Optimal Multiband Joint Detection for Spectrum Sensing in Cognitive Radio Networks
Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to legacy (primary) networks. In this paper, a novel wideband spectrum sensing technique referred to...
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| Published in | IEEE transactions on signal processing Vol. 57; no. 3; pp. 1128 - 1140 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
IEEE
01.03.2009
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1053-587X 1941-0476 1941-0476 |
| DOI | 10.1109/TSP.2008.2008540 |
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| Abstract | Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to legacy (primary) networks. In this paper, a novel wideband spectrum sensing technique referred to as multiband joint detection is introduced, which jointly detects the primary signals over multiple frequency bands rather than over one band at a time. Specifically, the spectrum sensing problem is formulated as a class of optimization problems, which maximize the aggregated opportunistic throughput of a cognitive radio system under some constraints on the interference to the primary users. By exploiting the hidden convexity in the seemingly nonconvex problems, optimal solutions can be obtained for multiband joint detection under practical conditions. The situation in which individual cognitive radios might not be able to reliably detect weak primary signals due to channel fading/shadowing is also considered. To address this issue by exploiting the spatial diversity, a cooperative wideband spectrum sensing scheme refereed to as spatial-spectral joint detection is proposed, which is based on a linear combination of the local statistics from multiple spatially distributed cognitive radios. The cooperative sensing problem is also mapped into an optimization problem, for which suboptimal solutions can be obtained through mathematical transformation under conditions of practical interest. Simulation results show that the proposed spectrum sensing schemes can considerably improve system performance. This paper establishes useful principles for the design of distributed wideband spectrum sensing algorithms in cognitive radio networks. |
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| AbstractList | Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to legacy (primary) networks. In this paper, a novel wideband spectrum sensing technique referred to as (multiband) (joint) (detection) is introduced, which jointly detects the primary signals over multiple frequency bands rather than over one band at a time. Specifically, the spectrum sensing problem is formulated as a class of optimization problems, which maximize the (aggregated) (opportunistic) (throughput) of a cognitive radio system under some constraints on the interference to the primary users. By exploiting the hidden convexity in the seemingly nonconvex problems, optimal solutions can be obtained for multiband joint detection under practical conditions. The situation in which individual cognitive radios might not be able to reliably detect weak primary signals due to channel fading/shadowing is also considered. To address this issue by exploiting the spatial diversity, a cooperative wideband spectrum sensing scheme refereed to as (spatial-spectral) (joint) (detection) is proposed, which is based on a linear combination of the local statistics from multiple spatially distributed cognitive radios. The cooperative sensing problem is also mapped into an optimization problem, for which suboptimal solutions can be obtained through mathematical transformation under conditions of practical interest. Simulation results show that the proposed spectrum sensing schemes can considerably improve system performance. This paper establishes useful principles for the design of distributed wideband spectrum sensing algorithms in cognitive radio networks. The cooperative sensing problem is also mapped into an optimization problem, for which suboptimal solutions can be obtained through mathematical transformation under conditions of practical interest. |
| Author | Shuguang Cui Poor, H.V. Zhi Quan Sayed, A.H. |
| Author_xml | – sequence: 1 surname: Zhi Quan fullname: Zhi Quan organization: Dept. of Electr. Eng., Univ. of California, Los Angeles, CA – sequence: 2 surname: Shuguang Cui fullname: Shuguang Cui organization: Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX – sequence: 3 givenname: A.H. surname: Sayed fullname: Sayed, A.H. organization: Dept. of Electr. Eng., Univ. of California, Los Angeles, CA – sequence: 4 givenname: H.V. surname: Poor fullname: Poor, H.V. organization: Dept. of Electr. Eng., Princeton Univ., Princeton, NJ |
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| Keywords | hypothesis testing Small signal behavior Information rate Optimal detection Optimization nonlinear optimization Frequency band Linear combination Wide band Convexity Multiple frequency Signal detection Fading multiband joint detection Small signal Space diversity Cognitive radio Information transmission Cognitive system Joint detection Mathematical transformation Simulation Optimal solution spectrum sensing Signal processing cooperative sensing Shadowing Radio communication Software radio |
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| Snippet | Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and to opportunistically use under-utilized frequency... The cooperative sensing problem is also mapped into an optimization problem, for which suboptimal solutions can be obtained through mathematical transformation... |
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| SubjectTerms | Algorithms Applied sciences Cognitive radio Constraint optimization cooperative sensing Detection Detection, estimation, filtering, equalization, prediction Exact sciences and technology Fading Frequency Frequency bands hypothesis testing Information, signal and communications theory Interference Interference constraints Mathematical analysis Miscellaneous multiband joint detection Networks nonlinear optimization Optimization Radio Radiofrequency interference Shadow mapping Signal and communications theory Signal detection Signal processing Signal, noise spectrum sensing Studies Telecommunications and information theory Throughput Wideband |
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| Title | Optimal Multiband Joint Detection for Spectrum Sensing in Cognitive Radio Networks |
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