Overview of spectrum sensing for cognitive radio
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paper_title: Software radios-survey, critical evaluation and future directions

paper_content:

Relates the performance of enabling hardware technologies to software radio requirements, portending a decade of shift from hardware radios toward software intensive approaches. Such approaches require efficient use of computational resources through topological consistency of radio functions and host architectures. This leads to a layered topology oriented design approach encapsulated in a canonical open architecture software radio model. This model underscores challenges in simulation and computer-aided design (CAD) tools for radio engineering. It aso provides a unified mathematical framework for quantitative analysis of algorithm structures, host architectures, and system performance for radio engineering CAD environments of the 1990s.<<ETX>>
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paper_title: Power scaling for cognitive radio

paper_content:

In this paper we explore the idea of using cognitive radios to reuse locally unused spectrum for their own transmissions. We impose the constraint that they cannot general e unacceptable levels of interference to licensed systems on the same frequency. Using received SNR as a proxy for distance, we prove that a cognitive radio can vary its transmit power while maintaining a guarantee of service to primary users. We consider the aggregate interference caused by multiple cognitive radios and show that aggregation causes a change in the effective decay rate of the interference. We examine the effects of heterogeneous propagation path loss functions and justify the feasibility of multiple secondary users with dynamic transmit powers. Finally, we prove the fundamental constraint on a cognitive radio's transmit power is the minimum SNR it can detect and explore the effect of this power cap.
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paper_title: Cognitive radio: brain-empowered wireless communications

paper_content:

Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a software-defined radio, is defined as an intelligent wireless communication system that is aware of its environment and uses the methodology of understanding-by-building to learn from the environment and adapt to statistical variations in the input stimuli, with two primary objectives in mind: /spl middot/ highly reliable communication whenever and wherever needed; /spl middot/ efficient utilization of the radio spectrum. Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks. 1) Radio-scene analysis. 2) Channel-state estimation and predictive modeling. 3) Transmit-power control and dynamic spectrum management. This work also discusses the emergent behavior of cognitive radio.
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paper_title: Cognitive radio in a frequency-planned environment: some basic limits

paper_content:

The objective of this work is to assess some fundamental limits for opportunistic spectrum reuse via cognitive radio in a frequency-planned environment. We present a first order analysis of the signal-to-noise-and-interference situation in a wireless cellular network, and analyze the impact of cognitive users starting to transmit. Two main conclusions emerge from our study. First, obtaining any substantial benefits from opportunistic spatial spectrum reuse in a frequency-planned network without causing substantial interference is going to be very challenging. Second, the cognitive users need to be more sensitive, by orders of magnitude, than the receivers in the primary system, especially if there is significant shadow fading. This latter problem can be alleviated by having cognitive users cooperate, but only if they are separated far apart so that they experience independent shadowing.
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paper_title: Energy detection of unknown deterministic signals

paper_content:

By using Shannon's sampling formula, the problem of the detection of a deterministic signal in white Gaussian noise, by means of an energy-measuring device, reduces to the consideration of the sum of the squares of statistically independent Gaussian variates. When the signal is absent, the decision statistic has a central chi-square distribution with the number of degrees of freedom equal to twice the time-bandwidth product of the input. When the signal is present, the decision statistic has a noncentral chi-square distribution with the same number of degrees of freedom and a noncentrality parameter λ equal to the ratio of signal energy to two-sided noise spectral density. Since the noncentral chi-square distribution has not been tabulated extensively enough for our purpose, an approximate form was used. This form replaces the noncentral chi-square with a modified chi-square whose degrees of freedom and threshold are determined by the noncentrality parameter and the previous degrees of freedom. Sets of receiver operating characteristic (ROC) curves are drawn for several time-bandwidth products, as well as an extended nomogram of the chi-square cumulative probability which can be used for rapid calculation of false alarm and detection probabilities. Related work in energy detection by J. I. Marcum and E. L Kaplan is discussed.
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paper_title: Cognitive radio in a frequency-planned environment: some basic limits

paper_content:

The objective of this work is to assess some fundamental limits for opportunistic spectrum reuse via cognitive radio in a frequency-planned environment. We present a first order analysis of the signal-to-noise-and-interference situation in a wireless cellular network, and analyze the impact of cognitive users starting to transmit. Two main conclusions emerge from our study. First, obtaining any substantial benefits from opportunistic spatial spectrum reuse in a frequency-planned network without causing substantial interference is going to be very challenging. Second, the cognitive users need to be more sensitive, by orders of magnitude, than the receivers in the primary system, especially if there is significant shadow fading. This latter problem can be alleviated by having cognitive users cooperate, but only if they are separated far apart so that they experience independent shadowing.
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paper_title: SNR Walls for Signal Detection

paper_content:

This paper considers the detection of the presence/absence of signals in uncertain low SNR environments. Small modeling uncertainties are unavoidable in any practical system and so robustness to them is a fundamental performance metric. The impact of these modeling uncertainties can be quantified by the position of the "SNR wall" below which a detector will fail to be robust, no matter how long it can observe the channel. We propose simple mathematical models for the uncertainty in the noise and fading processes. These are used to show what aspects of the model lead to SNR walls for differing levels of knowledge of the signal to be detected. These results have implications for wireless spectrum regulators. The context is opportunistically sharing spectrum with primary users that must be detected in order to avoid causing harmful interference on a channel. Ideally, a secondary system would be able to detect primaries robustly without having to know much about their signaling strategies. We argue that the tension between primary and secondary users is captured by the technical question of computing the optimal tradeoff between the primary user's capacity and the secondary user's sensing robustness as quantified by the SNR wall. This is an open problem, but we compute this tradeoff for some simple detectors.
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paper_title: Fundamental limits on detection in low SNR under noise uncertainty

paper_content:

In this paper we consider the problem of detecting whether a frequency band is being used by a known primary user. We derive fundamental bounds on detection performance in low SNR in the presence of noise uncertainty - the noise is assumed to be white, but we know its distribution only to within a particular set. For clarity of analysis, we focus on primary transmissions that are BPSK-modulated random data without any pilot tones or training sequences. The results should all generalize to more general primary transmissions as long as no deterministic component is present. Specifically, we show that for every 'moment detector' there exists an SNR below which detection becomes impossible in the presence of noise uncertainty. In the neighborhood of that SNR wall, we show how the sample complexity of detection approaches infinity. We also show that if our radio has a finite dynamic range (upper and lower limits to the voltages we can quantize), then at low enough SNR, any detector can be rendered useless even under moderate noise uncertainty.
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paper_title: Cyclostationarity: Half a century of research

paper_content:

In this paper, a concise survey of the literature on cyclostationarity is presented and includes an extensive bibliography. The literature in all languages, in which a substantial amount of research has been published, is included. Seminal contributions are identified as such. Citations are classified into 22 categories and listed in chronological order. Both stochastic and nonstochastic approaches for signal analysis are treated. In the former, which is the classical one, signals are modelled as realizations of stochastic processes. In the latter, signals are modelled as single functions of time and statistical functions are defined through infinite-time averages instead of ensemble averages. Applications of cyclostationarity in communications, signal processing, and many other research areas are considered.
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paper_title: Signal interception: performance advantages of cyclic-feature detectors

paper_content:

The problem of detecting the presence of spread-spectrum phase-shift-keyed signals in variable noise and interference backgrounds is considered, and the performances of four detectors are evaluated and compared. The detectors include the optimum radiometer, the optimum modified radiometer that jointly estimates the noise level and detects the signal, and the maximum-SNR spectral-line regenerator for spectral-line frequencies equal to the chip rate and the doubled carrier frequency. It is concluded that the spectral-line regenerators can outperform both types of radiometers by a wide margin. The performance advantages are quantified in terms of receiver operating characteristics for several noise and interference environments and receiver collection times. >
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paper_title: Spectral correlation based signal detection method for spectrum sensing in IEEE 802.22 WRAN systems

paper_content:

In this paper, signal detection methods for spectrum sensing in IEEE 802.22 wireless RAN systems are discussed. As most of the manmade signals can be treated as a cyclostationary random process, the spectral correlation function is effective for the detection of these signals. In WRAN systems, due to the specific detection environment, the computational complexity of the spectral correlation based method is significantly reduced. Peak detection in the high SNR environment together with contour figure based unique patterns search method in the low SNR environment are proposed for the primary user signal detection.
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paper_title: Exploitation of spectral redundancy in cyclostationary signals

paper_content:

It is shown that the cyclostationarity attribute, as it is reflected in the periodicities of (second-order) moments of the signal, can be interpreted in terms of the property that allows generation of spectral lines from the signal by putting it through a (quadratic) nonlinear transformation. The fundamental link between the spectral-line generation property and the statistical property called spectral correlation, which corresponds to the correlation that exists between the random fluctuations of components of the signal residing in distinct spectral bands, is explained. The effects on the spectral-correlation characteristics of some basic signal processing operations, such as filtering, product modulation, and time sampling, are examined. It is shown how to use these results to derive the spectral-correlation characteristics for various types of man-made signals. Some ways of exploiting the inherent spectral redundancy associated with spectral correlation to perform various signal processing tasks involving detection and estimation of highly corrupted man-made signals are described. >
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paper_title: A cyclostationary feature detector

paper_content:

Cyclostationary models for communications signals have been shown in recent years to offer many advantages over stationary models. Stationary models are adequate in many situations, but they cause important features of the signal to be overlooked. One such important feature is the correlation between spectral components that many signals exhibit. Cyclostationary models allow this spectral correlation to be exploited. This paper presents a signal detector that exploits spectral correlation to determine the presence or absence of a cyclostationary signal in noise. The detector's probability of false alarm is analytically derived. Computer simulations verify that the analytical derivation is correct. The detector's receiver operating characteristic curves are determined from the simulation data and the analytical expression for the probability of false alarm. >
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paper_title: Collaborative Cyclostationary Spectrum Sensing for Cognitive Radio Systems

paper_content:

This paper proposes an energy efficient collaborative cyclostationary spectrum sensing approach for cognitive radio systems. An existing statistical hypothesis test for the presence of cyclostationarity is extended to multiple cyclic frequencies and its asymptotic distributions are established. Collaborative test statistics are proposed for the fusion of local test statistics of the secondary users, and a censoring technique in which only informative test statistics are transmitted to the fusion center (FC) during the collaborative detection is further proposed for improving energy efficiency in mobile applications. Moreover, a technique for numerical approximation of the asymptotic distribution of the censored FC test statistic is proposed. The proposed tests are nonparametric in the sense that no assumptions on data or noise distributions are required. In addition, the tests allow dichotomizing between the desired signal and interference. Simulation experiments are provided that show the benefits of the proposed cyclostationary approach compared to energy detection, the importance of collaboration among spatially displaced secondary users for overcoming shadowing and fading effects, as well as the reliable performance of the proposed algorithms even in very low signal-to-noise ratio (SNR) regimes and under strict communication rate constraints for collaboration overhead.
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paper_title: Statistical tests for presence of cyclostationarity

paper_content:

The presence of kth-order cyclostationarity is defined in terms of nonvanishing cyclic-cumulants or polyspectra. Relying upon the asymptotic normality and consistency of kth-order cyclic statistics, asymptotically optimal /spl chi//sup 2/ tests are developed to detect the presence of cycles in the kth-order cyclic cumulants or polyspectra, without assuming any specific distribution on the data. Constant false alarm rate tests are derived in both time- and frequency-domain and yield consistent estimates of possible cycles present in the kth-order cyclic statistics. Explicit algorithms for k/spl les/4 are discussed. Existing approaches are rather empirical and deal only with k/spl les/2 case. Simulation results are presented to confirm the performance of the given tests. >
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paper_title: Cyclostationarity based air interface recognition for software radio systems

paper_content:

Reconfigurable software radio equipment is seen as the next evolutionary step in mobile communications. One of the most important properties of a software radio terminal is that it is capable of using a wide range of air interface standards, providing a seamless interoperability between different air interface standards and an enhanced roaming capability. This multimode operation has to be supported by a number of key functionalities, one of which is the air interface recognition. A software radio terminal has to be able to detect, recognize and monitor the air interfaces available in the frequency environment. In our work, we propose exploiting the distinct cyclostationary properties of signals from different air interfaces as features for air interface recognition.
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paper_title: Spectrum Sensing Using Cyclostationary Properties and Application to IEEE 802.22 WRAN

paper_content:

Spectrum sensing in a very low SNR environment (less than -20 dB) is considered in this paper. We make use of the noise rejection property of the cyclostationary spectrum. The sensing algorithms are based on measurement of the cyclic spectrum of the received signals. The statistics of the cyclic spectrum of the stationary white Gaussian process are fully analyzed for three measurement methods of the cyclic spectrum. The application to IEEE 802.22 WRAN is presented and the probability of false alarm is analytically derived. The operating characteristic curves for the sensing algorithms are determined from computer simulations using ATSC A/74 DTV signal captures as a test database.
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paper_title: Signal interception: a unifying theoretical framework for feature detection

paper_content:

The unifying framework of the spectral-correlation theory of cyclostationary signals is used to present a broad treatment of weak, random signal detection for interception purposes. The relationships among a variety of previously proposed ad hoc detectors, optimum detectors, and newly proposed detectors are established. The spectral-correlation-plane approach to the interception problem is put forth as especially promising for detection, classification, and estimation in particularly difficult environments involving unknown and changing noise levels and interference activity. A fundamental drawback of the popular radiometric methods in such environments is explained. >
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paper_title: Autocorrelation-Based Decentralized Sequential Detection of OFDM Signals in Cognitive Radios

paper_content:

This paper introduces a simple and computationally efficient spectrum sensing scheme for Orthogonal Frequency Division Multiplexing (OFDM) based primary user signal using its autocorrelation coefficient. Further, it is shown that the log likelihood ratio test (LLRT) statistic is the maximum likelihood estimate of the autocorrelation coefficient in the low signal-to-noise ratio (SNR) regime. Performance of the local detector is studied for the additive white Gaussian noise (AWGN) and multipath channels using theoretical analysis. Obtained results are verified in simulation. The performance of the local detector in the face of shadowing is studied by simulations. A sequential detection (SD) scheme where many secondary users cooperate to detect the same primary user is proposed. User cooperation provides diversity gains as well as facilitates using simpler local detectors. The sequential detection reduces the delay and the amount of data needed in identification of the underutilized spectrum. The decision statistics from individual detectors are combined at the fusion center (FC). The statistical properties of the decision statistics are established. The performance of the scheme is studied through theory and validated by simulations. A comparison of the SD scheme with the Neyman-Pearson fixed sample size (FSS) test for the same false alarm and missed detection probabilities is also carried out.
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paper_title: Significance Test for Sphericity of a Normal $n$-Variate Distribution

paper_content:

An elevator control system that utilizes a digital signal representative of the car position to provide the necessary information inputs to the selective logic system and motor control so that a smooth acceleration to maximum velocity and deceleration to stop at a selected floor. A drum selector is utilized to produce the digital number corresponding to elevator position. The motion input to this drum selector is linked to actual elevator motion. The system includes electronic provision for simulating the advance of the car position an amount dependent on it's velocity and locks out all floors behind that advanced position in order to allow adequate time for deceleration. The velocity command is compared to actual velocity and the power control section called on to make up any difference. Differences persisting for a period of time produce increasing commands in response, while damping means prevent overshoot.
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paper_title: GLRT-Based Spectrum Sensing for Cognitive Radio

paper_content:

In this paper, we propose several spectrum sensing methods designed using the generalized likelihood ratio test (GLRT) paradigm, for application in a cognitive radio network. The proposed techniques utilize the eigenvalues of the sample covariance matrix of the received signal vector, taking advantage of the fact that in practice, the primary signal in a cognitive radio environment will either occupy a subspace of dimension strictly smaller than the dimension of the observation space, or have a spectrum that is non-white. We show that by making various assumptions on the availability of side information such as noise variance and signal space dimension, several feasible algorithms result which all outperform the standard energy detector.
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paper_title: Exploitation of spectral redundancy in cyclostationary signals

paper_content:

It is shown that the cyclostationarity attribute, as it is reflected in the periodicities of (second-order) moments of the signal, can be interpreted in terms of the property that allows generation of spectral lines from the signal by putting it through a (quadratic) nonlinear transformation. The fundamental link between the spectral-line generation property and the statistical property called spectral correlation, which corresponds to the correlation that exists between the random fluctuations of components of the signal residing in distinct spectral bands, is explained. The effects on the spectral-correlation characteristics of some basic signal processing operations, such as filtering, product modulation, and time sampling, are examined. It is shown how to use these results to derive the spectral-correlation characteristics for various types of man-made signals. Some ways of exploiting the inherent spectral redundancy associated with spectral correlation to perform various signal processing tasks involving detection and estimation of highly corrupted man-made signals are described. >
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paper_title: Multiple antenna spectrum sensing in cognitive radios

paper_content:

In this paper, we consider the problem of spectrum sensing by using multiple antenna in cognitive radios when the noise and the primary user signal are assumed as independent complex zero-mean Gaussian random signals. The optimal multiple antenna spectrum sensing detector needs to know the channel gains, noise variance, and primary user signal variance. In practice some or all of these parameters may be unknown, so we derive the generalized likelihood ratio (GLR) detectors under these circumstances. The proposed GLR detector, in which all the parameters are unknown, is a blind and invariant detector with a low computational complexity. We also analytically compute the missed detection and false alarm probabilities for the proposed GLR detectors. The simulation results provide the available traded-off in using multiple antenna techniques for spectrum sensing and illustrates the robustness of the proposed GLR detectors compared to the traditional energy detector when there is some uncertainty in the given noise variance.
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paper_title: SNR Walls for Signal Detection

paper_content:

This paper considers the detection of the presence/absence of signals in uncertain low SNR environments. Small modeling uncertainties are unavoidable in any practical system and so robustness to them is a fundamental performance metric. The impact of these modeling uncertainties can be quantified by the position of the "SNR wall" below which a detector will fail to be robust, no matter how long it can observe the channel. We propose simple mathematical models for the uncertainty in the noise and fading processes. These are used to show what aspects of the model lead to SNR walls for differing levels of knowledge of the signal to be detected. These results have implications for wireless spectrum regulators. The context is opportunistically sharing spectrum with primary users that must be detected in order to avoid causing harmful interference on a channel. Ideally, a secondary system would be able to detect primaries robustly without having to know much about their signaling strategies. We argue that the tension between primary and secondary users is captured by the technical question of computing the optimal tradeoff between the primary user's capacity and the secondary user's sensing robustness as quantified by the SNR wall. This is an open problem, but we compute this tradeoff for some simple detectors.
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paper_title: Performance of Statistical Tests for Single-Source Detection Using Random Matrix Theory

paper_content:

This paper introduces a unified framework for the detection of a source with a sensor array in the context where the noise variance and the channel between the source and the sensors are unknown at the receiver. The Generalized Maximum Likelihood Test is studied and yields the analysis of the ratio between the maximum eigenvalue of the sampled covariance matrix and its normalized trace. Using recent results of random matrix theory, a practical way to evaluate the threshold and the $p$-value of the test is provided in the asymptotic regime where the number $K$ of sensors and the number $N$ of observations per sensor are large but have the same order of magnitude. The theoretical performance of the test is then analyzed in terms of Receiver Operating Characteristic (ROC) curve. It is in particular proved that both Type I and Type II error probabilities converge to zero exponentially as the dimensions increase at the same rate, and closed-form expressions are provided for the error exponents. These theoretical results rely on a precise description of the large deviations of the largest eigenvalue of spiked random matrix models, and establish that the presented test asymptotically outperforms the popular test based on the condition number of the sampled covariance matrix.
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paper_title: Non-Parametric Detection of the Number of Signals: Hypothesis Testing and Random Matrix Theory

paper_content:

Detection of the number of signals embedded in noise is a fundamental problem in signal and array processing. This paper focuses on the non-parametric setting where no knowledge of the array manifold is assumed. First, we present a detailed statistical analysis of this problem, including an analysis of the signal strength required for detection with high probability, and the form of the optimal detection test under certain conditions where such a test exists. Second, combining this analysis with recent results from random matrix theory, we present a new algorithm for detection of the number of sources via a sequence of hypothesis tests. We theoretically analyze the consistency and detection performance of the proposed algorithm, showing its superiority compared to the standard minimum description length (MDL)-based estimator. A series of simulations confirm our theoretical analysis.
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paper_title: Eigenvalue-based spectrum sensing algorithms for cognitive radio

paper_content:

Spectrum sensing is a fundamental component in a cognitive radio. In this paper, we propose new sensing methods based on the eigenvalues of the covariance matrix of signals received at the secondary users. In particular, two sensing algorithms are suggested, one is based on the ratio of the maximum eigenvalue to minimum eigenvalue; the other is based on the ratio of the average eigenvalue to minimum eigenvalue. Using some latest random matrix theories (RMT), we quantify the distributions of these ratios and derive the probabilities of false alarm and probabilities of detection for the proposed algorithms. We also find the thresholds of the methods for a given probability of false alarm. The proposed methods overcome the noise uncertainty problem, and can even perform better than the ideal energy detection when the signals to be detected are highly correlated. The methods can be used for various signal detection applications without requiring the knowledge of signal, channel and noise power. Simulations based on randomly generated signals, wireless microphone signals and captured ATSC DTV signals are presented to verify the effectiveness of the proposed methods.
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paper_title: Signal interception: performance advantages of cyclic-feature detectors

paper_content:

The problem of detecting the presence of spread-spectrum phase-shift-keyed signals in variable noise and interference backgrounds is considered, and the performances of four detectors are evaluated and compared. The detectors include the optimum radiometer, the optimum modified radiometer that jointly estimates the noise level and detects the signal, and the maximum-SNR spectral-line regenerator for spectral-line frequencies equal to the chip rate and the doubled carrier frequency. It is concluded that the spectral-line regenerators can outperform both types of radiometers by a wide margin. The performance advantages are quantified in terms of receiver operating characteristics for several noise and interference environments and receiver collection times. >
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paper_title: Cooperative Sensing among Cognitive Radios

paper_content:

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 individual detection requirements. Hard decisions perform almost as well as soft decisions in achieving these gains. Cooperative gains in a environment where shadowing is correlated, is limited by the cooperation footprint (area in which users cooperate). In essence, a few independent users are more robust 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 unmodeled ways or may be malicious, introduce a bound on achievable sensitivity reductions. As a rule of thumb, if we believe that 1/N users can fail in an unknown way, then the cooperation gains are limited to what is possible with N trusted users.
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paper_title: Soft Combination and Detection for Cooperative Spectrum Sensing in Cognitive Radio Networks

paper_content:

In this paper, we consider cooperative spectrum sensing based on energy detection in cognitive radio networks. Soft combination of the observed energy values from different cognitive radio users is investigated. Maximal ratio combination (MRC) is theoretically proved to be nearly optimal in low signal- to-noise ratio (SNR) region, an usual scenario in the context of cognitive radio. Both MRC and equal gain combination (EGC) exhibit significant performance improvement over conventional hard combination. Encouraged by the performance gain of soft combination, we propose a new softened hard combination scheme with two-bit overhead for each user and achieve a good tradeoff between detection performance and complexity. While traditionally energy detection suffers from an SNR wall caused by noise power uncertainty, it is shown in this paper that an SNR wall reduction can be achieved by employing cooperation among independent cognitive radio users.
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paper_title: Decentralized Detection With Censoring Sensors

paper_content:

In the censoring approach to decentralized detection, sensors transmit real-valued functions of their observations when "informative" and save energy by not transmitting otherwise. We address several practical issues in the design of censoring sensor networks including the joint dependence of sensor decision rules, randomization of decision strategies, and partially known distributions. In canonical decentralized detection problems involving quantization of sensor observations, joint optimization of the sensor quantizers is necessary. We show that under a send/no-send constraint on each sensor and when the fusion center has its own observations, the sensor decision rules can be determined independently. In terms of design, and particularly for adaptive systems, the independence of sensor decision rules implies that minimal communication is required. We address the uncertainty in the distribution of the observations typically encountered in practice by determining the optimal sensor decision rules and fusion rule for three formulations: a robust formulation, generalized likelihood ratio tests, and a locally optimum formulation. Examples are provided to illustrate the independence of sensor decision rules, and to evaluate the partially known formulations.
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paper_title: Censoring sensors: a low-communication-rate scheme for distributed detection

paper_content:

We consider a new scheme for distributed detection based on a "censoring" or "send/no-send" idea. The sensors are assumed to "censor" their observations so that each sensor sends to the fusion center only "informative" observations, and leaves those deemed "uninformative" untransmitted. The main result of this work is that with conditionally independent sensor data and under a communication rate constraint, in order to minimize the probability of error, transmission should occur if and only if the local likelihood ratio value observed by the sensor does not fall in a certain single interval. Similar results are derived from Neymarr-Pearson and distance-measure viewpoints. We also discuss simplifications for the most interesting case that the fusion center threshold is high and the communication constraint is severe. We compare censoring with the more common binary-transmission framework and observe its considerable decrease in communication needs. Finally, we explore the use of feedback to achieve optimal performance with very little communication.
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paper_title: Energy-efficient detection in sensor networks

paper_content:

There is significant interest in battery or solar-powered sensor networks to be used for detec- tion in a wide variety of applications from surveillance and security to biological applications. Severe energy and bandwidth constraints at each sensor node demand system-level approaches to design that consider de- tection performance jointly with system-resource con- straints. OUT approach is to formulate detection prob- lems with constraints on the ezpected cost arising from transmission (sensor nodes to a fusion center) and measurement (at each sensor node) to address some of the system-level costs in a sensor network. Un- der a send/no-send scenario for transmission, we find that randomization over the choice of measvrement and choice of send rate achieves the best performance (in a Bayesian, Neyman-Pearson, and Ali-Silvey sense) for a given resource constraint. To facilitate design, we de- scribe some special cases where the joint optimization over the sensor nodes is eliminated.
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paper_title: Energy-efficient spectrum sensing for cognitive sensor networks

paper_content:

We consider a combined sleeping and censoring scheme for energy-efficient spectrum sensing in cognitive sensor networks. We analyze the detection performance of this scheme by theoretically deriving the global probabilities of detection and false-alarm. Our goal is to minimize the energy consumption incurred in distributed sensing, given constraints on the global probabilities of detection and false-alarm, by optimally designing the sleeping rate and the censoring thresholds. Using specific transceiver models for sensors based on IEEE 802.15.4/ZigBee, we show the energy savings achieved under an optimum choice of the design parameters.
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paper_title: Detection with distributed sensors

paper_content:

The extension of classical detection theory, based on the theory of statistical hypothesis testing, to the case of distributed sensors is discussed. The development is based on the formulation of a decentralized or team hypothesis testing problem. Theoretical results concerning the form of the optimal decision rule, examples, application to data fusion, and open problems are presented.
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paper_title: Energy-efficient distributed spectrum sensing with convex optimization

paper_content:

We consider the problem of distributed spectrum sensing in cognitive radio networks with a central fusion center, from an energy efficiency viewpoint. In our scheme, each cognitive radio adopts a combination of sleeping and censoring to obtain a sensing result based on energy detection, while the fusion center combines all the sensing results using an OR decision rule. Our goal is to minimize the network energy consumption, given constraints on the global probabilities of detection and false-alarm. We show that the underlying optimization problem can be solved as a convex optimization problem. We then show the energy efficiency of our scheme via simulations using a ZigBee transceiver model.
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paper_title: Cooperative Spectrum Sensing for Cognitive Radios under Bandwidth Constraints

paper_content:

In cognitive radio systems, cooperative spectrum sensing is conducted among the cognitive users so as to detect the primary user accurately. However, when the number of cognitive users tends to be very large, the bandwidth for reporting their sensing results to the common receiver will be very huge. In this paper, the authors employ a censoring method with quantization to decrease the average number of sensing bits to the common receiver. By censoring the collected local observations, only the users with enough information will send their local one bit decisions (0 or 1) to the common receiver. The performance of spectrum sensing is investigated for both perfect and imperfect reporting channels. Numerical results show that the average number of sensing bits decreases greatly at the expense of a little sensing performance loss.
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paper_title: Cognitive radio: brain-empowered wireless communications

paper_content:

Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a software-defined radio, is defined as an intelligent wireless communication system that is aware of its environment and uses the methodology of understanding-by-building to learn from the environment and adapt to statistical variations in the input stimuli, with two primary objectives in mind: /spl middot/ highly reliable communication whenever and wherever needed; /spl middot/ efficient utilization of the radio spectrum. Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks. 1) Radio-scene analysis. 2) Channel-state estimation and predictive modeling. 3) Transmit-power control and dynamic spectrum management. This work also discusses the emergent behavior of cognitive radio.
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paper_title: Filter Bank Spectrum Sensing for Cognitive Radios

paper_content:

The primary task in any cognitive radio (CR) network is to dynamically explore the radio spectrum and reliably determine portion(s) of the frequency band that may be used for the communication link(s). Accordingly, each CR node in the network has to be equipped with a spectrum analyzer. In this paper, we propose filter banks as a tool for spectrum sensing in CR systems. Various choices of filter banks are suggested and their performance are evaluated theoretically and through numerical examples. Moreover, the proposed spectrum analyzer is contrasted with the Thomson's multitaper (MT) method - a method that in the recent literature has been recognized as the best choice for spectrum sensing in CR systems. A novel derivation of the MT method that facilitates our comparisons as well as reveals an important aspect of the MT method that has been less emphasized in the recent literature is also presented.
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paper_title: Cognitive Radio Sensing Information-Theoretic Criteria Based

paper_content:

In this paper1, we explore the Information-Theoretic Criteria, namely, Akaikes Information Criterion (AIC) and Minimum Description Length (MDL) as a tool to sense vacant sub-band over the spectrum bandwidth. The proposed technique is motivated by the fact that an idle sub-band (Normal process) presents a number of independent eigenvectors appreciably larger than for an occupied sub-band (Non-normal process). It turns out that, based on the number of the independent eigenvectors of a given covariance matrix of the observed signal, one can conclude on the nature of the sensed sub-band. Our-theoretical result as well as the empirical results are first applied on experimental measurement campaign conducted at the Eurecom PLATON Platform. We then apply our method to an IEEE 802.11b Wireless Fidelity (Wi-Fi) signal in order to analyze the robustness of the proposed approach in presence of increased levels of noise. We argue that the proposed sub-space based techniques give interesting results in terms of sensing the white space in the spectrum.
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paper_title: Spectrum Sensing for Cognitive Radio

paper_content:

Spectrum sensing is the very task upon which the entire operation of cognitive radio rests. For cognitive radio to fulfill the potential it offers to solve the spectrum underutilization problem and do so in a reliable and computationally feasible manner, we require a spectrum sensor that detects spectrum holes (i.e., underutilized subbands of the radio spectrum), provides high spectral-resolution capability, estimates the average power in each subband of the spectrum, and identifies the unknown directions of interfering signals. Cyclostationarity is another desirable property that could be used for signal detection and classification. The multitaper method (MTM) for nonparametric spectral estimation accomplishes these tasks accurately, effectively, robustly, and in a computationally feasible manner. The objectives of this paper are to present: 1) tutorial exposition of the MTM, which is expandable to perform space-time processing and time-frequency analysis; 2) cyclostationarity, viewed from the Loeve and Fourier perspectives; and 3) experimental results, using Advanced Television Systems Committee digital television and generic land mobile radio signals, followed by a discussion of the effects of Rayleigh fading.
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Title: Overview of Spectrum Sensing for Cognitive Radio

Section 1: INTRODUCTION
Description 1: Discuss the concept of spectrum sensing in cognitive radio, its importance, and the motivation behind it.

Section 2: MODEL
Description 2: Describe the preliminary model for signal detection, outlining the assumptions and hypotheses.

Section 3: ENERGY DETECTION
Description 3: Explain the energy detection technique, its performance, and limitations in cognitive radio.

Section 4: FUNDAMENTAL LIMITS ON DETECTION
Description 4: Discuss the fundamental limits of detection, including the impact of low SNR and imperfect noise variance knowledge.

Section 5: FEATURE DETECTION
Description 5: Present various detectors that utilize known features of the signal for improved performance.

Section 6: COOPERATIVE DETECTION
Description 6: Describe cooperative sensing techniques, including both soft and hard combining methods, and their impact on detection performance.

Section 7: CONCLUDING REMARKS
Description 7: Provide concluding remarks summarizing key points and mentioning areas not covered in the survey.