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Breaking Spectrum Gridlock with Cognitive Radios: An Information Theoretic Perspective
, 2008
"... Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified b ..."
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Cited by 265 (4 self)
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Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified by the definition of a cognitive radio as an intelligent wireless communication device that exploits side information about its environment to improve spectrum utilization. This side information typically comprises knowledge about the activity, channels, codebooks and/or messages of other nodes with which the cognitive node shares the spectrum. Based on the nature of the available side information as well as a priori rules about spectrum usage, cognitive radio systems seek to underlay, overlay or interweave the cognitive radios ’ signals with the transmissions of noncognitive nodes. We provide a comprehensive summary of the known capacity characterizations in terms of upper and lower bounds for each of these three approaches. The increase in system degrees of freedom obtained through cognitive radios is also illuminated. This information theoretic survey provides guidelines for the spectral efficiency gains possible through cognitive radios, as well as practical design ideas to mitigate the coexistence challenges in today’s crowded spectrum.
Joint design and separation principle for opportunistic spectrum access
- IEEE Transactions on Information Theory
, 2006
"... Abstract — This paper develops optimal strategy for opportunistic spectrum access (OSA) by integrating the design of spectrum sensor at the physical layer with that of spectrum sensing and access policies at the medium access control (MAC) layer. The design objective is to maximize the throughput of ..."
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Cited by 137 (35 self)
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Abstract — This paper develops optimal strategy for opportunistic spectrum access (OSA) by integrating the design of spectrum sensor at the physical layer with that of spectrum sensing and access policies at the medium access control (MAC) layer. The design objective is to maximize the throughput of secondary users while limiting their probability of colliding with primary users. By exploiting the rich structures of the problem, we establish a separation principle: the design of spectrum sensor and access policy can be decoupled from that of sensing policy without losing optimality. This separation principle enables us to obtain closedform optimal sensor operating characteristic and access policy, leading to significant complexity reduction. It also allows us to study the inherent interaction between spectrum sensor and access policy and the tradeoff between false alarm and miss detection in opportunity identification. I.
Optimality of Myopic Sensing in Multichannel Opportunistic Access
, 2008
"... We consider opportunistic communication over multiple channels where the state (“good ” or “bad”) of each channel evolves as independent and identically distributed Markov processes. A user, with limited channel sensing and access capability, chooses one channel to sense and subsequently access (bas ..."
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Cited by 112 (38 self)
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We consider opportunistic communication over multiple channels where the state (“good ” or “bad”) of each channel evolves as independent and identically distributed Markov processes. A user, with limited channel sensing and access capability, chooses one channel to sense and subsequently access (based on the sensed channel state) in each time slot. A reward is obtained whenever the user senses and accesses a “good ” channel. The objective is to design an optimal channel selection policy that maximizes the expected total (discounted or average) reward accrued over a finite or infinite horizon. This problem can be cast as a Partially Observable Markov Decision Process (POMDP) or a restless multi-armed bandit process, to which optimal solutions are often intractable. We show in this paper that a myopic policy that maximizes the immediate one-step reward is always optimal when the state transitions are positively correlated over time. When the state transitions are negatively correlated, we show that the same policy is optimal when the number of channels is limited to 2 or 3, while presenting a counterexample for the case of 4 channels. This result finds applications in opportunistic transmission scheduling in a fading environment, cognitive radio networks for spectrum overlay, and resource-constrained jamming and anti-jamming.
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 ..."
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Cited by 105 (1 self)
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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.
On Myopic Sensing for Multi-Channel Opportunistic Access: Structure, Optimality, and Performance
- IN PROC. ICC
, 2008
"... We consider a multi-channel opportunistic communication system where the states of these channels evolve as independent and statistically identical Markov chains (the Gilbert-Elliot channel model). A user chooses one channel to sense and access in each slot and collects a reward determined by the s ..."
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Cited by 104 (37 self)
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We consider a multi-channel opportunistic communication system where the states of these channels evolve as independent and statistically identical Markov chains (the Gilbert-Elliot channel model). A user chooses one channel to sense and access in each slot and collects a reward determined by the state of the chosen channel. The problem is to design a sensing policy for channel selection to maximize the average reward, which can be formulated as a multi-arm restless bandit process. In this paper, we study the structure, optimality, and performance of the myopic sensing policy. We show that the myopic sensing policy has a simple robust structure that reduces channel selection to a round-robin procedure and obviates the need for knowing the channel transition probabilities. The optimality of this simple policy is established for the two-channel case and conjectured for the general case based on numerical results. The performance of the myopic sensing policy is analyzed, which, based on the optimality of myopic sensing, characterizes the maximum throughput of a multi-channel opportunistic communication system and its scaling behavior with respect to the number of channels. These results apply to cognitive radio networks, opportunistic transmission in fading environments, downlink scheduling in centralized networks, and resource-constrained jamming and anti-jamming.
Opportunistic Spectrum Access via Periodic Channel Sensing
- IEEE Trans. Sig. Proc
, 2008
"... Abstract—The problem of opportunistic access of parallel channels occupied by primary users is considered. Under a continuoustime Markov chain modeling of the channel occupancy by the primary users, a slotted transmission protocol for secondary users using a periodic sensing strategy with optimal dy ..."
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Cited by 81 (14 self)
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Abstract—The problem of opportunistic access of parallel channels occupied by primary users is considered. Under a continuoustime Markov chain modeling of the channel occupancy by the primary users, a slotted transmission protocol for secondary users using a periodic sensing strategy with optimal dynamic access is proposed. To maximize channel utilization while limiting interference to primary users, a framework of constrained Markov decision processes is presented, and the optimal access policy is derived via a linear program. Simulations are used for performance evaluation. It is demonstrated that periodic sensing yields negligible loss of throughput when the constraint on interference is tight. Index Terms—Constrained Markov decision processes, dynamic spectrum access, resource allocation. I.
Distributed Spectrum Sensing for Cognitive Radio Networks by Exploiting Sparsity
"... Abstract—A cooperative approach to the sensing task of wireless cognitive radio (CR) networks is introduced based on a basis expansion model of the power spectral density (PSD) map in space and frequency. Joint estimation of the model parameters enables identification of the (un)used frequency bands ..."
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Cited by 80 (7 self)
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Abstract—A cooperative approach to the sensing task of wireless cognitive radio (CR) networks is introduced based on a basis expansion model of the power spectral density (PSD) map in space and frequency. Joint estimation of the model parameters enables identification of the (un)used frequency bands at arbitrary locations, and thus facilitates spatial frequency reuse. The novel scheme capitalizes on two forms of sparsity: the first one introduced by the narrow-band nature of transmit-PSDs relative to the broad swaths of usable spectrum; and the second one emerging from sparsely located active radios in the operational space. An estimator of the model coefficients is developed based on the Lasso algorithm to exploit these forms of sparsity and reveal the unknown positions of transmitting CRs. The resultant scheme can be implemented via distributed online iterations, which solve quadratic programs locally (one per radio), and are adaptive to changes in the system. Simulations corroborate that exploiting sparsity in CR sensing reduces spatial and frequency spectrum leakage by 15 dB relative to least-squares (LS) alternatives. Index Terms—Cognitive radios, compressive sampling, cooperative systems, distributed estimation, parallel network processing, sensing, sparse models, spectral analysis. I.
Distributed Learning in Multi-Armed Bandit with Multiple Players
- IEEE TRANSACTIONS ON SIGNAL PROCESSING
, 2010
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Cognitive Medium Access: Exploration, Exploitation and Competition
, 2007
"... This paper establishes the equivalence between cognitive medium access and the competitive multi-armed bandit problem. First, the scenario in which a single cognitive user wishes to opportunistically exploit the availability of empty frequency bands in the spectrum with multiple bands is considered ..."
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Cited by 61 (5 self)
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This paper establishes the equivalence between cognitive medium access and the competitive multi-armed bandit problem. First, the scenario in which a single cognitive user wishes to opportunistically exploit the availability of empty frequency bands in the spectrum with multiple bands is considered. In this scenario, the availability probability of each channel is unknown to the cognitive user a priori. Hence efficient medium access strategies must strike a balance between exploring the availability of other free channels and exploiting the opportunities identified thus far. By adopting a Bayesian approach for this classical bandit problem, the optimal medium access strategy is derived and its underlying recursive structure is illustrated via examples. To avoid the prohibitive computational complexity of the optimal strategy, a low complexity asymptotically optimal strategy is developed. The proposed strategy does not require any prior statistical knowledge about the traffic pattern on the different channels. Next, the multi-cognitive user scenario is considered and low complexity medium access protocols, which strike the optimal balance between exploration and exploitation in such competitive environments, are developed. Finally, this formalism is extended to the case in which each cognitive user is capable of sensing and using multiple channels simultaneously.
Indexability of Restless Bandit Problems and Optimality of Whittle's Index for Dynamic . . .
"... We consider a class of restless multi-armed bandit problems (RMBP) that arises in dynamic multichannel access, user/server scheduling, and optimal activation in multi-agent systems. For this class of RMBP, we establish the indexability and obtain Whittle’s index in closed-form for both discounted an ..."
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Cited by 59 (13 self)
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We consider a class of restless multi-armed bandit problems (RMBP) that arises in dynamic multichannel access, user/server scheduling, and optimal activation in multi-agent systems. For this class of RMBP, we establish the indexability and obtain Whittle’s index in closed-form for both discounted and average reward criteria. These results lead to a direct implementation of Whittle’s index policy with remarkably low complexity. When arms are stochastically identical, we show that Whittle’s index policy is optimal under certain conditions. Furthermore, it has a semi-universal structure that obviates the need to know the Markov transition probabilities. The optimality and the semi-universal structure result from the equivalency between Whittle’s index policy and the myopic policy established in this work. For non-identical arms, we develop efficient algorithms for computing a performance upper bound given by Lagrangian relaxation. The tightness of the upper bound and the near-optimal performance of Whittle’s index policy are illustrated with simulation examples.
