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		<title><![CDATA[ Wireless Communications, IEEE - new TOC ]]></title>
		<link>http://ieeexplore.ieee.org</link>
		<description>TOC Alert for Publication# 7742 </description>
		<year>2013</year>
		<month>May      </month>
		<day>23</day>
		<item>
			<title><![CDATA[IEEE Wireless Communications - Front cover]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507382]]></link>
			<description><![CDATA[Presents the front cover for this issue of the magazine.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507382]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>c1</startPage>
			<endPage>c1</endPage>
			<fileSize>1700</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[Table of contents]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507383]]></link>
			<description><![CDATA[Presents the table of contents for this issue of this magazine.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507383]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>1</startPage>
			<endPage>1</endPage>
			<fileSize>118</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[Next generation cognitive cellular networks: spectrum sharing and trading [Message from the editor-in-chief]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507384]]></link>
			<description><![CDATA[Dear readers, The April issue of this magazine offers you a Feature Topic (FT) on "Next Generation Cognitive Cellular Networks: Spectrum Sharing and Trading" with 12 articles authored/coauthored by experts from both industry and academia. The call for papers for this FT attracted a fairly large number of submissions. Therefore, it was indeed a great challenge for the Guest Editors to handle their reviews in a very timely manner, and to select the best papers to be included in this FT out of so many submissions.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507384]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>2</startPage>
			<endPage>3</endPage>
			<fileSize>310</fileSize>
			<authors><![CDATA[Chen, H.-H.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Incentive auction: a proposed mechanism to rebalance spectrum between broadcast television and mobile broadband [Spectrum policy and regulatory issues]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507385]]></link>
			<description><![CDATA[The lifeblood of wireless technology is the spectrum that it uses. Formal regulation of spectrum, on both the national and international levels, generally began after the Titanic disaster in 1912. Since that period the upper limit of practical spectrum use has moved steadily higher, spectrum efficiency has greatly improved, and new services have emerged that both serve the public and compete for spectrum with longer standing services. A general problem for spectrum managers around the world is how to adapt spectrum policy to such changes, for while technology moves at "Internet speed," most governments agencies move at "government speed," which is much slower.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507385]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>4</startPage>
			<endPage>5</endPage>
			<fileSize>44</fileSize>
			<authors><![CDATA[Marcus, M.J.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Book reviews (1 review)]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507386]]></link>
			<description><![CDATA[This book has five chapters, each intended by the authors to be a self contained unit for the reader. The first chapter introduces the concepts and technology of CR, presents standardization policies in place and planned for the future, and examines design of scalable CR networks. Chapter 2 details the information theoretic side of CR networks, The chapter also presents guidelines for the spectral efficiency that can be achieved by the three CR paradigms proposed in the literature: underlay, overlay, and interweave, and the corresponding capacity regions for each paradigm. Chapter 3 presents propagation issues in CR networks. Chapter 4 deals with spectrum sensing to be used especially in the interweaving and underlay paradigms. Chapter 5 deals with spectrum exploration and exploitation including advanced spectrum sensing technologies, such as distributed detection and sequential and quick detection. The book does not cover networking aspects of CR, protocols, and standardization efforts, as acknowledged by the authors. However, this book is a good starting point for a graduate class in cognitive radio, a good introduction for new researchers, and a good reference book for practitioners.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507386]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>6</startPage>
			<endPage>6</endPage>
			<fileSize>34</fileSize>
			<authors><![CDATA[Misra, S.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Scanning the literature]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507387]]></link>
			<description><![CDATA[Provides an overview of the technical articles and features presented in this issue.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507387]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>8</startPage>
			<endPage>9</endPage>
			<fileSize>44</fileSize>
			<authors><![CDATA[Li, P.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Next generation cognitive cellular networks: spectrum sharing and trading [Guest editorial]]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507388]]></link>
			<description><![CDATA[In the past few years, fundamental research has demonstrated great potentials of cognitive radio (CR) in increasing the spectrum agility and system capacity of wireless communications systems. With the ability to detect and adapt to the surrounding environment, CR has become one of the widely recognized features for future wireless communication systems. Specifically, CR has been recommended as a key technology to solve the spectrum scarcity problem in the next generation cellar networks. For example, the IEEE 802.16h standard was recently published for the license-exempt operation of WiMAX networks by defining a set of CR capabilities. On the other hand, a lot of efforts are being made to introduce CR features into 3GPP LTE-Advanced.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507388]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>10</startPage>
			<endPage>11</endPage>
			<fileSize>345</fileSize>
			<authors><![CDATA[Lu, K.;Rong, B.;Kota, S.L.;Liu, G.;Wang, X.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Expanding LTE network spectrum with cognitive radios: From concept to implementation]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507389]]></link>
			<description><![CDATA[Wireless data traffic is growing extraordinarily, with new wireless devices such as smartphones and bandwidth-demanding wireless applications such as video streaming becoming increasingly popular and widely adopted. Correspondingly, we have also witnessed the phenomenal wireless technology evolutions to support higher system capacities from generation to generation. Long Term Evolution has been developed as a 4G wireless technology that can support next generation multimedia applications with high capacity and high mobility needs. However, the peak data rate from 3G UMTS to 4G LTE-Advanced only increases 55 percent annually, while global mobile traffic has increased 66 times with an annual growth rate of 131 percent between 2008 and 2013. Clearly, there is a huge gap between the growth rate of the new air interface and the growth rate of customers&#x00BF; needs. A promising way to alleviate the contention between the actual traffic demands and the actual system capacity growth is to exploit more available spectrum resources. Recently, cognitive radio technology has been under extensive research and study. It aims to provide abundant new spectrum opportunities by exploiting underutilized or unutilized spectrum opportunistically. In this article, we discuss the technical solutions to expand LTE spectrum with CR technology (LTE-CR), and survey the advances in LTE-CR from both research and implementation aspects. We present detailed key technologies that enable LTE-CR in the TV white space (TVWS), and related standards and regulation progresses. To demonstrate the feasibility of deploying LTECR in TVWS, we have conducted extensive system-level simulations and also developed a LTE-CR prototype. Both simulation and laboratory testing results show that applying LTECR in TVWS can achieve satisfactory performance.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507389]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>12</startPage>
			<endPage>19</endPage>
			<fileSize>451</fileSize>
			<authors><![CDATA[Junfeng Xiao;Hu, R.Q.;Yi Qian;Lei Gong;Bo Wang;]]></authors>
		</item>
		<item>
			<title><![CDATA["Simple rules" for mobile network operators' strategic choices in future cognitive spectrum sharing networks]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507390]]></link>
			<description><![CDATA[Spectrum sharing is becoming a necessity in future cellular networks due to the increasing traffic demand and challenges of getting exclusive spectrum. This article reviews the spectrum sharing framework that consists of regulatory, technology, and business domains. For future mobile network operators, sharing of spectrum with other operators or with other radiocommunication services - especially when using cognitive radio system technologies - is a disruptive change. Building on alternative spectrum sharing scenarios, this article discusses a set of Simple Rules for mobile network operators, both dominators and challengers, regarding spectrum sharing in future cognitive cellular networks. The Simple Rules provide a dynamic framework for both dominating and challenger mobile network operators for developing their sharing-based business models.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507390]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>20</startPage>
			<endPage>26</endPage>
			<fileSize>177</fileSize>
			<authors><![CDATA[Ahokangas, P.;Matinmikko, M.;Yrjola, S.;Okkonen, H.;Casey, T.;]]></authors>
		</item>
		<item>
			<title><![CDATA[On the scalability of cognitive radio: assessing the commercial viability of secondary spectrum access]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507391]]></link>
			<description><![CDATA[We report results from the recently finished QUASAR project, which has studied overall system aspects of cognitive radio technologies and has paid attention particularly to the economic viability of different use cases. We find that successful secondary sharing goes far beyond the detection of spectrum holes. Large-scale commercial success requires that secondary systems are scalable so that a large number of users can be served in an economically viable fashion. Our key finding is that secondary spectrum use is not an attractive method for most of the commercially interesting scenarios, from neither a business nor technical perspective. Perhaps somewhat surprisingly, the likely commercial ??sweet spot?? for secondary sharing in the lower frequency bands is short-range indoor communications. We also find that regulation does not currently present a significant barrier in Europe or the United States.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507391]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>28</startPage>
			<endPage>36</endPage>
			<fileSize>543</fileSize>
			<authors><![CDATA[Zander, J.;Rasmussen, L.K.;Sung, K.;Mahonen, P.;Petrova, M.;Jantti, R.;Kronander, J.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Self-organization paradigms and optimization approaches for cognitive radio technologies: a survey]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507392]]></link>
			<description><![CDATA[Cognitive radio is regarded as a promising technology to provide high bandwidth to mobile users via heterogeneous wireless network architectures and dynamic spectrum access techniques. However, cognitive radio networks may also impose some challenges due to various factors such as the ever increasing complexity of network architecture, the high cost of configuring and managing large-scale networks, the fluctuating nature of the available spectrum, diverse QoS requirements of various applications, and the intensifying difficulties of centralized control. A plethora of work has been carried out to address the challenges aforementioned by employing cognitive radio functionalities with self-organization features. In this article, variant aspects of self-organization paradigms in cognitive radio networks, including critical functionalities of MAC- and network-layer operations, are surveyed. The main contributions of this survey include introducing the fundamentals of existing cognitive radio and self-organization techniques as well as their current progress, surveying critical cognitive radio issues (including common control channel management, cooperative spectrum sensing, bioinspired spectrum sharing, network scalability and adaptive routing) as well as their self-organization features, and identifying new directions and open problems in cognitive radio networks.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507392]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>36</startPage>
			<endPage>42</endPage>
			<fileSize>1274</fileSize>
			<authors><![CDATA[Zhongshan Zhang;Keping Long;Jianping Wang;]]></authors>
		</item>
		<item>
			<title><![CDATA[Cognitive femtocell networks: an opportunistic spectrum access for future indoor wireless coverage]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507393]]></link>
			<description><![CDATA[Femtocells have emerged as a promising solution to provide wireless broadband access coverage in cellular dead zones and indoor environments. Compared with other techniques for indoor coverage, femtocells achieve better user experience with less capital expenditure and maintenance cost. However, co-channel deployments of closed subscriber group femtocells cause coverage holes in macrocells due to co-channel interference. To address this problem, cognitive radio technology has been integrated with femtocells. CR-enabled femtocells can actively sense their environment and exploit the network side information obtained from sensing to adaptively mitigate interference. We investigate three CR-enabled interference mitigation techniques, including opportunistic interference avoidance, interference cancellation, and interference alignment. Macrocell activities can be obtained without significant overhead in femtocells. In this article, we present a joint opportunistic interference avoidance scheme with Gale-Shapley spectrum sharing (GSOIA) based on the interweave paradigm to mitigate both tier interferences in macro/femto heterogeneous networks. In this scheme, cognitive femtocells opportunistically communicate over available spectrum with minimal interference to macrocells; different femtocells are assigned orthogonal spectrum resources with a one-to-one matching policy to avoid intratier interference. Our simulations show considerable performance improvement of the GSOIA scheme and validate the potential benefits of CR-enabled femtocells for in-home coverage.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507393]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>44</startPage>
			<endPage>51</endPage>
			<fileSize>448</fileSize>
			<authors><![CDATA[Li Huang;Guangxi Zhu;Xiaojiang Du;]]></authors>
		</item>
		<item>
			<title><![CDATA[Self-coexistence in cellular cognitive radio networks based on the IEEE 802.22 standard]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507394]]></link>
			<description><![CDATA[Cellular networks are the most diffuse type of wireless networks; however, they suffer from spectrum shortage due to the recent increase in smartphone wireless applications and services. Cognitive radios offer a key technology to successfully maintain, optimize and upgrade wireless networks and effectively address spectrum overcrowding problem. CRs have the ability to sense the frequency spectrum, learn from history, and make intelligent decisions to adjust their transmission parameters, and hence, perfectly integrate themselves into the existing wireless networks. The main challenges for implementing cellular CR networks (CCRNs) include the coexistence between CR devices and external wireless cellular networks, and the self-coexistence among these devices. The coexistence/self-coexistence problem in CCRNs can be seen as a channel assignment problem among the network cells. Considering IEEE 802.22 as the standard reference for cellular network mechanisms, this article addresses the coexistence/self-coexistence issues, and proposes two channel assignment schemes for cooperative and non-cooperative CR devices along with their pros and cons. An experimental study and comparison with a random channel assignment demonstrate that a robust and efficient channel assignment scheme is a critical feature in CCRNs.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507394]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>52</startPage>
			<endPage>59</endPage>
			<fileSize>843</fileSize>
			<authors><![CDATA[Gardellin, V.;Das, S.K.;Lenzini, L.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Design and implementation of spatial interweave LTE-TDD cognitive radio communication on an experimental platform]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507395]]></link>
			<description><![CDATA[Cognitive radio, which enables smart use of wireless resources, is a key ingredient to achieve high spectral efficiency. LTE, the latest evolution of cellular standards, is widely adopted and also targets high spectral efficiency. Hence, to enable wide adoption of cognitive radio, using LTE as the physical layer is a natural choice. Targeting a real-time implementation of LTEbased cognitive radio, we focus on spatial interweave cognitive radio, in which a secondary user uses an antenna array to perform null-beamforming in the primary user's direction, hence reusing the spectrum spatially. To allow this, without any help from the primary system, we use the time-division duplex mode and take advantage of the channel reciprocity. However, this reciprocity is jeopardized by the mismatch between the RF front-ends. Hence, we design a calibration protocol to restore it. A key contribution is that this cognitive system calibration does not require cooperation from the primary user. The whole system is implemented and evaluated on EURECOM's experimental OpenAirInterface platform. Performance results are presented, showing the feasibility of spatial interweave cognitive radio on a real-time platform.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507395]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>60</startPage>
			<endPage>67</endPage>
			<fileSize>679</fileSize>
			<authors><![CDATA[Kouassi, B.;Deneire, L.;Zayen, B.;Knopp, R.;Kaltenberger, F.;Negro, F.;Slock, D.;Ghaur, I.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Overlay cognitive radio OFDM system for 4G cellular networks]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507396]]></link>
			<description><![CDATA[In this study, we integrate overlay cognitive radio technology into 4G cellular networks for the sharing of TV spectrum. On one hand, OFDM is a promising technique for high-speed data transmission over multipath fading channels and has been considered to be the best candidate for 4G mobile networks. On another hand, the overlay cognitive radio model makes it possible to have two concurrent transmissions in a given interference region, where conventionally only one communication takes place at a given time. We investigate different service provision scenarios and propose both time domain and frequency domain overlay cognitive radio OFDM systems for next generation cellular networks. Numerical results show our proposed schemes can achieve satisfying performance in different use cases.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507396]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>68</startPage>
			<endPage>73</endPage>
			<fileSize>296</fileSize>
			<authors><![CDATA[Songlin Sun;Yanhong Ju;Yamao, Y.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Wideband spectrum sensing for cognitive radio networks: a survey]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507397]]></link>
			<description><![CDATA[Cognitive radio has emerged as one of the most promising candidate solutions to improve spectrum utilization in next generation cellular networks. A crucial requirement for future cognitive radio networks is wideband spectrum sensing: secondary users reliably detect spectral opportunities across a wide frequency range. In this article, various wideband spectrum sensing algorithms are presented, together with a discussion of the pros and cons of each algorithm and the challenging issues. Special attention is paid to the use of sub-Nyquist techniques, including compressive sensing and multichannel sub- Nyquist sampling techniques.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507397]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>74</startPage>
			<endPage>81</endPage>
			<fileSize>221</fileSize>
			<authors><![CDATA[Hongjian Sun;Nallanathan, A.;Cheng-Xiang Wang;Yunfei Chen;]]></authors>
		</item>
		<item>
			<title><![CDATA[Deploying cognitive cellular networks under dynamic resource management]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507398]]></link>
			<description><![CDATA[Smartphone fever along with roaring mobile traffic pose great challenges for cellular networks to provide seamless wireless access to end users. Operators and vendors realize that new techniques are required to improve spectrum efficiency to meet the ever increasing user demand. In this article, we exploit the great opportunities provided by cognitive radio technology in conventional cellular networks. Specifically, we first present challenging issues including interference management, network coordination, and interworking between access networks in a tiered cognitive cellular network with both macrocells and small cells. Taking into consideration the different network characteristics of macrocells and small cells, we then propose an adaptive resource management framework to improve spectrum utilization efficiency and mitigate the co-channel interference between macrocell and small cell users. A game-theory-based approach to efficient power control has also been provided.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507398]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>82</startPage>
			<endPage>88</endPage>
			<fileSize>232</fileSize>
			<authors><![CDATA[Yongkang Liu;Cai, L.X.;Xuemin Shen;Hongwei Luo;]]></authors>
		</item>
		<item>
			<title><![CDATA[Spectrum prediction in cognitive radio networks]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507399]]></link>
			<description><![CDATA[Spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility are four major functions of cognitive radio systems. Spectrum sensing is utilized to observe the spectrum occupancy status and recognize the channel availability, while CR users dynamically access the available channels through the regulation processes of spectrum decision, spectrum sharing, and spectrum mobility. To alleviate the processing delays involved in these four functions and to improve the efficiency of spectrum utilization, spectrum prediction for cognitive radio networks has been extensively studied in the literature. This article surveys the state of the art of spectrum prediction in cognitive radio networks. We summarize the major spectrum prediction techniques, illustrate their applications, and present the relevant open research challenges.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507399]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>90</startPage>
			<endPage>96</endPage>
			<fileSize>237</fileSize>
			<authors><![CDATA[Xiaoshuang Xing;Tao Jing;Wei Cheng;Yan Huo;Xiuzhen Cheng;]]></authors>
		</item>
		<item>
			<title><![CDATA[Feasibility of cognitive machine-to-machine communication using cellular bands]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507400]]></link>
			<description><![CDATA[We evaluate the feasibility of cognitive machine-to-machine communication on cellular bands from engineering and business perspectives. We propose a hierarchical network structure for cognitive M2M communication, where cluster headers gather M2M traffic using cognitive radio and forward it to the cellular networks. This structure can resolve the congestion problem that arises in conventional M2M systems. We obtain the optimal network parameters that minimize congestion at the radio access network. In addition, we investigate the business value of cognitive M2M on cellular bands. Taking into account the network usage fee, service fee, and hardware production costs, we model the profit structure of M2M services and derive the condition under which the CR type of M2M communication is superior to conventional M2M communication. We find that the optimal network design parameters (i.e., the number of cluster headers and cluster size) for business value would be different from the parameters expected from an engineering point of view. We believe that cognitive M2M communication can be a good solution for dealing with excessive M2M traffic in cellular networks, in terms of technical feasibility and business opportunity.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507400]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>97</startPage>
			<endPage>103</endPage>
			<fileSize>187</fileSize>
			<authors><![CDATA[Hyun-Kwan Lee;Dong Min Kim;Youngju Hwang;Seung Min Yu;Seong-Lyun Kim;]]></authors>
		</item>
		<item>
			<title><![CDATA[A survey on mobile data offloading: technical and business perspectives]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507401]]></link>
			<description><![CDATA[Over the last few years, data traffic over cellular networks has seen an exponential rise, primarily due to the explosion of smartphones, tablets, and laptops. This increase in data traffic on cellular networks has caused an immediate need for offloading traffic for optimum performance of both voice and data services. As a result, different innovative solutions have emerged to manage data traffic. Some of the key technologies include Wi-Fi, femtocells, and IP flow mobility. The growth of data traffic is also creating challenges for the backhaul of cellular networks; therefore, solutions such as core network offloading and media optimization are also gaining popularity. This article aims to provide a survey of mobile data offloading technologies including insights from the business perspective as well.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507401]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>104</startPage>
			<endPage>112</endPage>
			<fileSize>357</fileSize>
			<authors><![CDATA[Aijaz, A.;Aghvami, H.;Amani, M.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Fractional frequency reuse for interference management in LTE-advanced hetnets]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507402]]></link>
			<description><![CDATA[Improvement of cell coverage and network capacity are two major challenges for the evolving 4G cellular wireless communication networks such as LTE-Advanced networks. In this context, hierarchical layering of cells with macro base stations coexisting with low-power and shortrange base stations (corresponding to picocells or femtocells) in a service area is considered to be an efficient solution to enhance the spectral efficiency of the network per unit area. Also, such a hierarchical cell deployment, which is referred to as a heterogeneous network, or Het- Net, provides significant improvement in the coverage of indoor and cell edge users and ensures better QoS to the users. Interference mitigation between different layers is one of the key issues that needs to be resolved for successful deployment of HetNets. To this end, fast frequency response, FFR, is considered to be an efficient intercell interference coordination technique for OFDMA-based HetNets. This article focuses on evaluating three state-of-the-art FFR deployment schemes: strict FFR, soft FFR, and FFR-3 schemes for OFDMA-based two-tier HetNets comprising macrocells overlaid with femtocells. Also, a variation of the FFR-3 scheme, which is referred to as the optimal static FFR (OSFFR) scheme, is proposed. A broad comparison among all these FFR schemes is performed by using Monte Carlo simulations considering performance metrics such as outage probability, average network sum rate, and spectral efficiency. Simulation results show that, the average gains in spectral efficiency (b/s/Hz) of the network are significantly higher for the proposed scheme when compared to the strict FFR, soft FFR, and FFR-3 schemes.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507402]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>113</startPage>
			<endPage>122</endPage>
			<fileSize>294</fileSize>
			<authors><![CDATA[Saquib, N.;Hossain, E.;Dong In Kim;]]></authors>
		</item>
		<item>
			<title><![CDATA[TABOA: terrain-aware beacon order adaptation scheme in 3D zigbee sensor networks]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507403]]></link>
			<description><![CDATA[This article proposes a novel simulation model, terrain-aware beacon order adaptation (TABOA), used in 3D Zigbee sensor networks. The TABOA scheme adapts the beacon interval and superframe duration to change the active period in the IEEE 802.15.4 MAC structure according to the intrinsic characteristics of different terrains and traffic loads. Our contribution is to evaluate the performance of the IEEE 802.15.4 network in different terrains via simulation setups that closely model reality and figure out the optimal beacon interval and superframe duration in the different 3D terrains.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507403]]></guid>
			<volume>20</volume>
			<issue>2</issue>
			<startPage>122</startPage>
			<endPage>128</endPage>
			<fileSize>253</fileSize>
			<authors><![CDATA[Mu-Sheng Lin;Jenq-Shiou Leu;Kuen-Han Li;Wu, J.C.;]]></authors>
		</item>
	</channel>
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