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NeXt generation/dynamic spectrum access/cognitive Radio Wireless Networks: A Survey
- COMPUTER NETWORKS JOURNAL (ELSEVIER
, 2006
"... Today's wireless networks are characterized by a fixed spectrum assignment policy. However, a large portion of the assigned spectrum is used sporadically and geographical variations in the utilization of assigned spectrum ranges from 15% to 85% with a high variance in time. The limited availabl ..."
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Cited by 746 (15 self)
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Today's wireless networks are characterized by a fixed spectrum assignment policy. However, a large portion of the assigned spectrum is used sporadically and geographical variations in the utilization of assigned spectrum ranges from 15% to 85% with a high variance in time. The limited available spectrum and the ine#ciency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically. This new networking paradigm is referred to as NeXt Generation (xG) Networks as well as Dynamic Spectrum Access (DSA) and cognitive radio networks. The term xG networks is used throughout the paper. The novel functionalities and current research challenges of the xG networks are explained in detail. More specifically, a brief overview of the cognitive radio technology is provided and the xG network architecture is introduced. Moreover, the xG network functions such as spectrum management, spectrum mobility and spectrum sharing are explained in detail. The influence of these functions on the performance of the upper layer protocols such as routing and transport are investigated and open research issues in these areas are also outlined. Finally, the cross-layer design challenges in xG networks are discussed.
A survey of dynamic spectrum access
- IEEE Signal Processing Magazine
, 2007
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Cooperative sensing among cognitive radios
- In Proc. of the IEEE International Conference on Communications (ICC
, 2006
"... Abstract — Cognitive Radios have been advanced as a technology for the opportunistic use of under-utilized spectrum since they are able to sense the spectrum and use frequency bands if no Primary user is detected. However, the required sensitivity is very demanding since any individual Radio might f ..."
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Cited by 289 (15 self)
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Abstract — Cognitive Radios have been advanced as a technology for the opportunistic use of under-utilized spectrum since they are able to sense the spectrum and use frequency bands if no Primary user is detected. However, the required sensitivity is very demanding since any individual Radio might face a deep fade. We propose light-weight cooperation in sensing based on hard decisions to mitigate the sensitivity requirements on individual radios. We show that the “link budget ” that system designers have to reserve for fading is a significant function of the required probability of detection. Even a few cooperating users (∼10-20) facing independent fades are enough to achieve practical threshold levels by drastically reducing the individual detection requirements. Hard decisions perform almost as well as soft decisions in achieving these gains. Shadowing correlation limits these gains and hence a few independent users perform better than many correlated users. Unfortunately, cooperative gain is very sensitive to adversarial/failing Cognitive Radios. Radios that fail in a known way (always report the presence/absence of a Primary user) can be compensated for by censoring them. On the other hand, radios that fail in unknown ways or may be malicious, introduce a bound on achievable sensitivity reductions. As a rule of thumb, if we believe that 1
Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals
, 2009
"... Wideband analog signals push contemporary analog-to-digital conversion systems to their performance limits. In many applications, however, sampling at the Nyquist rate is inefficient because the signals of interest contain only a small number of significant frequencies relative to the bandlimit, alt ..."
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Cited by 158 (18 self)
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Wideband analog signals push contemporary analog-to-digital conversion systems to their performance limits. In many applications, however, sampling at the Nyquist rate is inefficient because the signals of interest contain only a small number of significant frequencies relative to the bandlimit, although the locations of the frequencies may not be known a priori. For this type of sparse signal, other sampling strategies are possible. This paper describes a new type of data acquisition system, called a random demodulator, that is constructed from robust, readily available components. Let K denote the total number of frequencies in the signal, and let W denote its bandlimit in Hz. Simulations suggest that the random demodulator requires just O(K log(W/K)) samples per second to stably reconstruct the signal. This sampling rate is exponentially lower than the Nyquist rate of W Hz. In contrast with Nyquist sampling, one must use nonlinear methods, such as convex programming, to recover the signal from the samples taken by the random demodulator. This paper provides a detailed theoretical analysis of the system’s performance that supports the empirical observations.
Efficient discovery of spectrum opportunities with mac-layer sensing in cognitive radio networks
- IEEE Transactions on Mobile Computing
, 2008
"... Abstract—Sensing/monitoring of spectrum-availability has been identified as a key requirement for dynamic spectrum allocation in cognitive radio networks (CRNs). An important issue associated with MAC-layer sensing in CRNs is how often to sense the availability of licensed channels and in which orde ..."
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Cited by 153 (17 self)
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Abstract—Sensing/monitoring of spectrum-availability has been identified as a key requirement for dynamic spectrum allocation in cognitive radio networks (CRNs). An important issue associated with MAC-layer sensing in CRNs is how often to sense the availability of licensed channels and in which order to sense those channels. To resolve this issue, we address 1) how to maximize the discovery of spectrum opportunities by sensing-period adaptation and 2) how to minimize the delay in finding an available channel. Specifically, we develop a sensing-period optimization mechanism and an optimal channel-sequencing algorithm, as well as an environment-adaptive channel-usage pattern estimation method. Our simulation results demonstrate the efficacy of the proposed schemes and its significant performance improvement over nonoptimal schemes. The sensing-period optimization discovers more than 98 percent of the analytical maximum of discoverable spectrum-opportunities, regardless of the number of channels sensed. For the scenarios tested, the proposed scheme is shown to discover up to 22 percent more opportunities than nonoptimal schemes, which may become even greater with a proper choice of initial sensing periods. The idle-channel discovery delay with the optimal channel-sequencing technique ranges from 0.08 to 0.35 seconds under the tested scenarios, which is much faster than nonoptimal schemes. Moreover, our estimation method is shown to track time-varying channel-parameters accurately. Index Terms—Cognitive radios, spectrum agility, spectrum opportunity, spectrum sensing, channel-usage patterns. Ç 1
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.
Optimal linear cooperation for spectrum sensing in cognitive radio networks
- IEEE J. SEL. TOPICS SIGNAL PROCESS
, 2008
"... Cognitive radio technology has been proposed to improve spectrum efficiency by having the cognitive radios act as secondary users to opportunistically access under-utilized frequency bands. Spectrum sensing, as a key enabling functionality in cognitive radio networks, needs to reliably detect signal ..."
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Cited by 122 (8 self)
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Cognitive radio technology has been proposed to improve spectrum efficiency by having the cognitive radios act as secondary users to opportunistically access under-utilized frequency bands. Spectrum sensing, as a key enabling functionality in cognitive radio networks, needs to reliably detect signals from licensed primary radios to avoid harmful interference. However, due to the effects of channel fading/shadowing, individual cog-nitive radios may not be able to reliably detect the existence of a primary radio. In this paper, we propose an optimal linear cooperation framework for spectrum sensing in order to accu-rately detect the weak primary signal. Within this framework, spectrum sensing is based on the linear combination of local statistics from individual cognitive radios. Our objective is to minimize the interference to the primary radio while meeting the requirement of opportunistic spectrum utilization. We formulate the sensing problem as a nonlinear optimization problem. By exploiting the inherent structures in the problem formulation, we develop efficient algorithms to solve for the optimal solutions. To further reduce the computational complexity and obtain solutions for more general cases, we finally propose a heuristic approach, where we instead optimize a modified deflection coefficient that characterizes the probability distribution function of the global test statistics at the fusion center. Simulation results illustrate significant cooperative gain achieved by the proposed strategies. The insights obtained in this paper are useful for the design of optimal spectrum sensing in cognitive radio networks.
A survey of dynamic spectrum access: signal processing, networking, and regulatory policy
- in IEEE Signal Processing Magazine
, 2007
"... In this paper, we provide a survey of dynamic spectrum access techniques. Various approaches envisioned for dynamic spectrum access are broadly categorized under three models: dynamic exclusive use model, open sharing model, and hierarchical access model. Based on this taxonomy, we provide an overvi ..."
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Cited by 121 (6 self)
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In this paper, we provide a survey of dynamic spectrum access techniques. Various approaches envisioned for dynamic spectrum access are broadly categorized under three models: dynamic exclusive use model, open sharing model, and hierarchical access model. Based on this taxonomy, we provide an overview of the technical challenges and recent advances under each model. Index Terms: Dynamic spectrum access, spectrum property rights, spectrum commons, spectrum underlay, spectrum overlay, opportunistic spectrum access. 1.
Cooperative spectrum sensing in cognition radio networks: A survey
- PHYSICAL COMMUNICATION
, 2010
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Optimal Spectrum Sensing Framework for Cognitive Radio Networks
- IEEE TRANS. ON WIRELESS COMM
, 2008
"... Spectrum sensing is the key enabling technology for cognitive radio networks. The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive radio users without interfering with the operations of the licensed network. Hence, recent research has been focused on ..."
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Cited by 117 (10 self)
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Spectrum sensing is the key enabling technology for cognitive radio networks. The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive radio users without interfering with the operations of the licensed network. Hence, recent research has been focused on the interference avoidance problem. Moreover, current radio frequency (RF) front-ends cannot perform sensing and transmission at the same time, which inevitably decreases their transmission opportunities, leading to the so-called sensing efficiency problem. In this paper, in order to solve both the interference avoidance and the spectrum efficiency problem, an optimal spectrum sensing framework is developed. More specifically, first a theoretical framework is developed to optimize the sensing parameters in such a way as to maximize the sensing efficiency subject to interference avoidance constraints. Second, in order to exploit multiple spectrum bands, spectrum selection and scheduling methods are proposed where the best spectrum bands for sensing are selected to maximize the sensing capacity. Finally, an adaptive and cooperative spectrum sensing method is proposed where the sensing parameters are optimized adaptively to the number of cooperating users. Simulation results show that the proposed sensing framework can achieve maximum sensing efficiency and opportunities in multi-user/multi-spectrum environments, satisfying interference constraints.
