This paper investigates a signal area (SA) estimation method for wideband and long time duration spectrum measurements for dynamic spectrum access. SA denotes the area (in time/frequency domain) occupied by the primary user's signal. The traditional approach, which utilizes only Fourier transform (FT) and energy detector (ED) for SA estimation, can achieve low complexity, but its estimation performance is not very high. Against this issue, we apply post-processing to improve the performance of the FT-based ED. Our proposed method, simple SA (S-SA) estimation, exploits the correlation of the spectrum states among the neighboring tiles and the fact that SA typically has a rectangular shape to estimate SA with high accuracy and relatively low complexity compared to a conventional method, contour tracing SA (CT-SA) estimation. Numerical results will show that the S-SA estimation method can achieve better detection performance. The SA estimation and processing can reduce the number of bits needed to store/transmit the observed information compared to the FT-based ED. Thus, in addition to improved detection performance it also compresses the data.

Dynamic spectrum access (DSA) is an attractive approach to solve the spectrum scarcity problem. Among DSA techniques, spectrum overlay is an approach where the spectrum licensed to a primary user (PU) is shared by a secondary user (SU) while protecting the PU from the interference caused by SU spectrum reuse. In the case where PU traffic is dynamic, spectrum sharing is difficult as satisfying requirements of spectrum sensing, the challenging accuracy, quickness and low cost requirements in practice, is difficult. For this issue, we propose a new concept of smart spectrum access (SSA) where useful information related to PU spectrum utilization is used to achieve not only the above requirements but also more efficient spectrum utilization. We also show an approach to realize practical SSA and it consists of a spectrum awareness system (SAS) and a dynamic spectrum access system (DSAS). The main role of the SAS is to provide useful information to the DSAS. The information can be obtained by the SAS through spectrum utilization measurement and analysis of the measurement data. In this paper, we present a framework for smart spectrum access and discuss the challenges of this approach. In addition, we report some of the experimental results related to SAS. 23497S-1-63190-055-6

We create a practical method to set the segment size of the Welch FFT for wideband and long-term spectrum usage measurements in the context of hierarchical dynamic spectrum access (DSA). An energy detector (ED) based on the Welch FFT can be used to detect the presence or absence of primary user (PU) signal and to estimate the duty cycle (DC). In signal detection with the Welch FFT, segment size is an important design parameter since it determines both the detection performance and the frequency resolution. Between these two metrics, there is a trade-off relationship which can be controlled by adjusting the segment size. To cope with this trade-off relationship, we define an optimum and, more easy to analyze sub-optimum segment size design criterion. An analysis of the sub-optimum segment size criterion reveals that the resulting segment size depends on the signal-to-noise ratio (SNR) and the DC. Since in practice both SNR and DC are unknown, proper segment setting is difficult. To overcome this problem, we propose an adaptive segment size selection (ASSS) method that uses noise floor estimation outputs. The proposed method does not require any prior knowledge on the SNR or the DC. Simulation results confirm that the proposed ASSS method matches the performance achieved with the optimum design criterion.

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