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Abstract-In this paper, we propose a generalized code index modulation (CIM) technique for direct sequence-spread spectrum (DS-SS) communication. In particular, at the transmitter, the bit stream is divided into blocks in which each block is divided into two sub-blocks, named as mapped and modulated sub-block. Thereafter, the bits within the mapped sub-block are used to select one of the predefined spreading codes, which is then used to spread the modulated bits of the second sub-block. In this design, the use of the spreading code index as an information-bearing unit increases the overall spectral efficiency of this system. At the receiver side, the spreading code index is first estimated, thus resulting in a direct estimation of mapped sub-block bits. Consequently, the corresponding spreading code to this estimated index is used to de-spread the modulated symbol of the modulated sub-block. Subsequently, mathematical expressions for bit error rate, symbol error rate, throughput, energy efficiency, and the system complexity are derived to analyze the system performance. Finally, simulation results show that the proposed modulation scheme can achieve higher data rate than the conventional DS-SS system, with lower energy consumption and complexity.
Abstract. Author name ambiguity is one of the problems that decrease the quality and reliability of information retrieved from digital libraries. Existing methods have tried to solve this problem by predefining a feature set based on expert's knowledge for a specific dataset. In this paper, we propose a new approach which uses deep neural network to learn features automatically for solving author name ambiguity. Additionally, we propose the general system architecture for author name disambiguation on any dataset. We evaluate the proposed method on a dataset containing Vietnamese author names. The results show that this method significantly outperforms other methods that use predefined feature set. The proposed method achieves 99.31% in terms of accuracy. Prediction error rate decreases from 1.83% to 0.69%, i.e., it decreases by 1.14%, or 62.3% relatively compared with other methods that use predefined feature set (Table 3).
Most of the research in spectrum sharing has neglected the effect of interference from primary users. In this reported work, the performance of spectrum sharing amplify-and-forward relay networks under interference-limited environment, where the interference induced by the transmission of primary networks is taken into account, is investigated. In particular, a closed-form expression tight lower bound of outage probability is derived. To reveal additional insights into the effect of primary networks on the diversity and array gains, an asymptotic expression is also obtained.Introduction: Spectrum sharing relay networks have recently attracted much attention for providing higher reliability over direct transmission under scarce and limited spectrum conditions [1 -4]. Specifically, the performance of decode-and-forward (DF) relay networks in spectrum sharing environments has been reported [1 -3]. Recently, we have investigated the outage probability (OP) for spectrum sharing networks with amplify-and-forward (AF) relaying [4]. It has been shown in [1][2][3][4] that utilising DF/AF relaying significantly enhances system performance in such constrained transmission power conditions. However, most of the previous works have neglected the effect of the primary transmitter (PU-Tx), which significantly deteriorates the performance of the secondary network. In this Letter, to evaluate this interference effect, we derive a closed-form expression for OP and further calculate an asymptotic expression. We show that under fixed interference from primary networks, the diversity order remains unchanged and the loss only occurs in the array gain, which is theoretically quantified. However, when the interference is linearly proportional to the signal-to-noise ratio (SNR) of the secondary network, the system is severely affected, leading to an irreducible error floor of OP.
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