Results 1 - 10
of
122
Cooperative spectrum sensing in cognition radio networks: A survey
- PHYSICAL COMMUNICATION
, 2010
"... ..."
Advances in Cognitive Radio Networks: A Survey
- IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
, 2011
"... With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a bottleneck for more efficient spectrum utilization, under which a great portion of the licensed spe ..."
Abstract
-
Cited by 105 (1 self)
- Add to MetaCart
With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a bottleneck for more efficient spectrum utilization, under which a great portion of the licensed spectrum is severely under-utilized. The inefficient usage of the limited spectrum resources urges the spectrum regulatory bodies to review their policy and start to seek for innovative communication technology that can exploit the wireless spectrum in a more intelligent and flexible way. The concept of cognitive radio is proposed to address the issue of spectrum efficiency and has been receiving an increasing attention in recent years, since it equips wireless users the capability to optimally adapt their operating parameters according to the interactions with the surrounding radio environment. There have been many significant developments in the past few years on cognitive radios. This paper surveys recent advances in research related to cognitive radios. The fundamentals of cognitive radio technology, architecture of a cognitive radio network and its applications are first introduced. The existing works in spectrum sensing are reviewed, and important issues in dynamic spectrum allocation and sharing are investigated in detail.
A Review on Spectrum Sensing for Cognitive Radio: Challenges and Solutions
, 2010
"... Cognitive radio is widely expected to be the next Big Bang in wireless communications. Spectrum sensing, that is, detecting the presence of the primary users in a licensed spectrum, is a fundamental problem for cognitive radio. As a result, spectrum sensing has reborn as a very active research area ..."
Abstract
-
Cited by 60 (9 self)
- Add to MetaCart
Cognitive radio is widely expected to be the next Big Bang in wireless communications. Spectrum sensing, that is, detecting the presence of the primary users in a licensed spectrum, is a fundamental problem for cognitive radio. As a result, spectrum sensing has reborn as a very active research area in recent years despite its long history. In this paper, spectrum sensing techniques from the optimal likelihood ratio test to energy detection, matched filtering detection, cyclostationary detection, eigenvalue-based sensing, joint space-time sensing, and robust sensing methods are reviewed. Cooperative spectrum sensing with multiple receivers is also discussed. Special attention is paid to sensing methods that need little prior information on the source signal and the propagation channel. Practical challenges such as noise power uncertainty are discussed and possible solutions are provided. Theoretical analysis on the test statistic distribution and threshold setting is also investigated.
Dynamic resource allocation in cognitive radio networks
- IEEE Signal Process. Mag
, 2010
"... ar ..."
(Show Context)
Distributed compressive spectrum sensing in cooperative multihop cognitive networks
- IEEE Journal of Selected Topics in Signal Processing
, 2010
"... Abstract—In wideband cognitive radio (CR) networks, spectrum sensing is an essential task for enabling dynamic spectrum sharing, but entails several major technical challenges: very high sampling rates required for wideband processing, limited power and computing resources per CR, frequency-selectiv ..."
Abstract
-
Cited by 44 (0 self)
- Add to MetaCart
(Show Context)
Abstract—In wideband cognitive radio (CR) networks, spectrum sensing is an essential task for enabling dynamic spectrum sharing, but entails several major technical challenges: very high sampling rates required for wideband processing, limited power and computing resources per CR, frequency-selective wireless fading, and interference due to signal leakage from other coexisting CRs. In this paper, a cooperative approach to wideband spectrum sensing is developed to overcome these challenges. To effectively reduce the data acquisition costs, a compressive sampling mechanism is utilized which exploits the signal sparsity induced by network spectrum under-utilization. To collect spatial diversity against wireless fading, multiple CRs collaborate during the sensing task by enforcing consensus among local spectral estimates; accordingly, a decentralized consensus optimization algorithm is derived to attain high sensing performance at a reasonable computational cost and power overhead. To identify spurious spectral estimates due to interfering CRs, the orthogonality between the spectrum of primary users and that of CRs is imposed as constraints for consensus optimization during distributed collaborative sensing. These decentralized techniques are developed for both cases of with and without channel knowledge. Simulations testify the effectiveness of the proposed cooperative sensing approach in multi-hop CR networks. Index Terms—Collaborative sensing, compressive sampling, consensus optimization, distributed fusion, spectrum sensing. I.
Multi-antenna based spectrum sensing for cognitive radio: a GLRT approach
- IEEE TRANS. COMMUN
, 2010
"... In this letter, we propose multi-antenna based spectrum sensing methods for cognitive radios (CRs) using the generalized likelihood ratio test (GLRT) paradigm. The proposed methods utilize the eigenvalues of the sample covariance matrix of the received signal vector from multiple antennas, taking ad ..."
Abstract
-
Cited by 43 (3 self)
- Add to MetaCart
In this letter, we propose multi-antenna based spectrum sensing methods for cognitive radios (CRs) using the generalized likelihood ratio test (GLRT) paradigm. The proposed methods utilize the eigenvalues of the sample covariance matrix of the received signal vector from multiple antennas, taking advantage of the fact that in practice, the primary user signals to be detected will either occupy a subspace of dimension strictly smaller than the dimension of the observation space, or have a non-white spatial spectrum. These methods do not require prior knowledge of the primary user signals, or the channels from the primary users to the CR. By making different assumptions on the availability of the white noise power value at the CR receiver, we derive two algorithms that are shown to outperform the standard energy detector.
A distributed consensus-based cooperative spectrum-sensing scheme in cognitive radios
- IEEE Transactions on Vehicular Technology
, 2010
"... Abstract—In cognitive radio (CR) networks, secondary users can cooperatively sense the spectrum to detect the presence of primary users. In this paper, we propose a fully distributed and scalable cooperative spectrum-sensing scheme based on recent advances in consensus algorithms. In the proposed sc ..."
Abstract
-
Cited by 27 (5 self)
- Add to MetaCart
(Show Context)
Abstract—In cognitive radio (CR) networks, secondary users can cooperatively sense the spectrum to detect the presence of primary users. In this paper, we propose a fully distributed and scalable cooperative spectrum-sensing scheme based on recent advances in consensus algorithms. In the proposed scheme, the secondary users can maintain coordination based on only local information exchange without a centralized common receiver. Unlike most of the existing decision rules, such as the OR-rule or the 1-out-of-N rule, we use the consensus of secondary users to make the final decision. Simulation results show that the proposed consensus scheme can have significant lower missing detection probabilities and false alarm probabilities in CR networks. It is also demonstrated that the proposed scheme not only has proven sensitivity in detecting the primary user’s presence but also has robustness in choosing a desirable decision threshold. Index Terms—Cognitive radios (CRs), consensus, cooperative spectrum sensing, random graphs. I.
Giannakis, “Sequential and cooperative sensing for multi-channel cognitive radios
- IEEE Trans. Signal Process
, 2010
"... Abstract—Effective spectrum sensing is a critical prerequisite for multi-channel cognitive radio (CR) networks, where multiple spectrum bands are sensed to identify transmission opportunities, while preventing interference to the primary users. The present paper develops sequential spectrum sensing ..."
Abstract
-
Cited by 22 (1 self)
- Add to MetaCart
(Show Context)
Abstract—Effective spectrum sensing is a critical prerequisite for multi-channel cognitive radio (CR) networks, where multiple spectrum bands are sensed to identify transmission opportunities, while preventing interference to the primary users. The present paper develops sequential spectrum sensing algorithms which ex-plicitly take into account the sensing time overhead, and optimize a performance metric capturing the effective average data rate of CR transmitters. A constrained dynamic programming problem is formulated to obtain the policy that chooses the best time to stop taking measurements and the best set of channels to access for data transmission, while adhering to hard “collision ” constraints im-posed to protect primary links. Given the associated Lagrange mul-tipliers, the optimal access policy is obtained in closed form, and the subsequent problem reduces to an optimal stopping problem. A basis expansion-based sub-optimal strategy is employed to miti-gate the prohibitive computational complexity of the optimal stop-ping policy. A novel on-line implementation based on the recursive least-squares (RLS) algorithm along with a stochastic dual update procedure is then developed to obviate the lengthy training phase of the batch scheme. Cooperative sequential sensing generalizations are also provided with either raw or quantized measurements col-lected at a central processing unit. The numerical results presented verify the efficacy of the proposed algorithms. Index Terms—Cognitive radio, optimal stopping, sequential de-tection, spectrum sensing. I.
CRP: A routing protocol for cognitive radio ad hoc networks
- IEEE Journal of Selected Areas in Communications (JSAC
"... use of the vacant licensed frequency bands, thereby improving the spectrum utilization. However, the CR operation must not interfere with the transmissions of the licensed or primary users (PUs), and this is generally achieved by incurring a trade-off in the CR network performance. In order to evalu ..."
Abstract
-
Cited by 21 (0 self)
- Add to MetaCart
(Show Context)
use of the vacant licensed frequency bands, thereby improving the spectrum utilization. However, the CR operation must not interfere with the transmissions of the licensed or primary users (PUs), and this is generally achieved by incurring a trade-off in the CR network performance. In order to evaluate this trade-off, a distributed CR routing protocol for ad hoc networks (CRP) is proposed that makes the following contributions: (i) explicit protection for PU receivers that are generally not detected during spectrum sensing, (ii) allowing multiple classes of routes based on service differentiation in CR networks, and (iii) scalable, joint route-spectrum selection. A key novelty of CRP is the mapping of spectrum selection metrics, and local PU interference observations to a packet forwarding delay over the control channel. This allows the route formation undertaken over a control channel to capture the environmental and spectrum information for all the intermediate nodes, thereby reducing the computational overhead at the destination. Results reveal the importance of formulating the routing problem from the viewpoint of safeguarding the PU communication, which is a unique feature in CR networks.
Optimal spectral feature detection for spectrum sensing at very low SNR
- IEEE Trans Commun
, 2011
"... Abstract—Spectrum sensing is one of the enabling function-alities for cognitive radio systems to operate in the spectrum white space. To protect the primary incumbent users from interference, the cognitive radio is required to detect incumbent signals at very low signal-to-noise ratio (SNR). In this ..."
Abstract
-
Cited by 16 (1 self)
- Add to MetaCart
(Show Context)
Abstract—Spectrum sensing is one of the enabling function-alities for cognitive radio systems to operate in the spectrum white space. To protect the primary incumbent users from interference, the cognitive radio is required to detect incumbent signals at very low signal-to-noise ratio (SNR). In this paper, we study a spectrum sensing technique based on spectral correlation for detection of television (TV) broadcasting signals. The basic strategy is to correlate the periodogram of the received signal with the a priori known spectral features of the primary signal. We show that this sensing technique is asymptotically equivalent to the likelihood ratio test (LRT) at very low SNR, but with less computational complexity. That is, the spectral correlation-based detector is asymptotically optimal according to the Neyman-Pearson criterion. From the system design perspective, we analyze the effect of the spectral features on the spectrum sensing performance. Through the optimization analysis, we obtain useful insights on how to choose effective spectral features to achieve reliable sensing. Simulation results show that the proposed sensing technique can reliably detect analog and digital TV signals at SNR levels as low as −20 dB. Index Terms—Spectrum sensing, hypothesis testing, feature detection, optimization, cognitive radio. I.
