SNR-Walls in Eigenvalue-based Spectrum Sensing

Various spectrum sensing approaches have been shown to suffer from a so-called SNR-wall, an SNR value below which a detector cannot perform robustly no matter how many observations are used. Up to now, the eigenvalue-based maximum-minimum-eigenvalue (MME) detector has been a notable exception. For instance, the model uncertainty of imperfect knowledge of the receiver noise power, which is known to be responsible for the energy detector's fundamental limits, does not adversely affect the MME detector's performance. While additive white Gaussian noise (AWGN) is a standard assumption in wireless communications, it is not a reasonable one for the MME detector. In fact, in this work we prove that uncertainty in the amount of noise coloring does lead to an SNR-wall for the MME detector. We derive a lower bound on this SNR-wall and evaluate it for example scenarios. The findings are supported by numerical simulations.Comment: 17 pages, 3 figures, submitted to EURASIP Journal on Wireless Communications and Networkin

Particle Swarm Optimization and gravitational wave data analysis: Performance on a binary inspiral testbed

The detection and estimation of gravitational wave (GW) signals belonging to a parameterized family of waveforms requires, in general, the numerical maximization of a data-dependent function of the signal parameters. Due to noise in the data, the function to be maximized is often highly multi-modal with numerous local maxima. Searching for the global maximum then becomes computationally expensive, which in turn can limit the scientific scope of the search. Stochastic optimization is one possible approach to reducing computational costs in such applications. We report results from a first investigation of the Particle Swarm Optimization (PSO) method in this context. The method is applied to a testbed motivated by the problem of detection and estimation of a binary inspiral signal. Our results show that PSO works well in the presence of high multi-modality, making it a viable candidate method for further applications in GW data analysis.Comment: 13 pages, 5 figure

DVB-T signal detection for indoor environments in low-SNR regime

The problem of coexistence between the primary (licensed) and secondary (non-licensed) users can be solved in various ways. One of them assumes the application of the detailed Radio Environment Maps being a kind of database, where some crucial information about the licensed transmission can be stored. In this paper we propose the new methods for signal detection in low signal-to-noise regime and compare it through hardware experiment with other known techniques used for spectrum sensing.Peer ReviewedPostprint (author’s final draft

Optomechanical detection of weak forces

Optomechanical systems are often used for the measurement of weak forces. Feedback loops can be used in these systems for achieving noise reduction. Here we show that even though feedback is not able to improve the signal to noise ratio of the device in stationary conditions, it is possible to design a nonstationary strategy able to improve the sensitivity.Comment: 12 pages, 6 figures, contribution to the proceedings of the SPIE Conference on Fluctuations and Nois