20,928 research outputs found
Design and Optimal Configuration of Full-Duplex MAC Protocol for Cognitive Radio Networks Considering Self-Interference
In this paper, we propose an adaptive Medium Access Control (MAC) protocol
for full-duplex (FD) cognitive radio networks in which FD secondary users (SUs)
perform channel contention followed by concurrent spectrum sensing and
transmission, and transmission only with maximum power in two different stages
(called the FD sensing and transmission stages, respectively) in each
contention and access cycle. The proposed FD cognitive MAC (FDC-MAC) protocol
does not require synchronization among SUs and it efficiently utilizes the
spectrum and mitigates the self-interference in the FD transceiver. We then
develop a mathematical model to analyze the throughput performance of the
FDC-MAC protocol where both half-duplex (HD) transmission (HDTx) and FD
transmission (FDTx) modes are considered in the transmission stage. Then, we
study the FDC-MAC configuration optimization through adaptively controlling the
spectrum sensing duration and transmit power level in the FD sensing stage
where we prove that there exists optimal sensing time and transmit power to
achieve the maximum throughput and we develop an algorithm to configure the
proposed FDC-MAC protocol. Extensive numerical results are presented to
illustrate the characteristic of the optimal FDC-MAC configuration and the
impacts of protocol parameters and the self-interference cancellation quality
on the throughput performance. Moreover, we demonstrate the significant
throughput gains of the FDC-MAC protocol with respect to existing half-duplex
MAC (HD MAC) and single-stage FD MAC protocols.Comment: To Appear, IEEE Access, 201
Joint Optimization of Detection Threshold and Resource Allocation in Infrastructure-based Multi-band Cognitive Radio Networks
[EN] Consider an infrastructure-based multi-band cognitive radio network (CRN) where secondary users (SUs) opportunistically access a set of sub-carriers when sensed as idle. The carrier sensing threshold which affects the access opportunities of SUs is conventionally regarded as static and treated independently from the resource allocation in the model. In this article, we study jointly the optimization of detection threshold and resource allocation with the goal of maximizing the total downlink capacity of SUs in such CRNs. The optimization problem is formulated considering three sets of variables, i.e., detection threshold, sub-carrier assignment and power allocation, with constraints on the PUsÂż rate loss and the power budget of the CR base station. Two schemes, referred to as offline and online algorithms respectively, are proposed to solve the optimization problem. While the offline algorithm finds the global optimal solution with high complexity, the online algorithm provides a close-to-optimal solution with much lower complexity and realtime capability. The performance of the proposed schemes is evaluated by extensive simulations and compared with the conventional static threshold selection algorithm specified in the IEEE 802.22 standard.This work is supported by the EU FP7 S2EuNet project (247083), the National Nature Science Foundation of China (NSF61121001), Program for New Century Excellent Talents in University (NCET) and the Spanish Ministry of Education
and Science under project (TIN2008-06739-C04-02).Shi, C.; Wang, Y.; Wang, T.; Zhang, P.; MartĂnez Bauset, J.; Li, FY. (2012). Joint Optimization of Detection Threshold and Resource Allocation in Infrastructure-based Multi-band Cognitive Radio Networks. EURASIP Journal on Wireless Communications and Networking. 2012(334):1-16. https://doi.org/10.1186/1687-1499-2012-334S1162012334Wang B, Liu K: Advances in cognitive radio networks: a survey. IEEE J. Sel. Top. Signal Process 2011, 5: 5-23.Akyildiz I, Lee W, Vuran M, Mohanty S: Next generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Comput. Netw. 2006, 50(13):2127-2159. 10.1016/j.comnet.2006.05.001Haykin S: Cognitive radio: brain-empowered wireless communications. IEEE J. Sel. Areas Commun 2005, 23(2):201-220.Zhao Q, Sadler B: A survey of dynamic spectrum access. IEEE Signal Process. Mag 2007, 24(3):79-89.Nguyen M, Lee H: Effective scheduling in infrastructure-based cognitive radio network. IEEE Trans. Mobile Comput 2011, 10(6):853-867.Almalfouh S, Stuber G: Interference-aware radio resource allocation in OFDMA-based cognitive radio networks. IEEE Trans. Veh. Technol 2011, 60(4):1699-1713.Kang X, Liang Y, Nallanathan A, Garg H, Zhang R: Optimal power allocation for fading channels in cognitive radio networks: ergodic capacity and outage capacity. IEEE Trans. Wirel. Commun 2009, 8(2):940-950.Bansal G, Hossain M, Bhargava V: Optimal and suboptimal power allocation schemes for OFDM-based cognitive radio systems. IEEE Trans. Wirel. Commun 2008, 7(11):4710-4718.Yucek T, Arslan H: A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Commun. Surv. Tutor 2009, 11: 116-130.Cordeiro C, Ghosh M, Cavalcanti D, Challapali K: Spectrum sensing for dynamic spectrum access of TV bands. In Proceedings of the 2nd Cognitive Radio Oriented Wireless Networks and Communications (CrownCom’07). (Orlando, FL, USA, 1–3 Aug 2007);Chong J, Sung D, Sung Y: Cross-layer performance analysis for CSMA/CA protocols: impact of imperfect sensing. IEEE Trans. Veh. Technol 2010, 59(3):1100-1108.Seol D, Lim H, Im G: Cooperative spectrum sensing with dynamic threshold adaptation. In Proceedings of the IEEE Global Telecommunications Conference (GLOBECOM’09). Honolulu, HI, USA; 1.Liang Y, Zeng Y, Peh E, Hoang A: Sensing-throughput tradeoff for cognitive radio networks. IEEE Trans. Wirel. Commun 2008, 7(4):1326-1337.Kang X, Liang Y, Garg H, Zhang L: Sensing-based spectrum sharing in cognitive radio networks. IEEE Trans. Veh. Technol 2009, 58(8):4649-4654.Choi H, Jang K, Cheong Y: Adaptive sensing threshold control based on transmission power in cognitive radio systems. In Proceedings of the 3rd Cognitive Radio Oriented Wireless Networks and Communications (CrownCom’08). (Singapore, 15–17 May 2008), pp.1–6Gorcin A, Qaraqe K, Celebi H, Arslan H: An adaptive threshold method for spectrum sensing in multi-channel cognitive radio networks. In Proceedings of the IEEE International Conference on Telecommunications (ICT’10). Doha, Qatar; 4.Foukalas F, Mathiopoulos P, Karetsos G: Joint optimal power allocation and sensing threshold selection for SU’s capacity maximisation in SS CRN. Electron. Lett 2010, 46(20):1406-1407. 10.1049/el.2010.1355Jia P, Vu M, Le-Ngoc T, Hong S, Tarokh V: Capacity-and bayesian-based cognitive sensing with location side information. IEEE J. Sel. Areas Commun 2011, 29(2):276-289.Wang R, Lau V, Lv L, Chen B: Joint cross-layer scheduling and spectrum sensing for OFDMA cognitive radio systems. IEEE Trans. Wirel. Commun 2009, 8(5):2410-2416.Kang X, Garg H, Liang Y, Zhang R: Optimal power allocation for OFDM-based cognitive radio with new primary transmission protection criteria. IEEE Trans. Wirel. 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CYCLOSTATIONARY FEATURES OF PAL TV AND WIRELESS MICROPHONE FOR COGNITIVE RADIO APPLICATIONS
Frequency spectrum being a scarce resource in communication system design,
spectrum sharing seems to be the solution to an optimal utilization of frequency
spectrum. The traditional fixed frequency allocation is not suitable for futuristic
networks that demand more and more spectrum for new wireless services. Cognitive
radio is a new emerging technology based on spectrum sharing concept.
Spectrum sensing is a vital task in this emerging technology by which it is able to
scan the frequency spectrum to identify the unused spectrum bands and utilize them.
In this thesis, we discuss spectrum sensing in the context of IEEE 802.22 Wireless
Regional Area Network (WRAN). In order to do so, we develop the co-existence
scenario with three cases according to geographical positions of primary services and
secondary service. In WRAN application, the SUs utilize the unused channel in TV
spectrum, which means that the primary users are TV service and other FCC part 74
low power licensed devices. We focus on special case of Analog TV-PAL service and
wireless microphone service as part 74 devices. Before discussing the spectrum
sensing technique, we propose architecture for sensing receiver. The concept of noise
uncertainty is also introduced in this context. The cyclostationarity theory is
introduced and we explain the motivation behind using the theory for spectrum
sensing and the reason that makes the cyclostationary features detector a powerful
detection technique in cognitive radio. We obtain the cyclostationary features of these
primary signals using spectral correlation function. Based on these features, we
develop two algorithms for spectrum sensing and their performances are evaluated in
comparison with energy detector which is considered as the standard simple detector.
Given that the cyclostationary features are unique for a particular signal; these
features can be used for signals classification. In our case, we use those features to
decide if the licensed channel is used by TV service or wireless microphone service.
This provides additional information for spectrum management and power control. Implementation issue is very important in cognitive radio generally and spectrum
sensing specially, hence we discuss the implementation of cyclostationary features
detector and compare its complexity with that of energy detector
Full-Duplex Cognitive Radio: A New Design Paradigm for Enhancing Spectrum Usage
With the rapid growth of demand for ever-increasing data rate, spectrum
resources have become more and more scarce. As a promising technique to
increase the efficiency of the spectrum utilization, cognitive radio (CR)
technique has the great potential to meet such a requirement by allowing
un-licensed users to coexist in licensed bands. In conventional CR systems, the
spectrum sensing is performed at the beginning of each time slot before the
data transmission. This unfortunately results in two major problems: 1)
transmission time reduction due to sensing, and 2) sensing accuracy impairment
due to data transmission. To tackle these problems, in this paper we present a
new design paradigm for future CR by exploring the full-duplex (FD) techniques
to achieve the simultaneous spectrum sensing and data transmission. With FD
radios equipped at the secondary users (SUs), SUs can simultaneously sense and
access the vacant spectrum, and thus, significantly improve sensing
performances and meanwhile increase data transmission efficiency. The aim of
this article is to transform the promising conceptual framework into the
practical wireless network design by addressing a diverse set of challenges
such as protocol design and theoretical analysis. Several application scenarios
with FD enabled CR are elaborated, and key open research directions and novel
algorithms in these systems are discussed
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