This paper is concerned with Electroencephalography (EEG) seizure prediction, which means the detection of the pre-ictal state prior to ictal activity occurrence. The basic idea of the proposed approach for EEG seizure prediction is to work on the signals in the Hilbert domain. The operation in the Hilbert domain guarantees working on the low-pass spectra of EEG signal segments to avoid artifacts. Signal attributes in the Hilbert domain including amplitude, derivative, local mean, local variance, and median are analyzed statistically to perform the channel selection and seizure prediction tasks. Pre-defined prediction and false-alarm probabilities are set to select the channels, the attributes, and bins of probability density functions (PDFs) that can be useful for seizure prediction. Due to the multi-channel nature of this process, there is a need for a majority voting strategy to take a decision for each signal segment. Simulation results reveal an average prediction rate of 96.46%, an average false-alarm rate of 0.028077/h and an average prediction time of 60.1595 min for a 90-min prediction horizon.
相似文献A new subcarrier-user allocation algorithm for the downlink non-orthogonal multiple access system is presented in this paper. The proposed algorithm aims to enhance the spectral efficiency of the system and the successive interference cancelation performance by guaranteeing a high difference in channel-gain between the paired users per subcarrier. To enhance the spectral efficiency, the proposed algorithm provides a higher priority to the subcarrier that has a higher best (maximum) channel gain value rather than that has a lower best channel gain value. Also, it pairs the strong user with the second minimum channel-gain user rather than the minimum channel gain user. Besides, the proposed algorithm divides the subcarriers into two groups according to the standard deviation of the channel gain of each subcarrier. Then, it gives the priority to the group with low standard deviation values during subcarrier-user allocation to guarantee a high difference in channel-gain between the paired users per subcarrier. Later, fractional transmit power allocation is applied to distribute the subcarrier power between the paired users. Simulation results prove that the proposed algorithm improves the spectral efficiency of the system, and guarantees a significantly higher difference in channel-gain between the paired users per subcarrier compared to the conventional algorithms.
相似文献Orthogonal frequency division multiple access (OFDMA) is extensively utilized for the downlink of cellular systems such as long term evolution (LTE) and LTE advanced. In OFDMA cellular networks, orthogonal resource blocks can be used within each cell. However, the available resources are rare and so those resources have to be reused by adjacent cells in order to achieve high spectral efficiency. This leads to inter-cell interference (ICI). Thus, ICI coordination among neighboring cells is very important for the performance improvement of cellular systems. Fractional frequency reuse (FFR) has been widely adopted as an effective solution that improves the throughput performance of cell edge users. However, FFR does not account for the varying nature of the channel. Moreover, it exaggerates in caring about the cell edge users at the price of cell inner users. Therefore, effective frequency reuse approaches that consider the weak points of FFR should be considered. In this paper, we present an adaptive self-organizing frequency reuse approach that is based on dividing every cell into two regions, namely, cell-inner and cell-outer regions; and minimizing the total interference encountered by all users in every region. Unlike the traditional FFR schemes, the proposed approach adjusts itself to the varying nature of the wireless channel. Furthermore, we derive the optimal value of the inner radius at which the total throughput of the inner users of the home cell is as close as possible to the total throughput of its outer users. Simulation results show that the proposed adaptive approach has better total throughput of both home cell and all 19 cells than the counterparts of strict FFR, even when all cells are fully loaded, where other algorithms in the literature failed to outperform strict FFR. The improved throughput means that higher spectral efficiency can be achieved; i.e., the spectrum, which is the most precious resource in wireless communication, can be utilized efficiently. In addition, the proposed algorithm can provide significant power saving, that can reach 50% compared to strict FFR, while not penalizing the throughput performance.
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