The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.

A survey of spectrum sensing algorithms for cognitive radio applications

With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a bottleneck for more efficient spectrum utilization, under which a great portion of the licensed spectrum is severely under-utilized. The inefficient usage of the limited spectrum resources urges the spectrum regulatory bodies to review their policy and start to seek for innovative communication technology that can exploit the wireless spectrum in a more intelligent and flexible way. The concept of cognitive radio is proposed to address the issue of spectrum efficiency and has been receiving an increasing attention in recent years, since it equips wireless users the capability to optimally adapt their operating parameters according to the interactions with the surrounding radio environment. There have been many significant developments in the past few years on cognitive radios. This paper surveys recent advances in research related to cognitive radios. The fundamentals of cognitive radio technology, architecture of a cognitive radio network and its applications are first introduced. The existing works in spectrum sensing are reviewed, and important issues in dynamic spectrum allocation and sharing are investigated in detail.

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Advances in cognitive radio networks: A survey

Cognitive radio (CR) is a promising technology that can alleviate the spectrum shortage problem by enabling unlicensed users equipped with CRs to coexist with incumbent users in licensed spectrum bands while causing no interference to incumbent communications. Spectrum sensing is one of the essential mechanisms of CRs and its operational aspects are being investigated actively. However, the security aspects of spectrum sensing have garnered little attention. In this paper, we identify a threat to spectrum sensing, which we call the primary user emulation (PUE) attack. In this attack, an adversary's CR transmits signals whose characteristics emulate those of incumbent signals. The highly flexible, software-based air interface of CRs makes such an attack possible. Our investigation shows that a PUE attack can severely interfere with the spectrum sensing process and significantly reduce the channel resources available to legitimate unlicensed users. To counter this threat, we propose a transmitter verification scheme, called LocDef (localization-based defense), which verifies whether a given signal is that of an incumbent transmitter by estimating its location and observing its signal characteristics. To estimate the location of the signal transmitter, LocDef employs a non-interactive localization scheme. Our security analysis and simulation results suggest that LocDef is effective in identifying PUE attacks under certain conditions.

Defense against Primary User Emulation Attacks in Cognitive Radio Networks

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.

Robust Distributed Spectrum Sensing in Cognitive Radio Networks

Cognitive Radio (CR) is a promising technology that can alleviate the spectrum shortage problem by enabling unlicensed users equipped with CRs to coexist with incumbent users in licensed spectrum bands without inducing interference to incumbent communications. Spectrum sensing is one of the essential mechanisms of CRs that has attracted great attention from researhers recently. Although the operational aspects of spectrum sensing are being investigated actively, its security aspects have garnered little attention. In this paper, we describe an attack that poses a great threat to spectrum sensing. In this attack, which is called the primary user emulation (PUE) attack, an adversary's CR transmits signals whose characteristics emulate those of incumbent signals. The highly flexible, software-based air interface of CRs makes such an attack possible. Our investigation shows that a PUE attack can severely interfere with the spectrum sensing process and significantly reduce the channel resources available to legitimate unlicensed users. As a way of countering this threat, we propose a transmitter verification procedure that can be integrated into the spectrum sensing mechanism. The transmitter verification procedure employs a location verification scheme to distinguish incumbent signals from unlicensed signals masquerading as incumbent signals. Two alternative techniques are proposed to realize location verification: Distance Ratio Test and Distance Difference Test. We provide simulation results of the two techniques as well as analyses of their security in the paper.

Ensuring Trustworthy Spectrum Sensing in Cognitive Radio Networks

In future applications, next generation spectrally agile software defined radios (SASDR) will be equipped with advanced radio frequency (RF) sensors that will enable them to sense their environment and adaptively select the best and most stable portions of the spectrum to establish communications. This paper presents a robust method for estimating locally the unused or underutilized regions of RF spectrum to optimize dynamic spectrum usage. These adaptive algorithms are described and results of "open spectrum" estimation performed on real RF spectrum measurements illustrate the robust performance of the approach. Simulation results are shown along with results from real measurements that describe the RF resources in rural, suburban and urban areas in and around Philadelphia in the VHF and UHF bands. The measurements represent a good dynamic data set including motion and spatio-temporal diversity. The effect on reducing the risk of interference by collaborating across multiple nodes that provides increased robustness of sensing of open spectrum through spatial diversity is also discussed and quantitative values for the interference mitigation under collaborative behaviors are also presented

A scalable dynamic spectrum allocation system with interference mitigation for teams of spectrally agile software defined radios

Self-directed movement of radio devices can enable large amounts of power gain since the sources of fluctuations in received signal power due to multipath-induced small-scale fading have highly localized effects. We call the gain achieved by finding a better location the mobility gain. Experimental data for indoor as well as outdoor measurement studies are used to illustrate the potential of this RF-Mobility Gain concept over a wide range of frequencies. An analysis of the RF data reveals that a small amount of energy spent on searching for a better location can pay large dividends in long-term power expenditures for RF transmission. Challenges in building such a system for peer-to-peer links and network applications are discussed along with potential coordination algorithms.

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RF-mobility gain: concept, measurement campaign, and exploitation

This paper evaluates the reconfigurability of a 2D fractal tree antenna to improve the capacity of a 2×2 MIMO link using pattern diversity. Each fractal tree antenna possesses several degrees of freedom: number of fractal stages, branches per stage, angle between branches, and parent-to-child branch scaling length. Simulations of various Reconfigurable Printed Fractal Tree Arrays (RPFTAs) are conducted so their spatial correlation and MIMO channel capacity can be found. Capacity improvement from two different RPFTAs are reported, assuming a perfect feedback channel.

Evaluation of the reconfigurable Printed Fractal Tree antenna for enhanced pattern diversity in MIMO systems

State-based spatial multiplexing (SBSM) is a novel multiple input multiple output (MIMO) technology that enables MIMO operations between simple COTS radios. The SBSM technique works at the medium access control (MAC) layer; therefore, the radio only needs to be synchronized at the symbol level instead of the carrier. The technique uses a deconvolution based on an iterative Viterbi decoder to remove the effects of cascaded convolutional processes that represents the channel mixing plus a convolutional forward error correction (FEC) code. The technique uses only the symbol decisions obtained by a base-band demodulator, effectively sampled with relatively few bits of resolution. Combining MAC layer data streams of multiple observations in space provides robustness in addition to spatial multiplexing capabilities. This document presents the SBSM method, compares it to traditional MIMO methods, and concludes with simulated and measured performance for a 2times2 SBSM system.

Marc Olivieri

Papers

A scalable dynamic spectrum allocation system with interference mitigation for teams of spectrally agile software defined radios

RF-mobility gain: concept, measurement campaign, and exploitation

Evaluation of the reconfigurable Printed Fractal Tree antenna for enhanced pattern diversity in MIMO systems

State-based Spatial Multiplexing (SBSM)