Multiantenna spectrum sensing for Cognitive Radio: overcoming noise uncertainty Roberto López-Valcarce and Gonzalo Vazquez-Vilar Dept. Signal Theory & Communications University of Vigo 36310 Vigo, Spain email: {valcarce, gvazquez}@gts.tsc.uvigo.es Josep Sala Dept. Signal Theory & Communications Technical University of Catalonia 08034 Barcelona, Spain email: josep.sala@upc.edu Abstract—Spectrum sensing is a key ingredient of the dynamic spectrum access paradigm, but it needs powerful detectors operating at SNRs well below the decodability levels of primary signals. Noise uncertainty poses a significant challenge to the development of such schemes, requiring some degree of diversity (spatial, temporal, or in distribution) for identifiability of the noise level. Multiantenna detectors exploit spatial independence of receiver thermal noise. We review this class of schemes and propose a novel detector trading off performance and complexity. However, most of these methods assume that the noise power, though unknown, is the same at all antennas. As it turns out, calibration errors have a substantial impact on these detectors. Another novel detector is proposed, based on an approximation to the Generalized Likelihood Ratio, outperforming previous schemes for uncalibrated multiantenna receivers. I. I NTRODUCTION The apparent scarcity of spectral resources while most allocated frequency bands are underutilized motivates the Cognitive Radio (CR) paradigm [1]. The key idea of op- portunistically accessing momentarily unused licensed bands requires powerful spectrum monitoring techniques, since the interference produced to licensed (primary) users must be kept at sufficiently low levels. At the same time, the wireless medium makes reliable detection of primary users a very challenging task: due to fading and shadowing phenomena, the received primary signal may be very weak, resulting in very low Signal-to-Noise Ratio (SNR) operation conditions [2]. Certain properties of the primary signal, such as the presence of any pilots or cyclostationary features, could in principle be exploited in order to obtain powerful detectors. However, such approaches become very sensitive to synchro- nization errors [2]. With very low SNR, the synchronization loops of the monitoring system cannot be expected to provide the required accuracy for the carrier frequency and/or clock rate estimates. At the other end of the range of detection techniques one finds the popular Energy Detector, which has very low complexity, operates asynchronously, and does not require any a priori knowledge of primary signals. These desirable traits come at the cost of a reduced detection This work was supported by the Spanish Government under projects SPROACTIVE (reference TEC2007-68094-C02/TCM) and COMONSENS (CONSOLIDER-INGENIO 2010 CSD2008-00010). performance [2]. However, knowledge of the noise variance is required so that the threshold to which the received signal power is compared can be computed in order to set the desired probability of false alarm. A critical SNR level (an “SNR wall” [3]) appears if the actual value of the noise variance is different from the nominal value. Primary signals below this critical value become undetectable, even if the observation time goes to infinity. This serious drawback motivates the search for asynchronous detectors robust to noise uncertainty. In this regard, exploiting the availability of multiple anten- nas constitutes a promising approach. Multiple-input multiple- output (MIMO) technologies having reached considerable ma- turity, it is very likely for future CR terminals to incorporate them [4], [5]. In terms of transmission/reception, multiple antennas provide a means to increase channel capacity without bandwidth expansion, as well as to overcome the effects of fading via space-time coding [6]. Several authors have recently studied the benefits of having multiple antennas in terms of enhancing detection performance in the context of CR systems. In [7] an analysis was given for multiantenna Energy Detectors using maximal ratio combining and antenna selection; these schemes require knowledge of the channel from the primary user to the cognitive node and therefore are difficult to implement in practice. A priori knowledge about the spectral characteristics of the transmitted primary signal was exploited in [8] together with a multiantenna sensor in order to develop a generalized Energy Detector under a weak signal assumption. Both [7] and [8] assume knowledge of the noise variance, and therefore they inherit the sensitivity of the original Energy Detector to uncertainties about this parameter. However, with multiantenna sensors it is possible in prin- ciple to overcome this problem. The basic idea is to exploit the fact that, if the channel under scrutiny is being used by the primary network, then some spatial correlation should be present in the signals at different antennas. On the other hand, if the channel is idle so that the only contribution in the observations corresponds to thermal noise, then such correlation should be absent. Thus, detectors can be designed based on spatial correlation estimates, rather than received signal power. An alternative interpretation is that multiantenna sensors provide additional degrees of freedom which allow for simultaneous estimation of signal and noise parameters. This CIP2010: 2010 IAPR Workshop on Cognitive Information Processing 978-1-4244-6458-6/10/$26.00 ©2010 IEEE 310