Relevant bibliographies by topics / Adaptive power allocation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Adaptive power allocation'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Adaptive power allocation"

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Razmi, Shirin, and Naser Parhizgar. "Adaptive resources assignment in OFDM-based cognitive radio systems." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 3 (June 1, 2019): 1935. http://dx.doi.org/10.11591/ijece.v9i3.pp1935-1943.

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Spectrum efficiency of orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems can be improved by adaptive resources allocation. In resources allocation, transmission resources such as modulation level and transmission power are adaptively assigned based on channel variations. The goal of this paper is maximize the total transmission rate of secondary user (SU). Hence, we investigate adaptive power and modulation allocation to achieve this purpose. For power allocation, we investigate optimal and conventional methods and then introduce a novel suboptimal algorithm to calculate the transmission power of each subcarrier. In addition, for adaptive modulation, we consider two kinds of modulations including multi-quadrature amplitude modulation (MQAM) and multi-phase-shift keying (MPSK). Also, simulation results are indicated the performance of our algorithm.
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Gortz, N., and E. Bresch. "Source-adaptive power allocation for digital modulation." IEEE Communications Letters 7, no. 12 (December 2003): 569–71. http://dx.doi.org/10.1109/lcomm.2003.821312.

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Liu, Jue, Nan Sha, Weiwei Yang, Jia Tu, and Lianxin Yang. "Hierarchical Q-Learning Based UAV Secure Communication against Multiple UAV Adaptive Eavesdroppers." Wireless Communications and Mobile Computing 2020 (October 8, 2020): 1–15. http://dx.doi.org/10.1155/2020/8825120.

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In this paper, we investigate secure unmanned aerial vehicle (UAV) communication in the presence of multiple UAV adaptive eavesdroppers (AEs), where each AE can conduct eavesdropping or jamming adaptively by learning others’ actions for degrading the secrecy rate more seriously. The one-leader and multi-follower Stackelberg game is adopted to analyze the mutual interference among multiple AEs, and the optimal transmit powers are proven to exist under the existing conditions. Following that, a mixed-strategy Stackelberg Equilibrium based on finite and discretized power set is also derived and a hierarchical Q-learning based power allocation algorithm (HQLA) is proposed to obtain the optimal power allocation strategy of the transmitter. Numerical results show that secrecy performance can be degraded severely by multiple AEs and verify the availability of the optimal power allocation strategy. Finally, the effect of the eavesdropping cost on the AE’s attack mode strategies is also revealed.
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Liu, Wei, and Jing Min Tang. "Dynamic Subcarrier and Power Allocation Based on Nash Bargaining Solution in Symmetric Cooperative OFDMA Networks." Advanced Materials Research 187 (February 2011): 510–15. http://dx.doi.org/10.4028/www.scientific.net/amr.187.510.

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In this paper, subcarrier and power allocation are jointly considered in a three-node symmetric cooperation orthogonal frequency-division multiple access uplink system. With the help of Nash bargaining solution, the dynamic subcarrier allocation scheme and the adaptive power allocation scheme are proposed for joint optimization. The joint resource allocation is decomposed and solved by dynamic subcarrier allocation algorithm and adaptive power allocation algorithm. Simulation results show the effectiveness of the proposed cooperative scheme.
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Xu, Xiao Rong, Ai Ping Huang, Jian Rong Bao, and Hang Guan Shan. "Aadptive Subcarrier Allocation for Multiple Cognitive Users over Fading Channels." Advanced Materials Research 765-767 (September 2013): 647–52. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.647.

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In Cognitive Radio Network (CRN), where Primary User (PU) and multiple Secondary Users (SUs) wish to communicate with their corresponding receivers simultaneously over fading channels, spectrum utilization and efficient resource allocation are both significant points for CRN. Interference between PU and SUs should be eliminated in order to realize spectrum sharing. Multi-user resource allocation with the target of maximizing the spectral efficiency of SUs and satisfying the proportional rate constraint between SUs are proposed under the conditions of total SU interference constraint. An adaptive low-complexity suboptimal algorithm for subcarrier and power joint allocation is presented based on Rate Adaptive (RA) criterion, where adaptive subcarrier allocation is performed by assuming equal power distribution, while each subcarrier is assigned in accordance with subcarrier efficiency function. Moreover, linear water-filling algorithm for power allocation is applied within each subcarrier. Simulation results indicate that, with the proposed adaptive subcarrier allocation, spectral efficiency of multiple SUs is superior to traditional subcarrier power joint allocation algorithm. Low computational complexity and adaptive features make it available for implementation.
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Li, Yonghui, Branka Vucetic, Zhendong Zhou, and Mischa Dohler. "Distributed Adaptive Power Allocation for Wireless Relay Networks." IEEE Transactions on Wireless Communications 6, no. 3 (March 2007): 948–58. http://dx.doi.org/10.1109/twc.2007.05256.

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Dong, Zanyang, Tao Shang, Qian Li, and Tang Tang. "Adaptive Power Allocation Scheme for Mobile NOMA Visible Light Communication System." Electronics 8, no. 4 (March 29, 2019): 381. http://dx.doi.org/10.3390/electronics8040381.

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Recently, due to its higher spectral efficiency and enhanced user experience, non-orthogonal multiple access (NOMA) has been widely studied in visible light communication (VLC) systems. As a main concern in NOMA-VLC systems, the power allocation scheme greatly affects the tradeoff between the total achievable data rate and user fairness. In this context, our main aim in this work was to find a more balanced power allocation scheme. To this end, an adaptive power allocation scheme based on multi-attribute decision making (MADM), which flexibly chooses between conventional power allocation or inverse power allocation (IPA) and the optimal power allocation factor, has been proposed. The concept of IPA is put forward for the first time and proves to be beneficial to achieving a higher total achievable data rate at the cost of user fairness. Moreover, considering users’ mobility along certain trajectories, we derived a fitting model of the optimal power allocation factor. The feasibility of the proposed adaptive scheme was verified through simulation and the fitting model was approximated to be the sum of three Gaussian functions.
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Alhamad, Raed, and Hatem Boujemâa. "Optimal power allocation for CRN-NOMA systems with adaptive transmit power." Signal, Image and Video Processing 14, no. 7 (March 26, 2020): 1327–34. http://dx.doi.org/10.1007/s11760-020-01674-8.

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Xu, Xiao Rong, Jian Wu Zhang, Bao Yu Zheng, and Jun Rong Yan. "An Efficient Subcarrier Power Allocation Algorithm in Cognitive WSN." Advanced Materials Research 255-260 (May 2011): 2062–66. http://dx.doi.org/10.4028/www.scientific.net/amr.255-260.2062.

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In Cognitive Wireless Sensor Network (C-WSN), spectrum utilization and energy-efficiency are both significant items for the whole network. Interference between Primary User (PU) sensor and Secondary User (SU) sensor should be eliminated in order to realize spectrum sharing. In this paper, mathematical model of multi-carrier power allocation in cognitive OFDM is constructed. Multi-carrier power allocation based on rate adaptive criterion is proposed under the constraints of SUs’ power control. An efficient subcarrier power allocation algorithm based on adaptive water-filling is proposed. The improved algorithm could directly determine the sub-carriers that do not require additional power injection by rough estimation of water levels. Computational complexity of proposed algorithm could reduce rapidly. Meanwhile, theoretical derivation and numerical results both indicate that, with the proposed power allocation algorithm, SU’s spectral efficiency is superior to other traditional water-filling schemes, and the algorithm also has some adaptive features for practical implementation in C-WSN.
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Fan, Sen Quan, Yan Dong Huang, En Qing Xu, Kai Zhang, Hai Zhou Zhu, Hui Zhai, and Nan Jiang. "An Adaptive Power Allocation for Spatial Multiplexing in MIMO Channels." Advanced Materials Research 756-759 (September 2013): 4179–83. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.4179.

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This paper proposes an adaptive power allocation in multiple-input multiple-output (MIMO) spatial multiplexing slow fading channels, which improves spectral efficiency and reduces the complexity of systems at the same time. Under the constraint of the same signal-to-interference and noise ratio (SINR) at each receive antenna, an iteration formula of power allocation algorithm for transmit antennas is derived. Besides, for a certain channel gain matrix, the same SINR value at each receive antenna is proved to have the limit value. The simulations of the proposed adaptive power allocation show that the algorithm is effective and can reach the convergence fast.
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Dissertations / Theses on the topic "Adaptive power allocation"

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Chung, Jong-Sun. "Fast Power Allocation Algorithms for Adaptive MIMO Systems." Thesis, University of Canterbury. Electrical and Computer Engineering, 2009. http://hdl.handle.net/10092/3764.

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Recent research results have shown that the MIMO wireless communication architecture is a promising approach to achieve high bandwidth efficiencies. MIMO wireless channels can be simply defined as a link for which both the transmitting and receiving ends are equipped with multiple antenna elements. Adaptive modulation and power allocation could be used to further improve the performance of MIMO systems. This thesis focuses on developing a fast and high performance power allocation algorithm. Three power allocation algorithms are proposed in this thesis and their performances are compared in various system sizes and transceiver architectures. Among the three algorithms proposed in this thesis, the fast algorithm may be considered as the best power allocation algorithm since the performance of the fast algorithm is almost as good as the fullsearch (optimal)algorithm and the mean processing time is considerably less than the fullsearch algorithm. The fast algorithm achieves about 97.6% agreement with the optimal throughput on average. In addition, the time taken to find the power scaling factors using the fullsearch algorithm is about 2300 times longer than the processing time of the fast algorithm in a 6 x 6 system when the SNR is 20dB. As an extension to the power allocation process, excess power allocation methods are introduced. Excess power is the unused power during the power allocation process. The power allocation algorithm allocates power to each received SNR to maximize the throughput of the system whereas the excesspower allocation distributes the excess power to each SNR to improve both the instantaneous and temporal behavior of the system. Five different excess power allocation methods are proposed in this thesis. These methods were simulated in the Rayleigh fading channel with different Doppler frequencies, fD = 10Hz,50Hz and 100Hz, where the ACF of the channel coefficients are given by the Jakes' model. The equal BER improvement method showed a slightly better performance than the other methods. The equal BER improvement method enables the system to maintain the power scaling factors without sacrificing QoS for 19.6 ms on average when the maximum Doppler shift is 10Hz.
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Berggren, Fredrik. "Power control and adaptive resource allocation in DS-CDMA systems." Doctoral thesis, KTH, Signals, Sensors and Systems, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3568.

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Ahmed, Safayet N. "Adaptive CPU-budget allocation for soft-real-time applications." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/52215.

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The focus of this dissertation is adaptive CPU-budget allocation for periodic soft-real-time applications. The presented algorithms are developed in the context of a power-management framework. First, the prediction-based bandwidth scheduler (PBS) is developed. This algorithm is designed to adapt CPU-budget allocations at a faster rate than previous adaptive algorithms. Simulation results are presented to demonstrate that this approach allows for a faster response to under allocations than previous algorithms. A second algorithm is presented called Two-Stage Prediction (TSP) that improves on the PBS algorithm. Specifically, a more sophisticated algorithm is used to predict execution times and a stronger guarantee is provided on the timeliness of jobs. Implementation details and experimental results are presented for both the PBS and TSP algorithms. An abstraction is presented called virtual instruction count (VIC) to allow for more efficient budget allocation in power-managed systems. Power management decisions affect job-execution times. VIC is an abstract measure of computation that allows budget allocations to be made independent of power-management decisions. Implementation details and experimental results are presented for a VIC-based budget mechanism. Finally, a power-management framework is presented called the linear adaptive models based system (LAMbS). LAMbS is designed to minimize power consumption while honoring budget allocations specified in terms of VIC.
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Cardieri, Paulo. "Resource Allocation and Adaptive Antennas in Cellular Communications." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/29051.

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The rapid growth in demand for cellular mobile communications and emerging fixed wireless access has created the need to increase system capacity through more efficient utilization of the frequency spectrum, and the need for better grade of service. In cellular systems, capacity improvement can be achieved by reducing co-channel interference. Several techniques have been proposed in literature for mitigating co-channel interference, such as adaptive antennas and power control. Also, by allocating transmitter power and communication channels efficiently (resource allocation), overall co-channel interference can be maintained below a desired maximum tolerable level, while maximizing the carried traffic of the system. This dissertation presents investigation results on the performance of base station adaptive antennas, power control and channel allocation, as techniques for capacity improvement. Several approaches are analyzed. Firstly, we study the combined use of adaptive antennas and fractional loading factor, in order to estimate the potential capacity improvement achieved by adaptive antennas. Next, an extensive simulation analysis of a cellular network is carried out aiming to investigate the complex interrelationship between power control, channel allocation and adaptive antennas. In the first part of this simulation analysis, the combined use of adaptive antennas, power control and reduced cluster size is analyzed in a cellular system using fixed channel allocation. In the second part, we analyze the benefits of combining adaptive antennas, dynamic channel allocation and power control. Two representative channel allocation algorithms are considered and analyzed regarding how efficiently they transform reduced co-channel interference into higher carried traffic. Finally, the spatial filtering capability of adaptive antennas is used to allow several users to share the same channel within the same cell. Several allocation algorithms combined with power control are analyzed.
Ph. D.
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Tabatabaei, Yazdi Ehsan. "Adaptive Resource Allocation for Wireless Body Sensor Networks." Thesis, University of Canterbury. Computer Science and Software Engineering, 2014. http://hdl.handle.net/10092/9828.

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The IEEE 802.15.4 standard is an interesting technology for use in Wireless Body Sensor Networks (WBSN), where entire networks of sensors are carried by humans. In many environments the sensor nodes experience external interference for example, when the WBSN is operated in the 2.4 GHz ISM band and the human moves in a densely populated city, it will likely experience WiFi interference, with a quickly changing ``interference landscape''. In this thesis we propose Adaptive Resource Allocation schemes, to be carried out by the WBSN, which provided noticeable performance gains in such environments. We investigate a range of adaptation schemes and assess their performance both through simulations and experimentally.
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Liu, Feng. "Lifetime maximization through adaptive power allocation in reconfigurable system design for wireless systems /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?ECED%202009%20LIU.

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Huang, Jinliang. "Adaptive MIMO Systems with Channel State Information at Transmitter." Doctoral thesis, KTH, Kommunikationssystem, CoS, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-9777.

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This dissertation presents adaptation techniques that can achieve high spectral efficiency for single user multiple-input multiple-output (MIMO) systems. Two types of adaptation techniques, adaptive modulation and adaptive powe allocation, are employed to adapt the rate and the transmit power to fading channels. We start by investigating the adaptive modulation subject to a certain bit-error-ratio (BER) constraint, either instantaneous BER constraint or average BER constraint. The resulting average spectral efficiencies are obtained in closed-form expressions. It turns out that, by employing the average BER constraint, we can achieve the optimal average spectra efficiency at the cost of prohibitive computational complexity. On the other hand, instantaneous BER constraint leads to inferior performance with little computational complexity. In order to achieve comparable performance to the average BER constraint with limited complexity, a non-linear optimization method is proposed. To further enhance the average spectra efficiency, adaptive power allocation schemes are considered to adjust the transmit power across the temporal domain or the spatial domain, depending on the specific situation. Provided the closed-form expressions of the average spectral efficiency, the optimal MIMO coding scheme that offers the highest average spectral efficiency under the same circumstances can be identified. As we take into account the effect of imperfect channel estimation, the adaptation techniques are revised to tolerate interference introduced by the channel estimation errors. As a result, the degradation with respect to the average spectral efficiency is in proportion to signal-to-noise ratio (SNR). In order to facilitate fast development and verification of the adaptation schemes proposed for various MIMO systems, a reconfigurable Link Layer Simulator (LiLaS) which accommodates a variety of wireless/wireline applications is designed in the environment of MATLAB/OCTAVE. The idea of the simulator is originated from Software Defined Radio (SDR) and evolved to suit Cognitive Radio (CR) applications. For the convenience of modification and reconfiguration, LiLaS is functionally divided into generic blocks and all blocks are parameterized.
QC 20100812
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LI, XUAN. "Response Adaptive Designs in the Presence of Mismeasurement." Elsevier, 2012. http://hdl.handle.net/1993/8095.

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Response adaptive randomization represents a major advance in clinical trial methodology that helps balance the benefits of the collective and the benefits of the individual and improves efficiency without undermining the validity and integrity of the clinical research. Response adaptive designs use information so far accumulated from the trial to modify the randomization procedure and deliberately bias treatment allocation in order to assign more patients to the potentially better treatment. No attention has been paid to incorporating the problem of errors-in-variables in adaptive clinical trials. In this work, some important issues and methods of response adaptive design of clinical trials in the presence of mismeasurement are examined. We formulate response adaptive designs when the dichotomous response may be misclassified. We consider the optimal allocations under various objectives, investigate the asymptotically best response adaptive randomization procedure, and discuss effects of misclassification on the optimal allocation. We derive explicit expressions for the variance-penalized criterion with misclassified binary responses and propose a new target proportion of treatment allocation under the criterion. A real-life clinical trial and some related simulation results are also presented.
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Huang, Jinliang. "Adaptation in multiple input multiple output systems with channel state information at transmitter." Licentiate thesis, Stockholm : Institutionen för elektronik, dator- och programvarusystem, Kungliga tekniska högskolan, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4443.

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Dang, Hieu. "Adaptive multiobjective memetic optimization: algorithms and applications." Journal of Cognitive Informatics and Natural Intelligence, 2012. http://hdl.handle.net/1993/30856.

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The thesis presents research on multiobjective optimization based on memetic computing and its applications in engineering. We have introduced a framework for adaptive multiobjective memetic optimization algorithms (AMMOA) with an information theoretic criterion for guiding the selection, clustering, and local refinements. A robust stopping criterion for AMMOA has also been introduced to solve non-linear and large-scale optimization problems. The framework has been implemented for different benchmark test problems with remarkable results. This thesis also presents two applications of these algorithms. First, an optimal image data hiding technique has been formulated as a multiobjective optimization problem with conflicting objectives. In particular, trade-off factors in designing an optimal image data hiding are investigated to maximize the quality of watermarked images and the robustness of watermark. With the fixed size of a logo watermark, there is a conflict between these two objectives, thus a multiobjective optimization problem is introduced. We propose to use a hybrid between general regression neural networks (GRNN) and the adaptive multiobjective memetic optimization algorithm (AMMOA) to solve this challenging problem. This novel image data hiding approach has been implemented for many different test natural images with remarkable robustness and transparency of the embedded logo watermark. We also introduce a perceptual measure based on the relative Rényi information spectrum to evaluate the quality of watermarked images. The second application is the problem of joint spectrum sensing and power control optimization for a multichannel, multiple-user cognitive radio network. We investigated trade-off factors in designing efficient spectrum sensing techniques to maximize the throughput and minimize the interference. To maximize the throughput of secondary users and minimize the interference to primary users, we propose a joint determination of the sensing and transmission parameters of the secondary users, such as sensing times, decision threshold vectors, and power allocation vectors. There is a conflict between these two objectives, thus a multiobjective optimization problem is used again in the form of AMMOA. This algorithm learns to find optimal spectrum sensing times, decision threshold vectors, and power allocation vectors to maximize the averaged opportunistic throughput and minimize the averaged interference to the cognitive radio network.
February 2016
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Book chapters on the topic "Adaptive power allocation"

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Zhang, Jingmei, Ying Wang, and Ping Zhang. "STC-Based Cooperative Relaying System with Adaptive Power Allocation." In Lecture Notes in Computer Science, 343–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11424505_33.

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Lee, Ye Hoon. "A Multicarrier CDMA Communication System with Adaptive Transmission Power Allocation." In Frontiers in Computer Education, 769–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27552-4_101.

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Wang, Lei, Jun Lu, XianQing Ling, and Qian Huang. "Low Computation Resource Allocation for Adaptive OFDM Power Line Communication." In Advances in Intelligent and Soft Computing, 671–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30223-7_106.

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Lee, Ye Hoon. "A Multicarrier CDMA Communication System with Adaptive Transmission Power Allocation." In Communications in Computer and Information Science, 404–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35264-5_54.

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Wu, Xuan-li, Ming-xin Luo, Lu-kuan Sun, and Nan-nan Fu. "User Fairness-Based Adaptive Power Allocation in TD-LTE-A Downlink." In Advances in Intelligent Systems and Computing, 423–30. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1759-6_49.

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Maity, Santi P., and Sumanta Hati. "Adaptive Power Allocation in CI/MC-CDMA System Using Genetic Algorithms." In Advances in Computing and Communications, 580–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22720-2_61.

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Ren, Ren, and Shihua Zhu. "Novel Adaptive Subcarrier Power and Bit Allocation Using Wavelet Packet Parallel Architecture." In Distributed and Parallel Computing, 422–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11564621_49.

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Jia, Nianlong, Wenjiang Feng, Najashi Bara’u Gafai, and Weiheng Jiang. "Adaptive Modulation Based Relay Selection and Power Allocation in Cooperative OFDM Wireless Networks." In The Proceedings of the Second International Conference on Communications, Signal Processing, and Systems, 763–71. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00536-2_87.

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Wang, Yijie, and Kan Yang. "Research of Power-Aware Dynamic Adaptive Replica Allocation Algorithm in Mobile Ad Hoc Networks." In Parallel and Distributed Processing and Applications, 933–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11576235_93.

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Wang, Xi, Xiangbin Yu, Tao Teng, and Guangying Wang. "Energy-Efficient Power Allocation Scheme Based on Discrete-Rate Adaptive Modulation in Distributed Antenna System." In Machine Learning and Intelligent Communications, 284–92. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00557-3_29.

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Conference papers on the topic "Adaptive power allocation"

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Statovci, D., and T. Nordstrom. "Adaptive subcarrier allocation, power control, and power allocation for multiuser FDD-DMT systems." In 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577). IEEE, 2004. http://dx.doi.org/10.1109/icc.2004.1312443.

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Yu, Rongdao, and Tao Wu. "Adaptive Power Allocation for Double STTD System." In 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2010. http://dx.doi.org/10.1109/wicom.2010.5601162.

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Yang Hu, Xuedan Zhang, and Yuhan Dong. "Adaptive power allocation for wireless cooperative communications." In 2013 47th Annual Conference on Information Sciences and Systems (CISS 2013). IEEE, 2013. http://dx.doi.org/10.1109/ciss.2013.6552251.

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Huang, Jinliang, and Svan Signell. "Adaptive modulation and power allocation for OSTBC." In Signal Processing (ICICS). IEEE, 2009. http://dx.doi.org/10.1109/icics.2009.5397730.

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Li, Y., B. Vucetic, Z. Zhou, and M. Dohler. "Distributed Adaptive Power Allocation for Wireless Relay Networks." In 2007 IEEE International Conference on Communications. IEEE, 2007. http://dx.doi.org/10.1109/icc.2007.866.

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D'Alessandro, Salvatore, Andrea M. Tonello, and Lutz Lampe. "On power allocation in adaptive cyclic prefix OFDM." In ISPLC2010. IEEE, 2010. http://dx.doi.org/10.1109/isplc.2010.5479899.

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Mandyam, G., Zhigang Rong, and Lin Ma. "Adaptive power allocation in mixed-QoS CDMA systems." In Conference Record. Thirty-Fifth Asilomar Conference on Signals, Systems and Computers. IEEE, 2001. http://dx.doi.org/10.1109/acssc.2001.987015.

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Dan, Lilin, Chiheng Zhang, Jie Yuan, Peibo Wen, and Bin Fu. "Improved N-continuous OFDM using adaptive power allocation." In 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC). IEEE, 2018. http://dx.doi.org/10.1109/ccwc.2018.8301690.

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Weeraddana, P. C., Wei Li, Marian Codreanu, and Matti Latva-aho. "Adaptive subcarrier and power allocation for OFDMA systems." In 2008 1st IFIP Wireless Days (WD). IEEE, 2008. http://dx.doi.org/10.1109/wd.2008.4812830.

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Yang, Ming, Zhendong Li, Weiguo Di, and Xiaoping Wang. "Study on the optimum power allocation algorithm based on adaptive allocation technology." In 2011 International Conference on Photonics, 3D-imaging, and Visualization. SPIE, 2011. http://dx.doi.org/10.1117/12.906098.

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