• 제목/요약/키워드: Power Allocation Optimization

검색결과 175건 처리시간 0.024초

Relaying Protocols and Delay Analysis for Buffer-aided Wireless Powered Cooperative Communication Networks

  • Zhan, Jun;Tang, Xiaohu;Chen, Qingchun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권8호
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    • pp.3542-3566
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    • 2018
  • In this paper, we investigate a buffer-aided wireless powered cooperative communication network (WPCCN), in which the source and relay harvest the energy from a dedicated power beacon via wireless energy transfer, then the source transmits the data to the destination through the relay. Both the source and relay are equipped with an energy buffer to store the harvested energy in the energy transfer stage. In addition, the relay is equipped with a data buffer and can temporarily store the received information. Considering the buffer-aided WPCCN, we propose two buffer-aided relaying protocols, which named as the buffer-aided harvest-then-transmit (HtT) protocol and the buffer-aided joint mode selection and power allocation (JMSPA) protocol, respectively. For the buffer-aided HtT protocol, the time-averaged achievable rate is obtained in closed form. For the buffer-aided JMSPA protocol, the optimal adaptive mode selection scheme and power allocation scheme, which jointly maximize the time-averaged throughput of system, are obtained by employing the Lyapunov optimization theory. Furthermore, we drive the theoretical bounds on the time-averaged achievable rate and time-averaged delay, then present the throughput-delay tradeoff achieved by the joint JMSPA protocol. Simulation results validate the throughput performance gain of the proposed buffer-aided relaying protocols and verify the theoretical analysis.

An Efficient Channel Selection and Power Allocation Scheme for TVWS based on Interference Analysis in Smart Metering Infrastructure

  • Huynh, Chuyen Khoa;Lee, Won Cheol
    • Journal of Communications and Networks
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    • 제18권1호
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    • pp.50-64
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    • 2016
  • Nowadays, smart meter (SM) technology is widely effectively used. In addition, power allocation (PA) and channel selection (CS) are considered problems with many proposed approaches. In this paper, we will suggest a specific scenario for an SM configuration system and show how to solve the optimization problem for transmission between SMs and the data concentrator unit (DCU), the center that collects the data from several SMs, via simulation. An efficient CS with PA scheme is proposed in the TV white space system, which uses the TV band spectrum. On the basic of the optimal configuration requirements, SMs can have a transmission schedule and channel selection to obtain the optimal efficiency of using spectrum resources when transmitting data to the DCU. The optimal goals discussed in this paper are the maximum capacity or maximum channel efficiency and the maximum allowable power of the SMs used to satisfy the quality of service without harm to another wireless system. In addition, minimization of the interference to the digital television system and other SMs is also important and needs to be considered when the solving coexistence scenario. Further, we propose a process that performs an interference analysis scheme by using the spectrum engineering advanced Monte Carlo analysis tool (SEAMCAT), which is an integrated software tool based on a Monte-Carlo simulation method. Briefly, the process is as follows: The optimization process implemented by genetic evolution optimization engines, i.e., a genetic algorithm, will calculate the best configuration for the SM system on the basis of the interference limitation for each SM by SEAMCAT in a specific configuration, which reaches the solution with the best defined optimal goal satisfaction.

Load Dispatching Control of Multiple-Parallel-Converters Rectifier to Maximize Conversion Efficiency

  • Orihara, Dai;Saitoh, Hiroumi;Higuchi, Yuji;Babasaki, Tadatoshi
    • Journal of Electrical Engineering and Technology
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    • 제9권3호
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    • pp.1132-1136
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    • 2014
  • In the context of increasing electric energy consumption in a data center, energy efficiency improvement is strongly emphasized. In a data center, electric energy is largely consumed by DC power supply system, which is based on a rectifier composed by multiple parallel converters. Therefore, rectifier efficiency must be improved for minimizing loss of DC power supply system. Rectifier efficiency can be modulated by load allocation to converters because converter efficiency depends on input AC power. In this paper, we propose a new control method to maximize rectifier efficiency. The method can control load allocation to converters by introducing active power converter control scheme and start-and-stop of converters. In order to illustrate optimal load allocations in a rectifier, a maximization problem of rectifier efficiency is formulated as a nonlinear optimization one. The problem is solved by Lagrangian relaxation method and the computation results provide the validity of proposed method.

Coalition based Optimization of Resource Allocation with Malicious User Detection in Cognitive Radio Networks

  • Huang, Xiaoge;Chen, Liping;Chen, Qianbin;Shen, Bin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권10호
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    • pp.4661-4680
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    • 2016
  • Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

RIS Selection and Energy Efficiency Optimization for Irregular Distributed RIS-assisted Communication Systems

  • Xu Fangmin;Fu Jinzhao;Cao HaiYan;Hu ZhiRui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권7호
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    • pp.1823-1840
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    • 2023
  • In order to improve spectral efficiency and reduce power consumption for reconfigurable intelligent surface (RIS) assisted wireless communication systems, a joint design considering irregular RIS topology, RIS on-off switch, power allocation and phase adjustment is investigated in this paper. Firstly, a multi-dimensional variable joint optimization problem is established under multiple constraints, such as the minimum data requirement and power constraints, with the goal of maximizing the system energy efficiency. However, the proposed optimization problem is hard to be resolved due to its property of nonlinear nonconvex integer programming. Then, to tackle this issue, the problem is decomposed into four sub-problems: topology design, phase shift adjustment, power allocation and switch selection. In terms of topology design, Tabu search algorithm is introduced to select the components that play the main role. For RIS switch selection, greedy algorithm is used to turn off the RISs that play the secondary role. Finally, an iterative optimization algorithm with high data-rate and low power consumption is proposed. The simulation results show that the performance of the irregular RIS aided system with topology design and RIS selection is better than that of the fixed topology and the fix number of RISs. In addition, the proposed joint optimization algorithm can effectively improve the data rate and energy efficiency by changing the propagation environment.

CA Joint Resource Allocation Algorithm Based on QoE Weight

  • LIU, Jun-Xia;JIA, Zhen-Hong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권5호
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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.

다중 셀 네트워크에서 단말 간 직접 통신을 위한 자원 및 전력 할당 기법 (Resource and Power Allocation Method for Device-to-Device Communications in a Multicell Network)

  • 강길모;신오순
    • 한국통신학회논문지
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    • 제40권10호
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    • pp.1986-1993
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    • 2015
  • 본 논문에서는 다중 셀 셀룰러 네트워크에서 단말 간 직접 통신(Device-to-Device: D2D)의 성능을 최대화하기 위한 최적 자원 및 전력 할당 알고리즘을 제안한다. 셀룰러 단말과 D2D 단말이 통신 자원을 공유하는 상황에서 필연적으로 D2D 단말은 자신이 속한 셀뿐만 아니라 인접한 셀의 D2D 단말과 셀룰러 단말로부터 간섭을 받게 된다. 이러한 환경에서 셀 내의 간섭과 인접 셀의 간섭을 고려한 인집 기지국간의 협력적 D2D 자원 할당 방법을 제안한다. 또한 자원 할당이 이루어진 후 D2D 단말의 최적 전력 할당 문제를 제시하고 최적해를 찾는 알고리즘을 제시한다. 제안하는 D2D 자원 및 전력 할당 알고리즘은 셀룰러 단말의 성능을 보장하기 위해 D2D 단말의 송신전력 제약 조건을 갖는 상황에서 셀룰러 단말로부터의 간섭과 인접 셀 D2D 단말로부터의 간섭을 고려하여 D2D 단말이 얻을 수 있는 전송률을 최대화시킬 수 있다. 다중 셀 환경에서의 모의실험을 통하여 제안한 자원 및 전력 할당 알고리즘의 성능을 검증하고 기존의 비협력적 자원 할당 방식과 비교하여 제안한 협력적 자원 할당 방식의 성능 이득을 확인한다.

Optimal Power Allocation and Relay Selection for Cognitive Relay Networks using Non-orthogonal Cooperative Protocol

  • Lan, Peng;Chen, Lizhen;Zhang, Guowei;Sun, Fenggang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권5호
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    • pp.2047-2066
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    • 2016
  • In this paper, we investigate joint power allocation and relay selection (PARS) schemes in non-orthogonal cooperative protocol (NOCP) based cognitive relay networks. Generally, NOCP outperforms the orthogonal cooperative protocol (OCP), since it can provide more transmit diversity. However, most existing PARS schemes in cognitive relay networks focus on OCP, which are not suitable for NOCP. In the context of NOCP, we first derive the joint constraints of transmit power limit for secondary user (SU) and interference constraint for primary user (PU). Then we formulate optimization problems under the aforementioned constraints to maximize the capacity of SU in amplify-and-forward (AF) and decode-and-forward (DF) modes, respectively. Correspondingly, we derive the closed form solutions with respect to different parameters. Numerical results are provided to verify the performance improvement of the proposed PARS schemes.

Group Power Constraint Based Wi-Fi Access Point Optimization for Indoor Positioning

  • Pu, Qiaolin;Zhou, Mu;Zhang, Fawen;Tian, Zengshan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권5호
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    • pp.1951-1972
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    • 2018
  • Wi-Fi Access Point (AP) optimization approaches are used in indoor positioning systems for signal coverage enhancement, as well as positioning precision improvement. Although the huge power consumption of the AP optimization forms a serious problem due to the signal coverage requirement for large-scale indoor environment, the conventional approaches treat the problem of power consumption independent from the design of indoor positioning systems. This paper proposes a new Fast Water-filling algorithm Group Power Constraint (FWA-GPC) based Wi-Fi AP optimization approach for indoor positioning in which the power consumed by the AP optimization is significantly considered. This paper has three contributions. First, it is not restricted to conventional concept of one AP for one candidate AP location, but considered spare APs once the active APs break off. Second, it utilizes the concept of water-filling model from adaptive channel power allocation to calculate the number of APs for each candidate AP location by maximizing the location fingerprint discrimination. Third, it uses a fast version, namely Fast Water-filling algorithm, to search for the optimal solution efficiently. The experimental results conducted in two typical indoor Wi-Fi environments prove that the proposed FWA-GPC performs better than the conventional AP optimization approaches.

Energy-Efficiency of Distributed Antenna Systems Relying on Resource Allocation

  • Huang, Xiaoge;Zhang, Dongyu;Dai, Weipeng;Tang, She
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권3호
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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.