• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2086-2097
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• 2012

A terminal-based dynamic clustering algorithm is proposed in a multi-cell scenario, where the user could select the cooperative BSs from the predetermined static base stations (BSs) set based on dynamic channel condition. First, the user transmission rate is derived based on linear precoding and per-cell feedback scheme. Then, the dynamic clustering algorithm can be implemented based on two criteria: (a) the transmission rate should meet the user requirement for quality of service (QoS); (b) the rate increment exceeds the predetermined constant threshold. By adopting random vector quantization (RVQ), the optimized number of cooperative BSs and the corresponding channel conditions are presented respectively. Numerical results are given and show that the performance of the proposed method can improve the system resources utilization effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1828-1847
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• 2014

Coordinated multi-point (CoMP) transmission has been regarded as a potential technology for LTE-Advanced. In frequency division duplexing systems, channel quantization is applied for reporting channel state information (CSI). Considering the dynamic number of cooperation base stations (BSs), asymmetry feature of CoMP channels and high searching complexity, simply increasing the size of the codebook used in traditional multiple antenna systems to quantize the global CSI of CoMP systems directly is infeasible. Per-cell codebook based channel quantization to quantize local CSI for each BS separately is an effective method. In this paper, the theoretical upper bounds of system throughput are derived for two codeword selection schemes, independent codeword selection (ICS) and joint codeword selection (JCS), respectively. The feedback overhead and selection complexity of these two schemes are analyzed. In the simulation, the system throughput of ICS and JCS is compared. Both analysis and simulation results show that JCS has a better tradeoff between system throughput and feedback overhead. The ICS has obvious advantage in complexity, but it needs additional phase information (PI) feedback for obtaining the approximate system throughput with JCS. Under the same number of feedback bits constraint, allocating the number of bits for channel direction information (CDI) and PI quantization can increase the system throughput, but ICS is still inferior to JCS. Based on theoretical analysis and simulation results, some recommendations are given with regard to the application of each scheme respectively.

• Journal of Life Science
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• v.27 no.10
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• pp.1225-1231
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• 2017

Disruptive expression patterns of the circadian clock genes are highly associated with many human diseases, including cancer. Cell cycle and proliferation is linked to a circadian rhythm; therefore, abnormal clock gene expression could result in tumorigenesis and malignant development. The molecular network of the circadian clock is based on transcriptional and translational feedback loops orchestrated by a variety of clock activators and clock repressors. The expression of 10~15% of the genome is controlled by the overall balance of circadian oscillation. Among the many clock genes, Period 1 (Per1) and Period 2 (Per2) are clock repressor genes that play an important role in the regulation of normal physiological rhythms. It has been reported that PER1 and PER2 are involved in the expression of cell cycle regulators including cyclins, cyclin-dependent kinases (CDKs), and CDK inhibitors. In addition, correlation of the down-regulation of PER1 and PER2 with development of many cancer types has been revealed. In this review, we focused on the molecular function of PER1 and PER2 in the circadian clock network and the transcriptional and translational targets of PER1 and PER2 involved in cell cycle and tumorigenesis. Moreover, we provide information suggesting that PER1 and PER2 could be promising therapeutic targets for cancer therapies and serve as potential prognostic markers for certain types of human cancers.