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Spectrum sensing is the fundamental technology of Cognitive Radio (CR). This paper proposes a novel multiple-antenna based spectrum sensing method with random arrivals of primary users (PUs). The method first constructs a local test statistic for each antenna based on the assumption that the PU is randomly arriving, and then calculates the estimated optimum coefficient for every local test statistic...
Spectrum sensing is a fundamental technology to detect the presence of primary user in cognitive radio networks. Usually, the requirements for spectrum sensing are very stringent. It requires that the spectrum sensing scheme has a good performance even in extremely low signal-to-noise ratio (SNR) environments. In this paper, we propose a novel spectrum sensing method based on stochastic resonance...
In cognitive radio contexts, it is an important work to design an optimal spectrum sensing framework. Most of the previous work just focused on either the optimal sensing time (quiet period) or the maximal throughput constrained by the probability of detection or some interference level. In this paper, we propose an optimal spectrum sensing framework in cognitive radio contexts which jointly optimizes...
Achieving efficient bandwidth utilization in multi-channel sensor networks is a challenging research problem. In this paper, we present a cognitive load balance algorithm for single-hop multi-channel sensor networks. Based on the load distribution of all base stations, our algorithm dynamically alternates the communication channels. As a result, the extra load from over-loaded channels is directed...
Spectrum sensing is a key technology in cognitive radio (CR). It provides the CR system with available vacant channels list by sensing the spectrum environment over a wide frequency band. However, local sensing by single node will be compromised if the sensing node experiences shadowing or fading effect. Cooperative spectrum sensing is derived to solve this problem. In this paper, we propose an adaptive...
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