pastchannel history information to predict the spectrumavailability and select a channel with maximumidle time, and then switch to the channel withoutinterfering the PUs.
III. PRELIMINARY
In this section, we first describe the assumptions,LTE systems architecture, and we proposed systemmodel, and then we explain the challenges, the basicidea and the main contributions of this work.
A. LTE system architecture
The LTE systems provide frequency orthogonal-ity between users in both uplink and downlinkwithin a cell. Therefore, the performance of the LTEsystems in terms of available data rates and spec-trum efficiency is limited by interference from othercells (inter-cell interference). Inter-cell interferencecoordination is a scheduling method which the daterate are increased in the cell edge by taking inter-cell interference into account. Inter-cell interferencecoordination infers certain (frequency domain) re-strictions to the uplink and downlink schedulersin a cell to handle the inter-cell interference. Byrestricting the parts of the spectrum of transmissionpower in one cell, the interference appeared in theneighboring cells in this part of the spectrum willbe reduced. This part of the spectrum can provide
new_eNBold eNBPU1'
PU1
PU2
S1 S1
IMS
Server
HSS
P-GW
Internet
MME1/S-GW1
SGi
S6a
MME2/S-GW2
S6a
S5 S5
SU SU SU
X2
Fig. 2. System model.
higher data rates for user in the neighboring cell.in reality, the frequency reuse factor is different indifferent parts of the cell, shown as Fig. 1.
The other characteristic of LTE systems is thespectrum agility. The LTE systems support moredifferent bandwidth of channels. This characteristicof LTE systems is similar to the CR network,The proposed scheme presents the LTE systemsbased on CR to achieve the full frequency spectrumutilization. As shown in Fig. 2, the system modelconsist of the LTE core systems, PUs and SUs. SUshave opportunity to use the unoccupied spectrumby PUs and connect to the Internet throughout theLTE core systems. In the system model, SU movesas shown in Fig. 2. The initial location of SU isnot in the overlapped area. If the PU appeared,SU performs the proposed algorithm and selectsan adaptive spectrum hole to spectrum mobility.When the SUs move to the overlapped area. SUmoves from SU’ to SU”, there are two eventshappened, one is the spectrum mobility, and theother is handover to neweNB. In the proposedalgorithm, the algorithm focus on the mobility ofSUs in the overlapped area and non-overlapped area.The proposed scheme aims to decide the adaptiveallocation of spectrum holes for SUs.
B. Basic idea and challenge
The proposed scheme observes the spectrum oc-cupied ratio to predict the probability of the resourcereclaiming by PUs and the received signal strengthto perform handover to an appropriate base station(BS). The proposed scheme to achieve low trans-mission time, high successful rate, and throughput.In the proposed scheme, the expected transmissiontime of spectrum hole is mainly considered. Let
Observe environment
(mobile terminals)
Computation and
analysis
Evaluation and
transmission
Available spectrum holes
And characters
Switch spectrum hole
or handover base station
Information of radios
and SU requirements
Fig. 3. Cognitive cycle.
TE(SHi) denote as the expected transmission timeof spectrum holei for SU’s service data. WhenTE(SHi) is large, this represents the expected trans-mission time of the spectrum hole is higher, andthen SUs have to bear greater risks of PUs reclaimedresources. This may cause frequent spectrum mo-bility and handover. On the other hand, the smallertheTE(SHi) has high successful rate of service datatransmission without the PUs reclaimed resources.Hence, the minimumTE(SHi) is the basis fordecision-making.
The proposed scheme provides an overview ofthe cognitive cycle shown in Fig. 3. There are threemain steps on the cognitive cycle: environment ob-servation, computation and analysis, and evaluationand transmission. The detail as following.
• Environment observation - in the CR the SUsmonitor the spectrum utilization, received sig-nal power, and detect the appearance of PUs.
• Computation and analysis - according to ob-served information to analyze the spectrumhole characters such as transmission rate, un-occupied rate, etc.
• Evaluation and transmission - evaluate the ex-pected transmission time of SU service trans-mission by each spectrum hole, and then selectone to spectrum mobility and help the layerthree decision to handover adaptive base sta-tion.
In Hoyhtya et al.(10) proposed scheme, shownas Fig. 4(a), letTON denotes channel be occupiedby PU ,TOFF denotes the channel is idle,Tidle de-notes the channel idle time. the scheme divides thetime intoTON andTOFF . According to periodicallyrecorded the channel idle time, the next period thechannel idle time is acquired, and the channel withmaximumTidle is the best choice. In Fig. 4(a) theSU performs spectrum mobility formCH4 to CH1
with the maximumTidle. But the channel with themaximum idle time maybe not the appropriate in
new_eNBold eNB
SU
X2
S1 S1
IMS
Server
HSS
PU1
PU1
PU2
P-GW
Internet
MME1/S-GW1
SGi
S6a
MME2/S-GW2
S6a
S5 S5
TON
Tidle
TOFF
Sense & switch Remaining idle time
Tidle= 15s
(2 RB)
Tidle= 8s
(7 RB)
Tidle= 10s
(5 RB)
CH6
CH5
CH4
CH3
CH2
CH1
(a)
new_eNBold eNB
SU
X2
S1 S1
IMS
Server
HSS
PU
PU
PU
P-GW
TE=5s (2 RB)
TE=6s (7 RB)
TE=4s (5 RB)
Internet
MME1/S-GW1
SGi
S6a
MME2/S-GW2
S6a
S5 S5
Data
TE
TON TOFF
treq
Pu
CH6
CH5
CH4
CH3
CH2
CH1
(b)
Fig. 4. (a)The comparative scheme with the maximum idle time,(b)The proposed scheme with expected transmission time.
the proposed system model. Because the channelsize is different, the idle channel with the maximumidle time may be the minimum channel size. Ifthe maximum idle time channel with minimumchannel size is selected, the data need more timeto finish the transmission. But the more time thedata transmission need, the higher probability ofinterrupt. Therefore, in the proposed scheme, the
new_eNBold eNB
SU
X2
S1 S1
PU3PU2 SU
PU1
PU1'
IMS
Server
HSS
P-GW
Pu=0.7
TE=5s
Pu=0.3
TE=6s
Pu=0.5
TE=4s
11 dB10 dB
Pu=0.7
TE=4s
Pu=0.3
TE=8s
Pu=0.5
TE=5s
Internet
MME1/S-GW1
SGi
S6a
MME2/S-GW2
S6a
S5 S5
1
2SH2
SH1
SH3
SH2
SH1
SH3
Data
Fig. 5. The proposed scheme with expected transmission time.
number of PU reclaim spectrum hole in unit time ismain consideration, shown as Fig. 4(b), we assumethe spectrum hole size is equal to Fig. 4(a) channelsize, and then compute the SU service needed time.Let treq denotes the SU service required time,SHi
denotes theith spectrum hole, andPu(SHi, treq)denotes the probability of spectrum hole unoccu-pied by PUs. The probabilityPu(SHi, treq) is thespectrum holeSHi unoccupied probability in thetreq period. Calculation of the above parametersand consider the element of spectrum mobility, theSU service expected transmission time is evaluated.The proposed scheme supports flexible spectrumhole size, and this characteristic make the proposedalgorithm more considered. Because the differentspectrum hole size has different occupied proba-bility. Although the large of the spectrum holeshave fast transmission rate but the occupied rangeof frequency bands is wide. When PUs reclaimedspectrum resource, the spectrum resource is easilyoverlap with the spectrum hole. This cause thespectrum mobility ratio become higher. In steadof the smaller spectrum holes size are not easyto be occupied by PUs. The result of maximumexpected transmission time is selected. Then SUmoves from current spectrum holeCH4 to CH3
with the minimumTE .In the proposed scheme, when SU moves to the
center area of the overlapped area. The variation ofthe SNR makes the different BS spectrum holes oftransmission rate different. This factor may affectthe final outcomeTE . Hence, in Fig. 5, there aretwo sub cases happened, one performs spectrum
mobility in original old eNB, because of the min-imum TE of old eNB spectrum hole is lower thanthe minimumTE of new eNB spectrum hole with alayer three handover delay time, SU has a adaptivechoice of stay oldeNB to spectrum mobility. If theminimum TE of old eNB spectrum hole is greaterthan the neweNB spectrum hole with a layer threehandover delay time, this represent the spectrumholes of the oldeNB is the worthless choice, andthen SU handover to the neweNB.
IV. HYBRID SPECTRUM MOBILITY AND
HANDOVER PROTOCOL
This section presents the hybrid spectrum mo-bility and handover protocol in 3GPP cognitiveLTE systems. The proposed scheme evaluate theexpected transmission time of every spectrum holeto select the minimum expected transmission time ofspectrum hole to layer two spectrum mobility, andthe decision for layer three to handover an adaptivebase station. This scheme is split into three phase;(1) environment observation, (2) computation andanalysis, and (3) evaluation an transmission. LetSUx denotes thexth secondary user in the systems.In the phase of evaluation an transmission , thesecondary users (SUs) collect the information bythe SDR device. In the phase of computation andanalysis, the collected information is analyzed tocharacters of every spectrum hole. The charactersof each spectrum hole prepares for the next phase.In the phase of evaluation an transmission, thesecondary users evaluate expected transmission timeof each spectrum hole in transmitting the servicedata.
A. Phase of environment observation
The main task of this phase make use of SDR toobserve the signal power from the base station (BS),usage of each resource block, andSUx require-ments. The above information is acquired to knowthe spectrum distribution and utilization. As shownin Fig. 7, theSUx periodically senses the spectrumbands of each resource block in order to acquirethe information of each resource block occupiedfrequency and spectrum holeSHi that consistingof mi resource blocks. Letλmi
is number of timesthat mith RB be occupied in the time period. Ifthe λmi
is large, the PUs frequently occupied the
RB lower the opportunity of RB usage. Otherwise,if the λmi
is small, SU has more opportunity touse the RB without interrupted by PUs. The signalstrength is the basis on the wireless communicationsystems. The signal information assistSUx to getthe location from BS, and the transmission quality.The observation phase is operated as following.S1 SUx sense allRB in the spectrum bands, and
the continue idleRB regard as the spectrumholes (SH1, SH2,· · ·,SHi). And then eachRB occupied frequencyλmi
is also recordedin a time period. The signal strength theSUx
received record in every sensing period.S2 WhenSUx has requirement to spectrum mo-
bility or handover,SUx evaluates the currentservice data sizedt and trigger a request tonext phase.
B. Phase of computation and analysis
In the computation and analysis phase, due toSUx detectedPUy appearance, the proposed schemetriggers SUi to receive the observed informationfrom physical layer and then analyze the observedinformation in order to acquire the spectrum char-acters. The spectrum characters such as bandwidth,transmission rate, and signal to noise ratio (SNR)are important to evaluate the expected transmissiontime of SUx service. However,SUx in the over-lapped area and the non-overlapped area is different.Hence, the proposed scheme divides the system intotwo cases, the two cases are illustrated in section4.2.1 and section 4.2.2, respectively.
1) Secondary users in the non-overlapped area:In the non-overlapped case,SUx has only one avail-able serving BS, and then analyzes the spectrumcharacters of the BS. According toSUx receivedsignal from the BSs. If the received signal strengthfrom BS is greater than the signal threshold,SUx
can get service from the BS. Otherwise,SUx cannotget any service from the BS. As shown in Fig.??,SUx only receives oldeNB signal, and analyzes thespectrum characters of BS. The procedure of thecomputation and analysis is developed.S1 To evaluate the expected transmission time
TE of SUx’ service, the SNR is needed.The SNR is analyzed from the received sig-nal strengthα by the transformation equationdB = 10 logSNR, wheredB is the received
signal strength. Hence, theSNR is SNR =10
α10 .
S2 SUx determines the maximum transmissionrate for each spectrum holeSHi and the re-quired transmission timetreq of service datadt. Let Ri denotes the transmission rate inthe SHi. Due to theSHi is consist ofmi
resource blocksRB, the bandwidth ofSHi
is mi × RB. For determining theRi of SHi,a formal equation to evaluate the maximumtransmission rate proposed by Shannon (11).The maximum transmission rate is evaluated byC = B×log2(1+SNR), whereC is the maxi-mum channel capacity, andB is the bandwidth.Hence, theRi is mi × RB × log2(1 + SNR).And the the required transmission timetreq ofservice datadt is evaluated by datadt andRi.The treq is dt
mi×RB×log2(1+SNR).
S3 To predict the availability of spectrum holeSHi, the probability of SHi unoccupied isneeded to know. LetPu(SHi, treq) denotes theprobability of spectrum hole unoccupied byPUs. The probabilityPu(SHi, treq) is theSHi
unoccupied probability in thetreq period. Topredict the idleSHi in a service require timetreq. The proposed scheme use the Poissondistribution (12) to analyze theSHi. The for-mal equation of Poisson distribution is writtenas P (k, T ) = (λT )k
k!e−(λT ), where k is the
number of events,T is the period time, andλ is the proportion of average event happened.The P (k, T ) means in the time periodT , andthere arek events happened probability. Toanalyze the probability that theSHi is not beused in a service require timetreq. The k setszero, andT sets treq. Hence, if theSHi iscomposed ofmi RB, the probability is written
asPu(mi, treq) =mi∏
n=1
Pn(0, treq) = e−
mi∑
n=1
λntreq.
C. Secondary users in the overlapped area
In the overlapped area,SUx has one or moreavailable serving BS to build connection. The fre-quency spectrum in oldeNB cell edge do notinterfere with the frequency spectrum in neweNBcell edge because the allocated frequency in the celledge is divided into different frequency domain.The computation and analysis of these spectrum
holes are computed with the more than one BS. Thedifferent spectrum hole list in different BS makeSUx has more choice to determine which to use.The procedure is described below.
S1 To evaluate the expected transmission timeTE of SUx service, theSNR is needed. TheSNR can be analyzed form the received signalstrengthα and β by the transformation equa-tion dB = 10 logSNR. Hence, theSNR iswritten asSNR = 10
α10 andSNR = 10
β
10 .S2 SUx determines the maximum transmission
rate for each spectrum holeSHi and SH ′
j indifferent BS and the required transmission timetreq of service datadt in each spectrum hole.In old eNB, theSHi is consist ofmi resourceblocksRB, the bandwidth ofSHi is mi×RB.To determine the transmission rate ofSHi byShannon theorem, the maximum transmissionrate is evaluated byC = B × log2(1 + SNR).Hence, theRi is mi × RB × log2(1 + SNR).And the the required transmission timetreq ofservice datadt is evaluated by datadt andRi.The treq is dt
mi×RB×log2(1+SNR). In new eNB,
the SH ′
j is consist of m′
j resource blocksRB, the bandwidth ofSH ′
j is m′
j × RB. Todetermine the transmission rate ofSH ′
j byShannon theorem, the maximum transmissionrate is evaluated byC = B × log2(1 + SNR).Hence, theR′
j is m′
j ×RB × log2(1 + SNR).And the the required transmission timetreq ofservice datadt is evaluated by datadt andR′
j .The treq is dt
m′
j×RB×log2(1+SNR).
S3 To predict the availability of spectrum holeSHi in old eNB andSH ′
j in new eNB, theunoccupied probability of spectrum hole isneeded to evaluate the expected transmissiontime TE. Let Pu(SHi, treq) is the unoccu-pied probability of spectrum holeSHi andP ′
u(SH′
j, treq) is the unoccupied probability ofspectrum holeSH ′
j. In order to predict theSHi
andSH ′
j in different BS are not be used in aservice require timetreq. The proposed schemeuse the Poisson distribution to analyze theSHi
andSH ′
j. The formal equation of Poisson dis-
tribution is written asP (k, T ) = (λT )k
k!e−(λT ).
In old eNB, to analyze the probability thatthe SHi is not be used in a service require
time treq, the eventk is setting zero, and timeperiod T is settingtreq. Hence, if theSHi iscomposed ofmi resource block, the probability
is written asPu(SHi, treq) =mi∏
n=1
Pn(0, treq) =
e−
mi∑
n=1
λmitreq
. I n new eNB, to analyze theprobability that theSH ′
j is not be used ina service require timetreq, the probability is
written asPu(SH′
j, treq) =m′
j∏
n=1
Pn(0, treq) =
e−
m′
j∑
n=1
λm′
jtreq
.
D. Phase of evaluation and transmission
In evaluation and transmission phase, the maingoal is to evaluate the expected transmission timethat SUx service required, and then to selects anadaptive spectrum hole with the minimumTE . TheTE not only considers the transmission time thatSUx service datadt required but also theSHi char-acters such as bandwidth, SNR,SUx service datasize, and unoccupied ratio. These characters assistthe TE to predict the possibility of the candidateSHi spectrum mobility, and then add some penaltyto increase or decrease the value ofTE . And theminimum TE is the adaptive selection to spectrummobility and handover. The detailed operation isdeveloped as follows.
S1 LetTE(SHi) denotes the expected transmissiontime in theSHi of old eNB. In non-overlappedarea, for each spectrum hole in the oldeNB theequation ofTE(SHi) is written as equation (1),
TE(SHi) =dt
Pu(mi, treq)× Ri
+ (1 − Pu(mi, treq)) × TL2H (1)
The TL2H is layer 2 switch time, and(1 −
Pu(mi, treq)) is the probability ofSHi be oc-cupied. In fact the original transmission timeshould be dt
Ri. But the time may be inter-
rupted when PUs back. The expected trans-mission time should be added some penaltythat Pu(mi, treq) multiples Ri for increasingthe transmission time. And theSHi may in-terrupt when PUs back, theSUx should per-form spectrum mobility again. Hence, the event
is considered by the penalty of possible in-terrupted and spectrum mobility time,(1 −
Pu(mi, treq)) × TL2H . Therefore, the expectedtransmission time is the sum of data transmis-sion time and the penalty time.
S2 To evaluate the expected transmission time thatSUx service required. LetTE(SU
′
j) denotesthe expected transmission time in theSH ′
j
of new eNB In overlapped area, the equationof expected transmission time in neweNBspectrum bands is differ fromTE in old eNB.The equation of expected transmission time innew eNB should add a layer 3 handover proce-dure time, the equation is written as following.
T ′
E(SH′
j) = TL3H +dt
P ′
u(m′
j , treq)× R′
j
+ (1− P ′
u(m′
j , treq))× TL2H (2)
The TL3H is layer 3 handover procedure time.In the overlapped area,SUx has two selec-tion of BS spectrum bands. IfSUx select theold eNB spectrum bands, the evaluation ofTE is similar to equation (1). IfSUx selectthe new eNB spectrum bands, the expectedtransmission time should be increasing becausethe additional handover procedure timeTL3H .And then the expected transmission time is thesum of data transmission time , the penaltytime, and handover procedure time.
S3 The minimum expected transmission time isan adaptive selection. In the non-overlappedarea,SUx performs the spectrum mobility withthe spectrum holeSHi that has the minimumexpected transmission time to data transmis-sion. Due to the expected transmission time hasconsidered theSHi characters and added somepenalty in the transmission time, theTE(SHi)with minimum value has high successful rateand the shortest transmission time. In the over-lapped area,SUx selects spectrum holes inwhich old eNB or new eNB. Although thesignal strength betweenSUx and old eNB doesnot meet the signal strength threshold, the valueof T ′
E(SH′
j) is smaller thanTE(SHi) should bea proper spectrum hole to perform the handoverprocedure to the neweNB.
V. SIMULATION RESULTS
In this section, we evaluate the performance ofthe spectrum mobility and handover scheme in
SU
MME/S-GW
eNB
MME/S-GW
eNB
P-GW
PU
Fig. 6. Simulation architecture.
cognitive LTE systems. In the proposed scheme, thespectrum holes is similar to channels. The spectrumholes adopt AGWN channel and ignore the channelfading problem. The simulation results are thenanalyzed.
A. Simulation Setup
This work develop a spectrum mobility and han-dover protocol in 3GPP cognitive LTE systems.To evaluate the proposed scheme, using the Net-work Simulator-2 (NS-2) (1), ns-2 Cognitive RadioNetwork model, and euran module. The simulationarchitecture is shown as Fig. 6, and the parameteris setting up as Table 1.
Table-1Parameter ValueBS transmission range 50 kmNetwork size 500×500 kmSecondary users speed 0-100 km/hrNumber secondary user 0-20Spectrum sensing period 40 msSpectrum switching delay10 msHandover delay 200 - 350 msPacket size 1500 bytesSimulation time 100-1000 s
The performance metrics that be analyzed in oursimulations are shown as follows:
10 15 20 25 30 35 40 45 500
4
8
12
16
20
Tim
e (s
)
Data size (Mb)
Real transmission time TE
Fig. 7. The expected transmission time vs. real transmission time.
B. The expected transmission time
The proposed expected transmission timeTE isthe decision parameter. WhenTE is large, this repre-sents the expected transmission time of the spectrumhole is higher, and then SUs have to bear greaterrisks of PUs reclaimed resources. This may causefrequent spectrum mobility and handover. On theother hand, the smaller theTE has high successfulrate of service data transmission without the PUsreclaimed resources. Fig. 7 illustrates the expectedtransmission timeTE always higher than the realtransmission time. Because the expected transmis-sionTE according to the spectrum hole unoccupiedratio to add some penalty. The real transmissiontime includes number of spectrum mobility time,and less than the expected transmission timeTE .
C. The impact of spectrum hole size
We discuss the impact of spectrum hole size to thetotal transmission time, spectrum hole unoccupiedratio, and the number of spectrum mobility. Fig.8(a) illustrates the impact simulation of transmissiontime and the spectrum hole unoccupied ratio withdifferent spectrum hole size. The total transmissiontime decrease when the spectrum hole unoccupiedratio increase. Because the unoccupied ratio is in-crease, the secondary users have more opportunityto use the spectrum hole without interrupted. Thespectrum hole 5RB has lowest total transmissiontime because the transmission rate is higher thanothers. Fig. 8(b) illustrates the impact number of thespectrum mobility and spectrum hole unoccupiedratio. The number of spectrum mobility decreasewhen the spectrum hole unoccupied ratio increase.
When the spectrum hole unoccupied ratio is lessthan 0.5, the number of spectrum mobility is in-creasing violently. The spectrum hole 5RB haslowest number of spectrum mobility because thetransmission time is less than other, secondary useruse the spectrum hole 5RB encounter less interrup-tion.
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
275
550
825
1100
1375
1650
1925
Tota
l tra
nsm
issi
on ti
me
(ms)
Pu
5 RB 3 RB 1 RB
(a)
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.90
15
30
45
60
75
90
Num
ber o
f spe
ctru
m m
obili
ty
Pu
1 RB 3 RB 5 RB
(b)
Fig. 8. (a) Total transmission time vs. spectrum hole unoccupiedratio Pu. (b) number of spectrum mobility vs. spectrum hole unoc-cupied ratio.
D. The comparison of layer 2 scheme
The proposed scheme compares to the other layer2 scheme. The other layer 2 scheme according toperiodically recorded the channel idle time, the nextperiod the channel idle time is acquired, and thechannel has maximum idle time is the best choice.Our proposed scheme selects the minimum expectedtransmission time as the best choice. As the numberof spectrum hole is 5. Fig. 9(a) illustrates theimpact of end-to-end delay and number of primaryuser. When the number of spectrum hole is lessthan 5, the end-to-end delay of these two schemesare almost equal. As he number of primary useris more than 5, the end-to-end delay is violentlyincreasing. Fig. 9(b) illustrates the impact of num-ber of spectrum mobility and number of primaryuser. At beginning, the primary user is less. Thenumber of spectrum mobility of these two schemesis similar. When the primary user increase more,our number of spectrum mobility in our proposedscheme is less than the max idle time selectionscheme. Because the max idle time selection schemeis always selected the spectrum hole with the longidle time, the remain spectrum hole with short idle
time may not sufficient time to other user ser-vice transmission. Hence, the number of spectrummobility increase. Our proposed scheme increaseflatly. Because our proposed scheme selects adaptivespectrum according to the spectrum hole charactersand user conditions.
1 2 3 4 5 6 7 8 9 100
25
50
75
100
125
150
End-
to-e
nd d
elay
(ms)
Number of primary user
Max idle time scheme Min expected transmission time scheme
(a)
2 4 6 8 10 12 14 16 18 200
15
30
45
60
75
90
Num
ber o
f spe
ctru
m m
obili
ty
Number of primary user
Max idle time scheme Min expected transmission time scheme
(b)
Fig. 9. (a) The end-to-end delay vs. number of primary user, and(b) number of spectrum mobility vs. number of primary user.
E. The comparison of layer 3 scheme
The proposed scheme compares to the other layer3 protocol. The compared layer 3 protocol is mobileIPv6. The total transmission time and the throughputis compared. The exist layer 3 protocol is notconsider the layer 2 spectrum hole allocation, thelayer 3 protocol is always allocated layer 2 thefixed size spectrum resource. For this reason, Fig.10(a) illustrates the impact of total transmissiontime and the user service data size in these twoprotocol. In the same data size, the MIPv6 protocolneed more transmission time because the fixed spec-trum resource. In our proposed scheme, the layer2 support the dynamic spectrum holes informationto layer 3, and layer 3 may use the spectrum holewith the large size and low occupied ratio to datatransmission. Hence, the transmission time of ourproposed scheme is less than the MIPv6 protocol.Fig. 10(b) illustrates the impact of throughput andthe user service data size in these two protocol. Thethroughput at the small data size is similar to eachprotocols. But the data size is increasing, the MIPv6achieve the maximum throughput. Because the fixedspectrum resource in layer 2. Our proposed schemeis not always selected the large spectrum hole size tosecondary user, but the average throughput is higherthan the MIPv6 protocol.
10 15 20 25 30 35 40 45 50
5000
10000
15000
20000
25000
30000
Tota
l tra
nsm
issi
on ti
me
(ms)
Data size (Mb)
MIPv6 Min expected transmission time scheme
(a)
5 10 15 20 25 30 35 400
10
20
30
40
50
Thro
ughp
ut (M
bps)
Data size (Mb)
MIPv6 Min expected transmission time scheme
(b)
Fig. 10. (a) Total transmission time vs. data size, and (b) throughputvs. data size.
VI. CONCLUSIONS
In this paper, we proposed a spectrum mobilityand handover protocol for 3GPP LTE systems. TheThe secondary users in the systems observe thespectrum bands, analyze the characters of spectrumholes, and evaluate the expected transmission timeof spectrum holes. The expected transmission timeof spectrum holes is not only for layer 2 switchingthe spectrum bands, but also for layer 3 to quicklydetermine the handover base station with the mini-mum expected transmission time of spectrum hole.The protocol consider the remained service data sizeand the flexible spectrum hole size. The result of theselected spectrum hole may get more opportunity tofinish the data transmission. Finally, the simulationresults have shown that our protocol outperformsthe existing solutions in terms of spectrum mobilityand handover in the systems.
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