• 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.

• ETRI Journal
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• v.36 no.4
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• pp.519-527
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• 2014

An integrated multi-beam satellite and multi-cell terrestrial system is an attractive means for highly efficient communication due to the fact that the two components (satellite and terrestrial) make the most of each other's resources. In this paper, a terrestrial component reuses a satellite's resources under the control of the satellite's network management system. This allows the resource allocation for the satellite and terrestrial components to be coordinated to optimize spectral efficiency and increase overall system capacity. In such a system, the satellite resources reused in the terrestrial component may bring about severe interference, which is one of the main factors affecting system capacity. Under this consideration, the objective of this paper is to achieve an optimized resource allocation in both components in such a way as to minimize any resulting inter-component interference. The objective of the proposed scheme is to mitigate this inter-component interference by optimizing the total transmission power - the result of which can lead to an increase in capacity. The simulation results in this paper illustrate that the proposed scheme affords a more energy-efficient system to be implemented, compared to a conventional power management scheme, by allocating the bandwidth uniformly regardless of the amount of interference or traffic demand.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.784-795
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• 2016

In this paper, we investigate the resource allocation problem in time-varying heterogeneous wireless networks (HetNet) with multi-homing user equipments (UE). The stochastic optimization model is employed to maximize the network utility, which is defined as the difference between the HetNet's throughput and the total energy consumption cost. In harmony with the hierarchical architecture of HetNet, the problem of stochastic optimization of resource allocation is decomposed into two subproblems by the Lyapunov optimization theory, associated with the flow control in transport layer and the power allocation in physical (PHY) layer, respectively. For avoiding the signaling overhead, outdated dynamic information, and scalability issues, the distributed resource allocation method is developed for solving the two subproblems based on the primal-dual decomposition theory. After that, the adaptive resource allocation algorithm is developed to accommodate the timevarying wireless network only according to the current network state information, i.e. the queue state information (QSI) at radio access networks (RAN) and the channel state information (CSI) of RANs-UE links. The tradeoff between network utility and delay is derived, where the increase of delay is approximately linear in V and the increase of network utility is at the speed of 1/V with a control parameter V. Extensive simulations are presented to show the effectiveness of our proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.288-307
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• 2013

This paper formulates resource allocation for decode-and-forward (DF) relay assisted multi-cell orthogonal frequency division multiple (OFDM) networks as an optimization problem taking into account of inter-cell interference and users fairness. To maximize the transmit rate of system we propose a joint interference coordination, subcarrier and power allocation algorithm. To reduce the complexity, this semi-distributed algorithm divides the primal optimization into three sub-optimization problems, which transforms the mixed binary nonlinear programming problem (BNLP) into standard convex optimization problems. The first layer optimization problem is used to get the optimal subcarrier distribution index. The second is to solve the problem that how to allocate power optimally in a certain subcarrier distribution order. Based on the concept of equivalent channel gain (ECG) we transform the max-min function into standard closed expression. Subsequently, with the aid of dual decomposition, water-filling theorem and iterative power allocation algorithm the optimal solution of the original problem can be got with acceptable complexity. The third sub-problem considers dynamic co-channel interference caused by adjacent cells and redistributes resources to achieve the goal of maximizing system throughput. Finally, simulation results are provided to corroborate the proposed algorithm.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.6
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• pp.350-356
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• 2013

Single Carrier Frequency Domain Multiple Access (SC-FDMA) has proven to be the best long term evolution for uplink multiple access because of its low Peak to Average Power Ratio (PAPR), a feature that leads to low power consumption. This is achievable only if the resource allocation is performed in a contiguous manner. This paper proposes a new approach with an improvement in the global resources allocation. The new approach presented utilizes the gain function, which adopts some of the procedures deduced from the older Recursive Maximum Expansion (RME) algorithm. The experiment proved that the new approach is better than the original RME algorithms and in most cases, is closer to the optimal solution.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.565-581
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• 2019

This paper investigates the wireless powered two way relay network (WPTWRN), where two single-antenna users and one single-antenna relay firstly harvest energy from signals emitted by a multi-antenna power beacon (PB) and then two users exchange information with the help of the relay by using their harvested energies. In order to improve the energy transfer efficiency, energy beamforming at the PB is deployed. For such a network, to explore the performance limit of the presented WPTWRN, an optimization problem is formulated to obtain the achievable rate region bounds by jointly optimizing the time allocation and energy beamforming design. As the optimization problem is non-convex, it is first transformed to be a convex problem by using variable substitutions and semidefinite relaxation (SDR) and then solve it efficiently. It is proved that the proposed method achieves the global optimum. Simulation results show that the achievable rate region of the presented WPTWRN architecture outperforms that of wireless powered one way relay network architecture. Results also show that the relay location has significant impact on achievable rate region of the WPTWRN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4819-4834
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• 2015

The spectral efficiency of cellular networks can be improved when proximate users engage in device-to-device (D2D) communications to communicate directly without going through a base station. However, D2D communications that are not properly designed may generate interference with existing cellular networks. In this paper, we study resource allocation and power control to minimize the probability of an outage and maximize the overall network throughput. We investigate three power control-based schemes: the Partial Co-channel based Overlap Resource Power Control (PC.OVER), Fractional Frequency Reuse based Overlap Resource Power Control (FFR.OVER) and Fractional Frequency Reuse based Adaptive Power Control (FFR.APC) and also compare their performance. In PC.OVER, a certain portion of the total bandwidth is dedicated to the D2D. The FFR.OVER and FFR.APC schemes combine the FFR techniques and the power control mechanism. In FFR, the entire frequency band is partitioned into two parts, including a central and edge sub-bands. Macrocell users (mUEs) transmit using uniform power in the inner and outer regions of the cell, and in all three schemes, the D2D receivers (D2DRs) transmit with low power when more than one D2DRs share a resource block (RB) with the macrocells. For PC.OVER and FFR.OVER, the power of the D2DRs is reduced to its minimum, and for the FFR.APC scheme, the transmission power of the D2DRs is iteratively adjusted to satisfy the signal to interference ratio (SIR) threshold. The three schemes exhibit a significant improvement in the overall system capacity as well as in the probability of a user outage when compared to a conventional scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1325-1344
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• 2019

Recently, to satisfy mobile users' increasing data transmission requirement, energy efficiency (EE) resource allocation in distributed antenna systems (DASs) has become a hot topic. In this paper, we aim to maximize EE in DASs subject to constraints of the minimum data rate requirement and the maximum transmission power of distributed antenna units (DAUs) with different density distributions. Virtual cell is defined as DAUs selected by the same user equipment (UE) and the size of virtual cells is dependent on the number of subcarriers and the transmission power. Specifically, the selection rule of DAUs is depended on different scenarios. We develop two scenarios based on the density of DAUs, namely, the sparse scenario and the dense scenario. In the sparse scenario, each DAU can only be selected by one UE to avoid co-channel interference. In order to make the original non-convex optimization problem tractable, we transform it into an equivalent fractional programming and solve by the following two sub-problems: optimal subcarrier allocation to find suitable DAUs; optimal power allocation for each subcarrier. Moreover, in the dense scenario, we consider UEs could access the same channel and generate co-channel interference. The optimization problem could be transformed into a convex form based on interference upper bound and fractional programming. In addition, an energy-efficient DAU selection scheme based on the large scale fading is developed to maximize EE. Finally, simulation results demonstrate the effectiveness of the proposed algorithm for both sparse and dense scenarios.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1095-1104
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• 2008

In multiuser OFDM systems, subcarrier and bit allocation plays an important role for the efficient resource use. However, in multiuser adaptive allocation as a non-linear problem, it is impractical to compute all to get the best solution because of the complexity. We set the goal of minimizing the transmit power while satisfying the BER and minimum bits required to transmit through the highest fitness combination of subcarriers and users. The proposed improved genetic algorithm employs the diversity of adaptive allocation more than existing genetic algorithm. Therefore, from the numerical simulation results, we find that the proposed heuristic algorithm has more performance than the existing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.2047-2066
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• 2024

In order to improve the coverage and achieve massive spectrum access, non-orthogonal multiple access (NOMA) technology is applied in millimeter wave massive multiple-input multiple-output (mMIMO) communication network. However, the power assumption of active sensors greatly limits its wide applications. Recently, Intelligent Reconfigurable Surface (IRS) technology has received wide attention due to its ability to reduce power consumption and achieve passive transmission. In this paper, spectral efficiency maximum problem in the millimeter wave mMIMO-NOMA system with IRS is considered. The sparse RF chain antenna structure is designed at the base station based on continuous phase modulation. Furthermore, a joint optimization problem for power allocation, power splitting, analog precoding and IRS reconfigurable matrices are constructed, which aim to achieve the maximum spectral efficiency of the system under the constraints of user's quality of service, minimum energy harvesting and total transmit power. A three-stage iterative algorithm is proposed to solve the above mentioned non-convex optimization problems. We obtain the local optimal solution by fixing some optimization parameters firstly, then introduce the relaxation variables to realize the global optimal solution. Simulation results show that the spectral efficiency of the proposed scheme is superior compared to the conventional system with phase shifter modulation. It is also demonstrated that IRS can effectively assist mmWave communication and improve the system spectral efficiency.