• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3821-3841
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• 2019

Cloud radio access networks (C-RANs) have been regarded in recent times as a promising concept in future 5G technologies where all DSP processors are moved into a central base band unit (BBU) pool in the cloud, and distributed remote radio heads (RRHs) compress and forward received radio signals from mobile users to the BBUs through radio links. In such dynamic environment, automatic decision-making approaches, such as artificial intelligence based deep reinforcement learning (DRL), become imperative in designing new solutions. In this paper, we propose a generic framework of autonomous cell activation and customized physical resource allocation schemes for energy consumption and QoS optimization in wireless networks. We formulate the problem as fractional power control with bandwidth adaptation and full power control and bandwidth allocation models and set up a Q-learning model to satisfy the QoS requirements of users and to achieve low energy consumption with the minimum number of active RRHs under varying traffic demand and network densities. Extensive simulations are conducted to show the effectiveness of our proposed solution compared to existing schemes.

• 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.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.72-79
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• 2010

Device-to-device(D2D) links which share resources in a cellular network present a challenge in radio resource management due to the potentially severe interference they may cause to the cellular network. In this paper, a resource allocation scheme based on subset reuse methods is proposed to minimize the interference from the D2D links. We consider an adaptive group-wise subset reuse method to enhance the efficiency of frequency resource allocation for cellular and D2D links. A power optimization scheme is also proposed for D2D links if cellular links are interfered by adjacent D2D transmissions. The computer simulation results show that performance gain is obtained in link SINR, and total cell throughput increases as nearby traffic becomes more dominant.

• ETRI Journal
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• v.33 no.2
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• pp.184-193
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• 2011

Tailored for wireless local area networks, the present paper proposes a cross-layer resource allocation scheme for multiple-input multiple-output orthogonal frequency-division multiplexing systems. Our cross-layer resource allocation scheme consists of three stages. Firstly, the condition of sharing the subchannel by more than one user is studied. Secondly, the subchannel allocation policy which depends on the data packets' lengths and the admissible combination of users per subchannel is proposed. Finally, the bits and corresponding power are allocated to users based on a greedy algorithm and the data packets' lengths. The analysis and simulation results demonstrate that our proposed scheme not only achieves significant improvement in system throughput and average packet delay compared with conventional schemes but also has low computational complexity.

• 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.18 no.1
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• pp.211-232
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• 2024

In this paper, we consider the resource allocation and offloading decisions of device-to-device (D2D) cooperative UAV-assisted mobile edge computing (MEC) system, where the device with task request is served by unmanned aerial vehicle (UAV) equipped with MEC server and D2D device with idle resources. On the one hand, to ensure the fairness of time-delay sensitive devices, when UAV computing resources are relatively sufficient, an optimization model is established to minimize the maximum delay of device computing tasks. The original non-convex objective problem is decomposed into two subproblems, and the suboptimal solution of the optimization problem is obtained by alternate iteration of two subproblems. On the other hand, when the device only needs to complete the task within a tolerable delay, we consider the offloading priorities of task to minimize UAV computing resources. Then we build the model of joint offloading decision and power allocation optimization. Through theoretical analysis based on KKT conditions, we elicit the relationship between the amount of computing task data and the optimal resource allocation. The simulation results show that the D2D cooperation scheme proposed in this paper is effective in reducing the completion delay of computing tasks and saving UAV computing resources.

• Journal of IKEEE
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• v.10 no.2 s.19
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• pp.103-108
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• 2006

This paper proposed a low power resource allocation algorithm for the minimum switching activity of operators in high level synthesis. In this paper, the proposed method finds switching activity in circuit each functional unit exchange for binary sequence length and value bit are logic one value. To use the switching activity was found the allocation with minimal power consumption, the proposed method visits all control steps one by one and determines the allocation with minimal power consumption at each control step. As the existing method, the execution time can be fast according to use the number of operator and maximal control step. And it is the reduction effect from 8.5% to 9.3%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1825-1842
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• 2013

Rapid growth of the IT industry has led to significant energy consumption in the last decade. Data centers swallow an enormous amount of electrical energy and have high operating costs and carbon dioxide excretions. In response to this, the dynamic consolidation of virtual machines (VMs) allows for efficient resource management and reduces power consumption through the live migration of VMs in the hosts. Moreover, each client typically has a service level agreement (SLA), this leads to stipulations in dealing with energy-performance trade-offs, as aggressive consolidation may lead to performance degradation beyond the negotiation. In this paper we propose a heuristic based resource allocation of VM selection and a VM allocation approach that aims to minimize the total energy consumption and operating costs while meeting the client-level SLA. Our experiment results demonstrate significant enhancements in cloud providers' profit and energy savings while improving the SLA at a certain level.

• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.166-171
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• 2003

In this paper, we propose a minimal power data path allocation algorithm for low power circuit design. The proposed algorithm minimizes switching activity for input variables in scheduled CDFG. Allocations are further divided into the tasks of register allocation and module allocation. The register allocation algorithm execute that it eliminate spurious switching activity in functional unit and minimize the numbers of multiplexer. Also, resource allocation method selects a sequence of operations for a module such that the switching activity is reduced. Therefore, the algorithm executes to minimize the switching activity of input values, sequence of operations and number of multiplexer. Experimental results using benchmarks show that power is reduction effect from 13% to 17% power consumption, when compared with the Genesis-lp high-level synthesis system.