Power Assignment Scheme Research Articles

Development of Reactive Power Allocation Method for Radial Structure Wind Farm Considering Multiple Connections

In recent years, the number of wind farms consisting of type 3 and type 4 wind turbines located within the distribution system has been growing rapidly. Wind turbines can be utilized as a continuous reactive power source to support the system voltage by taking advantage of their reactive power control capability. This paper aims to further develop the reactive power assignment strategy in order to minimize losses in wind farms described in the published paper. We introduce the method of reconfiguration and numbering to apply the algorithm to the wind farm structure and develop the previously-defined allocation ratio into two types of allocation ratios. The goal is to apply the loss minimization algorithm to a wind farm configuration with up to two wind turbines connected to one ring main unit (RMU). The proposed strategy reduces power loss and increases the real power flow in the wind farm by allocating reactive power to connected wind turbines taking into account the resistance value. The proposed allocation technique is validated in a Real Time Digital Simulator (RTDS)-based Hardware-in-the-loop Simulation (HILS) environment considering the Dongbok wind farm configuration in Jeju, South Korea. In the simulation, a Raspberry Pi acts as a wind farm controller sending a reactive power dispatch signal to each wind turbine via Modbus TCP/IP protocol. The simulation results mean that, applying the proposed algorithm, we can expect loss reduction effects in the wind farm.

Network-state-dependent routing and route-dependent spectrum assignment for PRMLSA problem in all-optical elastic networks

The advent of Elastic Optical Networks (EON) has led to significant improvements in optical network spectrum utilization when compared to Wavelength Division Multiplexing Optical Networks. However, the EON brought challenges to be explored, notably the Power, Routing, Modulation Level and Spectrum Assignment (PRMLSA) problem. This article aims to explore techniques for the PRMLSA problem, being developed two strategies named Shortest and Least Allocated (SLA) Path and Route-Based Spectrum Assignment (RBSA), which, respectively, include the link power spectral density inspection dynamic for routing and a physical layer factor (distance traveled) for Spectrum Assignment. Furthermore, a simplified version of the Adaptive Power Assignment (APA) [1] algorithm is presented, in which a power value between the minimum necessary and the maximum allowed is assigned to the signal. The simultaneous use of the SLA and RBSA algorithms resulted in locks of up to 0.00132%, being more than 10 times lower than the 0.0164% of the Shortest-Path and First-Fit algorithms. While the simplification of the APA resulted in 18.38% of the execution time of its respective original version, but with an increase in the blocking probability, which went from 0.016% to 0.031%, despite still being below conventional techniques, as the Constant Power Assignment strategy.

Spectral efficiency (SE) enhancement of NOMA system through iterative power assignment

This paper studies enhancing non-orthogonal multiple access (NOMA) spectral efficiency (SE) through optimizing the assigned power to each NOMA user depending on their channel states. This would improves the overall NOMA system performance in an adaptive manner in accordance with the channel state variations. An optimization problem for SE maximization is presented to optimize the performance of NOMA system. To solve the formulated problem, three power assignment schemes are proposed; firstly, a constant weight based water- filling approach is proposed, where it assigns the power to all subcarriers per each NOMA user iteratively. Secondly, two power assignment schemes are proposed, namely; high weight and low weight based power assignment (PA) schemes. Where they depend on constant weights to assign the power. In particular, the high weight based PA scheme depends on a weighting factor that uses the user index within the decoding order to fractions a high portion of the available total transmission power and allocate it to the respective user. On the other hand, the low weight based PA works based on a weighting factor that fractions low amount of the total transmission power. Both of these techniques take into account each user rank index within the decoding order with respect to its counterpart, and they also take into consideration the total number of active users. The results obtained from the simulations reveal that the proposed PA techniques maintains very good SE performances that are close to the numerical solution. It is worth mentioning that the numerical solution is obtained based on genetic algorithm. Nevertheless, the simulations results also confirm that the proposed approaches surpass the fractional transmission power approach simulated from literature works.

Chimp

Radio links in wireless body area networks (WBANs) commonly experience highly time-varying attenuation due to the dynamic network topology and frequent occlusions caused by body movements, making it challenging to design a reliable, energy-efficient, and real-time communication protocol for WBANs. In this article, we present Chimp, a learning-based power-aware communication protocol in which each sending node can self-learn the channel quality and choose the best transmission power level to reduce energy consumption and interference range while still guaranteeing high communication reliability. Chimp is designed based on learning automata that uses only the acknowledgment packets and motion data from a local gyroscope sensor to infer the real-time channel status. We design a new cost function that takes into account the energy consumption, communication reliability and interference and develop a new learning function that can guarantee to select the optimal transmission power level to minimize the cost function for any given channel quality. For highly dynamic postures such as walking and running, we exploit the correlation between channel quality and motion data generated by a gyroscope sensor to fastly estimate channel quality, eliminating the need to use expensive channel sampling procedures. We evaluate the performance of Chimp through experiments using TelosB motes equipped with the MPU-9250 motion sensor chip and compare it with the state-of-the-art protocols in different body postures. Experimental results demonstrate that Chimp outperforms existing schemes and works efficiently in most common body postures. In high-date-rate scenarios, it achieves almost the same performance as the optimal power assignment scheme in which the optimal power level for each transmission is calculated based on the collected channel measurements in an off-line manner.

Power Control for Cognitive M2M Communications Underlaying Cellular With Fairness Concerns

The explosion in the number of machine-to-machine (M2M) devices, as envisioned in the Internet of Things (IoT), will create a significant challenge in terms of spectrum scarcity. One promising approach for addressing this problem is to accommodate the fast-growing M2M traffic with temporally unused or under-used licensed bands. In this paper, a cognitive M2M communications underlaying cellular network is studied where M2M devices reuse licensed spectrum of cellular users in an opportunistic and fair manner. In particular, we consider two fairness metrics: 1) proportional fairness; and 2) max-min fairness, and design two transmit power assignment strategies for M2M devices that achieve the global fairness objectives, while satisfying an interference temperature constraint at the base station (BS) side. Furthermore, we provide a heuristical floating-ceiling water-filling (FCWF) algorithm with little computational overhead to obtain the optimal solutions. The numerical results show that the proportional fair power assignment could maximize the joint system utility and improve average SINR, while denying data transmission to some M2M devices with high interfering channel gain to the BS; On the other hand, the max-min fair power assignment protects those with high interfering channel gain to the BS by offering them the largest possible power allocation, which is more applicable to scenarios where at least a minimum level of QoS should be guaranteed.

Laboratory Experiment of Blind Adaptive Array with Subcarrier Transmission Power Assignment in Spectrum Superposing Scenarios

This paper experimentally validates the basic feasibility of our proposed blind adaptive array (BAA) with subcarrier transmission power assignment (STPA) scheme using a prototype. The proposed STPA-BAA enables spectrum superposing without any channel state information between two different wireless communication systems: employing STPA-BAA to the secondary system, inter-system interference from/to the primary system can be suppressed. Exploiting the characteristics of constant modulus algorithm (CMA) and power inversion (PI), the secondary transmitter provides two levels of power density for each subcarrier: high and low levels. It enables the secondary receiver to suppress interference with almost the same level of the desired signal. It is also effective in reducing interference to the primary receiver that has no interference suppression function. This paper conducts laboratory experiments of spectrum superposition in two multicarrier systems by wired setup. Though the practical performance of STPA-BAA is limited due to the quantization level or dynamic range of the transceiver, effectiveness of the proposed scheme is confirmed.

Energy Management for Energy Harvesting Wireless Sensors With Adaptive Retransmission

This paper analyzes the communication between two energy harvesting wireless sensor nodes. The nodes use automatic repeat request and forward error correction mechanism for the error control. The random nature of available energy and arrivals of harvested energy may induce interruption to the signal sampling and decoding operations. We propose a selective sampling scheme, where the length of the transmitted packet to be sampled depends on the available energy at the receiver. The receiver performs the decoding when complete samples of the packet are available. The selective sampling information bits are piggybacked on the automatic repeat request messages for the transmitter use. This way, the receiver node manages more efficiently its energy use. Besides, we present the partially observable Markov decision process formulation, which minimizes the long-term average pairwise error probability and optimizes the transmit power. Optimal and suboptimal power assignment strategies are introduced for retransmissions, which are adapted to the selective sampling and channel state information. With finite battery size and fixed power assignment policy, an analytical expression for the average packet drop probability is derived. Numerical simulations show the performance gain of the proposed scheme with power assignment strategy over the conventional scheme.

Power allocation for multi-user OFDM-DCSK system in frequency selective fading channel

In this paper, we introduce a grouping approach for power allocation in the multi-user OFDM-DCSK (MU-OFDM-DCSK) system under the frequency selective fading channels. The suggested procedure is convenient also for the other comb-type non-coherent schemes with similar structure. Furthermore, we derive analytical bit error rate (BER) expression for the grouped scheme and offer an optimal power distribution policy for both the single- and multi-user scenarios. This power assignment strategy is formulated by a min–max problem with the target of the worst group BER minimization incorporating total power and interference constraints. Simulation results confirm the advantages of the proposed power allocation scheme.

A Loss Minimization Method on a Reactive Power Supply Process for Wind Farm

Owing to the large physical area of a wind farm, some uncertainty and inefficiency issues exist in the related power delivery process. To provide required ancillary services regarding reactive power for the utility grid, further optimization processes are needed to maintain the reliability and efficiency of the entire system. In this paper, we introduce a reactive power assignment strategy that is based on the linearized system components of a wind farm, which comprises a power conversion system. Additionally, we perform realistic assignment processes to verify the effectiveness of this strategy with electromagnetic transients using dc software tool. Reducing the total apparent power flow by utilizing the radial structure of the wind farm is explored by assigning reactive power to nearby wind turbines. The verification process focuses on comparing the loss in output profile of a normal assignment and the proposed method in a designated wind farm.

Learning Automata Based Channel Assignment with Power Control in Multi-Radio Multi-Channel Wireless Mesh Networks

Wireless channel assignment is one of the major challenging issues in multi hop wireless mesh networks (WMN) when there is the need to design them in a distributed fashion, specifically for multi-radio multi-channel (MRMC) systems. In this work, a new learning automata based channel and power assignment scheme which adaptively improve network overall throughput by expecting network dynamics was proposed. First, a utility function which reflected the user’s preference for the signal to interference and noise ratio (SINR) was applied, and then the transmitter power. The distributed channel assignment and power control problem is formulated as a multiple payoff stochastic game of automata. In this game, each user evaluates a channel and power selection strategy by computing a utility value. This evaluation is performed using a stochastic iterative procedure. The utility function that potentially reflected a measure of satisfaction of every node was used by every node as an environmental response for the current selected strategy chosen by the nodes. According to dynamics of system, the proposed algorithm assigned channels and powers to radio interface such that it minimized interference in the neighborhood of a node. The stability of the system was analyzed via appropriate Lyapunov-like trajectory; it was shown that the stability and optimum point of the system converged.

Real-Time power control algorithm for reactive power reserve of Wind Farm

Abstract: Reactive power assignment has not been considered seriously in wind power because many system owners manage real power output firstly and maintain the required voltage for each wind turbine. However, renewable resources penetration is being continuously increased and power system operator might ask additional service to improve the reliability and stability issues. Owing to the system loss by the extensive area, the uncertainty of transferred power from large-scale wind farm is considerable. Counterbalancing the gap between expected and real output quantity is available with additional control design but reducing the occurred error is more effectual to not only the system efficiency but also the system stability. In this paper, a reactive power assignment strategy based on the relative distance of each wind turbine in farm, and realistic assignment processes to verify the positive effect are performed by PSCAD/EMTDC. The strategy is considering voltage fluctuation and system loss by two distinguished assignment processes that regarding array and turbines.

Power control for data load balancing with coverage in dynamic femtocell networks

We consider the load balancing and coverage problem of femtocell networks in indoor environment. We propose a novel framework exploiting the Voronoi diagram with respect to the radio propagation distance. Our initial power assignment scheme achieves maximal indoor coverage with minimized maximum required transmit power, which results in reduced interference. Our approach can adopt any radio propagation model to achieve more accurate coverage for an indoor environment with various obstacles. Time varying data traffic may cause unbalanced data load of base stations producing traffic overload. Our dynamic power control algorithm redistributes the data load by automatically adjusting transmit power levels according to data traffic estimation while preserving coverage. Moreover, we present an algorithm to cope with the dynamic deletion and insertion of femto base stations. Simulations show that the proposed scheme achieves better coverage, reduced interference, and good load balance compared to previous algorithms.

The Impact of Transmission Power Control Strategies on Lifetime of Wireless Sensor Networks

Transmission power control has paramount importance in the design of energy-efficient wireless sensor networks (WSNs). In this paper, we systematically explore the effects of various transmission power control strategies on WSN lifetime with an emphasis on discretization of power levels and strategies for transmission power assignment. We investigate the effects of the granularity of power levels on energy dissipation characteristics through a linear programming framework by modifying a well known and heavily utilized continuous transmission power model (HCB model). We also investigate various transmission power assignment strategies by using two sets of experimental data on Mica motes. A novel family of mathematical programming models are developed to analyze the performance of these strategies. Bandwidth requirements of the proposed transmission power assignment strategies are also investigated. Numerical analysis of our models are performed to characterize the effects of various design parameters and to comparethe relative performance of transmission power assignment strategies. Our results show that the granularity of discrete energy consumption has a profound impact on WSN lifetime, furthermore, more fine-grained control of transmission power (i.e., link level control) can extend network lifetime up to 20% in comparison to optimally-assigned network-level single transmission power.

Max-Min Fair Link Quality in WSN Based on SINR

This paper addresses first the problem of max-min fair (MMF) link transmissions in wireless sensor networks (WSNs) and in a second stage studies the joint link scheduling and transmission power assignment problem. Given a set of concurrently transmitting links, the MMF link transmission problem looks for transmission powers of nodes such that the signal-to-interference and noise ratio (SINR) values of active links satisfy max-min fairness property. By guaranteeing a “fair” transmission medium (in terms of SINR), other network requirements may be directly affected, such as the schedule length, the throughput (number of concurrent links in a time slot), and energy savings. Hence, the whole problem seeks to find a feasible schedule and a power assignment scheme such that the schedule length is minimized and the concurrent transmissions have a fair quality in terms of SINR. The focus of this study falls on the transmission power control strategy, which ensures that every node that is transmitting in the network chooses a transmission power that will minimally affect the other concurrent transmissions and, even more, achieves MMF SINR values of concurrent link transmissions. We show that this strategy may have an impact on reducing the network time schedule.

Local adaptive transmit power assignment strategy for wireless sensor networks

A distributed local adaptive transmit power assignment (LA-TPA) strategy was proposed to construct a topology with better performance according to the environment and application scenario and prolong the network lifetime. It takes the path loss exponent and the energy control coefficient into consideration with the aim to accentuate the minimum covering district of each node more accurately and precisely according to various network application scenarios. Besides, a self-healing scheme that enhances the robustness of the network was provided. It makes the topology tolerate more dead nodes than existing algorithms. Simulation was done under OMNeT++ platform and the results show that the LA-TPA strategy is more effective in constructing a well-performance network topology based on various application scenarios and can prolong the network lifetime significantly.

Body-posture-based dynamic link power control in wearable sensor networks

This article explores on-body energy management mechanisms in the context of emerging wireless body area networks. In severely resource-constrained systems such as WBANs, energy can usually be traded for packet delay, loss, and system throughput, whenever applicable. Using experimental results from a prototype wearable sensor network, the article first characterizes the dynamic nature of on-body links with varying body postures. A literature review follows to examine the relevant transmission power control mechanisms for ensuring a balance between energy consumption and packet loss on links between body-mounted sensors. Specific emphasis is put on approaches that are customized for TPC via tracking of postural node mobility. Then the article develops a WBAN-specific dynamic power control mechanism that performs adaptive body posture inference for optimal power assignments. Finally, performance of the mechanism is experimentally evaluated and compared with a number of static and dynamic power assignment schemes.

An 802.11n Wireless Local Area Network Transmission Scheme for Wireless Telemedicine Applications

In this paper, an 802.11 n transmission scheme is proposed for wireless telemedicine applications. IEEE 802.11n standards, a power assignment strategy, space-time block coding (STBC), and an object composition Petri net (OCPN) model are adopted. With the proposed wireless system, G.729 audio bit streams, Joint Photographic Experts Group 2000 (JPEG 2000) clinical images, and Moving Picture Experts Group 4 (MPEG-4) video bit streams achieve a transmission bit error rate (BER) of 10-7, 10-4, and 103 simultaneously. The proposed system meets the requirements prescribed for wireless telemedicine applications. An essential feature of this proposed transmission scheme is that clinical information that requires a high quality of service (QoS) is transmitted at a high power transmission rate with significant error protection. For maximizing resource utilization and minimizing the total transmission power, STBC and adaptive modulation techniques are used in the proposed 802.11 n wireless telemedicine system. Further, low power, direct mapping (DM), low-error protection scheme, and high-level modulation are adopted for messages that can tolerate a high BER. With the proposed transmission scheme, the required reliability of communication can be achieved. Our simulation results have shown that the proposed 802.11 n transmission scheme can be used for developing effective wireless telemedicine systems.

Capacity Regions and Optimal Power Allocation for CDMA Cellular Radio

The capacity region of code-division multiple access (CDMA) is determined by the set of transmission rates combined with quality-of-service (QoS) requirements which allow for a feasible power allocation scheme for n mobiles in a cellular network. The geometrical and topological properties of the capacity region are investigated in the present paper for the case of unlimited and limited power, respectively. As a central result, we show that the capacity region is convex by breaking the complicated topological structure into characteristic properties of its boundary and interior points, each of interest in itself. Based on these results, we furthermore investigate optimal power assignment schemes in the case that the demand of a community of users is infeasible. Weighted minimax and Bayes solutions are explicitly determined as appropriate means to share the capacity of a cellular network in a reasonable and fair way.

Performance evaluation of random power capture on mobile communications

AbstractPower assignment schemes are man‐made methods to enhance the capture effect of radio communications. In a previous study, Wen and Yang investigated the combined capture effect of the fixed power assignment scheme, Rayleigh fading, and near–far effect on the performance of packet radios. The performance analysis was limited to an infinite population environment. This assumption is reasonable for a conventional packet radio system with a vast service area. However, for a cellular mobile system, a finite population model should be used. In this paper, we analyse the combined natural and man‐made capture effect on the performance of a cellular system with finite population in each cell. A random power assignment scheme is adopted to produce the man‐made capture. The system throughput and delay are carried out by a Markov model. Some numerical calculations are used to demonstrate the degree of performance improvement. Copyright © 2001 John Wiley & Sons, Ltd.