• ETRI Journal
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• v.42 no.6
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• pp.846-858
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• 2020

The non-orthogonal multiple access (NOMA) technique offers throughput improvement to meet the demands of the future generation of wireless communication networks. The objective of this work is to further improve the throughput by including an underlay cognitive radio network with an existing multi-carrier NOMA network, using cooperative communication. The throughput is maximized by optimal resource allocation, namely, power allocation, subcarrier assignment, relay selection, user pairing, and subcarrier pairing. Optimal power allocation to the primary and secondary users is accomplished in a way that target rate constraints of the primary users are not affected. The throughput maximization is a combinatorial optimization problem, and the computational complexity increases as the number of users and/or subcarriers in the network increases. To this end, to reduce the computational complexity, a dynamic network resource allocation algorithm is proposed for combinatorial optimization. The simulation results show that the proposed network improves the throughput.

• ETRI Journal
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• v.38 no.1
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• pp.62-69
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• 2016

In this paper, we propose two novel user selection algorithms for multiuser multiple-input and multiple-output downlink wireless systems, in which both a base station (BS) and mobile stations (MSs) are equipped with multiple antennas. Linear transmit beamforming at the BS and receive combining at the MSs are used to avoid interference between users and find a better sum-rate capacity performance. An optimal technique for selecting users would entail an exhaustive search, which in practice becomes computationally complex for a realistic number of users. Suboptimal algorithms with low complexity are proposed for a coordinated beamforming scheme. Simulation results show that the performance of the proposed algorithms is better than that provided by previous algorithms and is very close to an optimal approach with reduced complexity.

• Journal of electromagnetic engineering and science
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• v.12 no.1
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• pp.1-7
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• 2012

In this paper, we investigated the throughput of a cognitive radio network where two primary frequency channels (PCs) are sensed and opportunistically accessed by N secondary users. The sharing sensing member (SSM) protocol is introduced to sense both PCs simultaneously. According to the SSM protocol, N SUs (Secondary User) are divided into two groups, which allows for the simultaneous sensing of two PCs. With a frame structure, after determining whether the PCs are idle or active during a sensing slot, the SUs may use the remaining time to transmit their own data. The throughput of the network is formulated as a convex optimization problem. We then evaluated an iterative algorithm to allocate the optimal sensing time, fusion rule and the number of members in each group. The computer simulation and numerical results show that the proposed optimal allocation improves the throughput of the SU under a misdetection constraint to protect the PCs. If not, its initial date of receipt shall be nullified.

• Journal of Industrial Convergence
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• v.17 no.4
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• pp.131-137
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• 2019

In infrastructure wireless mesh networks (WMNs), in order to improve mobile users' satisfaction for the given cache hit ratio, we investigate an User centric Cache Allocation (UCA) scheme while reducing cache cost in a mesh router (MR) and expected transmission time (ETT) for content search in cache. To minimize ETT values of mobile users, a genetic algorithm based UCA (GA-UCA) scheme is provided. The goal is to maximize mobile users' satisfaction via our well defined utility, which considers content popularity and the number of mobile users. Finally, through solving optimization problem we show the optimal cache can be allocated for UCA and GA-UCA. Besides, a WMN provider can find the optimal number of mobile users for user centric cache allocation in infrastructure WMNs.

• Journal of Advanced Navigation Technology
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• v.17 no.5
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• pp.506-515
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• 2013

In cognitive radio networks, several research works typically address the framework which consists of a spectrum sensing period and a data transmission period. When the frame period is short, there is the problem that the throughput of secondary users decrease. In this paper, aggregated data slot structure is considered to increase the throughput of secondary users. Chapman-Kolmogorov equation is used for the modeling of the transmission probability of primary users and formulation of an optimization problem to maximize the throughput of secondary users. Solution of the optimization problem results in the optimal spectrum sensing time, the length of data slot and the number of data slots governed by a spectrum sensing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.175-186
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• 1996

An optimal channel input-traffic control (OCIC) policy is proposed for slotted frequency-hopped spread-spectrum multiple access communication systems. When the number of channel input packets is set to the optimal number, the conditional throughput for the OCIC policy is analyzed. The state transition probability is derived, the steady state performance is analyzed, and the mean pracket delay is obtained. It is shown that the mean packet delay decreases considerably when the priority of transmission is given to backlogged users. The smaller is the number of requency slots, the larger are the differences between the preformance of the OCIC policy and that of the other policies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.77-82
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• 2015

Recently, multi-user massive MIMO (MU-Massive MIMO) network has attracted a lot of attention as a technology to accommodate explosively increasing mobile data traffic. However, the MU-Massive MIMO network causes a tremendous hardware complexity in a base station and computational complexity to select optimal set of users. In this paper, we thus propose a simple algorithm for selecting antennas and users while reducing the hardware and computational complexities simultaneously. The proposed scheme has a computational complexity of $O((N-S_a+1){\times}min(S_a,K))$, which is significantly reduced compared to the complexity of optimal scheme based on Brute-Force searching, $$O\left({_N}C_S_a\sum_{i=1}^{min(S_a,K)}_KC_i\right)$$, where N, $S_a$, and K denote the number of total transmit antennas, the number of selected antennas, and the number of all users, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1102-1112
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• 2012

We propose a cell selection and resource allocation scheme that assigns users to nearby accessible cells in heterogeneous wireless networks consisting of macrocell, femtocells, and Wi-Fi access points, under overload situation. Given the current power level of all accessible cells nearby users, the proposed scheme finds all possible cell assignment mappings of which user should connect to which cell to maximize the number of users that the network can accommodate at the same time. We formulate the cell selection problem with heterogeneous cells into an optimization problem of binary integer programming, and compute the optimal solution. We evaluate the proposed algorithm in terms of network access failure compared to a local ad-hoc based cell selection scheme used in practical systems using network level simulations. We demonstrate that our cell selection algorithm dramatically reduces network access failure in overload situation by fully leveraging network resources evenly across heterogeneous networks. We also validate the practical feasibility in terms of computational complexity of our binary integer program by measuring the computation time with respect to the number of users.

• Journal of electromagnetic engineering and science
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• v.11 no.2
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• pp.71-75
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• 2011

The sum-rate maximization rule can find an optimal user set that maximizes the sum capacity in multiple input multiple output (MIMO) broadcast channels (BCs), but the search space for finding the optimal user set becomes prohibitively large as the number of users increases. The proposed algorithm selects a user set of the largest effective channel norms based on statistical channel state information (CSI) for reducing the computational complexity, and uses Tomlinson-Harashima precoding (THP) for minimizing the interference between selected users in time-varying MIMO BCs.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.688-698
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• 2016

In this paper, we investigate the achievable sum rate and energy efficiency of downlink massive multiple-input multiple-output antenna systems with zero-forcing precoding, by taking into account the randomness of user locations. Specifically, we propose two types of non-uniform user distributions, namely, center-intensive user distribution and edge-intensive user distribution. Based on these user distributions, we derive novel tight lower and upper bounds on the average sum rate. In addition, the impact of user distributions on the optimal number of users maximizing the sum rate is characterized. Moreover, by adopting a realistic power consumption model which accounts for the transmit power, circuit power and signal processing power, the energy efficiency of the system is studied. In particular, closed-form solutions for the key system parameters, such as the number of antennas and the optimal transmit signal-to-noise ratio maximizing the energy efficiency, are obtained. The findings of the paper suggest that user distribution has a significant impact on the system performance: for instance, the highest average sum rate is achieved with the center-intensive user distribution, while the lowest average sum rate is obtained with the edge-intensive user distribution. Also, more users can be served with the center-intensive user distribution.