Optimal Linear Cooperation for Spectrum Sensing in Cognitive Radio Networks

By Zhi Quan, Shuguang Cui, Ali H. Sayed. IEEE Journal on Selected Topics in Signal Processing, 2008

1,090 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/e4b9d11ef515d8e467aaa7beac9fcc38c6ea31bb

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

In Electrical and Electronic Engineering

Citations in the corpus

Advances in cognitive radio networks: A survey (2011, background): “proposed in [78], where the global decision is a linear combina-”
Collaborative wideband sensing for cognitive radios (2008, methodology): “For ε > 1/2 and Q−1 (1 − ε) > 0, problem (33) becomes one of maximizing a convex function (or minimizing a concave function) over an ellipsoid, which can be efficiently solved through an iterative algorithm using quadratic-constraint quadraticprogramming (QCQP) reformulations [30].”
Ergodic Stochastic Optimization Algorithms for Wireless Communication and Networking (2010, background): “Particular examples where this type of problem formulation might arise include optimization of orthogonal frequency division multiplexing (OFDM), [3], beamforming, [4], [5] and cognitive radio, [6], [7].”
CRAHNs: Cognitive radio ad hoc networks (2009, neutral): “In [72], an optimal cooperative sensing strategy is proposed, where the final decision is based on a linear combination of the local test statistics from individual CR users.”
Cooperative spectrum sensing in cognitive radio networks: A survey (2011, background): “Due to the computational complexity of the LRT-based fusion methods that involves quadratic forms, an efficient linear combination of local test statistics is proposed in [58].”
Optimal Multiband Joint Detection for Spectrum Sensing in Cognitive Radio Networks (2008, methodology): “Along with these works, we have developed an optimal cooperation strategy [21] based on a linear combination of local statistics from multiple cognitive radios.”
A Review on Spectrum Sensing for Cognitive Radio: Challenges and Solutions (2010, background): “If the source signal power received by each user is known, the optimal combining coefficients can be found [38, 43].”
A Survey on Security Threats and Detection Techniques in Cognitive Radio Networks (2013, methodology): “Energy detection is the most widely method used because of its simplicity and low computational overhead [72], [73], [74], [75].”
An Adaptive Cooperation Diversity Scheme With Best-Relay Selection in Cognitive Radio Networks (2010, background): “In [11], a linear cooperative sensing framework has been proposed based on the combination of local statistics from individual cognitive users.”
Distributed Compressive Spectrum Sensing in Cooperative Multihop Cognitive Networks (2011, background): “Second, conventional cooperation schemes require a fusion center that collects measurements from all CRs and makes centralized sensing decisions [3], which may incur high communication costs and render the entire network vulnerable to node failure.”
Dynamic Resource Allocation in Cognitive Radio Networks (2010, background): “Spectrum sensing is now a very active area for research; the interested readers may refer to, e.g., [4], [5], [6], [7] for an overview of the state-of-art results in this area.”
Cognitive radio networking and communications: an overview (2011, background): “Ideal reporting is assumed in [44], whereas reporting channel noises are considered in [45], and the optimal weights under the Neyman– Pearson criterion are derived.”
Ten years of research in spectrum sensing and sharing in cognitive radio (2012, methodology): “Since the last kind is too complex and of limited interest in applications, only the first two have been studied in [47].”
Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks (2009, background): “It should be mentioned that optimal spectrum sensing under data fusion was investigated in [9], where the optimal linear function of weighted data fusion has been obtained.”
Optimization of Cooperative Sensing in Cognitive Radio Networks: A Sensing-Throughput Tradeoff View (2009, background): “There are various cooperative schemes to combine the sensing information from the secondary users, such as the k-out-of-N fusion rule [11], soft decision based fusion [12], and weighted data based fusion [13].”