Optimal Multiband Joint Detection for Spectrum Sensing in Cognitive Radio Networks

By Zhi Quan, Shuguang Cui, Ali H. Sayed, H. Vincent Poor. IEEE Transactions on Signal Processing, 2008

766 citations recorded by the source corpus.

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.

Subfields: Aerospace Engineering, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/7057a0717f366d715fc5b7e6978d321a011006a0

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Citations in the corpus

Cooperative spectrum sensing in cognitive radio networks: A survey (2011, methodology): “Unlike the multi-band sensing scheme in [34], each of cooperating CR users senses a different channel.”
Wideband spectrum sensing for cognitive radio networks: a survey (2013, background): “In each band, the corresponding portion of the spectrum for the wideband signal was down-converted to base-band and then low-pass ﬁltered.”
Advances on Spectrum Sensing for Cognitive Radio Networks: Theory and Applications (2017, methodology): “One way is to sense K bands from M spatially distributed CR users and then the statistics are combined at the FC [94] which makes a cooperative decision on each band.”
Collaborative wideband sensing for cognitive radios (2008, methodology): “We will describe a cross-layer design principle for collaborative wideband sensing, in which spectrum sensing at the physical (PHY) layer, and the maximization of opportunistic throughput at higher layers, are integrated into a unified framework based on the multiband joint detection (MJD) scheme in”
Cognitive radio networking and communications: an overview (2011, background): “Wideband spectrum sensing with cooperation is addressed in [47] using ED.”
Ten years of research in spectrum sensing and sharing in cognitive radio (2012, methodology): “Based on energy detector for narrowband sensing, the sensing time and detection thresholds for each narrowband detector are optimized jointly, which is different from the previous multiband joint detection framework in [44].”
Distributed Spectrum Sensing for Cognitive Radio Networks by Exploiting Sparsity (2010, background): “At the expense of commensurate communication overhead [12], these cooperative sensing and detection schemes have been shown to increase reliability, reduce the average detection time, cope with fading propagation effects, and improve throughput [9], [11], [14], [17].”