The most notable candidate for rural cognitive radio technology is the IEEE 802.22 standard that is currently being developed and is based on time division duplexing, orthog-onal frequen
Trang 1WRAN BS
Microphone protection area Wireless microphones
W IRELESS T ECHNOLOGIES A DVANCES FOR
E MERGENCY AND R URAL C OMMUNICATIONS
I NTRODUCTION
According to a report published by the United Nations, more than three billion people are cur-rently living in rural areas [1] In developing countries like China and India, about 70 percent
of the total population live in rural communities, which are spread far and wide over large geo-graphic areas For these communities, it is believed that providing communications services
is an important step to facilitate development and social equity [2] Apart from that, rural
com-munications networks are crucial in disaster/emergency response scenarios
However, providing rural communications is often challenging due to the mismatch between costs and demand Most rural areas have low population density and the demand for services per individual or household can be much lower
in rural areas if compared to urban areas To create a viable business, operators must aim for low-cost solutions However, the deployment and maintenance of rural communications networks can be costly due to large areas requiring cover-age, lack of transportation, and difficult terrains This is particularly true for wired networks because wires or cables must be laid all the way
to the destinations As a result, wireless tech-nologies usually are preferred for rural connec-tivity
In fact, there are various approaches that consider wireless technologies for rural commu-nications [3–7] Proposals that make use of cellu-lar or satellite technologies can be found in [3, 4] Recently, with the proliferation of Wi-Fi, there have been proposals to extend this short-range/local-area-network technology for rural coverage [5–7] Nevertheless, the challenges of providing low-cost services to a low-demand market still remain
Cognitive radio is an emerging technology that promises to overcome one of the most chal-lenging problems of modern wireless communi-cations, namely, spectrum scarcity Access to radio spectrum today is based largely on fixed allocation, that is, different frequency bands are allocated to different services With the prolifer-ation of wireless applicprolifer-ations and services in many countries, most of the available spectrum has been allocated On the other hand, careful studies reveal that most of the allocated spec-trum experiences low utilization [8] By intelli-gently detecting and making use of the allocated but under-utilized spectrum, cognitive radio enables wireless networks to operate without requiring dedicated spectrum This, in the
A BSTRACT
Employing wireless technologies to provide connectivity for rural areas is an active topic in the academic and industrial communities In this article we begin by discussing the challenges of rural communications and reviewing existing wireless technologies that have been proposed or implemented for this market We then focus on
an emerging technology, cognitive radio, that promises to be a viable solution for rural com-munications The most notable candidate for rural cognitive radio technology is the IEEE 802.22 standard that is currently being developed and is based on time division duplexing, orthog-onal frequency division multiple access, and opportunistic use of the VHF/UHF TV bands
We address two important issues that can affect the success of IEEE 802.22 technology in rural deployments, namely, to:
• Provide suitable service models
• Overcome the problem of long TDD turn-around time in large rural cells
For the first issue, we introduce a service model that combines TV broadcasting and data services to facilitate service adoption For the second issue, we propose an adaptive TDD approach that effectively eliminates the require-ment for long TDD turn-around time and thus, increases the efficiency of large-coverage rural networks
We discuss the challenges of rural communications and reviewing existing wireless technologies that have been proposed or implemented for this market We then focus on an emerging technology, cognitive radio, that promises
to be a viable solution for rural communications.
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text of rural communications, means cognitive radio networks can be deployed at lower costs
The most notable example of cognitive radio technologies for rural communications is the IEEE 802.22 wireless regional area network (WRAN) standard that is currently being devel-oped, which is based on time division duplexing (TDD), orthogonal frequency division multiple access (OFDMA), and opportunistic use of very high frequency/ultra high frequency (VHF/UHF)
TV bands [9] Apart from the fact that 802.22 technology does not require dedicated spectrum, which significantly saves deployment costs, the large network coverage makes this technology particularly suitable for rural deployment Due
to the favorable propagation condition in the VHF/UHF bands, an 802.22 WRAN signal can reach a much longer distance, compared to
Wi-Fi and WiMAX signals transmitted on frequen-cies above 2 GHz In fact, 802.22 WRAN is designed to provide wireless broadband access to rural and suburban areas, with an average cover-age radius of 33 km that can increase to 100 km
To realize the advantages of 802.22
technolo-gy, there are many technical challenges that must be overcome For example, to avoid caus-ing interference to incumbent users, namely, TV receivers and FCC Part 74 wireless microphones, WRAN systems must be able to perform spec-trum sensing and detect these incumbents at very low signal strength [9] Another challenge is how multiple WRANs can coexist and interact with networks of other types Whereas these challenges are general in any 802.22 deployment, for rural scenarios the success of 802.22 technol-ogy and the like depends on two important fac-tors, namely:
• Whether service providers can offer attractive content models for the rural market
• How to ensure the efficiency of operation in large coverage scenarios
In terms of service content, it should be noted that customers in rural communities are more familiar with and have higher demand for tradi-tional applications such as telephony and TV broadcasting, than for the Internet, data, or other multimedia applications [7] To account for this, we propose a service model that com-bines TV broadcasting and data services to facil-itate the growth of rural demand for connectivity
To reduce costs and increase customer popu-lation, rural wireless networks must be deployed
in large coverage areas In such cases, if TDD is used as in 802.22 WRAN, the system efficiency will be seriously affected by the TDD turn-around time, that is, the time a system must stay idle for nearby and faraway subscribers to synchronize their uplink transmission To address this prob-lem, we propose an adaptive TDD technology that effectively eliminates the requirement for long TDD turn-around time and thus increases the efficiency of large coverage rural networks
R URAL C ONNECTIVITY : C HALLENGES AND
E XISTING T ECHNOLOGIES
In this section, we highlight the challenges faced
by service providers in the rural information and communications technology (ICT) market This
is followed by a discussion of existing technolo-gies that were proposed or deployed for rural communications
Compared to the urban ICT market, the rural market exhibits a significant mismatch between costs and demand In particular, the rural ICT market can be characterized as follows
• High deployment/maintenance cost: Deploying
and maintaining a communications network in rural areas often incurs higher costs, com-pared to doing so in urban areas This is due
to large coverage areas, difficult terrains, lack
of transportation, and often a shortage of local trained staff
• Low customer density and demand: Most rural
areas are sparsely populated Moreover, cus-tomers in the rural market often have lower incomes than those in urban areas and there-fore, have less to spend on ICT services The low service demand also is due to low cus-tomer awareness and expertise This is partic-ularly true in developing countries
• Slow service adoption rate: It has been observed
that it takes longer for consumers in rural areas to adopt new services compared to those
in urban areas [7]
With the previously mentioned characteristics
of the rural ICT market, service providers tend
to face the following chicken and egg problem
To reduce the service costs, network providers require a large or fast-growing customer base;
however, in rural markets, the customer demand can only be increased if services are offered at sufficiently low rates To overcome this problem, rural network providers should aim for solutions that incur low costs and offer large coverage
In the following, we discuss the technologies that were proposed or deployed for rural communi-cations
Cellular/Wireless Local Loop/Satellite — Fixed
cellu-lar and wireless local loop (WLL) technologies have been proposed for rural communications, for example, in [4] Their advantage is the rela-tively short deployment time Moreover, with the proliferation of cellular technologies, the cost of portable devices has decreased significantly
Nevertheless, these technologies still require a large user base to offset their costs
Small satellite earth stations are widely used
in developing regions, usually for distribution of
TV signals and interactive voice/data Examples include the bank networks in remote parts of Brazil and the India National Information Cen-ter Network for government data services [2]
However, the hardware costs and service charges
of satellite communications are relatively high for the rural market [7]
Wi-Fi and WiMAX — With the success of Wi-Fi
technology for short-distance, local area network applications, there has been significant interest
in using this technology for rural connectivity
An example is the Digital Gangetic Plain pro-ject, developed jointly by IIT Kanpur, India and Media Lab Asia, where IEEE 802.11
technolo-The rural ICT market exhibits a significant mismatch between costs and demand.
To overcome this problem, rural network providers should aim for solutions that incur low costs and offer large coverage.
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gies are used to provide long-haul access links.
This is achieved by using highly directional antennas mounted on tall structures and tuning 802.11 protocols to obtain a much longer cover-age (more than 30 km) [5] Compared to cellular and satellite technologies, the advantages of
Wi-Fi include ease of set-up and maintenance, rela-tively high bandwidth, and low costs for both users and providers Another candidate technol-ogy is WiMAX, which is based on the IEEE 802.16 standards WiMAX is described as an enabling technology that provides last mile wire-less broadband access as an alternative to cable and DSL Currently, WiMAX trials are being performed in several countries
DakNet — Asynchronous Service Network — DakNet
is a network architecture based on store-and-for-ward Instead of real-time services, DakNet pro-vides remote communities with useful asynchronous Internet access The rationale are [7]:
• Real-time communications are generally too expensive as a widespread investment for the nascent rural ICT market
• Asynchronous ICT services appear to be suffi-cient to meet most of the needs of rural com-munities
• Local information caches can be used to pro-vide local users with immediate access to com-monly requested information without the need for real-time Internet access
The three major entities in DakNet are the hub, the mobile access point (MAP), and Info Kiosk A physical transport vehicle, for example,
a car or motorbike, carries a MAP through a rural area where the DakNet service is provided
When a MAP reaches within the communication range of an Internet hub or an Info Kiosk, it uploads or downloads e-mail, voice mail, and other offline data content [7] However, due to its asynchronous nature, DakNet is not suitable for disaster/emergency relief situations
C OGNITIVE R ADIO AS AN E MERGING
In this section, we introduce the concepts of opportunistic spectrum access and cognitive radio After that, we describe how the IEEE 802.22 cognitive radio technology can be employed in rural communications and highlight challenges that must be overcome
Traditionally, the U.S Federal Communications Commission (FCC) regulates the radio spectrum resource by allocating separate frequency bands for different purposes Today, nearly 75 percent
of the UHF band (300 MHz–3 GHz) has been
allocated in this command and control manner.
Such a rigid and long-term allocation approach leads to spectrum under-utilization Recent mea-surements by the FCC show that 70 percent of the allocated spectrum in the United States is not utilized [11] This motivates the concept of
opportunistic spectrum access that allows
sec-ondary networks to borrow unused radio spec-trum from primary licensed networks [14]
The core technology behind opportunistic
spectrum access is cognitive radio ([12]), which
consists of the following components:
• Spectrum sensing: cognitive radio devices can
sense the spectrum environment to identify frequency bands that are not occupied by pri-mary users
• Dynamic spectrum management: cognitive radio
networks can dynamically select the best avail-able frequency bands for communications and monitor the spectrum environment to protect primary users
• Adaptive communications: Cognitive radio
devices can configure their transmission parameters to opportunistically make the best use of the ever-changing available spectrum Cognitive radio targets spatial and temporal spectrum white space by allowing secondary users to identify and exploit local and instanta-neous spectrum availability in non-intrusive manners
IEEE 802.22 — PROVIDINGRURALWIRELESS
The IEEE 802.22 Working Group was formed
in 2004 to develop a standard for wireless regional area networks (WRANs), based on cognitive radio technology [10] WRAN sys-tems will operate on the VHF/UHF TV bands, that is, from 54 MHz to 862 MHz, by oppor-tunistically making use of the unused TV chan-nels While doing so, it must ensure that no harmful interference is caused to the incum-bent users, which include TV receivers and FCC Part 74 wireless microphones [10] Figure
1 illustrates a typical WRAN deployment that consists of a WRAN base station (WRAN BS) serving multiple fixed-location wireless cus-tomer premise equipment (CPE) Figure 1 also shows a TV station and a wireless microphone system The WRAN must ensure that interfer-ence caused to all TV receivers within the TV protection contour (around 150 km from the
TV station) is below a predefined threshold Similarly, there is a protection area for the microphone system, but with a much smaller size (a few hundred meters)
For rural communications, 802.22 technology offers two main advantages, that is, no dedicated spectrum is required, and the coverage is large These two advantages help service providers address the cost-demand mismatch discussed earlier In particular, as no dedicated spectrum
is required, service providers can save the cost of obtaining a spectrum license In addition, wide coverage is essential to reach a large customer base in rural areas 802.22 technology is designed
to provide the average coverage of 33 km and can increase to 100 km
Although most of the 802.22 related work has focused on various technical challenges, such as designing advanced spectrum sensing to detect weak TV and microphone signals or providing coexistence for multiple WRANs, we contend that these issues may not be critical for remote, rural WRAN deployments In particular, in remote areas, there may be TV channels that are always available for 802.22 access, that is, with-out any need of spectrum sensing Also, it is not
WRAN systems will operate on the VHF/UHF TV bands, that is, from 54 MHz
to 862 MHz, by opportunistically making use of the unused TV channels.
While doing so,
it must ensure that
no harmful interfer-ence is caused to the incumbent users.
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likely that multiple WRANs will be deployed in
a sparsely populated region
Based on the previously mentioned argu-ments, we believe that the success of 802.22 as a technology for rural communications,
significant-ly depends on whether a scalable service model can be introduced for the rural market, and whether the technology can be deployed in an efficient way A scalable service model that is tailored for rural customer demand and aware-ness is discussed later Regarding system effi-ciency, a major concern is that when TDD is used in WRANs with large coverage areas, the long TDD turn-around time will significantly reduce the system throughput We will discuss
an approach to overcome this problem
C OMBINING TV A ND D ATA S ERVICES FOR
R URAL A REAS
Two important factors that determine the growth
of the rural ICT market are cost and service con-tent In terms of service content, as pointed out
in [7] and other surveys, although there are many potential applications, in the short-term, only e-mail, scan-e-mail, voice-over-e-e-mail, and chat are likely to be revenue-generating applications for the rural market We further contend that to increase the demand in the initial phase of net-work deployment, service providers should focus
on traditional applications such as telephone and
TV broadcasting Data services such as e-mail, Internet access, and video streaming, should be introduced gradually, in accordance with the adoption and awareness of rural customers
Based on the above arguments, we propose that service providers start with a TV broadcast-ing service, as the demand and awareness already exist in rural communities This TV broadcasting can be combined with delay-tolerant, asyn-chronous data applications such as e-mail and voice mail These data applications can be scaled
up in accordance with demand Furthermore, when the need arises, such as in emergency/disas-ter responses, TV broadcasting can be switched off to deliver command, control, and rescue infor-mation With this, we can eventually create a widespread wireless infrastructure that grows seamlessly with the rural communications market
Figure 2 illustrates how digital TV and data payloads can be multiplexed into the downlink (DL) channel, in both time and frequency
domains, for a system that employs TDD and OFDMA, that is, similar to IEEE 802.22 In sce-nario (a), a digital TV payload is transmitted on the earlier time slots of the downlink subframe
This is followed by downlink and uplink (UL) data payloads In scenario (b), both TV and DL data payloads can be transmitted simultaneously, but on orthogonal frequency subchannels These two configurations provide the flexibility to sup-port different amounts of data payload, for example, e-mail, file transfer, and different latency requirements
We note that there are existing technologies that support digital TV broadcasting, such as the European Digital Video Broadcasting standards (DVB-T for terrestrial and DVB-H for hand-helds), the North America Advanced Television
■Figure 1 IEEE 802.22 WRAN deployment Each WRAN system consists of
a BS serving fixed wireless subscribers (CPE) Incumbent users are TV receivers and FCC's Part 74 wireless microphones.
WRAN BS
WRAN CPE
WRAN coverage
Microphone protection area Wireless microphones
TV protection contour
TV station
■Figure 2 Different frame configurations that support combined digital TV and data services for a system
that employs TDD and OFDMA (e.g., IEEE 802.22).
Time
UL subframe
Control and signaling
DL data payload UL data payload
DL subframe
(a)
Time
UL subframe
Control and signaling
TV payload
DL data payload
DL subframe
(b) CHEN LAYOUT 6/5/08 1:24 PM Page 19
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Systems Committee (ATSC) standards, and mul-tichannel multipoint distribution service (MMDS) DVB and MMDS are also based on OFDM DVB and ATSC technologies only focus
on TV broadcasting, not general data services
MMDS can be used for both video and data ser-vices, but the high operating frequency (above 2 GHz) makes it unsuitable for large rural cover-age In our opinion, 802.22 technology that oper-ates on VHF/UHF bands and supports the flexible frame structures in Fig 2 can be a good solution to provide both TV and data services to the rural market
A DAPTIVE TDD FOR L ARGE R URAL
TDD TURN-AROUNDTIME
The operation of a point-to-multipoint system employing TDD and OFDMA can be illustrated
in Fig 3 Time is divided into fixed-length frames; each consists of a DL subframe and an
UL subframe that are used respectively for downlink and uplink transmissions In the time domain, DL and UL subframes are further
divid-ed into multiple OFDMA symbols; each consists
of a set of orthogonal subchannels in the fre-quency domain
Due to the difference in propagation delay from BS to the CPE, different CPE finish the downlink reception at different time instances Specifically, a nearby CPE can finish its DL reception long before a faraway CPE does This also means that a nearby CPE is ready to start uplink transmission before a faraway CPE is However, to guarantee reliable reception at the
BS, the UL transmissions from different CPE must be scheduled in a way such that the OFDMA symbol boundaries are aligned at the BS
The existing approach is to schedule the UL transmissions of all CPE based on the farthest one Specifically, even when nearby CPE finish
DL reception and are ready for UL transmis-sion, it is delayed so that UL transmissions reach the BS at the same time as those from the far-thest CPE This can be illustrated in Fig 3, where the UL transmission of nearby CPE 1 is delayed to align (at the BS) with that of the far-away CPE 2 The delay CPE 1 endures is equal
to the difference in round-trip propagation delays between CPE 1 and CPE 2
As was mentioned, 802.22 rural networks should target large service areas, for example, up
to 100 km in a coverage radius This means that the difference in the round-trip propagation delay between nearby and edge CPE can be sig-nificant For example, if the coverage radius is
100 km, then the difference in round-trip propa-gation delay will be {2×100×103/3×108} = 660 ×
the typical frame duration of 5 to 10 ms is signif-icant and can seriously reduce the operation effi-ciency of 802.22 WRANs
Our proposed scheme, termed adaptive TDD (ATTD), allows the transition gap between DL and UL subframes to be CPE-dependant Specif-ically, after finishing their downlink reception, nearby CPE is scheduled to start uplink trans-mission first, and far-away CPE start uplink transmission later While doing so, the OFDMA symbol boundaries of all CPE are synchronized
at the BS for reliable communications
Adaptive TDD is illustrated in Fig 4 When the difference between the round-trip propaga-tion delays of nearby CPE 1 and faraway CPE 2
is comparable to the OFDMA symbol duration, CPE 1 is allowed to start UL transmission right after finishing DL reception Faraway CPE 2 is scheduled to start UL transmission later such that the OFDMA symbol boundaries of all CPE are aligned at the BS In Fig 4, at the BS, the first OFDMA symbol of CPE 2 is aligned with the fourth OFDMA symbol of CPE 1
When adaptive TDD allows nearby CPE to start uplink transmission early and gain extra OFDMA symbols, this throughput gain can be beneficial to all users in the system and for both
■Figure 3 Structure of conventional TDD Uplink transmission from nearby
CPE 1 is delayed to align with uplink transmission from faraway CPE 2.
BS
CPE1
CPE2
Time
1 OFDMA symbol UL subframe
UL subframe
DL subframe
DL subframe
Propagation delay from BS to CPE2
UL subframe
DL subframe
Switch from receiving to transmitting mode
■Figure 4 Structure of proposed adaptive TDD Uplink transmission from
nearby CPE1 arrives at the BS earlier than that from faraway CPE 2 The OFDMA symbol boundaries of CPE 1 and CPE 2 uplink transmissions are synchronized at the BS.
BS
CPE1
CPE2
Time
Extra symbols gained by ATDD
UL subframe
Propagation delay from BS to CPE2
DL subframe
Switch from receiving to transmitting mode CHEN LAYOUT 6/5/08 1:24 PM Page 20
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uplink and downlink usage This is because the
BS can exploit the throughput gain of adaptive TDD in different ways, for example, to give some users extra uplink bandwidth or to support more users in the uplink, or even to keep the uplink load unchanged and schedule more down-link transmission
The above arguments are illustrated in Fig 5, where example bandwidth allocations are shown for the conventional TDD and the adaptive TDD approaches When conventional TDD is used, the BS can schedule DL and UL traffic for four users When adaptive TDD is used, two nearby users, namely, user 1 and 4 can transmit
UL data two symbols earlier than the rest Due
to this gain of two OFDMA symbols, the BS can schedule the DL and UL traffic for one extra user, namely, user 5, whereas the bandwidth allocated to the existing four users remains unchanged
To demonstrate the performance gain of adap-tive TDD, we consider a 802.22 deployment sce-nario with the following parameters The cell radius is 50 km; all CPE located inside a 5 km inner disk from the BS is regarded as nearby, and all CPE locating outside this inner disk is regarded as far away We vary the percentage of nearby CPE from 1 percent to 90 percent, where the low and high percentages of nearby CPE, respectively, represent the case of uniform and center-concentrated CPE distributions As
near-by CPE usually experience good channel condi-tions, they can transmit at higher rates compared
to faraway CPE Here, we assume that all CPE inside the inner disk can transmit using 64-QAM and 3/4 code rate and that all CPE outside the inner disk can transmit using quadrature phase shift keying (QPSK) and 1/2 code rate When the number of extra OFDMA symbols gained is fixed, the percentage gain in uplink capacity depends on the frame size The shorter the frame size, the higher the percentage gain in uplink capacity We consider the frame sizes of
5, 10, and 20 ms The TV channel bandwidth is 6 MHz, and OFDMA is based on 2048 fast
Fouri-er transform (FFT) size with cyclic prefix set at 1/4 and 1/8
In Fig 6, we plot the percentage gain in the uplink throughput versus the percentage of
near-by CPE With the chosen parameters, a CPE located inside the inner 5 km disk can transmit
UL data at one OFDMA symbol earlier than CPE located outside the inner disk As can be seen, the gain in average UL capacity when employing the proposed adaptive TDD scheme
is significant The highest gain is around 30 per-cent, and the lowest gain is around 5 percent
The gain decreases when the percentage of
near-by CPE increases This trend can be explained as follows The absolute gain, in terms of UL throughput, is almost constant (due to the fixed one OFDMA symbol gain) On the other hand, the absolute average throughput increases with the percentage of nearby CPE As a result, the percentage gain, which is equivalent to absolute
■Figure 5 Exploiting the gain of adaptive TDD Two OFDMA symbols are gained by adaptive TDD, and the BS can use this gain to
support one extra user (user 5) in both DL and UL.
Frame structure for conventional TDD
DL for user 1
DL for user 2
OFDMA symbols
UL for user 1
UL for user 2
UL for user 3
UL for user 4
DL for user 3
DL for user 4
Frame structure for conventional adaptive TDD
DL for user 1
UL for user 1
UL for user 4
UL for user 3
UL for user 2
UL for user 5
DL for user 2 OFDMA symbols
DL for user 3
DL for user 4
■Figure 6 Throughput gain of adaptive TDD.
Percentage of nearby CPEs 15
10 0
10
tage increase in UL throughput 20 30 40 50 60
20 25 30 35 40 45 50 55 60
Frame size = 5 ms, CP = 1/4 Frame size = 5 ms, CP = 1/8 Frame size = 10 ms, CP = 1/4 Frame size = 10 ms, CP = 1/8 Frame size = 20 ms, CP = 1/4 Frame size = 20 ms, CP = 1/8
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gain divided by the absolute throughput, will decrease as the percentage of nearby CPE increases
C ONCLUSIONS
In this article, we began with a discussion on the challenges of rural communications and then reviewed existing wireless technologies that were implemented or proposed for this market We then focused on an emerging technology, cognitive radio, that promises to be a viable solution for rural communications The most notable example
of a rural cognitive radio system is the IEEE 802.22 standard that currently is being developed, which is based on TDD, OFDMA, and opportunistic use of VHF/UHF TV bands We discussed two important issues that can affect the success of IEEE 802.22 technology for rural applications:
• Providing a suitable rural service model
• Overcoming the problem of long TDD turn-around time in large rural cells
For the first issue, we introduced a service model that combines TV broadcasting and data services to facilitate the growth of rural demand for connectivity For the second issue, we pro-posed adaptive TDD technology that effectively eliminates the requirement for long TDD turn-around time and thus, increases the efficiency of large coverage, rural networks
[1] Department of Economic and Social Affairs, United Nations, “World Urbanization Prospects: The 2005 Revi-sion,” Oct 2006; http://www.un.org/esa/population/
publications/WUP2005/2005wup.htm [2] E Hudson, “Economic and Social Benefits of Rural Telecommunications: A Report to the World Bank,”
June 1995.
[3] M D Farrimond, “PCN and Other Radio-Based Telecom-munications Technologies for Rural Regions of the
World,” Proc 2nd Int’l Conf Rural Telecommun.,
Lon-don, U.K., 1990, pp 99–104.
[4] R Westerveld and R Prasad, “Rural Communication in
India Using Fixed Cellular Radio Systems,” IEEE
Com-mun Mag., Oct 1994, pp 70–74.
[5] RuralNet 802.11-Based Low-Cost Networking for Rural India; http://www.cse.iitk.ac.in/users/braman/dgp.html [6] Y Kawasumi, “Deployment of WiFi for Rural Communi-ties in Japan and ITU’s Initiative for Pilot Projects,”
Proc 6th Int’l Wksp Enterprise Networking and Com-puting in Healthcare Industry, 2004, HEALTHCOM
2004, June 2004.
[7] A Pentland, R Fletcher, and A Hasson, “DakNet:
Rethinking Connectivity in Developing Nations,” IEEE
Computer, vol 37, no 1, Jan 2004, pp 78–83.
[8] FCC, “Facilitating Opportunities for Flexible, Efficient, and Reliable Spectrum Use Employing Cognitive Radio Technologies, Notice of Proposed Rule Making and Order, FCC 03-322,” Dec 2003.
[9] IEEE 802.22 WG Web site; http://www.ieee802.org/22/
[10] IEEE 802.22 Wireless RAN, “Functional Requirements for the 802.22 WRAN Standard, IEEE 802.22-05/0007r46,” Oct 2005.
[11] Federal Communications Commission, “Spectrum
Poli-cy Task Force Report, FCC 02-155,” Nov 2002 [12] J Mitola, “Cognitive Radio for Flexible Mobile
Multi-media Communications,” Proc IEEE Int’l Wksp Mobile
Multimedia Commun., 1999, pp 3–10.
[13] Y.-C Liang et al., “System Description and Operation
Principles for IEEE 802.22 WRANs,” http://www.ieee802 org/22/, Nov 2005.
[14] Y.-C Liang et al., “Sensing-Throughput Tradeoff for Cognitive Radio Networks,” IEEE Trans Wireless
Com-mun., vol 7, no 4, Apr 2008, pp 1326–37.
Y ING -C HANG L IANG [SM’00] (ycliang@i2r.a-star.edu.sg) is cur-rently a senior scientist at the Institute for Infocomm Research (I2R), Singapore He also holds adjunct associate professorship positions in Nanyang Technological University and National University of Singapore His research interests include cognitive radio, reconfigurable signal processing systems for broadband communications, space-time wire-less communications, and information theory From December 2002 to December 2003, he was a visiting
schol-ar with the Depschol-artment of Electrical Engineering, Stanford University At I2R he has been leading the research activi-ties in cognitive radio and standardization activiactivi-ties in IEEE 802.22 WRANs He received Best Paper Awards from IEEE VTC-Fall 1999 and IEEE PIMRC 2005.
A NH T UAN H OANG [M] (athoang@i2r.a-star.edu.sg) received
a Bachelor’s degree (with First Class Honors) in telecommu-nications engineering from the University of Sydney in
2000 He completed his Ph.D degree in electrical engineer-ing at the National University of Sengineer-ingapore in 2005 He is currently a research fellow in the Department of Network-ing Protocols, I2R His research focuses on design/optimiza-tion of wireless communicadesign/optimiza-tion networks Specific areas of interest include cross-layer design, dynamic spectrum access, and cooperative communications.
H SIAO -H WA C HEN [SM’00] (hshwchen@ieee.org) is currently a full professor in the Department of Engineering Science, National Cheng Kung University, Taiwan, and he was the founding director
of the Institute of Communications Engineering of the National Sun Yat-Sen University, Taiwan he received B.Sc and M.Sc degrees from Zhejiang University, China, and a Ph.D degree from the Uni-versity of Oulu, Finland, in 1982, 1985, and 1990, respectively, all
in electrical engineering He has authored or co-authored over 200 technical papers in major international journals and conferences, five books, and several book chapters in the areas of
communica-tions, including the books entitled Next Generation Wireless
Sys-tems and Networks and The Next Generation CDMA Technologies
(Wiley, 2005 and 2007) He has been an active volunteer for vari-ous IEEE technical activities for over 20 years Currently, he is serv-ing as chair of the IEEE ComSoc Radio Communications Committee and vice chair of the IEEE ComSoc Communications & Information Security Technical Committee He served or is serving as symposium chair/co-chair of many major IEEE conferences, including VTC, ICC, GLOBECOM, and WCNC, and so on He served or is serving
as associate editor and/or guest editor of numerous important tech-nical journals in communications He is serving as Chief Editor (Asia
and Pacific) for Wiley's Wireless Communications and Mobile
Computing Journal and Wiley's International Journal of Communi-cation Systems Currently, he is Editor-in-Chief of Wiley's Security and Communication Networks Journal (http://www.interscience.
wiley.com/journal/security) He is also an adjunct professor at Zhe-jiang University, China, and Shanghai Jiao Tong University, China.
We discussed two important issues that can affect the success
of IEEE 802.22 technology for rural applications:
providing a suitable rural service model;
overcoming the problem of long TDD turn-around time in large rural cells.
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