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Ni J.,Guilin University of Electronic Technology | Xiao H.,Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing | Xiao H.,China Mobile
Eurasip Journal on Wireless Communications and Networking | Year: 2016

In this paper, we present a game-theoretic approach to the problem of joint transmit beamforming and power control in cognitive radio (CR) multiple-input multiple-output broadcast channels (MIMO-BCs), where the primary users (PUs) coexist with the secondary users (SUs) and share the same spectrum. The cognitive base station (CBS) is equipped with multiantenna and transmits independent data streams to several decentralized single-antenna terminals. Our design goal is to jointly adjust the beamformers and transmission powers according to individual SINR (signal-to-interference-plus-noise ratio) requirements in order to meet SINR balancing for CR MIMO-BCs. In this context, two problems need to be solved: (1) the design beamforming must enable a balancing of the SINR among all SUs for a fixed total power of CBS and (2) the total transmission power must be minimized while satisfying a set of SINR constraints for fixed beamformers. The proposed approach is an application of separable games, where beamforming vectors are modeled as beamforming subgame and power control is modeled as power control subgame. We then use the convex theory of noncooperative game to solve the optimalization problem. Finally, we propose an iterative algorithm to reach Nash equilibrium (NE) of the joint beamforming subgame and power control subgame. Numerical results are provided to validate the optimality and the convergence of the proposed algorithm. © 2016, Ni and Xiao. Source


Gu L.,Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing | Gu L.,Nanjing University of Posts and Telecommunications
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

The locality sensitive k-means clustering has been proposed recently. However, it performance depends greatly on the choice of the initial centers and only proper initial centers enable this clustering approach to produce a better accuracies. In this paper, an evolutionary locality sensitive k-means clustering method is presented. This new approach uses the genetic algorithms for finding its initial centers by minimizing the Davies Bouldin clustering validity index regarded as the fitness function. To investigate the effective of our approach, some experiments are done on several datasets. Experimental results show that the proposed method can get the clustering performance significantly compared to other clustering algorithms. © 2013 Springer-Verlag Berlin Heidelberg. Source


Gu L.,Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing | Gu L.,Nanjing University of Posts and Telecommunications
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

Semi-supervised clustering can take advantage of some labeled data called seeds to bring a great benefit to the clustering of unlabeled data. This paper uses the seeding-based semi-supervised idea for a fuzzy clustering method inspired by diffusion processes, which has been presented recently. To investigate the effectiveness of our approach, experiments are done on three UCI real data sets. Experimental results show that the proposed algorithm can improve the clustering performance significantly compared to other semi-supervised clustering approaches. © 2013 Springer-Verlag Berlin Heidelberg. Source


Gu L.,Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing | Gu L.,Nanjing University of Posts and Telecommunications
Proceedings - 2012 International Conference on Control Engineering and Communication Technology, ICCECT 2012 | Year: 2012

The traditional one-class support vector machines problem can be transformed into solving the minimum enclose-ing ball problem by the use of the corset. In this paper, the notion of the corset is applied to a semi-supervised clustering using one-class support vector machines. Experimental results show that this proposed algorithm not only can maintain the clustering performance, but also can decrease the running time of the clustering method. © 2012 IEEE. Source


Li J.,South China Normal University | Chen P.,South China Normal University | Zhang H.,South China Normal University | Zhang H.,Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing | Zhang H.,Guangdong Provincial Engineering Research Center for Optoelectronic Instrument
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC | Year: 2015

This paper considers a wireless-energy-transfer (WET)-enabled massive multiple-input-multiple-output (MIMO) system based on superimposed pilot (SP). With the aid of SP, the uplink (UL) channel estimation and wireless information transmission (WIT) that powered by the downlink (DL) WET can be operated simultaneously, and thus provide the potential for improving the UL achievable rate. The impact that SP has on the performance of such a WET-enabled massive MIMO system is mathematically characterized, and the UL achievable throughput is maximized by optimizing the variables, including the SP power-allocation factor and the time-allocation factor between the duration of WET and WIT. Numerical results validate the effectiveness of the proposed scheme. © 2015 IEEE. Source

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