Ahmet Hasim Gokceoglu

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In this paper, we study simultaneous multi-channel spectrum sensing in cognitive radio context. The sensing receiver RF front-end is assumed to deploy wideband multi-channel IQ down-conversion which is well-suited for highly-integrated circuit implementations. Such RF front-end is, however, also prone to several RF impairments, such as IQ imbalance, which(More)
Spectrum sensing of primary users under very low signal-to-noise ratio (SNR) and noise uncertainty is crucial for cognitive radio (CR) systems. To overcome the drawbacks of weak signal and noise uncertainty, eigenvalue-based spectrum sensing methods have been proposed for advanced CRs. However, one pressing disadvantage of eigenvalue-based spectrum sensing(More)
In this paper, we address the spectrum sensing task of cognitive radio from Bayesian detection (BD) perspective. We first show that BD essentially simplifies to classical energy detection (ED) under Gaussian signal assumption but the threshold setting has more degrees of freedom to optimize the sensing performance, e.g., against given spectrum utilization.(More)
Balancing between power amplifier (PA) linearity and power efficiency is one of the biggest implementation challenges in radio communication transmitters. Among various linearization methods, the feedforward linearization technique is a fairly established principle offering a good tradeoff between linearity and power-efficiency even under wideband(More)
Dynamic and flexible RF spectrum access through software-defined radio technologies is known to be limited by transmitter RF impairments, most notably spurious emissions due to mixer I/Q imbalance and power amplifier nonlinearity. In this article, a novel digital predistortion structure is developed for joint mitigation of frequency-dependent I/Q imbalance(More)