The detection and classification of the Wireless Microphone signal in the IEEE 802.22 WRAN system

Lim, Sunmin; Kim, Sangwon; Park, Chang-Hyun; Song, Mee

doi:10.1109/apmc.2007.4554785

Cited by 12 publications

(4 citation statements)

References 1 publication

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“…In each cluster, each secondary user senses the spectrum and searches for subchannels unused by primary users, which, for instance, may be wireless microphones or other Part 74 devices [19]. The spectrum sensing results consist of binary indicators specifying the availability of subchannels.…”

Section: Dynamic Spectrum Access and Fairness Issuesmentioning

confidence: 99%

Decentralized Fair Scheduling in Two-Hop Relay-Assisted Cognitive OFDMA Systems

Wang

Lau

Cui

2011

IEEE J. Sel. Top. Signal Process.

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In this paper, we consider a two-hop relay-assisted cognitive downlink OFDMA system (named as secondary system) dynamically accessing a spectrum licensed to a primary network, thereby improving the efficiency of spectrum usage. A cluster-based relay-assisted architecture is proposed for the secondary system, where relay stations are employed for minimizing the interference to the users in the primary network and achieving fairness for cell-edge users. Based on this architecture, an asymptotically optimal solution is derived for jointly controlling data rates, transmission power, and subchannel allocation to optimize the average weighted sum goodput where the proportional fair scheduling (PFS) is included as a special case. This solution supports decentralized implementation, requires small communication overhead, and is robust against imperfect channel state information at the transmitter (CSIT) and sensing measurement. The proposed solution achieves significant throughput gains and better user-fairness compared with the existing designs. Finally, we derived a simple and asymptotically optimal scheduling solution as well as the associated closed-form performance under the proportional fair scheduling for a large number of users. The system throughput is shown to be O N (1 − q p )(1 − q N p ) ln ln K c , where K c is the number of users in one cluster, N is the number of subchannels and q p is the active probability of primary users.

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Section: Dynamic Spectrum Access and Fairness Issuesmentioning

confidence: 99%

Decentralized Fair Scheduling in Two-Hop Relay-Assisted Cognitive OFDMA Systems

Wang

Lau

Cui

2011

IEEE J. Sel. Top. Signal Process.

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“…In reference [8], ployphase DFT filter banks are proposed for spectrum detection, in which the TV channel is divided into 6 sub bands and the filter banks presented in [8] are used to detect 5 continuous TV channels. Furthermore, reference [9] uses DFT filter bank (DFTFB) to detect the WM. If WM spans two filters, reference [9] uses the cyclostationary property to detect the precise frequency.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, reference [9] uses DFT filter bank (DFTFB) to detect the WM. If WM spans two filters, reference [9] uses the cyclostationary property to detect the precise frequency.…”

Section: Introductionmentioning

confidence: 99%

Novel filter banks based wireless microphone detection in IEEE 802.22 WRAN

Cui

Zhao

Zhang

2010

Proceedings of the 5th International ICST Conference on Communications and Networking in China

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The primary task in any cognitive radio (CR) network is to dynamically explore the spectrum and determine spectrum band that can be used without causing interference to other users.In this paper, we propose a multistage filter banks to sense the spectrum band. Compared with the conventional filter banks, our proposed method has low complexity but high detection precision. The proposed scheme has been analyzed and tested through simulations on wireless microphone detection in IEEE 802.22 WRAN.

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“…To avoid interfering to each other, these WM signals must operate in different center frequencies with enough guard bandwidth. To detect multiple WM signals in a wide bandwidth, (Lim et al, 2007) suggested to use a cyclostationary filter with a filterbank to detect every sub-channel which is divided from the wide sensing spectrum in advance. If a conventional energy detector is used, the sensing process has to include two steps: coarse sensing and fine sensing.…”

Section: Basic Assumptions and Problem Formulationmentioning

confidence: 99%