Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> There is an increasing interest in employing multiple sensors for surveillance and communications. Some of the motivating factors are reliability, survivability, increase in the number of targets under consideration, and increase in required coverage. Tenney and Sandell have recently treated the Bayesian detection problem with distributed sensors. They did not consider the design of data fusion algorithms. We present an optimum data fusion structure given the detectors. Individual decisions are weighted according to the reliability of the detector and then a threshold comparison is performed to obtain the global decision. <s> BIB001 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> Traditionally, frequency spectrum is licensed to users by government agencies in a fixed manner where licensee has exclusive right to access the allocated band. This policy has been de jure practice to protect systems from mutual interference for many years. However, with increasing demand for the spectrum and scarcity of vacant bands, a spectrum policy reform seems inevitable. Meanwhile, recent measurements suggest the possibility of sharing spectrum among different parties subject to interference-protection constraints. In this paper we study spectrum-sharing between a primary licensee and a group of secondary users. In order to enable access to unused licensed spectrum, a secondary user has to monitor licensed bands and opportunistically transmit whenever no primary signal is detected. However, detection is compromised when a user experiences shadowing or fading effects. In such cases, user cannot distinguish between an unused band and a deep fade. Collaborative spectrum sensing is proposed and studied in this paper as a means to combat such effects. Our analysis and simulation results suggest that collaboration may improve sensing performance significantly <s> BIB002 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> The problem of collaborative spectrum sensing by a group of unlicensed devices is considered in this paper. The problem is placed in the specific setting of identifying available TV channels for use by the unlicensed devices. The system model and analysis developed in the paper is applicable to a number of more general dynamic spectrum sharing scenarios. Through analysis and simulations, it is shown in the paper that collaboration among nodes leads to more efficient spectrum utilization from a system-level point of view, while decreasing computational complexity of detection algorithms at the individual sensing nodes <s> BIB003 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> Under the current system of spectrum allocation, rigid partitioning has resulted in vastly underutilized spectrum bands, even in urban locales. Cognitive radios have been proposed as a way to reuse this underutilized spectrum in an opportunistic manner. To achieve this reuse while guaranteeing non-interference with the primary user, cognitive radios must detect very weak primary signals. However, uncertainties in the noise+interference impose a limit on how low of a primary signal can be robustly detected. ::: In this paper, we show that the presence/absence of possible interference from other opportunistic spectrum users represents a major component of the uncertainty limiting the ability of a cognitive radio network to reclaim a band for its use. Coordination among nearby cognitive radios is required to control this uncertainty. While this coordination can take a form similar to a traditional MAC protocol for data communication, its role is different in that it aims to reduce the uncertainty about interference rather than just reducing the interference itself. ::: We show how the degree of coordination required can vary based on the coherence times and bandwidths involved, as well as the complexity of the detectors themselves. The simplest sensing strategies end up needing the most coordination, while more complex strategies involving adaptive coherent processing and interference prediction can be individually more robust and thereby reduce the need for coordination across different networks. We also show the existence of a coordination radius wall which limits secondary user densities that can be supported irrespective of coordination involved. Furthermore, local cooperation among cognitive radios for collective decision making can reduce the fading margins we need to budget for. This cooperation benefits from increased secondary user densities and hence induces a minima in the power-coordination tradeoff. <s> BIB004 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> 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. <s> BIB005 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> Wireless radios of the future will likely be frequency-agile, that is, supporting opportunistic and adaptive use of the RF spectrum. Such radios must coordinate with each other to build an accurate and consistent map of spectral utilization in their surroundings. We focus on the problem of sharing RF spectrum data among a collection of wireless devices. The inherent requirements of such data and the time-granularity at which it must be collected makes this problem both interesting and technically challenging. We propose GUESS, a novel incremental gossiping approach to coordinated spectral sensing. It (1) reduces protocol overhead by limiting the amount of information exchanged between participating nodes, (2) is resilient to network alterations, due to node movement or node failures, and (3) allows exponentially-fast information convergence. We outline an initial solution incorporating these ideas and also show how our approach reduces network overhead by up to a factor of 2.4 and results in up to 2.7 times faster information convergence than alternative approaches. <s> BIB006 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> In cognitive radio networks, cognitive (unlicensed) users need to continuously monitor spectrum for the presence of primary (licensed) users. In this paper, we illustrate the benefits of cooperation in cognitive radio. We show that by allowing the cognitive users operating in the same band to cooperate we can reduce the detection time and thus increase the overall agility. We first consider a two-user cognitive radio network and show how the inherent asymmetry in the network can be exploited to increase the agility. We show that our cooperation scheme increases the agility of the cognitive users by as much as 35%. We then extend our cooperation scheme to multicarrier networks with two users per carrier and analyze asymptotic agility gain. In Part II of our paper [1], we investigate multiuser single carrier networks. We develop a decentralized cooperation protocol which ensures agility gain for arbitrarily large cognitive network population. <s> BIB007 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> In cognitive radio networks, the secondary users can use the frequency bands when the primary users are not present. Hence secondary users need to constantly sense the presence of the primary users. When the primary users are detected, the secondary users have to vacate that channel. This makes the probability of detection important to the primary users as it indicates their protection level from secondary users. When the secondary users detect the presence of a primary user which is in fact not there, it is referred to as false alarm. The probability of false alarm is important to the secondary users as it determines their usage of an unoccupied channel. Depending on whose interest is of priority, either a targeted probability of detection or false alarm shall be set. After setting one of the probabilities, the other can be optimized through cooperative sensing. In this paper, we show that cooperating all secondary users in the network does not necessary achieve the optimum performance, but instead, it is achieved by cooperating a certain number of users with the highest primary user's signal to noise ratio. Computer simulations have shown that the Pd can increase from 92.03% to 99.88% and Pf can decrease from 6.02% to 0.06% in a network with 200 users. <s> BIB008 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> In this letter, we consider cooperative spectrum sensing based on energy detection in cognitive radio networks. Soft combination of the observed energies from different cognitive radio users is investigated. Based on the Neyman-Pearson criterion, we obtain an optimal soft combination scheme that maximizes the detection probability for a given false alarm probability. Encouraged by the performance gain of soft combination, we further propose a new softened hard combination scheme with two-bit overhead for each user and achieve a good tradeoff between detection performance and complexity. <s> BIB009 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> 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. <s> BIB010 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> This article considers spectrum-on-demand in a cellular system. A communication system that wants to access spectrum to which it does not own a license must perform spectrum sensing to identify spectrum opportunities, and to guarantee that it does not cause unacceptable interference to the license owner. Because a single sensor may be in a fading dip, cooperative sensing among multiple sensors which experience uncorrelated fading is required to guarantee reliable sensing performance. At the same time, as few sensors as possible should be used to reduce the battery consumption, while still employing enough many for the sensing to be reliable. Since shadow fading is correlated for closely spaced sensors, it is desired to select sensors which are sufficiently spatially separated. The present article addresses the problem of selecting appropriate sensors from a candidate set to engage in cooperative sensing, using different degrees of knowledge about the sensor positions. Three different algorithms for sensor selection are presented and evaluated by means of simulation. It is shown that all algorithms outperform random selection of the sensors. <s> BIB011 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> In a cognitive radio network (CRN), in-band spectrum sensing is essential for the protection of legacy spectrum users, with which the presence of primary users (PUs) can be detected promptly, allowing secondary users (SUs) to vacate the channels immediately. For in-band sensing, it is important to meet the detectability requirements, such as the maximum allowed latency of detection (e.g., 2 seconds in IEEE 802.22) and the probability of mis-detection and false-alarm. In this paper, we propose an effcient periodic in-band sensing algorithm that optimizes sensing-frequency and sensing-time by minimizing sensing overhead while meeting the detectability requirements. The proposed scheme determines the better of energy or feature detection that incurs less sensing overhead at each SNR level, and derives the threshold aRSSthreshold on the average received signal strength (RSS) of a primary signal below which feature detection is preferred. We showed that energy detection under lognormal shadowing could still perform well at the average SNR <s> BIB012 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> Cognitive radio is being recognized as an intelligent technology due to its ability to rapidly and autonomously adapt operating parameters to changing environments and conditions. In order to reliably and swiftly detect spectrum holes in cognitive radios, spectrum sensing must be used. In this paper, we consider cooperative spectrum sensing in order to optimize the sensing performance. We focus on energy detection for spectrum sensing and find that the optimal fusion rule is the half-voting rule. Next, the optimal detection threshold of energy detection is determined numerically. Finally, we propose a fast spectrum sensing algorithm for a large network which requires fewer than the total number of cognitive radios to perform cooperative spectrum sensing while satisfying a given error bound. <s> BIB013 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> One of the main requirements of cognitive radio systems is the ability to reliably detect the presence of licensed primary transmissions. Previous works on the problem of detection for cognitive radio have suggested the necessity of user cooperation in order to be able to detect at the low signal-to-noise ratios experienced in practical situations. We consider a system of cognitive radio users who cooperate with each other in trying to detect licensed transmissions. Assuming that the cooperating nodes use identical energy detectors, we model the received signals as correlated log-normal random variables and study the problem of fusing the decisions made by the individual nodes. We design a linear-quadratic (LQ) fusion strategy based on a deflection criterion for this problem, which takes into account the correlation between the nodes. Using simulations we show that when the observations at the sensors are correlated, the LQ detector significantly outperforms the counting rule, which is the fusion rule that is obtained by ignoring the correlation. <s> BIB014 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> In this letter, a method is proposed to optimally combine the received signal samples in space and time based on the principle of maximizing the signal-to-noise ratio (SNR). After the combining, energy detection (ED) is used. However, optimal combining needs information of the source signal and channel, which is usually unknown. To overcome this difficulty, a method is proposed to blindly combine the signal samples. Similar to energy detection, blindly combined energy detection (BCED) does not need any information of the source signal and the channel a priori. BCED can be much better than ED for highly correlated signals, and most importantly, it does not need noise power estimation and overcomes ED's susceptibility to noise uncertainty. Also, perfect synchronization is not required. Simulations based on wireless microphone signals and randomly generated signals are presented to verify the methods. <s> BIB015 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> 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 cognitive 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 accurately 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. <s> BIB016 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> Distributed spectrum sensing (DSS) enables a Cognitive Radio (CR) network to reliably detect licensed users and avoid causing interference to licensed communications. The data fusion technique is a key component of DSS. We discuss the Byzantine failure problem in the context of data fusion, which may be caused by either malfunctioning sensing terminals or Spectrum Sensing Data Falsification (SSDF) attacks. In either case, incorrect spectrum sensing data will be reported to a data collector which can lead to the distortion of data fusion outputs. We investigate various data fusion techniques, focusing on their robustness against Byzantine failures. In contrast to existing data fusion techniques that use a fixed number of samples, we propose a new technique that uses a variable number of samples. The proposed technique, which we call Weighted Sequential Probability Ratio Test (WSPRT), introduces a reputation-based mechanism to the Sequential Probability Ratio Test (SPRT). We evaluate WSPRT by comparing it with a variety of data fusion techniques under various network operating conditions. Our simulation results indicate that WSPRT is the most robust against the Byzantine failure problem among the data fusion techniques that were considered. <s> BIB017 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> In this paper, a general framework for performance evaluation of cooperative spectrum sensing methods over realistic propagation environments is proposed. In particular, the framework accounts for correlated Log-Normal shadowing in both sensing and reporting channels, and yields simple and easy-to-use formulas for computing the Detection Probability of a distributed network of secondary users using Amplify and Forward (AF) relying for data reporting to the fusion center. Numerical results are also shown to substantiate the accuracy of the proposed framework. <s> BIB018 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> Cooperation can improve the performance of spectrum sensing. However, the sensing overhead is generally increasing with the number of cooperating users as more data needs to be reported to the fusion center. Most existing works assume a general time frame structure in which spectrum observing and sensing results reporting are conducted sequentially. We argue that this frame structure is inefficient, since the time consumed by reporting contributes little to the performance of spectrum sensing. In this paper, we propose a pipelined spectrum sensing framework, in which spectrum observing is conducted concurrently with results reporting in a pipelined way. By making use of the reporting time for sensing, the new framework provides a much wider observing window for spectrum measurement, which results in a performance improvement of spectrum sensing. Besides, we also present a multi-threaded sequential probability ratio test method (MTSPRT) which is very suitable for the pipelined framework as the data fusion technique. The MTSPRT method can improve the sensing speed significantly. Numerical results indicate that our pipelined sensing scheme incorporating with MTSPRT shows a better performance than the cooperative sensing based on the general frame structure. <s> BIB019 </s> Advances in cognitive radio networks: A survey <s> C. Cooperative Sensing <s> In a wireless system with opportunistic spectrum sharing, secondary users equipped with cognitive radios attempt to access radio spectrum that is not being used by the primary licensed users. On a given frequency channel, a secondary user can perform spectrum sensing to determine spatial or temporal opportunities for spectrum reuse. Whereas most prior works address either spatial or temporal sensing in isolation, we propose a joint spatial-temporal spectrum sensing scheme, which exploits information from spatial sensing to improve the performance of temporal sensing. Our simulation results show that the proposed joint spatial-temporal approach significantly outperforms existing temporal sensing schemes. <s> BIB020
The performance of spectrum sensing is limited by noise uncertainty, shadowing, and multi-path fading effect. When the received primary SNR is too low, there exists a SNR wall, below which reliable spectrum detection is impossible even with a very long sensing time. If secondary users cannot detect the primary transmitter, while the primary receiver is within the secondary users' transmission range, a hidden primary user problem will occur, and the primary user's transmission will be interfered. By taking advantage of the independent fading channels (i.e., spatial diversity) and multiuser diversity, cooperative spectrum sensing is proposed to improve the reliability of spectrum sensing, increase the detection probability to better protect a primary user, and reduce false alarm to utilize the idle spectrum more efficiently. In centralized cooperative spectrum sensing, a central controller, e.g., a secondary base station, collects local observations from multiple secondary users, decides the available spectrum channels using some decision fusion rule, and informs the secondary users which channels to access. In distributed cooperative spectrum sensing, secondary users exchange their local detection results among themselves without requiring a backbone infrastructure with reduced cost. Relays can also be used in cooperative spectrum sensing, such as the cooperative sensing scheme proposed in BIB007 , where the cognitive users operating in the same band help each other relay information using amplify-and-forward protocol. It is shown that the inherent network asymmetry can be exploited to increase the agility. There also exist several challenges on cooperative spectrum sensing. For instance, secondary users can be low-cost devices only equipped with a limit amount of power, so they can not afford very complicated detection hardware and high computational complexity. In wideband cooperative sensing, multiple secondary users have to scan a wide range of spectrum channels and share their detection results. This results in a large amount of sensory data exchange, high energy consumption, and an inefficient data throughput. If the spectrum environment is highly dynamic, the sensed information may even be stale due to user mobility, channel fading, etc. 1) User Selection: Due to secondary users' different locations and channel conditions, it is shown in BIB008 that cooperating all secondary users in spectrum sensing is not optimal, and the optimum detection/false alarm probability is achieved by only cooperating a group of users who have higher SNR of the received primary signal. Since detecting a primary user costs battery power of secondary users, and shadow fading may be correlated for nearby secondary users, an optimal selection of secondary users for cooperative spectrum sensing is desirable. In BIB011 , different algorithms based on different amount of available information are proposed to select a proper set of sensors that experience uncorrelated shadow fading. A joint spatial-temporal sensing scheme for CR networks is proposed in BIB020 , where secondary users collaboratively estimate the location and transmit power of the primary transmitter to determine their maximum allowable transmission power, and use the location information to decide which users should participate in collaborative sensing in order to minimize correlation among the secondary users. Performance evaluation of cooperative spectrum sensing over realistic propagation environments, i.e., correlated log-normal shadowing in both sensing and reporting channels, is investigated in BIB018 . This work also provides guidelines to select the optimal number of users in order to guarantee a certain detecting performance in a practical radio environment. In a CR sensor network, individual sensor nodes may experience heterogeneous false alarm and detection probability due to their different locations, making it harder to determine the optimal number of cooperative nodes. Sensor clustering is proposed in BIB012 , where the optimal cluster size is derived so as to upper-bound the variation of the average received signal strength in a cluster of sensor nodes. Moreover, sensor density is optimized so that average distance between neighboring nodes is lower-bounded and their measurements are nearly independent without much correlation. If a secondary user can not distinguish between the transmissions of a primary user and another secondary user, he will lose the opportunity to use the spectrum. It is shown in BIB004 that the presence/absence of possible interference from other secondary users is the main reason of the uncertainty in primary user detection, and coordinating nearby secondary users can greatly reduce the noise uncertainty due to shadowing, fading, and multi-path effect. A good degree of coordination should be chosen based on the channel coherent times, bandwidths, and the complexity of the detectors. 2) Decision Fusion: Different decision fusion rules for cooperative spectrum sensing have been studied in the literature. Logic OR rule is used BIB002 for combining multiple users' decisions for spectrum sensing in fading environments. Cooperative spectrum sensing using counting rule is studied in  , where sensing errors are minimized by choosing the optimal settings for both matched filtering and energy detection. It is shown in BIB013 that half-voting rule is the optimal decision fusion rule in cooperative sensing based on energy detection. Light-weight cooperation based on hard decisions is proposed BIB005 for cooperative sensing to alleviate the sensitivity requirements on individual users. A liner-quadratic strategy is developed BIB014 to combat the detriment effects of correlation between different secondary users. A good way to optimally combine the received primary signal samples in space and time is to maximize the SNR of local energy detectors. However, optimal combination requires information of the signal and channel. Blindly combined energy detection is proposed in BIB015 , without requiring such information and noise power estimation, while performing much better than energy detector and more robust to noise uncertainty. Hard decision combining with the logic AND rule and soft decision using the likelihood ratio test are proposed in BIB003 in collaborative detection of TV transmissions. It is shown that soft decision combining for spectrum sensing yields more precise detection than hard decision combining. Soft decision combination for cooperative sensing based on energy detection is investigated in BIB009 , and maximal ratio combination is proved to be near optimal in low SNR region and reduce the SNR wall. In general, cooperative sensing is coordinated over a separate control channel, so a good cooperation schemes should be able to use a small bandwidth and power for exchanging local detection results while maximizing the detection reliability. An efficient linear cooperation framework for spectrum sensing is proposed in BIB016 , where the global decision is a linear combination of the local statistics collected from individual nodes using energy detection. Compared to the likelihood ratio test, the proposed method has lower computational complexity, closed-form expressions of detection and false alarm probabilities, and comparable detection performance. Performance of cooperative spectrum sensing depends on the correctness of the local sensing data reported by the secondary users. If malicious users enter a legitimate secondary network and compromise the secondary users, false detection results will be reported to the fusion center, and this kind of attack is called spectrum sensing data falsification (SSDF) attack BIB017 . In order to guarantee satisfying detection performance under the SSDF attack, a weighted sequential probability ratio test (WSPRT) is proposed in BIB017 , which incorporates a reputation-based mechanism to the sequential probability ratio test. If a secondary user's local detection result is identical to the final result after decision fusion, his/her reports will carry more weight in future decision fusion. The proposed WSPRT approach is more robust against the SSDF attack than commonly adopted decision fusion rules, such as AND, OR, and majority rules BIB001 . 3) Efficient Information Sharing: In order to coordinate the cooperation in spectrum sensing, a lot of information exchange is needed among secondary users, such as their locations, estimation of the primary user's location and power, which users should be clustered into a group, which users should perform cooperative sensing at a particular time epoch, and so on. Such a large amount of information exchange brings a lot of overhead to the secondary users, which necessitates an efficient information sharing among the secondary users. GUESS protocol, an incremental gossiping approach is proposed in BIB006 , to coordinate the dissemination of spectrum sensing results with reduced overhead. In order to reduce the bandwidth required by a large number of secondary users for reporting their sensing results, a censoring method with quantization is proposed in BIB010 . Only users with reliable information will send their local observations, i.e., one bit decision 0 or 1, to the common receiver. A pipelined spectrum sensing framework is proposed in BIB019 , where spectrum sensing is conducted concurrently with when secondary users are sending their detection reports. The proposed method alleviates sensing overhead by making use of the reporting time, provides more time for spectrum sensing, and thus improves the detection performance. 