Journal articles: 'Adaptive transmit power allocation'

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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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Wen, Juan, and Qi Ming Tian. "A Fast Adaptive Transmit Power and Bit Allocation in OFDM System." Advanced Materials Research 765-767 (September 2013): 444–47. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.444.

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In this paper, we propose a fast and optimal adaptive transmit power and bit allocation algorithm, which is called Bisection Searching Level (BSL) for wireless OFDMA systems. The algorithm aims at maximization of data rate under the constraints of total transmit power and bit error rate (BER). BSL is based on water pouring approach, and adopt bisection algorithm to find the water pouring level under discrete bit restriction. Both theoretical analysis and simulation results demonstrate the optimality of our proposed algorithm.

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Larsson, E. G., and Yang Cao. "Collaborative transmit diversity with adaptive radio resource and power allocation." IEEE Communications Letters 9, no. 6 (June 2005): 511–13. http://dx.doi.org/10.1109/lcomm.2005.1437354.

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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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Salh, Adeeb, Lukman Audah, Nor Shahida M Shah, and Shipun A. Hamzah. "Adaptive Antenna Selection and Power Allocation in Downlink Massive MIMO Systems." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (December 1, 2017): 3521. http://dx.doi.org/10.11591/ijece.v7i6.pp3521-3528.

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Massive multi-input, multi-output (MIMO) systems are an exciting area of study and an important technique for fifth-generation (5G) wireless networks that support high data rate traffic. An increased number of antenna arrays at the base station (BS) consumes more power due to a higher number of radio frequency (RF) chains, which cannot be neglected and becomes a technical challenge. In this paper, we investigated how to obtain the maximal data rate by deriving the optimal number of RF chains from a large number of available antenna arrays at the BS when there is equal power allocation among users. Meanwhile, to mitigate inter-user-interference and to compute transmit power allocation, we used the precoding scheme zero forcing beamforming (ZFBF). The achievable data rate is increased because the algorithm of ZFBF enables the choosing of the maximum power in relation to the optimal antenna selection. We conclude that the transmit power allocation allows the use of less number of RF chains which provides the maximum achievable data rate depending on the optimal RF chain at the BS.

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Alhamad, Raed, and Hatem Boujemâa. "Correction to: Optimal power allocation for CRN-NOMA systems with adaptive transmit power." Signal, Image and Video Processing 14, no. 8 (May 13, 2020): 1717. http://dx.doi.org/10.1007/s11760-020-01704-5.

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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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Li, Suoping, Wenwu Liang, Vicent Pla, Nana Yang, and Sa Yang. "Two-Stage Adaptive Relay Selection and Power Allocation Strategy for Cooperative CR-NOMA Networks in Underlay Spectrum Sharing." Applied Sciences 11, no. 21 (November 6, 2021): 10433. http://dx.doi.org/10.3390/app112110433.

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In this paper, we consider a novel cooperative underlay cognitive radio network based on non-orthogonal multiple access (CR-NOMA) with adaptive relay selection and power allocation. In secondary networks, dedicated relay assistance and user assistance are used to achieve communication between the base station and the far (and near) user. Here, a two-stage adaptive relay selection and power allocation strategy is proposed to maximize the achievable data rate of the far user while ensuring the service quality of near user. Furthermore, the closed-form expressions of outage probability of two secondary users are derived, respectively, under interference power constraints, revealing the impact of transmit power, number of relays, interference threshold and target data rate on system outage probability. Numerical results and simulations validate the advantages of the established cooperation and show that the proposed adaptive relay selection and power allocation strategy has better outage performance.

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Guo, Xinyue, Keer Zhang, and Xufa Huang. "Switching MIMO System with Adaptive OFDM Modulation for Indoor Visible Light Communication." Advances in Condensed Matter Physics 2018 (September 2, 2018): 1–7. http://dx.doi.org/10.1155/2018/5694196.

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In this paper, we propose and experimentally demonstrate a switching multiple input and multiple output (MIMO) system combining with adaptive orthogonal frequency division multiplexing (OFDM) modulation for high-speed indoor visible light communications. The adaptive OFDM modulation, which is realized by power and bit allocation on OFDM subchannels, is utilized to achieve the maximum channel capacity under a given target bit error rate (BER). Meanwhile, the MIMO mode switches between spatial multiplexing and transmit diversity adapting to the channel correlation, where the modulation order solved by adaptive OFDM modulation is chosen as the switching criterion. Experimental results validate data rates improvement over the pure spatial multiplexing and the pure transmit diversity system, where BERs are all below the 7% preforward error correction (pre-FEC) threshold of 3.8 × 10−3 in experiments.

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Sadr, Sanam, Alagan Anpalagan, and Kaamran Raahemifar. "Suboptimal Rate Adaptive Resource Allocation for Downlink OFDMA Systems." International Journal of Vehicular Technology 2009 (August 18, 2009): 1–10. http://dx.doi.org/10.1155/2009/891367.

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This paper aims to study the performance of low complexity adaptive resource allocation in the downlink of OFDMA systems with fixed or variable rate requirements (with fairness consideration). Two suboptimal resource allocation algorithms are proposed using the simplifying assumption of transmit power over the entire bandwidth. The objective of the first algorithm is to maximize the total throughput while maintaining rate proportionality among the users. The proposed suboptimal algorithm prioritizes the user with the highest sensitivity to the subcarrier allocation, and the variance over the subchannel gains is used to define the sensitivity of each user. The second algorithm concerns rate adaptive resource allocation in multiuser systems with fixed rate constraints. We propose a suboptimal joint subchannel and power allocation algorithm which prioritizes the users with the highest required data rates. The main feature of this algorithm is its low complexity while achieving the rate requirements.

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Han, Shiying, and Zixiong Wang. "A Low-Complexity Resource Allocation for Multiple Access Passive IoT System." Electronics 8, no. 12 (November 28, 2019): 1421. http://dx.doi.org/10.3390/electronics8121421.

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An ambient backscatter communication (AmBC) system with multiple backscatter devices (BDs) is investigated in this work. The cooperative reader receives the information from the primary transmitter (PT) and the multiple BDs simultaneously. With the asymptotic signal-to-noise-plus-interference ratio (SINR) of the BDs, an optimization problem that jointly optimizes the reflection coefficients of BDs and the primary transmit power is formulated. Considering that the adaptive optimization of reflection coefficients according to the instantaneous primary channel state information (CSI) is unaffordable in practice, we propose a low-complexity resource allocation scheme, which results in a long-term configuration of the BD reflection coefficients before the primary transmit power is allocated. With the long-term reflection coefficients, the transmit power of the primary system is optimized by solving the transformed two cascaded optimization problems which have closed-form solutions. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

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Li, Su Fang, Ming Yan Jiang, An Ming Dong, and Dong Feng Yuan. "Adaptive Subcarrier, Bit and Power Allocation Based on Hopfield Neural Network for Multiuser OFDM." Applied Mechanics and Materials 325-326 (June 2013): 1706–11. http://dx.doi.org/10.4028/www.scientific.net/amm.325-326.1706.

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A kind of adaptive subcarrier, bit and power allocation method utilizing Hopfield neural network (HNN) to minimize the overall transmit power of multiuser OFDM is studied in this paper. In order to find the power optimal subcarrier, bit and power allocation under the constraints that one subcarrier can only be allocated to one user and all users are allocated the same numbers of subcarrier, the number of bits of each subcarrier is finite, bit data can be allocated to each subcarrier, two kinds of new energy constrained functions are constructed for the HNN. It is shown through numerical simulations that the proposed methods can find the optimal allocation with less complexity compared with the exhaustive method.

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Yang, Xiao Long, Lin Ma, and Xue Zhi Tan. "Power-Weight Allocation Algorithm for OFDM-Based Cognitive Radio System." Advanced Materials Research 546-547 (July 2012): 932–36. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.932.

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Cognitive Radio (CR) has been proposed as one of the most promising technologies to provide efficient utilization of the limited wireless spectrum. In this paper, we investigate the power allocation for CR system based on orthogonal frequency division multiplexing (OFDM), and an improved allocation algorithm called power-weight algorithm is proposed. This algorithm performs initial allocation via Lagrange multiplier method, and then accomplishes second allocation based on power weight obtained in initial allocation. The analytical results reveal that the total transmission rate of all subcarriers is much closer to the optimal algorithm (i.e. the greedy algorithm) than the water-level algorithm, the Krongold algorithm and adaptive water-filling algorithm, subject to transmit power constraint and bit error rate (BER) constraint. These algorithms are all based on water-filling thought. Finally, simulation results verify our analysis.

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Heo, Joo, Insuk Cha, and KyungHi Chang. "Effective adaptive transmit power allocation algorithm considering dynamic channel allocation in reuse partitioning-based OFDMA system." Wireless Personal Communications 43, no. 2 (April 6, 2007): 677–84. http://dx.doi.org/10.1007/s11277-007-9272-5.

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Chen, Xiaomin, Xiangbin Yu, and Dazhuan Xu. "SVD-Aided Power Allocation and Iterative Detection Scheme for Turbo-BLAST System with Imperfect Channel State Information." International Journal of Antennas and Propagation 2011 (2011): 1–8. http://dx.doi.org/10.1155/2011/505606.

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A new technique that combines adaptive power allocation and iterative detection based on singular value decomposition (SVD) is introduced for the modified Turbo-BLAST system with imperfect channel state information (I-CSI). At the transmitter, in order to maximize the capacity performance, the MIMO channel is decomposed into several parallel eigen subchannels by SVD, and then proper power based on the water-filling principle is allocated to every subchannel subject to the total transmit power constraint. At the receiver, the modified MMSE detector taking the CSI imperfection into account is used to remove the coantenna interference, and then the turbo idea is employed for iterative detection to lower the system BER. As a result, the BER performance is effectively enhanced. Numerical results show that the introduced SVD-aided adaptive power allocation method is valid to improve not only the capacity but also the BER performance in the presence of channel state information imperfection, while the iterative detector can further lower the BER results.

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Haider and Hwang. "Adaptive Transmit Power Control Algorithm for Sensing-Based Semi-Persistent Scheduling in C-V2X Mode 4 Communication." Electronics 8, no. 8 (July 29, 2019): 846. http://dx.doi.org/10.3390/electronics8080846.

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For cellular-based vehicle-to-everything (C-V2X) communication, vital information about status and intention is periodically broadcasted by each vehicle using the cooperative awareness message (CAM) service. In C-V2X, the task of resource allocation can either be carried out in a centralized manner by the network, termed Mode 3, or by the vehicles themselves in a distributed manner without any core network support, termed Mode 4. Mode 4 scheduling is accomplished by employing sensing-based semi-persistent scheduling (SB-SPS), where the vehicles sense the medium and identify the best time-frequency resource combination for transmission of the CAM. Focusing on Mode 4 in this paper, we present a comprehensive analysis of the impact of variations in the transmit power of the vehicle on the performance of SB-SPS for C-V2X communications in various traffic scenarios through simulations. An adaptive-transmit power control (A-TPC) algorithm is presented to improve the quality of service for various large-scale traffic scenarios, where each vehicle uses real-time channel-sensing information to adjust the transmit power in order to avoid interference with neighbouring vehicles. The results demonstrate that our proposed algorithm outperforms the conventional TPC schemes.

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Yang, Liejun, Hui Wang, Yexian Fan, Fang Luo, and Wei Feng. "Reinforcement Learning for Distributed Energy Efficiency Optimization in Underwater Acoustic Communication Networks." Wireless Communications and Mobile Computing 2022 (February 24, 2022): 1–12. http://dx.doi.org/10.1155/2022/5042833.

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To solve the problems of poor quality of service and low energy efficiency of nodes in underwater multinode communication networks, a distributed power allocation algorithm based on reinforcement learning is proposed. The transmitter with reinforcement learning capability can select the power level autonomously to achieve the goal of getting higher user experience quality with lower power consumption. Firstly, we propose a distributed power optimization model based on the Markov decision process. Secondly, we further give a reward function suitable for multiobjective optimization. Finally, we present a distributed power allocation algorithm based on Q-learning and use it as an adaptive mechanism to enable each transmitter in the network to adjust the transmit power according to its own environment. The simulation results show that the proposed algorithm not only increases the total channel capacity of the system but also improves the energy efficiency of each transmitter.

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Ali, Zulfiqar, Kashif Naseer Qureshi, Kainat Mustafa, Rasool Bukhsh, Sheraz Aslam, Hana Mujlid, and Kayhan Zrar Ghafoor. "Edge Based Priority-Aware Dynamic Resource Allocation for Internet of Things Networks." Entropy 24, no. 11 (November 4, 2022): 1607. http://dx.doi.org/10.3390/e24111607.

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The exponential growth of the edge-based Internet-of-Things (IoT) services and its ecosystems has recently led to a new type of communication network, the Low Power Wide Area Network (LPWAN). This standard enables low-power, long-range, and low-data-rate communications. Long Range Wide Area Network (LoRaWAN) is a recent standard of LPWAN that incorporates LoRa wireless into a networked infrastructure. Consequently, the consumption of smart End Devices (EDs) is a major challenge due to the highly dense network environment characterised by limited battery life, spectrum coverage, and data collisions. Intelligent and efficient service provisioning is an urgent need of a network to streamline the networks and solve these problems. This paper proposes a Dynamic Reinforcement Learning Resource Allocation (DRLRA) approach to allocate efficient resources such as channel, Spreading Factor (SF), and Transmit Power (Tp) to EDs that ultimately improve the performance in terms of consumption and reliability. The proposed model is extensively simulated and evaluated with the currently implemented algorithms such as Adaptive Data Rate (ADR) and Adaptive Priority-aware Resource Allocation (APRA) using standard and advanced evaluation metrics. The proposed work is properly cross validated to show completely unbiased results.

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Yang, Yunji, Yonggi Hong, and Jaehyun Park. "Efficient Gradient Updating Strategies with Adaptive Power Allocation for Federated Learning over Wireless Backhaul." Sensors 21, no. 20 (October 13, 2021): 6791. http://dx.doi.org/10.3390/s21206791.

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In this paper, efficient gradient updating strategies are developed for the federated learning when distributed clients are connected to the server via a wireless backhaul link. Specifically, a common convolutional neural network (CNN) module is shared for all the distributed clients and it is trained through the federated learning over wireless backhaul connected to the main server. However, during the training phase, local gradients need to be transferred from multiple clients to the server over wireless backhaul link and can be distorted due to wireless channel fading. To overcome it, an efficient gradient updating method is proposed, in which the gradients are combined such that the effective SNR is maximized at the server. In addition, when the backhaul links for all clients have small channel gain simultaneously, the server may have severely distorted gradient vectors. Accordingly, we also propose a binary gradient updating strategy based on thresholding in which the round associated with all channels having small channel gains is excluded from federated learning. Because each client has limited transmission power, it is effective to allocate more power on the channel slots carrying specific important information, rather than allocating power equally to all channel resources (equivalently, slots). Accordingly, we also propose an adaptive power allocation method, in which each client allocates its transmit power proportionally to the magnitude of the gradient information. This is because, when training a deep learning model, the gradient elements with large values imply the large change of weight to decrease the loss function.

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Kim, Joongheon, Jae-Jin Lee, and Woojoo Lee. "Strategic Control of 60 GHz Millimeter-Wave High-Speed Wireless Links for Distributed Virtual Reality Platforms." Mobile Information Systems 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/5040347.

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This paper discusses the stochastic and strategic control of 60 GHz millimeter-wave (mmWave) wireless transmission for distributed and mobile virtual reality (VR) applications. In VR scenarios, establishing wireless connection between VR data-center (called VR server (VRS)) and head-mounted VR device (called VRD) allows various mobile services. Consequently, utilizing wireless technologies is obviously beneficial in VR applications. In order to transmit massive VR data, the 60 GHz mmWave wireless technology is considered in this research. However, transmitting the maximum amount of data introduces maximum power consumption in transceivers. Therefore, this paper proposes a dynamic/adaptive algorithm that can control the power allocation in the 60 GHz mmWave transceivers. The proposed algorithm dynamically controls the power allocation in order to achieve time-average energy-efficiency for VR data transmission over 60 GHz mmWave channels while preserving queue stabilization. The simulation results show that the proposed algorithm presents desired performance.

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Chen, Xiaomin, Dazhuan Xu, and Xiangbin Yu. "ADAPTIVE TRANSMIT ANTENNA SELECTION AND POWER ALLOCATION SCHEME FOR TURBO-BLAST SYSTEM WITH IMPERFECT CHANNEL STATE INFORMATION." Progress In Electromagnetics Research C 10 (2009): 215–30. http://dx.doi.org/10.2528/pierc09071503.

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Anwar, Khola, Taj Rahman, Asim Zeb, Inayat Khan, Mahdi Zareei, and Cesar Vargas-Rosales. "RM-ADR: Resource Management Adaptive Data Rate for Mobile Application in LoRaWAN." Sensors 21, no. 23 (November 30, 2021): 7980. http://dx.doi.org/10.3390/s21237980.

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LoRaWAN is renowned and a mostly supported technology for the Internet of Things, using an energy-efficient Adaptive Data Rate (ADR) to allocate resources (e.g., Spreading Factor (SF)) and Transmit Power (TP) to a large number of End Devices (EDs). When these EDs are mobile, the fixed SF allocation is not efficient owing to the sudden changes caused in the link conditions between the ED and the gateway. As a result of this situation, significant packet loss occurs, increasing the retransmissions from EDs. Therefore, we propose a Resource Management ADR (RM-ADR) at both ED and Network Sides (NS) by considering the packet transmission information and received power to address this issue. Through simulation results, RM-ADR showed improved performance compared to the state-of-the-art ADR techniques. The findings indicate a faster convergence time by minimizing packet loss ratio and retransmission in a mobile LoRaWAN network environment.

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Chen, Yang, Zhongpei Zhang, and Bingrui Li. "Cooperative Secure Transmission in MISO-NOMA Networks." Electronics 9, no. 2 (February 19, 2020): 352. http://dx.doi.org/10.3390/electronics9020352.

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In this paper, we investigate cooperative secure transmission in non-orthogonal multiple access (NOMA) networks where a source (Alice) intends to transmit confidential messages to one legitimate user with high-level security requirement (LU1), and serve another normal one (LU2) simultaneously. In order to enhance the transmission security, a cooperative jammer (Charlie) is employed to confuse multiple non-colluding eavesdroppers (Eves). Taking both secrecy outage restriction of LU1 and the desired quality of service (QoS) requirement of LU2 into consideration, we propose an adaptive power allocation strategy for maximizing secrecy rate. Numerical results are provided to validate that our proposed scheme significantly outperforms the conventional NOMA secure transmission scheme.

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Ghamari Adian, Mehdi, and Mahin Ghamari Adyan. "Optimal and Suboptimal Resource Allocation in MIMO Cooperative Cognitive Radio Networks." Journal of Optimization 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/190196.

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The core aim of this work is the maximization of the achievable data rate of the secondary user pairs (SU pairs), while ensuring the QoS of primary users (PUs). All users are assumed to be equipped with multiple antennas. It is assumed that when PUs are present, the direct communication between SU pairs introduces intolerable interference to PUs and thereby SUs transmit signal using the cooperation of one of the SUs and avoid transmission in the direct channel. In brief, an adaptive cooperative strategy for MIMO cognitive radio networks is proposed. At the presence of PUs, the issue of joint relay selection and power allocation in underlay MIMO cooperative cognitive radio networks (U-MIMO-CCRN) is addressed. The optimal approach for determining the power allocation and the cooperating SU is proposed. Besides, the outage probability of the proposed system is further derived. Due to high complexity of the optimal approach, a low complexity approach is further proposed and its performance is evaluated using simulations. The simulation results reveal that the performance loss due to the low complexity approach is only about 14%, while the complexity is greatly reduced.

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Song, Yi, Weiwei Yang, Zhongwu Xiang, Yiliang Liu, and Yueming Cai. "Secure Transmission in mmWave Wiretap Channels: On Sector Guard Zone and Blockages." Entropy 21, no. 4 (April 22, 2019): 427. http://dx.doi.org/10.3390/e21040427.

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Millimeter-wave (mmWave) communication is one of the key enabling technologies for fifth generation (5G) mobile networks. In this paper, we study the problem of secure communication in a mmWave wiretap network, where directional beamforming and link blockages are taken into account. For the secure transmission in the presence of spatially random eavesdroppers, an adaptive transmission scheme is adopted, for which sector secrecy guard zone and artificial noise (AN) are employed to enhance secrecy performance. When there exists no eavesdroppers within the sector secrecy guard zone, the transmitter only transmits information-bearing signal, and, conversely, AN along with information-bearing signal are transmitted. The closed-form expressions for secrecy outage probability (SOP), connection outage probability (COP) and secrecy throughput are derived under stochastic geometry. Then, we evaluate the effect of the sector secrecy guard zone and AN on the secrecy performance. Our results reveal that the application of the sector secrecy guard zone and AN can significantly improve the security of the system, and blockages also can be utilized to improve secrecy performance. An easy choice of transmit power and power allocation factor is provided for achieving higher secrecy throughput. Furthermore, increasing the density of eavesdroppers not always deteriorates the secrecy performance due to the use of the sector secrecy guard zone and AN.

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Lin, Chin-Feng, Tsung-Jen Su, Hung-Kai Chang, Chun-Kang Lee, Shun-Hsyung Chang, Ivan A. Parinov, and Sergey Shevtsov. "Direct-Mapping-Based MIMO-FBMC Underwater Acoustic Communication Architecture for Multimedia Signals." Applied Sciences 10, no. 1 (December 27, 2019): 233. http://dx.doi.org/10.3390/app10010233.

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In this paper, a direct-mapping (DM)-based multi-input multi-output (MIMO) filter bank multi-carrier (FBMC) underwater acoustic multimedia communication architecture (UAMCA) is proposed. The proposed DM-based MIMO-FBMC UAMCA is rare and non-obvious in the underwater multimedia communication research topic. The following are integrated into the proposed UAMCA: A 2 × 2 DM transmission mechanism, a (2000, 1000) low-density parity-check code encoder, a power assignment mechanism, an object-composition petrinet mechanism, adaptive binary phase shift keying modulation and 4-offset quadrature amplitude modulation methods. The multimedia signals include voice, image, and data. The DM transmission mechanism in different spatial hardware devices transmits different multimedia packets. The proposed underwater multimedia transmission power allocation algorithm (UMTPAA) is simple, fast, and easy to implement, and the threshold transmission bit error rates (BERs) and real-time requirements for voice, image, and data signals can be achieved using the proposed UMTPAA. The BERs of the multimedia signals, data symbol error rates of the data signals, power saving ratios of the voice, image and data signals, mean square errors of the voice signals, and peak signal-to-noise ratios of the image signals, for the proposed UAMCA with a perfect channel estimation, and channel estimation errors of 5%, 10%, and 20%, respectively, were explored and demonstrated. Simulation results demonstrate that the proposed 2 × 2 DM-based MIMO-FBMC UAMCA is suitable for low power and high speed underwater multimedia sensor networks.

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Akter, Lutfa, and Normin Nahar. "Specific Quality of Service Constrained Optimal Allocation of Transmit Power in Uplink Cognitive OFDMA System." International Journal of Computer and Communication Engineering 9, no. 3 (2020): 105–21. http://dx.doi.org/10.17706/ijcce.2020.9.3.105-121.

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This paper investigates an optimal allocation of transmit power for uplink cognitive OFDMA system. The aim is to construct two optimization frameworks namely, framework-I and II for uplink cognitive OFDMA system that minimizes it’s transmit power while maintaining Quality of Service (QoS). The measures for QoS include SNR threshold for framework-I whereas, for framework-II, it is measured by minimum rate requirement (bits/sec/Hz) to obtain a certain bit error rate (BER). Simulation results reveal the effectiveness of the proposed frameworks. Additionally, for framework-I, effects of different SNR threshold and users’ power budget are observed on the allocation of transmit power. Whereas, for framework-II, effects of different target BER, users’ power budget and minimum rate requirement are observed on the allocation of transmit power. Results are also compared with the results obtained from conventional capacity maximization based resource allocation approaches in terms of allocated transmit power, energy efficiency (EE) and spectral efficiency (SE). Simulation results reveal that, the proposed frameworks are incredibly successful in terms of utilization of power budget of users and EE compared to conventional capacity maximization based resource allocation approaches.

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Ahrens, Andreas, and Christoph Lange. "Transmit power allocation in SVD equalized multicarrier systems." AEU - International Journal of Electronics and Communications 61, no. 1 (January 2007): 51–61. http://dx.doi.org/10.1016/j.aeue.2006.03.002.

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Manalang, Dana, Benjamin Waters, Chasen Smith, Philip LaMothe, Matt Carlson, and Kedi Yan. "Adaptive Wireless Power for Subsea Vehicles." Marine Technology Society Journal 56, no. 5 (October 14, 2022): 36–44. http://dx.doi.org/10.4031/mtsj.56.5.9.

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Abstract Wireless power transfer in seawater removes the inherent risks and complexities of mating conductive surfaces in seawater. An effective underwater wireless power transfer system for subsea vehicles must maintain power transfer despite the potential for dynamic misalignment between the power transmission and receive elements and therefore requires an adaptive system. We describe the development and characterization of a subsea wireless power system, including a transmit-receive coil pair optimized for seawater performance. Built on the adaptive resonant wireless power transfer technology of WiBotic, Inc., the system automatically adjusts for misalignment and separation between the transmit and receive coils. We demonstrate that transmit-receive coil pairs can be effectively tuned to provide adaptive wireless power transfer in salt water, with no significant effects of increased pressure at depth. Furthermore, we describe the full system marinization of the wireless power system and its application to a system that uses a wave energy converter for subsea vehicle charging.

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Mehrotra, Rashi, and Ranjan Bose. "Energy-Efficient Joint Power Allocation and Relay Selection in Bit Error Rate Constrained Two-Way Relay Network." International Journal of Interdisciplinary Telecommunications and Networking 7, no. 4 (October 2015): 1–14. http://dx.doi.org/10.4018/ijitn.2015100101.

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In this paper, the authors have proposed energy efficient power allocation and relay selection scheme in a two-way amplify-and-forward (AF) relay under bit error rate (BER) constrained network. They have derived an expression for the overall BER for Rayleigh fading channel. Based on minimum power consumption in the network, the authors have addressed the problem of power allocation by converting geometric programming to a convex optimization problem. A closed form solution of power allocation is found, which aims at minimizing total transmit power for the overall BER constrained network. The authors have evaluated minimum total transmit power for two-way AF relay network. Based on minimum total transmit power, a novel relay selection scheme has been proposed. Simulation results demonstrate that the proposed two-way power allocation and relay selection scheme can significantly minimize power consumption under BER constrained network as compared to the existing relay transmission. The proposed power allocation scheme gives 3 dBW gain than one-way relay transmission. The proposed relay selection method also outperforms the random relay selection by 24 dBW. The simulation results are corroborated with the analytical result

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Zhang, Yuexia, and Pengfei Zhang. "User-Centric UAV Group Power Allocation Algorithm." Wireless Communications and Mobile Computing 2021 (October 31, 2021): 1–11. http://dx.doi.org/10.1155/2021/1629012.

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User-centric unmanned aerial vehicle group (UUAVG) organizes a dynamic user-centric access point group for each user, which can improve user service quality and throughput. However, in UUAVG, unmanned aerial vehicle user equipment (UUE) and device-to-device user equipment (DUE) using the same frequency will cause co-frequency interference and reduce system performance. In response to this problem, a power allocation algorithm of the two-level Stackelbreg game (PAOTLSG) is proposed. The algorithm builds a two-level Stackelberg game model based on UUE and DUE and uses power control coefficients and other parameters to control UAV adjust with the transmit power of DUE to achieve dynamic balance. The optimal transmit power of UAV and DUE is theoretically deduced to achieve the game Nash equilibrium and theoretically prove the existence and uniqueness of the Nash equilibrium solution. The simulation results show that compared with the pricing-based Stackelbreg game (PSG) algorithm, the PAOTLSG algorithm can effectively increase the throughput by 4.65%.

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Song, Xin, MingLei Zhang, WenMIn Liu, and ShengBao Wang. "Threshold-based hybrid relay selection and power allocation scheme." Journal of Communications Technology, Electronics and Computer Science 8 (November 7, 2016): 16. http://dx.doi.org/10.22385/jctecs.v8i0.126.

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Abstract—To minimize total transmit power in a system while guaranteeing the outage probability at the same time in a cooperative system, we propose and analyse two threshold-based hybrid relay selection and power allocation schemes for a three-node cooperative relaying system. They are designated as: the hybrid amplify-direct-forward relaying (HADF) and incremental hybrid decode-direct-forward relaying (IHDDF) schemes. In the HADF scheme, a specific outage probability threshold is derived to determine that the system chooses to optimize power allocation of its source and relay in amplify-and-forward (AF) mode or optimize the power of its source in direct-transmit (DT) mode without a relay. In IHDDF, according to the outage probability threshold, the system chooses to optimize its power in turn with incremental decode-and-forward opportunistic relaying (IDFO) mode or DT mode. Closed-form expressions of the total transmit power of the proposed HADF and IHDDF schemes are derived. The proposed schemes have low computational complexity and system cost. Theoretical analysis and simulation results show that the HADF scheme outperforms the AF and DT schemes, and the total transmission power of the IHDDF scheme is reduced significantly compared with the IDFO and DT schemes. Compared with the HADF scheme, the IHDDF scheme has a better total transmit power in special channel condition.Keywords—power allocation, three-node cooperative relaying system, amplify-and-forward, incremental decode-and-forward opportunistic relaying.

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Li, Qun, and Ding Xu. "Power Allocation for Energy-Harvesting-based Fading Cognitive Multiple Access Channels: with or without Successive Interference Cancellation." International Journal of Electronics and Telecommunications 63, no. 1 (March 1, 2017): 65–72. http://dx.doi.org/10.1515/eletel-2017-0009.

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Abstract This paper considers a fading cognitive multiple access channel (CMAC), where multiple secondary users (SUs), who share the spectrum with a primary user (PU), transmit to a cognitive base station (CBS). A power station is assumed to harvest energy from the nature and then provide power to the SUs. We investigate the power allocation problems for such a CMAC to maximize the SU sum rate under the interference power constraint, the sum transmit power constraint and the peak transmit power constraint of each individual SU. In particular, two scenarios are considered: with successive interference cancellation (SIC) and without SIC. For the first scenario, the optimal power allocation algorithm is derived. For the second scenario, a heuristic algorithm is proposed. We show that the proposed algorithm with SIC outperforms the algorithm without SIC in terms of the SU sum rate, while the algorithm without SIC outperforms the algorithm with SIC in terms of the number of admitted SUs for a high sum transmit power limit and a low peak transmit power limit of each individual SU.

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Li, Jun, Tong Gao, Bo He, Wenjing Zheng, and Fei Lin. "Power Allocation and User Grouping for NOMA Downlink Systems." Applied Sciences 13, no. 4 (February 14, 2023): 2452. http://dx.doi.org/10.3390/app13042452.

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Non-orthogonal multiple access (NOMA) technology allows multiple users to use the same time-frequency resource to send signals, which can improve spectral efficiency and throughput. We study the problems of user grouping and power allocation in the downlink of a multi-carrier NOMA system. The sum rate is the optimization goal. A step-by-step optimization is adopted. Users are grouped first and then power is allocated. For user grouping, the user grouping method based on the maximum channel gain difference is improved to prevent users with similar channel gains from being grouped together. For power allocation, the deep learning power allocation algorithm is used among subcarriers. Then, the closed-form expressions of power allocation between multiplexed users are derived according to the minimum transmission rate constraint. The simulation results show that compared with the fractional transmit power allocation method and fixed power allocation method, the deep learning power allocation method improves the system sum rate by about 2.2% and 19%, respectively. The power allocation methods we propose improve the system sum rate by about 10% compared to the fractional transmit power allocation method used among subcarriers and between multiplexed users.

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Ahrens, Andreas, and Christoph Lange. "Modulation-mode and power assignment in SVD-equalized MIMO systems." Facta universitatis - series: Electronics and Energetics 21, no. 2 (2008): 167–81. http://dx.doi.org/10.2298/fuee0802167a.

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Existing bit loading and transmit power allocation techniques are often optimized for maintaining both a fixed transmit power and a fixed target bit-error rate while attempting to maximize the overall data-rate. However, delay-critical real-time interactive applications, such as voice or video transmission, may require a fixed data rate. In this contribution the number of activated layers in a multiple input multiple output (MIMO) system and the number of bits per symbol along with the appropriate allocation of the transmit power are jointly optimized under the constraint of a given fixed data throughput. Our results show that in order to achieve the best bit-error rate, not necessarily all MIMO layers have to be activated. .

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Fu, Hong Shuang, Yi Jun Zhu, and Wen Bing Cai. "Optimal Power Allocation in SM-OFDM System Based on Visible Light Communications." Applied Mechanics and Materials 513-517 (February 2014): 3429–33. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3429.

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Spatial Modulation is a kind of spatial multiplexing schemes conveying information by the location of transmit antennas and spatial modulation (SM) along with OFDM can be applied to visible light communications for higher data rates. The closed form of symbol error rate (SER) in optical SM-OFDM communication system is derived in this paper. SER is a convex function of power allocation coefficients, therefore there exist optimal allocation coefficients minimizing SER. The optimal allocation coefficients are derived for different channels and numbers of transmit antennas. Analytical results are validated by Monte Carlo simulation results and these results show that a significant SER improvement is obtained by using the power allocation. In addition, the optimal allocation coefficients are affected by the channel and number of transmitters.

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Nam, S. H., O. S. Shin, and K. B. Lee. "Transmit Power Allocation for a Modified V-BLAST System." IEEE Transactions on Communications 52, no. 7 (July 2004): 1074–79. http://dx.doi.org/10.1109/tcomm.2004.831368.

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Mietzner, J., L. Lampe, and R. Schober. "Distributed transmit power allocation for multihop cognitive-radio systems." IEEE Transactions on Wireless Communications 8, no. 10 (October 2009): 5187–201. http://dx.doi.org/10.1109/twc.2009.081318.

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Zhengyan Shi and H. Leib. "Transmit Antenna Selected V-BLAST Systems With Power Allocation." IEEE Transactions on Vehicular Technology 57, no. 4 (July 2008): 2293–304. http://dx.doi.org/10.1109/tvt.2007.913181.

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Wang, Zhengqiang, Kunhao Huang, Xiaona Yang, Xiaoyu Wan, Zifu Fan, and Yongjun Xu. "Price-Based Resource Allocation in Wireless Power Transfer-Enabled Massive MIMO Networks." Sensors 19, no. 15 (July 26, 2019): 3298. http://dx.doi.org/10.3390/s19153298.

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This paper considers the price-based resource allocation problem for wireless power transfer (WPT)-enabled massive multiple-input multiple-output (MIMO) networks. The power beacon (PB) can transmit energy to the sensor nodes (SNs) by pricing their harvested energy. Then, the SNs transmit their data to the base station (BS) with large scale antennas by the harvesting energy. The interaction between PB and SNs is modeled as a Stackelberg game. The revenue maximization problem of the PB is transformed into the non-convex optimization problem of the transmit power and the harvesting time of the PB by backward induction. Based on the equivalent convex optimization problem, an optimal resource allocation algorithm is proposed to find the optimal price, energy harvesting time, and power allocation for the PB to maximize its revenue. Finally, simulation results show the effectiveness of the proposed algorithm.

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Yang, Zhou, Wenqian Jiang, and Gang Li. "Resource Allocation for Green Cognitive Radios: Energy Efficiency Maximization." Wireless Communications and Mobile Computing 2018 (July 5, 2018): 1–16. http://dx.doi.org/10.1155/2018/1327030.

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Green cognitive radios are promising in future wireless communications due to high energy efficiency. Energy efficiency maximization problems are formulated in delay-insensitive green cognitive radio and delay-sensitive green cognitive radio. The optimal resource allocation strategies for delay-insensitive green cognitive radio and delay-sensitive green cognitive radio are designed to maximize the energy efficiency of the secondary user. The peak interference power and the average/peak transmit power constraints are considered. Two algorithms based on the proposed resource allocation strategies are proposed to solve the formulated problems. Simulation results show that the maximum energy efficiency of the secondary user achieved under the average transmit power constraint is higher than that achieved under the peak transmit power constraint. It is shown that the design of green cognitive radio should take the tradeoff between its complexity and its achievable maximum energy efficiency into consideration.

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Niamah, Khoirun, Solichah Larasati, and Raudhatul Jannah. "Effects of Power Allocation and User Mobility on Non-Orthogonal Multiple Access Using Successive Interference Cancellation." ELKHA 13, no. 1 (April 20, 2021): 1. http://dx.doi.org/10.26418/elkha.v13i1.41708.

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This research based on simulation to show impact of the power allocation on Non-Orthogonal Multiple Access (NOMA) using Successive Interference Cancellation (SIC). NOMA used superposition code (SC) on the transmitter and SIC on the receiver. NOMA has two categories power domain (PD) and code domain (CD). This research based on PD-NOMA simulated for downlink. The number of users who use the same recourse block are divided into two conditions: user with apply SIC and without SIC base on the value of channel gain from each user. Applying SC on the transmitter and SIC on the receiver will cancel of interference. Novelties of this research are the best performance of power allocation and user mobility based on parameter BER and SNR. Allocation of the power transmit based on value of channel gain every user, where user with value of channel gain is low will be allocated high power transmit, and otherwise. The best result performance of BER vs SNR used ratio power transmit 0.45 dB:0.55 dB, BER get value SNR for 17 dB and 18 dB. The best performance SNR for mobility of user with speed = 40 km/h value SNR 18 dB for BER . This research has proposed to show impact of power transmit and interference in performance NOMA.

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Mo, Jinrong, Shengbo Hu, Tingting Yan, Xiaowei Song, and Yanfeng Shi. "Transmit Power Allocation with Connectivity Probability for Multi-QoS in Cluster Flight Spacecraft Network." Wireless Communications and Mobile Computing 2020 (February 17, 2020): 1–11. http://dx.doi.org/10.1155/2020/8676835.

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In this paper, we investigate the transmit power allocation problem to minimize the average packet error rate at the access point in the cluster flight spacecraft network, which adopts the CSMA/CA channel access mechanism. First, the node mobility, nodal distance distribution, and probabilistic adjacency matrix were formulated for cluster flight spacecraft network based on twin-satellite mode. Then, the optimization-theoretic model described the optimized transmit power allocation strategy and its implementation algorithm was proposed. And the problem of minimizing the packet error rate of the cluster flight spacecraft network system can be converted into maximizing the expectation of the binary probabilistic adjacency matrix, i.e., maximizing the sum of the nondiagonal elements in the probabilistic adjacency matrix. Due to discreteness of nodal distance distribution, Monte Carlo method was applied to solve the transmit power allocation problem. Yet importantly, the influence of node transmit power on the QoS performance of cluster flight spacecraft network was simulated and analyzed under the assumption of finite overall network transmit power and low traffic load. Finally, the results show that the pocket error rate increases with the provided traffic load, but the pocket error rate hardly changes with the same traffic load in different sequential time slots of any orbital hyperperiod or in the same time slot of different orbital hyperperiods, and by maximizing the sum of the nondiagonal elements in the probabilistic adjacency matrix, the pocket error rate minimum is achieved for a given total network transmit power at any time slot for cluster flight spacecraft network.

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Salh, Adeeb, Lukman Audah, Nor S. M. Shah, and Shipun A. Hamzah. "Maximizing Energy Efficiency in Downlink Massive MIMO Systems by Full-complexity Reduced Zero-forcing Beamforming." International Journal of Engineering & Technology 7, no. 4.1 (September 12, 2018): 33. http://dx.doi.org/10.14419/ijet.v7i4.1.19487.

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Energy efficiency (EE) is one of the key design goals for fifth-generation (5G) cellular networks due to the intermittent properties of renewable energy sources and limited battery capacity. In this paper, we analyze the EE of downlink (DL) massive multi-user multiple-input multiple-output (MIMO) system based on circuit power consumption for the transmit antenna configuration. We designed full complexity reduced zero-forcing (ZF) beamforming to cancel out interbeam interference when the number of antennas and minimized the power consumption model, when formulating the power allocation optimization problem with the Lagrange duality method, in order to maximize EE. Simulation results revealed that the EE in the base station (BS) could be improved when the number of radio frequency (RF) chains was proportional to the optimal transmit power allocation and when the consumption circuit power was comparable to the transmit power.

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Lau, Vincent. "Adaptive resource allocation for multiuser MIMO systems with transmit group MMSE." IEEE Transactions on Wireless Communications 8, no. 5 (May 2009): 2362–68. http://dx.doi.org/10.1109/twc.2009.070219.

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Ye, Hengdong, Zhengchuan Chen, Yunjian Jia, and Shutong Chen. "The Optimal Power Allocation for Sum Rate and Energy Efficiency of Full-Duplex Two-Way Communication Network." Entropy 24, no. 4 (April 11, 2022): 537. http://dx.doi.org/10.3390/e24040537.

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Full-duplex (FD) transmission holds a great potential of improving the sum data rate of wireless communication systems. However, the self-interference introduced by the full-duplex transmitter brings a big challenge to enhance the energy efficiency. This paper investigates the power allocation problem in a full-duplex two-way (FDTW) communication network over an OFDM channel, aiming at improving the sum data rate and energy efficiency. We first characterize the sum rate and energy efficiency achieved in a single-carrier FDTW system. The optimal transmit power that achieves the maximal sum data rate is presented. The energy efficiency maximization problem is solved by using fractional programming. Then we further formulate sum rate and energy efficiency maximization problem in a multi-subcarrier FDTW system. In particular, the sub-optimal transmit power allocation which achieves a decent sum rate improvement is found by using a proposed iterative algorithm. By combining the iterative algorithm and fractional programming, we further maximize the energy efficiency of the multi-subcarrier system. With our proposed algorithm, we can easily obtain an optimal transmit power that approximates the global optimal solution. Simulation results show that using the obtained optimal transmit power allocation algorithm can significantly improve the sum rate and energy efficiency in both single-carrier and multi-subcarrier systems.

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Hameed, Iqra, Pham-Viet Tuan, Mario R. Camana, and Insoo Koo. "Optimal Energy Beamforming to Minimize Transmit Power in a Multi-Antenna Wireless Powered Communication Network." Electronics 10, no. 4 (February 22, 2021): 509. http://dx.doi.org/10.3390/electronics10040509.

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In this paper, we study the transmit power minimization problem with optimal energy beamforming in a multi-antenna wireless powered communication network (WPCN). The considered network consists of one hybrid access point (H-AP) with multiple antennae and multiple users with a single antenna each. The H-AP broadcasts an energy signal on the downlink, using energy beamforming to enhance the efficiency of the transmit energy. In this paper, we jointly optimize the downlink time allocation for wireless energy transfer (WET), the uplink time allocation for each user to send a wireless information signal to the H-AP, the power allocation to each user on the uplink, and the downlink energy beamforming vectors while controlling the transmit power at the H-AP. It is challenging to solve this non-convex complex optimization problem because it is numerically intractable and involves high computational complexity. We exploit a sequential parametric convex approximation (SPCA)-based iterative method, and propose optimal and sub-optimal solutions for the transmit power minimization problem. All the proposed schemes are verified by numerical simulations. Through the simulation results, we present the performance of the proposed schemes based on the effect of the number of transmit antennae and the number of users in the proposed WPCN. Through the performance evaluation, we show that the SPCA-based joint optimization solution performance is superior to other solutions.

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Tarhuni, N. G., M. Elmusrati, and M. Al-Nadabi. "Stochastic Allocation of Transmit Power for Realistic Wireless Channel Models." Journal of Engineering Research [TJER] 15, no. 2 (June 1, 2016): 72. http://dx.doi.org/10.24200/tjer.vol13iss1pp72-79.

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Control of transmitted power is crucial for the successful operation of multi-user wireless channels communications. There are practical situations in which the transmitted power cannot be adjusted by feedback information; hence, only forward transmit power allocation can be applied, especially in situations where a feedback channel is not available in a wireless network or when wireless nodes are only transmit types. Conventionally, transmitted power can be fixed. Higher gain may be observed if the sensors’ transmitted power is randomized. In this work, random power allocation for a Nakagami-m distributed wireless channel model was investigated, and a number of random distributions were evaluated theoretically and tested by simulations. The outage probability was evaluated theoretically and validated by Monte Carlo simulations.

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Kim, Donghee, Jae Young Ahn, and Hojoon Kim. "Downlink Transmit Power Allocation in Soft Fractional Frequency Reuse Systems." ETRI Journal 33, no. 1 (February 7, 2011): 1–5. http://dx.doi.org/10.4218/etrij.11.0110.0141.

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Wu, Bo, Jun Shen, and Haige Xiang. "Resource allocation with minimum transmit power in multicast OFDM systems." Journal of Systems Engineering and Electronics 21, no. 3 (June 2010): 355–60. http://dx.doi.org/10.3969/j.issn.1004-4132.2010.03.002.

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Journal articles on the topic 'Adaptive transmit power allocation'

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