On collaborative detection of TV transmissions in support of dynamic spectrum sharing

By E. Visotsky, S. Kuffner, R. Peterson. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005., 2005

549 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/3f4f8e279b48a3acc3365fc7a49e678277694251

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Ian F. Akyildiz
2. Brandon F. Lo
3. Ravikumar Balakrishnan
4. K. Liu
5. Beibei Wang
6. H. Vincent Poor
7. Ali H. Sayed
8. Khaled Ben Letaief

In Electrical and Electronic Engineering

1. H. Vincent Poor
2. Ian F. Akyildiz
3. Brandon F. Lo
4. Beibei Wang
5. K. Liu
6. Ravikumar Balakrishnan
7. Khaled Ben Letaief
8. Shuguang Cui

Citations in the corpus

• Experimental study of spectrum sensing based on energy detection and network cooperation (2006, background): “However, due to variability of signal strength at various locations, this worst case condition could be avoided if multiple radios share their individual sensing measurements via network cooperation [9],[10],[11].”
• Cooperative spectrum sensing in cognitive radio networks: A survey (2011, methodology): “To facilitate the analysis of cooperative sensing, we classify cooperative spectrum sensing into three categories based on how cooperating CR users share the sensing data in the network: centralized [10] [6] [11], distributed [12], and relay-assisted [13] [14] [15].”
• Robust Distributed Spectrum Sensing in Cognitive Radio Networks (2008, methodology): “Recent studies [8], [10], [12] suggest that reliable spectrum sensing requires multiple CRs to cooperate and carry”
• Spectrum Sharing for Multi-Hop Networking with Cognitive Radios (2008, background): “A frequency-agile radio module is capable of sensing the available bands [3], [9], [10], [20], [26], [30], reconfiguring RF, and switching to newlyselected frequency bands.”
• Collaborative wideband sensing for cognitive radios (2008, methodology): “Likewise, an AND logic operation can be used [24], which decides H1 if, and only if, all the nodes claim that H1 is true.”
• Cooperative Sensing among Cognitive Radios (2006, background): “It has been argued that soft decision combining of sensing results yields gains that are much better than hard decision combining [16].”
• Cooperative Sensing for Primary Detection in Cognitive Radio (2008, background): “Previous works on user-cooperation for cognitive radio systems [3], [4] have considered two kinds of schemes: one where some kind of joint detection is employed among all the cooperating users and another where the final decision is made based on hard decisions made by each of the cooperating users.”
• Optimal Linear Cooperation for Spectrum Sensing in Cognitive Radio Networks (2008, methodology): “This cooperative method is different from those discussed in [12]–[14], since it requires a wide-band control channel.”
• Cooperative Communications for Cognitive Radio Networks (2009, methodology): “Instead of transmitting the 1-bit decision to the common receiver in step 2) of the above algorithm, each CR can just send its observation value directly to the common receiver [ 51 ].”
• A survey of spectrum sensing algorithms for cognitive radio applications (2009, methodology): “The results presented in [33], [34] show that soft information-combining outperforms hard information-combining method in terms of the probability of missed opportunity.”
• Advances in cognitive radio networks: A survey (2011, methodology): “Hard decision combining with the logic AND rule and soft decision using the likelihood ratio test are proposed in [76] in collaborative detection of TV transmissions.”
• Optimal Multiband Joint Detection for Spectrum Sensing in Cognitive Radio Networks (2008, methodology): “In [16], two decision-combining approaches were studied: hard decision with the AND logic operation, and soft decision using the likelihood ratio test [12].”
• Efficient Discovery of Spectrum Opportunities with MAC-Layer Sensing in Cognitive Radio Networks (2008, background): “On the other hand, the MAC-layer sensing determines when SUs have to sense which channels.”
• Game Theory in Wireless and Communication Networks (2008, methodology): “, using the OR rule [491], to obtain a final sensing decision (e.”