• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4748-4765
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• 2016

We consider a virtualized cognitive radio (CR) network, where multiple virtual network operators (VNOs) who own different virtual cognitive base stations (VCBSs) share the same physical CBS (PCBS) which is owned by an infrastructure provider (InP), sharing the spectrum with the primary user (PU). The uplink scenario is considered where the secondary users (SUs) transmit to the VCBSs. The PU is protected by constraining the interference power from the SUs. Such constraint is applied by the InP through pricing the interference. A Stackelberg game is formulated to jointly maximize the revenue of the InP and the individual utilities of the VNOs, and then the Stackelberg equilibrium is investigated. Specifically, the optimal interference price and channel allocation for the VNOs to maximize the revenue of the InP and the optimal power allocation for the SUs to maximize the individual utilities of the VNOs are derived. In addition, a low‐complexity ±‐optimal solution is also proposed for obtaining the interference price and channel allocation for the VNOs. Simulations are provided to verify the proposed strategies. It is shown that the proposed strategies are effective in resource allocation and the ±‐optimal strategy achieves practically the same performance as the optimal strategy can achieve. It is also shown that the InP will not benefit from a large interference power limit, and selecting VNOs with higher unit rate utility gain to share the resources of the InP is beneficial to both the InP and the VNOs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10A
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• pp.1023-1033
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• 2007

This study considers a joint congestion control, routing and power control for energy-constrained wireless networks. A mathematical model is introduced which includes maximization of network utility, maximization of network lifetime, and trade-off between network utility and network lifetime. The framework would maximize the overall throughput of the network where the overall throughput depends on the data flow rates which in turn is dependent on the link capacities. The link capacity on the other hand is a function of transmit power levels and link Signal-to-Interference-plus-Noise-Ratio (SINR) which makes the power allocation problem inherently difficult to solve. Using dual decomposition techniques, subgradient method, and logarithmic transformations, a joint algorithm for rate and power allocation problems was formulated. Numerical examples for each optimization problem were also provided.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.173-181
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• 2010

In this paper, we propose a new resource allocation scheme for an OFDMA relay network with multicells. In the proposed scheme, by sharing the channel state information (CSI) between base stations, resources are allocated to users and relays to maximize the overall sum of the achievable rate under fairness constraints. In order to reduce the computational complexity, a resource allocation scheme is proposed by separating subcarrier allocation and power allocation into two parts. First of all, by considering inter-cell interference (ICI), a subcarrier is allocated to a user-relay pair, and power is allocated relays. Simulation results show that the proposed scheme achieves higher spectral efficiency per subcarrier than the static scheme and reduces the outage probability compared to the static and greedy schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2233-2252
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• 2018

For the problem of cross-layer joint resource allocation (JRA) in the Long-Term Evolution (LTE)-Advanced standard using carrier aggregation (CA) technology, it is difficult to obtain the optimal resource allocation scheme. This paper proposes a joint resource allocation algorithm based on the weights of user's average quality of experience (JRA-WQOE). In contrast to prevalent algorithms, the proposed method can satisfy the carrier aggregation abilities of different users and consider user fairness. An optimization model is established by considering the user quality of experience (QoE) with the aim of maximizing the total user rate. In this model, user QoE is quantified by the mean opinion score (MOS) model, where the average MOS value of users is defined as the weight factor of the optimization model. The JRA-WQOE algorithm consists of the iteration of two algorithms, a component carrier (CC) and resource block (RB) allocation algorithm called DABC-CCRBA and a subgradient power allocation algorithm called SPA. The former is used to dynamically allocate CC and RB for users with different carrier aggregation capacities, and the latter, which is based on the Lagrangian dual method, is used to optimize the power allocation process. Simulation results showed that the proposed JRA-WQOE algorithm has low computational complexity and fast convergence. Compared with existing algorithms, it affords obvious advantages such as improving the average throughput and fairness to users. With varying numbers of users and signal-to-noise ratios (SNRs), the proposed algorithm achieved higher average QoE values than prevalent algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1277-1282
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• 2016

In the next generation wireless communication systems, an energy harvesting from radio frequency signals is considered as a method to solve the lack of power supply problem for sensors. In this paper, we try to propose an efficient algorithm for simultaneous wireless information and power transfer in energy harvesting networks with channel estimation error. At first, we find an optimal channel training interval using one-dimensional exhaustive search, and estimate a channel using MMSE channel estimator. Based on the estimated channel, we propose a power allocation and splitting algorithm for maximizing the data rate while guaranteeing the minimum required harvested energy constraint, The simulation results confirm that the proposed algorithm has an insignificant performance degradation less than 10%, compared with the optimal scheme which assumes a perfect channel estimation, but it can improve the data rate by more than 20%, compared to the conventional scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2949-2963
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• 2019

A novel distributed compress-and-forward (CF) system based on multi-relay network is presented. In this system, as the direct link between the source and destination is invalid due to some reasons, such as the limited power, special working environment, or even economic factors, relays are employed to receive analog signals and carry on distributed compressed encoding. Subsequently, the digital signals are transmitted to the destination via wireless channel. Moreover, a theoretical analysis for the system is provided by utilizing the Chief Executive Officer (CEO) theory and Shannon channel capacity theory, and the rate-distortion function as well as the connection between the transmission rate and the channel capacity are constructed. In addition, an optimal signal-to-noise ratio (SNR) -based power allocation method is proposed to maximize the quantization SNR under the limited total power. Simulation result shows that the proposed CF system outperforms the amplify-and-forward (AF) system versus the SNR performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9A
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• pp.998-1004
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• 2004

In this paper we propose a discrete bit-loading algorithm that maximizes the transmit bit rate using the channel information. to optimize the performance of the very high-speed digital subscriber line(VDSL) system under the constraint of a maximum transmit power for each user. When the power level of crosstalk is high, the power allocation of a user changes the crosstalk experienced by the other users in the same binder. In this case, the performance of DSL modems can be improved by jointly considering the bit and power allocation of all users Simulation results shows that the proposed method improves the performance compared With that of iterative water-filling method.

• Korean Management Science Review
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• v.29 no.1
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• pp.153-168
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• 2012

Order allocation is one of the most important decision-making problems of firms having significant influences on performances of themselves and the whole supply chain. Existing researches about order allocation have mainly focused on evaluating capabilities of directly connected suppliers so that it is hard to consider effects and interactions from undirected connections over multiple lower-layers. To alleviate the limitation, this paper proposed a novel approach to order allocation using structural hole. By applying the concept of structural hole to the supply network, we could evaluate the structural supplying powers of firms with respect to both of direct and indirect connections. In the proposed approach, we derived a methodology to measure the potential supplying power of each firm by modifying the effective size as one of the measurements of structural hole and then, proposed its application, the structural hole based order allocation strategy. Furthermore, we conducted the agent based modeling of supply chain to perform the decision-making process of order allocation and simulated the proposed strategy. As a results, by coping with the variance of demand more stably, it could improve the performance of supply chain from the aspects of fill rate, inventory level and demand-supply balance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1057-1073
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• 2015

In this paper, we consider cooperative D2D communications in cellular networks. More precisely, a cellular user leases part of its spectrum to facilitate the D2D communication with a goal of improving the energy efficiency of a D2D pair. However the D2D pair is untrusted to the cellular user, such resource sharing may result in the information of this cellular user unsecured. In order to motivate the cellular user's generosity, this D2D pair needs to help the cellular user maintain a target secrecy rate. To address this issue, we formulate a joint spectrum and power allocation problem to maximize the energy efficiency of the D2D communication while guaranteeing the physical layer security of the cellular user. Then, a theorem is proved to indicate the best resource allocation strategy, and accordingly, an algorithm is proposed to find the best solution to this resource allocation problem. Numerical results are finally presented to verify the validity and effectiveness of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1733-1751
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• 2015

The IEEE 802.15.4 standard not only provides a maximum of seven guaranteed time slots (GTSs) for allocation within a superframe to support time-critical traffic, but also achieves ultralow complexity, cost, and power in low-rate and short-distance wireless personal area networks (WPANs). Real-time wireless body area sensor networks (WBASNs), as a special purpose WPAN, can perfectly use the IEEE 802. 15. 4 standard for its wireless connection. In this paper, we propose an adaptive GTS allocation scheme for real-time WBASN data transmissions with different priorities in consideration of low latency, fairness, and bandwidth utilization. The proposed GTS allocation scheme combines a weight-based priority assignment algorithm with an innovative starvation avoidance scheme. Simulation results show that the proposed method significantly outperforms the existing GTS implementation for the traditional IEEE 802.15.4 in terms of average delay, contention free period bandwidth utilization, and fairness.