Blind Symbol Rate Estimation of Faster-than-Nyquist Signals Based on Higher-Order Statistics

Both faster-than-Nyquist (FTN) and cognitive radio go towards an efficient use of spectrum in radio communications systems at the cost of an added computational complexity at the receiver side. To gain the maximum potential from these techniques, non-data-aided receivers are of interest. In this paper, we use fourth-order statistics to perform blind symbol rate estimation of FTN signals. The estimator shows good performance results for moderate system's densities beyond the Nyquist rate and for a reasonable number of received samples

Resource management in location aware cognitive radio networks

Dynamic spectrum access (DSA) aims at utilizing spectral opportunities both in time and frequency domains at any given location, which arise due to variations in spectrum usage. Recently, Cognitive radios (CRs) have been proposed as a means of implementing DSA. In this work we focus on the aspect of resource management in overlaid CRNs. We formulate resource allocation strategies for cognitive radio networks (CRNs) as mathematical optimization problems. Specifically, we focus on two key problems in resource management: Sum Rate Maximization and Maximization of Number of Admitted Users. Since both the above mentioned problems are NP hard due to presence of binary assignment variables, we propose novel graph based algorithms to optimally solve these problems. Further, we analyze the impact of location awareness on network performance of CRNs by considering three cases: Full location Aware, Partial location Aware and Non location Aware. Our results clearly show that location awareness has significant impact on performance of overlaid CRNs and leads to increase in spectrum utilization effciency

Higher-Order Cyclostationarity Detection for Spectrum Sensing

<p/> <p>Recent years have shown a growing interest in the concept of Cognitive Radios (CRs), able to access portions of the electromagnetic spectrum in an opportunistic operating way. Such systems require efficient detectors able to work in low Signal-to-Noise Ratio (SNR) environments, with little or no information about the signals they are trying to detect. Energy detectors are widely used to perform such blind detection tasks, but quickly reach the so-called SNR wall below which detection becomes impossible Tandra (2005). Cyclostationarity detectors are an interesting alternative to energy detectors, as they exploit hidden periodicities present in man-made signals, but absent in noise. Such detectors use quadratic transformations of the signals to extract the hidden sine-waves. While most of the literature focuses on the second-order transformations of the signals, we investigate the potential of higher-order transformations of the signals. Using the theory of Higher-Order Cyclostationarity (HOCS), we derive a fourth-order detector that performs similarly to the second-order ones to detect linearly modulated signals, at SNR around 0 dB, which may be used if the signals of interest do not exhibit second-order cyclostationarity. More generally this paper reviews the relevant aspects of the cyclostationary and HOCS theory, and shows their potential for spectrum sensing.</p

Higher-Order Cyclostationarity Detection for Spectrum Sensing

Recent years have shown a growing interest in the concept of Cognitive Radios (CRs), able to access portions of the electromagnetic spectrum in an opportunistic operating way. Such systems require efficient detectors able to work in low Signal-to-Noise Ratio (SNR) environments, with little or no information about the signals they are trying to detect. Energy detectors are widely used to perform such blind detection tasks, but quickly reach the so-called SNR wall below which detection becomes impossible Tandra (2005). Cyclostationarity detectors are an interesting alternative to energy detectors, as they exploit hidden periodicities present in man-made signals, but absent in noise. Such detectors use quadratic transformations of the signals to extract the hidden sine-waves. While most of the literature focuses on the second-order transformations of the signals, we investigate the potential of higher-order transformations of the signals. Using the theory of Higher-Order Cyclostationarity (HOCS), we derive a fourth-order detector that performs similarly to the second-order ones to detect linearly modulated signals, at SNR around 0 dB, which may be used if the signals of interest do not exhibit second-order cyclostationarity. More generally this paper reviews the relevant aspects of the cyclostationary and HOCS theory, and shows their potential for spectrum sensing