Danijela Cabric

Implementation issues in spectrum sensing for cognitive radios

There are new system implementation challenges involved in the design of cognitive radios, which have both the ability to sense the spectral environment and the flexibility to adapt transmission parameters to maximize system capacity while coexisting with legacy wireless networks. The critical design problem is the need to process multigigahertz wide bandwidth and reliably detect presence of primary users. This places severe requirements on sensitivity, linearity and dynamic range of the circuitry in the RF front-end. To improve radio sensitivity of the sensing function through processing gain we investigated three digital signal processing techniques: matched filtering, energy detection and cyclostationary feature detection. Our analysis shows that cyclostationary feature detection has advantages due to its ability to differentiate modulated signals, interference and noise in low signal to noise ratios. In addition, to further improve the sensing reliability, the advantage of a MAC protocol that exploits cooperation among many cognitive users is investigated.

Spectrum Sensing Measurements of Pilot, Energy, and Collaborative Detection

In this paper we present an experimental study that comprehensively evaluates the performance of three different detection methods proposed for sensing of primary user signals in cognitive radios. For pilot and energy detection, our measurement results confirmed the theoretical expectations on sensing time performance. However, a physical implementation of these detectors in the presence of real noise uncertainties, analog impairments and interference allowed us to establish practical bounds on the detectable signal levels. In the case of collaborative detection, our analysis of experimental data collected in indoor environments identified the design parameters that can significantly improve the sensing gain: adaptive threshold, spatial separation and multiple antennas

Experimental study of spectrum sensing based on energy detection and network cooperation

Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. Recent research studied spectrum sensing using energy detection and network cooperation via modeling and simulations. However, there is a lack of experimental study that shows the feasibility and practical performance limits of this approach under real noise and interference sources in wireless channels. In this work, we implemented energy detector on a wireless testbed and measured the required sensing time needed to achieve the desired probability of detection and false alarm for modulated and sinewave-pilot signals in low SNR regime. We measured the minimum detectable signal levels set by the receiver noise uncertainties. Our experimental study also measured the sensing improvements achieved via network cooperation, identified the robust threshold rule for hard decision combining and quantified the effects of spatial separation between radios in indoor environments.

Spectrum sharing radios

A major shift in radio design is now just beginning which attempts to share spectrum in a fundamentally new way. These radios are addressing the fact that spectrum is actually poorly utilized in many bands, in spite of the increasing demand for wireless connectivity. The new approaches to spectrum sharing make use of the advances in technology to implement new wireless systems that can share previously allocated spectra in such a way that the primary users of these spectra are not affected. Additionally, the allowed use of this band is on an unlicensed basis. Two methods that are being investigated to accomplish this task are the use of ultra wideband transmission and cognitive techniques. Ultra wideband transmission relies on the fact that if the bandwidth is increased, that reliable data transmission can occur even at power levels so low that primary radios in the same spectral bands are not affected. On the other hand the cognitive approach does not necessarily limit the transmission power, but rather attempts to share the spectra through a dynamic avoidance strategy. The opportunities and challenges of this new era in radio design are described along with the open questions in their implementation

Physical layer design issues unique to cognitive radio systems

Cognitive radio systems offer the opportunity to improve spectrum utilization by detecting unoccupied spectrum bands and adapting the transmission to those bands while avoiding the interference to primary users. This novel approach to spectrum access introduces unique functions at the physical layer: reliable detection of primary users and adaptive transmission over a wide bandwidth. In this paper, we address design issues involved in an implementation of these functions that could limit their performance or even make them infeasible. The critical design problem at the receiver is to achieve stringent requirements on radio sensitivity and perform signal processing to detect weak signals received by a wideband RF front-end with limited dynamic range. At the transmitter, wideband modulation schemes require adaptation to different frequency bands and power levels without creating interference to active primary users. We introduce algorithms and techniques whose implementation could meet these challenging requirements

Cognitive radio: Ten years of experimentation and development

The year 2009 marked the 10th anniversary of Mitola and Maguire Jr. introducing the concept of cognitive radio. This prompted an outpouring of research work related to CR, including the publication of more than 30 special issue scientific journals and more than 60 dedicated conferences and workshops. Although the theoretical research is blooming, with many interesting results presented, hardware and system development for CR is progressing at a slower pace. We provide synopses of the commonly used platforms and testbeds, examine what has been achieved in the last decade of experimentation and trials relating to CR, and draw several perhaps surprising conclusions. This analysis will enable the research community to focus on the key technologies to enable CR in the future.

Reputation-based cooperative spectrum sensing with trusted nodes assistance

Existing cooperative spectrum sensing (CSS) schemes are typically vulnerable to attacks where misbehaved cognitive radios (CRs) falsify sensing data. To ensure the robustness of spectrum sensing, this letter presents a secure CSS scheme by introducing a reputation-based mechanism to identify misbehaviors and mitigate their harmful effect on sensing performance. Encouraged by the fact that such secure CSS is sensitive to the correctness of reputations, we further present a trusted node assistance scheme. This scheme starts with reliable CRs. Sensing information from other CRs are incorporated into cooperative sensing only when their reputation is verified, which increases robustness of cooperative sensing. Simulations verify the effectiveness of the proposed schemes.

Energy Detection Based Spectrum Sensing Over

Energy detection (ED) is a simple and popular method of spectrum sensing in cognitive radio systems. It is also widely known that the performance of sensing techniques is largely affected when users experience fading effects. This paper investigates the performance of an energy detector over generalized κ-μ and κ- μ extreme fading channels, which have been shown to provide remarkably accurate fading characterization. Novel analytic expressions are firstly derived for the corresponding average probability of detection for the case of single-user detection. These results are subsequently extended to the case of square-law selection (SLS) diversity and for collaborative detection scenarios. As expected, the performance of the detector is highly dependent upon the severity of fading since even small variations of the fading conditions affect significantly the value of the average probability of detection. Furthermore, the performance of the detector improves substantially as the number of branches or collaborating users increase in both severe and moderate fading conditions, whereas it is shown that the κ- μ extreme model is capable of accounting for fading variations even at low signal-to-noise values. The offered results are particularly useful in assessing the effect of fading in ED-based cognitive radio communication systems; therefore, they can be used in quantifying the associated tradeoffs between sensing performance and energy efficiency in cognitive radio networks.

\kappa{-}\mu

In this article we present a feasibility study of spectrum-sensing techniques using a research testbed platform for exploration and demonstration of cognitive radio systems. Our cognitive radio testbed is particularly suited for the development of physical and network layer functionalities and their experimental characterization in realistic wireless scenarios. Advanced testbed capabilities include real-time high-speed signal processing and protocol implementation, and support for multiple networks interaction and multiple antennas operation. This testbed is used for an experimental study of a set of prominent candidate techniques proposed in the literature for implementation of spectrum sensing functionality. We first consider three physical layer signal processing approaches based on energy, pilot, and feature detection. Our experimental results show that theoretical performance of these approaches for spectrum sensing cannot be achieved for the detection of very weak signals using a practical sensing receiver implementation. Also, we explain why these limitations exist by identifying sources of errors and provide basis for the design of robust spectrum sensing techniques. Next, we consider spectrum sensing techniques that use multiple measurements to improve sensing reliability. Our experimental study demonstrates practically achievable gains by exploiting multipath channel diversity through multiple antenna processing, and spatial diversity using user cooperation in a typical indoor environment.

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Information about primary transmitter location is crucial in enabling several key capabilities in cognitive radio networks, including improved spatio-temporal sensing, intelligent location-aware routing, as well as aiding spectrum policy enforcement. Compared to other proposed non-interactive localization algorithms, the weighted centroid localization (WCL) scheme uses only the received signal strength information, which makes it simple to implement and robust to variations in the propagation environment. In this paper we present the first theoretical framework for WCL performance analysis in terms of its localization error distribution parameterized by node density, node placement, shadowing variance, correlation distance and inaccuracy of sensor node positioning. Using this analysis, we quantify the robustness of WCL to various physical conditions and provide design guidelines, such as node placement and spacing, for the practical deployment of WCL. We also propose a power-efficient method for implementing WCL through a distributed cluster-based algorithm, that achieves comparable accuracy with its centralized counterpart.