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Shuang Liang,Shouyi Yang,Wanming Hao,Bing Ning 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.3
In this study, energy-efficient (EE) resource allocation in orthogonal frequency division multiplexing-based cognitive radio networks with imperfect spectrum sensing is investigated. We present a new EE model by considering the sensing errors. Optimizing such an EE expression saves valuable resources, such as battery life, by selectively allocating power to underutilized subcarriers, and also achieves EE gain compared with general EE expression. Given that the primary user’s interference tolerance can be defined as either the Peak Interference Power (PIP) constraint or Average Interference Power (AIP) constraint for all subchannels, we compare the EE performance for the two interference power constraints. Finally, we propose an optimal EE resource allocation scheme based on the quasiconcave relation between the EE and transmit power. Simulations show that the new EE design improves EE compared with the conventional EE design, and the EE is higher with AIP constraint than that with PIP constrain under certain interference power.
( Bing Ning ),( Shouyi Yang ),( Xiaomin Mu ),( Yanhui Lu ),( Wanming Hao ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.11
The energy-efficient design of sensing-based spectrum sharing of a multi-input and multi-output (MIMO) cognitive radio (CR) system with imperfect multiple antenna spectrum sensing is investigated in this study. Optimal resource allocation strategies, including sensing time and power allocation schemes, are studied to maximize the energy efficiency (EE) of the secondary base station under the transmit power and interference power constraints. EE problem is formulated as a nonlinear stochastic fractional programming of a nonconvex optimal problem. The EE problem is transformed into its equivalent nonlinear parametric programming and solved by one-dimension search algorithm. To reduce searching complexity, the search range was founded by demonstration. Furthermore, simulation results confirms that an optimal sensing time exists to maximize EE, and shows that EE is affected by the spectrum detection factors and corresponding constraints.
( Aihua Zhang ),( Shouyi Yang ),( Jianjun Li ),( Chunlei Li ),( Zhoufeng Liu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.8
We investigate the channel state information (CSI) in multi-input multi-output (MIMO) cooperative networks that employ the amplify-and-forward transmission scheme. Least squares and expectation conditional maximization have been proposed in the system. However, neither of these two approaches takes advantage of channel sparsity, and they cause estimation performance loss. Unlike linear channel estimation methods, several compressed channel estimation methods are proposed in this study to exploit the sparsity of the MIMO cooperative channels based on the theory of compressed sensing. First, the channel estimation problem is formulated as a compressed sensing problem by using sparse decomposition theory. Second, the lower bound is derived for the estimation, and the MIMO relay channel is reconstructed via compressive sampling matching pursuit algorithms. Finally, based on this model, we propose a novel algorithm so called sparsity adaptive expectation maximization (SAEM) by using Kalman filter and expectation maximization algorithm so that it can exploit channel sparsity alternatively and also track the true support set of time-varying channel. Kalman filter is used to provide soft information of transmitted signals to the EM-based algorithm. Various numerical simulation results indicate that the proposed sparse channel estimation technique outperforms the previous estimation schemes.
Relay Selection Fairness and Resource Allocation for OFDMA Networks
Jingran Huang,Fang Wang,Shouyi Yang 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.6
In this paper, resource allocation for a relay-based multi-user Orthogonal Frequency-Division Multiple Access (OFDMA) uplink system is studied. All the relays adopt the decode-and-forward protocol and assist the transmission from the source to destination. In current wireless networks, the terminal depends more on battery power. Given that, battery life is limited, prolonging the service life of equipment is a key problem in ensuring the information transmission and in reducing the financial burden of the batteries. We aim to maximize the survival time of the relay system and to reduce the rate of loss. Therefore, we formulate the problem in which the subcarriers select the optimal relay based on both the channel gain and the residual capacity of the relays. We also consider a weighting factor that reflects the residual capacity of different relays. Simulation results show that the proposed algorithms can achieve longer survival time of the relay systems.
Design and Analysis of a Novel 16/10 Segmented Rotor SRM for 60V Belt-Driven Starter Generator
Xiaodong Sun,Zhengwang Xue,Shouyi Han,Xing Xu,Zebin Yang,Long Chen 한국자기학회 2016 Journal of Magnetics Vol.21 No.3
This paper proposes a novel 16/10 segmented rotor switched reluctance motor (SSRM) for belt-driven starter generators (BSGs). Different from conventional SRMs, the stator of the proposed SSRM consists of two types of stator poles, i.e., exciting and auxiliary poles, and the rotor is constructed from a series of discrete segments. The topology and operation principle of this proposed SSRM are illustrated firstly, and then the design rules are listed. In addition, the finite element method (FEM) is employed to get the static and dynamic characteristics of the proposed SSRM. Finally, the simulation results are presented to show the validity of the proposed SSRM for BSGs.
Energy Efficiency Optimization for multiuser OFDM-based Cognitive Heterogeneous networks
( Bing Ning ),( Aihua Zhang ),( Wanming Hao ),( Jianjun Li ),( Shouyi Yang ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.6
Reducing the interference to the licensed mobile users and obtaining the energy efficiency are key issues in cognitive heterogeneous networks. A corresponding rate loss constraint is proposed to be used for the sensing-based spectrum sharing (SBSS) model in cognitive heterogeneous networks in this paper. Resource allocation optimization strategy is designed for the maximum energy efficiency under the proposed interference constraint together with average transmission power constraint. An efficiency algorithm is studied to maximize energy efficiency due to the nonconvex optimal problem. Furthermore, the relationship between the proposed protection criterion and the conventional interference constraint strategy under imperfect sensing condition for the SBSS model is also investigated, and we found that the conventional interference threshold can be regarded as the upper bound of the maximum rate loss that the primary user could tolerate. Simulation results have shown the effectiveness of the proposed protection criterion overcome the conventional interference power constraint.