Research Article Implementation of an Optical-Wireless Network …downloads.hindawi.com/journals/ijap/2014/670930.pdf · Spectrum Sensing and Dynamic Resource Allocation Using Optically

Research ArticleImplementation of an Optical-Wireless Network withSpectrum Sensing and Dynamic Resource Allocation UsingOptically Controlled Reconfigurable Antennas

E. Raimundo-Neto,1 J. R. G. da Rosa,1 M. A. F. Casaroli,2 I. Feliciano da Costa,1,3

A. M. Alberti,2 and Arismar Cerqueira Sodré Jr.1

1 Laboratory WOCA (Wireless and Optical Convergent Access), National Institute of Telecommunications (Inatel),Joao de Camargo Avenue 510, 37540-000 Santa Rita do Sapucaı, MG, Brazil

2 “NovaGenesis” Project, National Institute of Telecommunications (Inatel), Joao de Camargo Avenue 510, 37540-000Santa Rita do Sapucaı, MG, Brazil

3 Federal University of Itajuba (Unifei), Benedito Pereira dos Santos Avenue, 1303, 37500-903 Itajuba, MG, Brazil

Correspondence should be addressed to E Raimundo-Neto; [email protected]

Received 14 December 2013; Revised 14 February 2014; Accepted 22 February 2014; Published 30 April 2014

Academic Editor: Ali El-Hajj

Copyright © 2014 E. Raimundo-Neto et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

Thiswork proposes the concept and reports the implementation of an adaptive and cognitive radio over fiber architecture. It is aimedat dealing with the new demands for convergent networks by means of simultaneously providing the functionalities of multibandradiofrequency spectrum sensing, dynamic resource allocation, and centralized processing capability, as well as the use of opticallycontrolled reconfigurable antennas and radio over fiber technology. The performance of this novel and innovative architecturehas been evaluated in a geographically distributed optical-wireless network under real conditions and for different fiber lengths.Experimental results demonstrate reach extension of more than 40 times and an enhancement of more than 30 dB in the carrier tointerference plus noise ratio parameter.

1. Introduction

The development of telecommunications systems and net-works has increasingly influenced the people’s life style andvice versa. People desire to be connected anywhere, anytime,and at high data rate and quality. Social networks, real timevideo, and photo share applications have been demandingnew and tough requirements. While the research in wirelesscommunication systems is mainly focused on providing fast,energy-efficient, and reliable connections to the final users,studies have been developed and applied in all networklayers. Among various research areas, two of them have beenparticularly successful in the last years: radio over fiber (RoF)systems [1] and cognitive radio (CR) [2].

The next generation of telecom systems will requireextremely high capacity and reliable mobility. Enabling theconvergence of wired and wireless services can satisfy these

two requirements. In this way, it would be practicable tosimultaneous delivery voice and data and video servicesin order to serve the fixed and mobile users in a unifiednetworking platform. The radio over fiber (RoF) technologyrepresents a key solution for taking advantage of both systemsin a unique way. In other words, it enables making use of thehuge bandwidth offered by optical communications systemswith themobility and flexibility provided by wireless systems.

RoF systems play an important role in the convergenceof optical and wireless networks and, additionally, can takeadvantage of photonics technology in order to efficientlyenable the generation and detection of microwave signals inthe optical domain [3, 4].These systems have been considereda key solution to connect base stations to the antenna unitsnot only for the current cellular systems but also forWi-Fi and4G networks [5–7]. Other applications include hybrid passiveoptical network (PON) implementations [8] and transport

Hindawi Publishing CorporationInternational Journal of Antennas and PropagationVolume 2014, Article ID 670930, 11 pageshttp://dx.doi.org/10.1155/2014/670930

2 International Journal of Antennas and Propagation

sensorial information in wireless sensor networks (WSNs)[9].

Cognitive radio technology is the target of a large numberof researches focused on a better frequency spectrum usage,as well as network self-management, self-optimization, andmachine learning [10]. Spectrum sensing (SS) techniques andalgorithms for multiple access are also being developed foropportunistic spectrum management [11]. CR can be seenas a self-aware, environment-aware, and regulation-awaredevice. It can estimate the spectrum occupancy by using a SStechnique and, consequently, determining opportunities in afrequency range of interest, based on the occupation or not ofthe channels by licensed users (also known as primary users)[12].

Some researchers have been working on the synergy ofcognitive radio and different photonics technologies in thelast years. Different applications and system architectureshave been proposed in literature, such as cognitive radio overfiber (CRoF) for microcell applications [13], cognitive wire-less LAN over fiber (CWLANoF) [14], cognitive front endsusing optically pumped reconfigurable antennas (OPRAS)[15], and photonic analog-to-digital converter (Ph-ADC)[16, 17]. The CRoF architecture is based on RoF technologyfor connecting CRs. Al-Dulaimi et al. have numericallydemonstrated that CRoF is able to use local spectrum holesefficiently and provide higher throughput to secondary usersif compared to the traditional CR functioning [13]. On theother hand, Attar et al. have reported a WLANoF based ona multiuser MAC with CR capability for multiple cooper-ating receivers with distributed antennas [14]. It consists ofa number of access points without processing capabilitiesconnected via RoF links to a cognitive access point (CogAp).The latter one is responsible for all processing functions andthe spectrum sensing is performed based on MAC layerinformation. In [15], the development of a cognitive front-end based on a UWB antenna and an optically pumpedreconfigurable antenna is presented. The latter one is acti-vated by local laser diodes, which had been incorporatedto its structure for illuminating a photoconductive switch.The main drawback of this approach is that the laser is onlylocally controlled, since it is integrated to the antenna ratherthan using an optical fiber to control the antenna properties.Finally, Llorente et al. have published some articles on theexperimental demonstration of a time-stretched photonicanalog-to-digital converter with optical amplification appliedto sense ultralow power signals for cognitive radio applica-tions [16, 17]. They have indeed demonstrated the feasibilityof a Ph-ADC and a bidirectional UWB radio over fibertransmission in a dispersion compensating fiber (DCF). Theexperiment has confirmed that the proposed Ph-ADC can beused for UWB signal distribution at DCF dispersion values𝐷2≈ −2500 ps/nm for in-building communications. Higher

dispersion values distort severely UWB carrier constellation[16].

This work proposes the concept and reports the imple-mentation of an innovative architecture called ACRoF, whichstands for adaptive and cognitive radio over fiber. It is basedon a central office with multiband SS and dynamic resourceallocation functionalities and simple remote antenna units

composed of previous developed optically controlled recon-figurable antennas for data transmission and a broadbandantenna for continuously sensing the frequency spectrum.There are six main contributions of the current work whencompared to others previously published in literature. First,ACRoF can be considered innovative and unique, sinceit takes advantage of RoF and CR technologies in anadaptive way, since the antenna electromagnetic propertiesare constantly reconfigured as a function of SS informa-tion. Secondly, this work presents an implementation in areal optical-wireless network, whereas CRoF has been onlyanalyzed numerically [13]. If compared to [14], our maincontribution concerns the cognition in the physical layer andnot in medium access control, as well as the possibility ofperforming multiband SS.

The OPRAS antenna reported in [16] is locally manipu-lated by a diode laser differently to our optically controlledantenna that is remotely reconfigured by using a dedicatedoptical link from the central office to the remote antenna unit.Moreover, the current paper presents experimental resultson the network performance parameters based on onlineSS. Finally, [16, 17] report the development and laboratoryexperiments of a Ph-ADC, whereas this work proposesthe use a spectrum analyzer as ADC and RoF links forenabling centralized processing capability in a geographicallydistributed optical-wireless network.

2. Cognitive Radio and Spectrum Sensing

Software-defined radio (SDR) and cognitive radio (CR)represent two remarkable concepts on the wireless com-munications evolution, which are frequently attributed toMitola III [18, 19]. A SDR is a radio in which the phys-ical layer signal processing is software-controlled ratherthan using a dedicated hardware to handle radio frequency(RF) signals. It is capable of reconfiguring its parame-ters and even functionalities according to the softwarecontrols. On the other hand, a CR is a software-definedwireless communication that provides the functionalitiesof self-organization, self-management, and self-adaptationas a function of the radio environment, spectrum occu-pancy and regulation, user requirements, internal capa-bilities, and operational constraints. Several technologiesinspired on human biology have been suggested to achievethese complex objectives. The inspirations typically comefrom our sensory system (spectrum sensing), somatic ner-vous system (controllers and actuators), autonomic ner-vous system (self-management, situation-awareness, and self-management) [20], and human brains (analyzing, corre-lating, decision making, learning, planning, and experi-menting) [10]. A CR must be aware of many aspects,namely, the radio frequency spectrum and channels situa-tion (environment-awareness), its own devices and systems(self-awareness), regulations (regulation-awareness), servicerequirements (service-awareness), business plans (business-awareness), and etiquettes/policies [21, 22]. It can experi-ment new configurations and functionalities, correlating theapplied plans to the obtained results. Therefore, it can learn

International Journal of Antennas and Propagation 3

Central office Remote antenna unit

Fiber link

Fiber link

PA

LNA

Laser

LaserPhotodetector

Photodetector

Antenna

RF circulator

Figure 1: RoF system block diagram.

from previous experiences in order to optimize its func-tionalities. A CR must perform spectrum sensing constantlyfor finding out new bandwidth opportunities that could beexplored by its radio capabilities. Furthermore, it needs tosense and monitor the radio channels to detect primaryusers’ transmissions, aswell as secondary users’ transmissions(coexistence). If a primary signal is detected, the secondarytransmission should immediately stop to avoid interference.

The increasing demand for high data rates in wirelesscommunications has motivated the emergence of CR asa key solution for the limited and underutilized wirelesselectromagnetic spectrum resources. The licensed spectrumis allocated during long time periods exclusively to licensedusers, that is, the primary users. Many studies on spectrumutilization have demonstrated the unused frequency time andspace resources of this strategy [23, 24]. CR aims to exploitthese opportunities without causing significant interferenceto primary users [10]. It is aimed at reusing the unused spec-trum in an opportunistic way. In order to avoid interferencewith the primary users, CR must monitor constantly thespectrum usage and determine the possibilities for spectrumoccupancy. Transceivers based on this technology are able tosense the frequency spectrum and determine its occupancyby one or more primary users [25].

The spectrum sensing can be simply modeled in decidingwhether a slice of spectrum is available or not. It can bediscriminated in two hypotheses:

𝐻0: y [𝑛] = w [𝑛] , 𝑛 = 1, 2, . . . , 𝑁

𝐻1: y [𝑛] = x [𝑛] + w [𝑛] , 𝑛 = 1, 2, . . . , 𝑁,

(1)

where x[𝑛] represents a primary user,w[𝑛] is the noise, and nrepresents time.The sensed signal y[𝑛] is a vector with length𝐿.

First, CR needs to perform a test statistic Λ(𝑦) usingthe received data y[𝑛] and compare it with predeterminedvalues of the threshold 𝜆. If Λ(𝑦) > 𝜆, CR decides the 𝐻

1

hypothesis. Otherwise, if Λ(𝑦) < 𝜆, CR decides 𝐻0. The

detector performance is quantified by a receiver operatingcharacteristics (ROC) curve, which gives the probability ofdetection 𝑃

𝐷as function of the probability of false alarm 𝑃FA

by varying the threshold [26].The parameters 𝑃𝐷and 𝑃FA are

defined by the following expressions:

𝑃𝐷= Pr (𝐻

1| 𝐻1)

𝑃FA = Pr (𝐻1 | 𝐻0) .(2)

The choices of the optimum number of required samplesand threshold 𝜆 are very crucial, since they strongly affectthe detection performance [27]. Recently, some SS tech-niques have been proposed and investigated, such as energydetection (ED) [28], cyclostationary detection [29], featuredetection, covariance matrix [30, 31], and blind detection[32]. The ED technique has been chosen for the optical-wireless network implementation, whichwill be subsequentlydescribed. In this approach, a CR measures the energy of thereceived signal over a finite time interval and compares it toa predetermined decision threshold. The test statistic Λ(𝑦) isgiven by

Λ (𝑦) =1

𝑁

𝑁⋅𝐿

∑

𝑖=1

[y (𝑛)]2. (3)

Note that higher values of the 𝑁 ⋅ 𝐿 product lead to amore precise estimate of Λ(𝑦). However, this is not typicallyused in practical cases due to the dynamic variations of thespectrum occupancy during long periods of time. Therefore,the parameters𝑁 and 𝐿 need to be properly chosen in orderto enable a good and fast sensing performance.

3. Radio over Fiber Technology

The radio over fiber technology consists of a heteroge-neous network formed by optical and wireless links. Unliketraditional optical communications networks, in which abaseband signal is transmitted into the optical fibers, in RoFsystems one or multiple analogous carriers are transportedinto the fibers [9], as presented in Figure 1. The signaltransmission is realized by directly or externally modulatinglasers with the analogous radio frequency signals. On thereceiver side, the transmitted signal is recuperated by usinga photodetector. Moreover, RF amplifiers can be built inthe RoF system to further increase its reach. In this way,using fiber-optic links ensures the transmission of RF signals


RRU

RRU: remote radio unit

DWDM optical backhaul

Fiber Fiber

FiberFiber

OCRAP: optically controlled reconfigurable antenna processingSSSP: spectrum and spatial sensing processingDRA: dynamic resource allocation

Central office

OCRAP SSSP

OCRA

OCRA OCRA

DRA

OCRA

𝜆 sensin

gan

d 𝜆uplin

k

𝜆 downlink

and 𝜆

control

𝜆sensing and

𝜆uplink𝜆

downlink and𝜆control

𝜆 sensin

gan

d 𝜆uplin

k

𝜆 downlink

and 𝜆

control

𝜆sensing and

𝜆uplink

𝜆downlink and

𝜆control

𝜆1, 𝜆2, 𝜆3, . . . , 𝜆n

Figure 2: Adaptive and cognitive radio over fiber architecture.

between a central office (CO) and a given number of RAUs.The final users are commonly mobile devices, which areconnected to RAUs via a wireless link.

The integration of optical and wireless broadband infras-tructures into the same backhaul network leads to a sig-nificant systemic simplification and cost reduction, since allrouting, switching, and processing are performed at CO [33].The signal processing centralization makes possible equip-ment sharing and dynamic resource allocation. Ideally, a RoFsystem can be entirely transparent to all signals transmittedin the optical channel, because the transmission is ensuredby modulating the optical carrier with the RF signal. RoFlinks can simultaneously transport several wireless standards,such as Wi-Fi, GSM, UMTS, WiMAX, LTE, and UWB [14].Furthermore, low attenuation, electromagnetic interferenceimmunity, low energy consumption, and large bandwidth areother advantages of this technology.

4. ACRoF-Adaptive and CognitiveRadio over Fiber

The proposed architecture for the implementation of anoptical-wireless network and spectrum sensing allocation iscalled ACRoF (adaptive and cognitive radio over fiber) and

is illustrated in Figure 2. It consists of a CO and severalRAUs. The CO concentrates the following elements: (i)remote radio unit (RRU), which consists of a radio capableof transmitting and receiving data to/from different RAUs;(ii) optically controlled reconfigurable antenna processing(OCRAP), which is responsible for optically reconfiguringthe antenna electromagnetic properties; (iii) spectrum andspatial sensing processing (SSSP), responsible for collectingthe spectrum samples of the radio environment and process-ing and making them available to DRA; and (iv) dynamicresource allocation (DRA), which dynamically performsspectrum resource allocation based on the SSSP information.On the other side, RAU is based on a previously developedoptically controlled reconfigurable antenna (OCRA) [34] fordata transmission and a broadband antenna for performingSS.

The proposed ACRoF architecture has been implementedin an optical-wireless network under real conditions, asreported in Figure 3.Themain blocks of our testbed are a CO,a RAU, a bidirectional RoF link, and an optical control link.The RoF modules perform the electrical-optical and optical-electrical signal conversion. The RF signal distribution iscarried out using bidirectional RoF links.The antenna controllink enables the transmission of an additional optical signal


SSSP RRU

OCRAP

RoF

RoF

Antenna control link

Bidirectional communication link

RAU

DRA

Central office

Figure 3: Block diagram of the optical-wireless network implementation.

Spectrum analyzer

Dual-bandaccess point

Not

eboo

k

RF interface

Central office

∙ SSSP∙ DRA∙ OCRAP

∙ RRU

∙ SS data collection

Dual-bandaccess point

Notebook

Spectrum analyzer

Central office

Figure 4: Components and functionalities of the central office.

responsible for reconfiguring its electromagnetic character-istics. Finally, an optically reconfigurable antenna and acommercial broadband log-periodic antenna (680MHz to10GHz) compose RAU and are used for data transmissionand spectrum sensing, respectively.

The ACRoF operational principle is described as follows:(i) the frequency spectrum is sensed by RAUs and rawsamples are transmitted to CO through the optical links;(ii) the information is extracted and processed using anED algorithm, with the purpose of choosing the frequencychannel and/or band at a lower level of energy; (iii) DRAis conducted by setting the RF parameters (number of theselected channels and the antenna operation bands: 2.4GHzor 5GHz); (iv) the system operates at the new allocatedchannel until the next estimation is performed.

CO integrates a spectrum analyzer, a dual-band accesspoint (AP), and a notebook, as illustrated in Figure 4. Itreceives the RF signal composed of the uplink and sensedspectrum data. AP processes the uplink data, whereas senseddata is forwarded to a portable spectrum analyzer, whichis directly connected to the notebook by using a USB port.The ED algorithm is then online processed by the notebookin order to define the channel and/or band which is goingto be used. After taking this decision, it sends a commandto AP for setting the best channel, as well as an opticalcontrol signal to reconfigure the antenna electromagneticcharacteristics. Note that data communication is performedby using a bidirectional optical link and the control signal

RF interfacesOptical interfaces

Figure 5: RoF transceiver used in the experiments.

uses a dedicated link to adapt the antenna properties, suchas bandwidth and radiation pattern.

The broadband RoF modules operate from 30MHz upto 6GHz using direct modulation. Figure 5 displays a pho-tograph of a RoF module, including some indications of itsoptical and electrical interfaces. It operates at different wave-lengths for downlink and uplink. Therefore, a unique opticalfiber is required to enable bidirectional communication.

Figure 6 shows the antennas used in the RAU. Theoptically controlled reconfigurable antenna is based on an“E”-shape slot, previously developed by our research group[34]. Its operational bandwidth and radiation pattern can bereconfigured through 2.4 or 5GHz bands by controlling theoptical power launched on its photoconductive switch.


A commercial hyperlog antenna(spectrum sensing and data reception)

The developed antenna(data transmission)

Figure 6: “E”-shape and Hyperlog antennas.

5. Optically ControlledReconfigurable Antenna

Patch antennas have been intensely exploited in the lastdecades due to their low-profile structure and facility tobe embedded in handheld wireless devices. Furthermore,they provide other advantages, such as good radiation effi-ciency, simple manufacturing, low cost, easy integrationwith microwave integrated circuits (MIC), light weight, lowvolume, and the possibility to be made conformal to the hostsurface.

Khidre et al. have recently reported some results on acircular polarization reconfigurable E-shaped patch antennausing 2 PIN diodes [35]. Our proposed patch antenna isbased on E-shape printed slot, as presented in Figure 7(a).It has been fabricated using a low-cost fiberglass dielectricsubstrate. It is elevated from the ground plane with asizable air gap to achieve wide bandwidth. Therefore, theelectromagnetic coupling is ensured by a printed probelocated in the bottom plane of the antenna structure, asshown in Figure 7(b). Its main advantages compared totraditional electrically controlled reconfigurable antennas areeasy integration to optical systems, absence of bias lines,linear behavior, and activation without producing harmonicsand intermodulation. An intrinsic silicon photoconductiveswitch has been fixed to the printed probe for enabling us toreconfigure the antenna frequency response as a function ofthe incident optical power. A fiber has been used to illuminatea silicon dice, as shown in Figure 7(b). Table 1 presents thetypical antenna electromagnetic properties for the centralfrequencies from 2.4 and 5GHz ISM bands. It operates in the2.4GHz band if the photoconductive switch is illuminated(“ON” state), since its reflection coefficient is very low. On theother hand, in the absence of light (“OFF” state), the antennaoperation is reconfigured to the 5GHz band, giving rise toa gain of 5.22 dBi. Therefore, it provides two operational andreconfigurable frequency bands: one from 2.407 to 2.524GHzand the other from 5.033GHz up to 6GHz. Some examplesof its radiation pattern are reported in Figures 7(a) and 7(c).

6. Implementation of ACRoF Architecture

The proposed ACRoF architecture has been implementedin a real geographically distributed optical-wireless network

Table 1: Typical reconfigurable antenna parameters for the centralfrequencies of 2.4 and 5GHz bands.

Frequency(GHz) Switch state Reflection coefficient

(dB)Gain(dBi)

2.47GHz “OFF” −2.18 1.42“ON” −14.37 3.28

5.41 GHz “OFF” −17.42 5.22“ON” −9.51 3.21

Table 2: System reach in meters.

Network type/frequency band 2.4GHz 5GHzPure wireless 45 25ACRoF 1,045 1,035

located in the campus of the Brazilian National Institute ofTelecommunications (Inatel). Figure 8 shows a Google Earthimage with indications of the implemented network compo-nents.The optical links are composed of two pieces of 1,020msingle-mode fibers, under real conditions of temperature,humidity, and pressure. CO is located in the second floorof the main building and RAU is placed at the LaboratoryWOCA (Wireless and Optical Convergent Access), whichallows covering an internal square from the campus.

Initially, an experiment has been carried out at 2.4GHzto systemically evaluate the antenna performance. Figure 9reports RSSI (received signal strength indicator) and PER(packet error rate) measurements as a function of the lasercurrent by means of combining a 1 km fiber with a 2mwireless link. The higher the laser current is, the higher theRSSI is. By increasing the current from 0A (“OFF” state) to2.5 A (“ON” state), equivalent to approximately 2Wof opticalpower, RSSI is significantly enhanced from −66 to −57 dBm.Moreover, PER is improved from 32 to 18%.

The maximum fiber-optic length that could be usedin the optical network has been evaluated considering themaximum allowed delay established by the IEEE 802.11nMAC layer standard for each particular frequency band (2.4and 5GHz). It requires a shorter delay for the 5GHz bandwhen compared to the 2.4GHz band [36–38]. Figures 10 and11 present the obtained RSSI and throughput as a functionof the fiber length for the two frequency bands, respectively.In both cases, a back-to-back measurement had been firstconducted for comparison purposes. The fiber links havebeen varied from 370m to 1.37 km.These results demonstratethat the ACRoF concept has been successfully implemented,since they are in accordance with the nominal value for the802.11n standard, in which the minimum value to establisha connection is around −90 dBm. The throughput numbersare also in agreement with the back-to-back case with 370mand 1,020m fiber lengths. On the other side, there was nodata transmission at 5GHz for the 1.37 km link because ofthe time delay. It is important to highlight the proposedarchitecture implied in a significant reach enhancement: from45 to 1,045m at 2.4GHz (23 times longer) and from 25 to1,035m (41 times longer) at 5GHz, in both cases using 1,020mof fiber. Table 2 reports the system reach comparison betweena pure wireless network and the ACRoF architecture.


0 15 30 (mm)

Gai

n (d

Bi)

2.89

0.97

−0.95

−2.87

−4.79

−6.71

−8.64

−10.56

−12.48

−14.40

−16.33

−18.25

−20.17

−22.09

−24.02

−25.94

−27.86

(a)

Fiber optics

Photoconductiveswitch

SMA

conn

ecto

r

(b)

2.00

0.00

−2.00

−4.00

0

30

60

90

120

150

−180

−150

−120

−90

−60

−30

2.4 GHz5.8 GHz

(c)

Figure 7: “E”-shaped optically controlled reconfigurable antenna.

The proposed dynamic spectrum allocation algorithmconsists of selecting the best channel for data transmissionaccording to the following steps: (i) the spectrum samplesare processed at CO and the average power of each channelis estimated; (ii) the algorithm defines the channel with thelowest energy level at each band; (iii) the signal to noiseratio (SNR) is estimated considering the average noise levelof each channel, which had been previously experimentallyobtained for our portable spectrum analyzer; (iv) the EDalgorithm chooses the channel that has the lowest estimatedSNR between the best ones from each ISM band; (v) thenotebook fromCO sets the chosen channel in the AP and the

antenna optical signal control to ensure data transmission atthe most appropriate channel.

The SS algorithm performed data collection consideringthe following system parameters: number of samples overtime (𝑁 = 50) and samples frequency spacing 𝑑

𝑠= 1MHz.

Therefore, the total number of samples over frequency was𝐿 = 101. All experiments have been carried out considering a22MHz channel. Therefore, the total number of samples foreach channel status estimation was 𝑁 ⋅ 𝐿 = 1,100. Figure 12displays an example of the measurement spectrum in the2.4GHz band, from 2400 to 2500MHz, which is extremelycrowded as expected. Figure 13 reports an example of the


Envi

ronm

ent o

f sen

singCO

ERAU

Figure 8: Google Earth image of the implemented real optical-wireless network.

0 0.5 2−70

−65

−60

−55

Current (A)

RSSI

(dBm

)

1 1.5 2.510

20

30

40

PER

(%)

PERRSSI

Figure 9: Measurements of RSSI and PER parameters as a functionof the laser current.

measured SS in the 5GHz band, from 5100 up to 5900MHzfor𝐿 = 801. It is clear that thereweremuchmorewhite spacesover this frequency band.

According to the IEEE 802.11 standard, different mod-ulation and coding schemes (MCS) can be adopted bynetwork devices depending on the communication channelconditions [39]. Therefore, the network throughput can besignificantly increased if the interference caused by othernetworks is reduced. In order to evaluate the impacts causedby cochannel interference in Wi-Fi networks based onACRoF architecture, a wireless scenario has been createdwith other Wi-Fi networks. Three other Wi-Fi access pointshave been used to carry out performance measurements.Thenetwork performance has been evaluated using the followingparameters: carrier to interference plus noise ratio (CINR),throughput, and PER. Moreover, four different conditionshave been considered: (i) cochannel interferences originatingfrom three other radio transmitters, (ii) cochannel interfer-ences originating from two other radio transmitters, (iii)cochannel interferences originating from only one radiotransmitter, and (iv) no cochannel interference. Tables 3 and 4present the experiment results for 2.4GHz and 5GHz bands,respectively. As shown in Table 3, the CINR, throughput, andPER could be improved up to 39 dB, 29.6Mbps, and 11%,respectively, by proper selecting of a channel over the 2.4GHzband. They could also be enhanced to 30 dB, 22.7Mbps, and

0 200 400 600 800 1000 1200 1400−64−62−60−58−56−54−52−50−48

Fiber length (m)

RSSI

(dBm

)

2.4 GHz5.8 GHz

Figure 10: RSSI measurement as a function of the fiber length forthe two frequency bands.

0 200 400 600 800 1000 1200 14000

5

10

15

20

25

30

35

Fiber length (m)

Thro

ughp

ut (M

bps)

2.4 GHz5.8 GHz

Figure 11:Throughputmeasurement as a function of the fiber lengthfor the two frequency bands.

Table 3: Performance evaluation considering different levels ofcochannel interference in the 2.4GHz band.

Test conditions CINR (dB) Throughput(Mbps) PER (%)

3 cochannel interferences 0.5 20.5 252 cochannel interferences 10 23.3 231 cochannel interference 20 25.5 18The best channel 39.6 29.6 11

Table 4: Performance evaluation considering different levels ofcochannel interference in the 5GHz band.

Test conditions CINR (dB) Throughput(Mbps) PER (%)

3 cochannel interferences −3 0.252 232 cochannel interferences 7 1.087 221 cochannel interference 17 2.28 18The best channel 30 22.7 7

7%, respectively, using the same strategy in the 5GHz band,as shown in Table 4.


2.4 2.42 2.44 2.46 2.48 2.5−90−80−70−60−50−40

RF p

ower

(dBm

)

Frequency (Hz)Samples−90

−80

−70

−60

−50

−40

2 44 2.46 2.48S ×10

9

0400 200

6008001000

Figure 12: Sensed spectrum in the 2.4GHz band.

5.1 5.2 5.3 5.4 5.55.9

5.6 5.7 5.8

0400 200

6008001000−90−80−70−60−50−40

RF p

ower

(dBm

)

Frequency (Hz)Samples−80−78−76−74−72−70−68−66−64−62

5 8600800

×109

Figure 13: Sensed spectrum in the 5GHz band.

Finally, the entire ACRoF architecture has been experi-mentally analyzed and its performance has been optimizedunder two different contexts: using the most appropriatechannel from the 2.4GHz band and using the most appro-priate channel from 2.4 and 5GHz bands. Initially, the datacommunication had been conducted by using the Wi-Fichannel 6 (2,437MHz), which is the default channel forthe most commercial APs, and then new channels havebeen used in accordance with the methodology previouslydescribed in the previous sections. Figure 14 reports a signif-icant enhancement on the network performance parametersobtained by using ACRoF. CINR can be further improved to40 dB by using the best channel from 2.4 and 5GHz bands.It is important to remark that the maximum MCS indexfor this particular system is MCS 7, which has the followingconfigurations: (i) SISO (single input single output), (ii) 1spatial stream, (iii) 20MHz channel bandwidth, and (iv)800 ns of guard interval. Theoretically, for this scenario, themaximum throughput that can be achieved is 65Mbps [40].However, the previous experiments have shown that themaximum downlink throughput for this system is 32Mbps.

7. Conclusions

Thiswork has proposed the concept and reported a successfulimplementation of an adaptive and cognitive radio over fiberarchitecture in a geographically distributed optical-wirelessnetwork. It consists of a central office that centralizes allnetwork functionalities and simple remote antenna unitsbased on optically controlled reconfigurable antennas fordata transmission and broadband antennas for performingspectrum sensing. Experimental results have demonstrated

0 5 10 15 20 25 30 35 40

Def

ault

Throughput (Mbps)CINR (dB)PER (%)

The b

est b

etw

een

2 ba

nds

The b

est a

t2.

4GH

z

Figure 14: Significant enhancement on the network performanceparameters using ACRoF.

that the network performance can be significantly improvedin terms of CINR, throughput, and PER by using multibandspectrum sensing and dynamic resource allocation. Partic-ularly, it has reported a reach extension of more than 40times and an enhancement of more than 30 dB in the CINRparameter. Futureworkswill regard the integration ofACRoFwith the NovaGenesis “Future Internet” architecture [41].

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper.

Acknowledgments

The authors are grateful for the financial support fromCNPq, MCTI, CAPES, FAPEMIG, FINATEL, ESSS-ANSYS,Prysmian-Draka, and Huber-Suhner and the technical sup-port from TIM.

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