Proposed Power Control Scheme Research Articles

Power Control for Two-Way AF Relay Assisted D2D Communications Underlaying Cellular Networks

As a key technology of the 5G communication system, device-to-device (D2D) communications have drawn significant research interests. However, the advantage of D2D communications may be limited when D2D users are far away from each other or the communication environments are harsh. In order to extend the range of D2D communications, a promising way is to use relaying technique to assist the communications. In this paper, we use a two-way amplify-and-forward (AF) relay to assist the underlay D2D communications and investigate the power control problem. Specifically, we formulate the power control problem as the optimization of the performance of the D2D link while fulfilling the quality-of-service (QoS) requirement of the cellular link. Two optimization objectives are considered for the D2D link, i.e., maximization of the minimum SINR at D2D users and maximization of the sum-rate of D2D users. For the first optimization objective, we can compare the possible optimal solutions for the three boundary conditions and obtain the optimal solutions. For the second optimization objective, we can convert the objective function into a concave function based on difference of convex (D. C.) structure, and use an iterative algorithm to solve the optimization problem. The simulation results show that the proposed power control scheme can improve the performance of the D2D link.

Adaptive Power Control for D2D Communications in Downlink SWIPT Networks With Partial CSI

In this letter, we consider the device-to-device (D2D) communication in downlink cellular networks, where the cellular user (CU) both decodes information and harvests the energy. Unlike the conventional D2D communications, we figure out that it is possible for the D2D pair to communicate without degrading the performance of the CU. Based on this observation, D2D transmit power control schemes are proposed for D2D rate maximization subject to maintaining the CU performance. In a decentralized way, the proposed power control schemes are performed at the D2D transmitter (DT) with instantaneous channel state information (CSI) of only the link between the D2D pair. For performance analysis, an asymptotic upper bound is provided on the D2D rates of the proposed schemes. Numerical results confirm the effectiveness of the proposed schemes.

Power dispatching tracking control of wind turbine considering maximum and limited power generation below rated wind speed

Wind turbines should respond to power dispatching of power grid at all times. According to this demand, this paper puts forward a set of feasible power control strategies below rated wind speed. Firstly, the operation state of wind turbine is divided into two working modes: maximum power generation and wind power curtailment generation. Different control strategies are adopted in different working conditions. Under the mode of maximum power generation, the model predictive control (MPC) algorithm is used to give a torque compensation gain. The MPC controller not only improves the utilization efficiency of wind energy, but also reduces the mechanical load. Under the mode of wind curtailment, a hybrid tracking control strategy of giving priority to torque control than pitch regulation is adopted. It reduces the frequency and amplitude of the pitch mechanism greatly. By comparing the simulation results under various wind speeds, it is found that the proposed power control strategy can adapt to different power dispatching scenes, and can respond to power dispatching with greater performance. It is very significant for the improvement of wind power generation system.

Transmission Power Adjustment Scheme for Mobile Beacon-Assisted Sensor Localization

Localization, as a crucial service for sensor networks, is an energy-demanding process for both indoor and outdoor scenarios. GPS-based localization schemes are infeasible in remote, indoor areas, and it is not a cost-effective solution for large-scale networks. Single mobile-beacon architecture is recently considered to localize sensor networks with the aim of removing numerous GPS-equipped nodes. The critical issue for the mobile beacon-assisted localization is to preserve the consumed power to increase the lifetime. This paper presents a novel power control scheme, namely “ Z -power,” for mobile beacon traveling along a predefined path. The proposed scheme takes the advantage of deterministic path traveled by the single beacon to efficiently adjust the transmission power. Based on the extensive results, the proposed power control scheme could successfully improve the beacon and sensors energy consumption about 25.37% and 34.09%, respectively. A significant energy-accuracy tradeoff was achieved using Z -power, which could successfully keep the same level of accuracy while providing lower energy consumption. Another group of results collected when obstacle-handling algorithm was applied at the presence of obstacles. In this scenario, Z -power improves energy consumption and localization accuracy with the same level of success.

Power management control strategy using physics-based battery models in standalone PV-battery hybrid systems

Abstract The rechargeable lithium-ion batteries (LiBs) are becoming a technology of choice for energy storage applications, due to its high energy and power density. In this paper, a power management control strategy is proposed for a standalone PV-Battery Energy Storage (BES) hybrid system. The proposed control algorithm tracks the Maximum Power Point (MPP) of the solar-cells while avoiding overcharging of LiBs under different solar radiation and load conditions. The controller has two regulation modes; (a) MPP Tracking mode, (b) battery state of charge limit mode. The standalone PV-BES hybrid system is represented as a system of differential algebraic equations and enables effective implementation of control algorithms. A physics-based single particle model accounting for internal states of a battery is implemented in the simulation and control algorithm. A mixed-order finite difference method with optimal node spacing and strong stability-preserving time-stepping Runge–Kutta scheme is used to solve the battery model. A case study is provided to demonstrate the effectiveness of the proposed strategy using real world data. The study reveals that the proposed power control strategy is robust and meets multiple objectives of standalone PV-BES hybrid systems such as no overcharging, 0% excess output power production, and ensuring no energy is transferred to the dump load.

Power Control via Stackelberg Game for Small-Cell Networks

In this paper, power control in the uplink for two-tier small-cell networks is investigated. We formulate the power control problem as a Stackelberg game, where the macrocell user equipment (MUE) acts as the leader and the small-cell user equipment (SUE) acts as the follower. To reduce the cross-tier and cotier interferences and the power consumption of both the MUE and SUE, we propose optimizing not only the transmit rate but also the transmit power. The corresponding optimization problems are solved through a two-layer iteration. In the inner iteration, the SUE items (SUEs) compete with each other, and their optimal transmit powers are obtained through iterative computations. In the outer iteration, the optimal transmit power of the MUE is obtained in a closed form based on the transmit powers of the SUEs through proper mathematical manipulations. We prove the convergence of the proposed power control scheme, and we also theoretically show the existence and uniqueness of the Stackelberg equilibrium (SE) in the formulated Stackelberg game. The simulation results show that the proposed power control scheme provides considerable improvements, particularly for the MUE.

Optimized Power Control for Massive MIMO With Underlaid D2D Communications

In this paper, we consider device-to-device (D2D) communication that is underlaid in a multi-cell massive multiple-input multiple-output (MIMO) system and propose a new framework for power control and pilot allocation. In this scheme, the cellular users (CUs) in each cell get orthogonal pilots which are reused with reuse factor one across cells, while all the D2D pairs share another set of orthogonal pilots. We derive a closed-form capacity lower bound for the CUs with different receive processing schemes. In addition, we derive a capacity lower bound for the D2D receivers and a closed-form approximation of it. We provide power control algorithms to maximize the minimum spectral efficiency (SE) and maximize the product of the signal-to-interference-plus-noise ratios in the network. Different from prior works, in our proposed power control schemes, we consider joint pilot and data transmission optimization. Finally, we provide a numerical evaluation where we compare our proposed power control schemes with the maximum transmit power case and the case of conventional multi-cell massive MIMO without D2D communication. Based on the provided results, we conclude that our proposed scheme increases the sum SE of multi-cell massive MIMO networks.

Intelligent Secure Communication for Internet of Things With Statistical Channel State Information of Attacker

In this paper, we investigate the power control strategy of intelligent secure communication with statistic channel state information (CSI) for Internet of Things (IoT) networks, where a transceiver and an attacker with several attack types, including silent, eavesdrop, jamming and spoofing, are considered. In order to solve the security problem that the transmitter only knows the statistical CSI of attacker, we propose a power control strategy based on Q-learning. In particular, Alice and Eve can choose their actions flexibly to maximize their reward under different system state and learn their best strategy according to the proposed strategy. In addition, the interactions between Alice and Eve are formulated as a zero-sum game, the Nash equilibrium and its existence conditions are deduced. Simulation results show that the impact of statistical CSI of attacker on system security performance can be reflected by the cost of attacker to launch attack and the average channel gain parameters. More importantly, the obtained results also show that the proposed power control strategy based on statistical CSI of attacker is worse than the scheme based on instantaneous CSI for statistical CSI leads a performance loss in terms of security.

Subcarrier and Power Allocation for the Downlink of Multicarrier NOMA Systems

This paper investigates the joint subcarrier and power allocation problem for the downlink of a multi-carrier non-orthogonal multiple access (MC-NOMA) system. A novel three-step resource allocation framework is designed to deal with the sum rate maximization problem. In Step 1, we relax the problem by assuming that each of the users can use all the subcarriers simultaneously. With this assumption, we prove the convexity of the resultant power control problem and solve it via convex programming tools to get a power vector for each user. In Step 2, we allocate the subcarriers to users by a heuristic greedy manner with the obtained power vectors in Step 1. In Step 3, the proposed power control schemes used in Step 1 are applied once more to further improve the system performance with the obtained subcarrier assignment of Step 2. To solve the maximization problem with fixed subcarrier assignments in both Step 1 and Step 3, a centralized power allocation method based on projected gradient descent algorithm and two distributed power control strategies based, respectively, on pseudo-gradient algorithm and iterative waterfilling algorithm are investigated. Numerical results show that our proposed three-step resource allocation algorithm could achieve comparable sum rate performance to the existing near-optimal solution with much lower computational complexity and outperforms power controlled OMA scheme. Besides, a tradeoff between user fairness and sum rate performance can be achieved via applying different user power constraint strategies in the proposed algorithm.

Optimal Power Control for Fading Channels With Arbitrary Input Distributions and Delay-Sensitive Traffic

This paper presents the optimal power control policies maximizing the effective capacity achieved with arbitrary input distributions subject to an average power constraint and quality of service (QoS) requirements. The analysis leads to simplified expressions for the optimal power control strategies in the low power regime and two limiting cases, i.e., extremely stringent QoS constraints and vanishing QoS constraints. In the low power regime, the energy efficiency (EE) performance with the constant-power scheme is also determined by characterizing both the minimum energy per bit and wideband slope for arbitrary input signaling and general fading distributions. Subsequently, the results are specialized to Nakagami- $m$ and Rician fading channels. Also, tradeoff between the effective capacity and EE is studied by determining the optimal power control scheme that maximizes the effective capacity subject to constraints on the minimum required EE and average transmission power. Circuit power consumption is explicitly considered in the EE formulation. Through numerical results, the performance comparison between constant-power and optimal power control schemes for different signal constellations and Gaussian signals is carried out. The impact of QoS constraints, input distributions, fading severity, and average transmit power level on the proposed power control schemes, maximum achievable effective capacity and EE is evaluated.

Novel Transient Power Control Schemes for BTB VSCs to Improve Angle Stability

This paper proposes two novel power control strategies to improve the angle stability of generators using a Back-to-Back (BTB) system-based voltage source converter (VSC). The proposed power control strategies have two communication systems: a bus angle monitoring system and a special protection system (SPS), respectively. The first power control strategy can emulate the behaviour of the ac transmission to improve the angle stability while supporting the ac voltage at the primary level of the control structure. The second power control scheme uses an SPS signal to contribute stability to the power system under severe contingencies involving the other generators. The results for the proposed control scheme were validated using the PSS/E software package with a sub-module written in the Python language, and the simple assistant power control with two communication systems is shown to improve the angle stability. In conclusion, BTB VSCs can contribute their power control strategies to ac grid in addition to offering several existing advantages, which makes them applicable for use in the commensurate protection of large ac grid.

A Power Control Algorithm Based on Outage Probability Awareness in Vehicular Ad Hoc Networks

This paper addresses the problem of adaptive power control based on outage probability minimization in Vehicular Ad Hoc Networks (VANETs), called a Power Control Algorithm Based on Outage Probability Awareness (PC-OPA). Unlike most of the existing works, our power control method aims at minimizing the outage probability and then is subject to the density of nodes in certain area. To fulfill power control, cumulative interference is assumed to be available at the transmitter of each terminal. The transmitters sent data by maximum power and then get the cumulative interference-aware outage probability. Furthermore, we build the interference model by stochastic geometric theory and then derive the expression between outage probability and cumulative interference. According to the expression, we adjust the transmitter power and optimize the outage probability. Simulation results are provided to demonstrate the effectiveness of the proposed power control strategies. It is shown that the PC-OPA can achieve a significant performance gain in terms of the outage probability and throughputs. Comparing MPC (Maximum Power Control algorithm) and WFPC (Water-Filled Power Control algorithm), the proposed PC-OPA decreased by 23% in terms of the outage probability and increased by 25% in terms of throughputs.

Spectral Efficiency Maximization of Multiuser Massive MIMO Systems With Finite-Dimensional Channel via Control of Users’ Power

This brief investigates the spectral efficiency of multiuser massive multiple-input multiple-output systems with a very large number of antennas at a base station serving single-antenna users. A practical physical channel model is proposed by dividing the angular domain into a finite number of distinct directions. A lower bound on the achievable rate of uplink data transmission is derived using a linear detector for each user and employed in defining the spectral efficiency. The obtained lower bound is further modified for the maximum-ratio combining and zero-forcing receivers. A power control scheme based on the large-scale fading is also proposed to maximize the spectral efficiency under peak power constraint. Experiments are conducted to evaluate the obtained lower bounds and the performance of the proposed method. The numerical results show a comparison between the performances of both receivers along with the advantage of the proposed power control scheme in terms of the spectral efficiency.

Joint mode selection and power allocation for better traffic offloading in D2D communications

Device-to-Device (D2D) technology underlying the cellular network is an attractive solution for future generation network to increase cellular traffic offloading. When two devices are close enough, D2D communication allows a direct communication between them without the mediation of the cellular base station. However, since D2D communication shares the same uplink cellular network radio resource, D2D communication mode selection remains challenging to limit the mutual interference between D2D and cellular links. In this paper, a new D2D mode selection scheme based on a new criterion is proposed aiming at maximizing the cellular traffic offload while respecting the quality of service of cellular users. More precisely, we introduce a noise rise parameter which takes into account the cellular link distance, the D2D link distance, and user’s required throughput. The D2D links are admitted under the constraint of a certain noise rise threshold. To further enhance the achieved throughput of D2D users while respecting the overall interference level in the network, a new power control algorithm is also proposed. Simulation results show that our proposed mode selection scheme provides a tradeoff between traffic offloading and the overall radio capacity in the network. They also prove that the D2D communication mode is more attractive at the cell edge and when D2D users are close enough to each other. In addition, we show the effectiveness of our proposed power control scheme as compared to both static and Rate-Adaptive Water Filling power allocation schemes.

Optimal Power Control in Cognitive Satellite Terrestrial Networks With Imperfect Channel State Information

To address the spectrum scarcity in future satellite communications, employing the cognitive technique in the satellite systems is considered as a promising candidate, which leads to an advanced architecture known as cognitive satellite terrestrial networks. Power control is a significant research challenge in cognitive satellite terrestrial networks, especially when the perfect channel state information (CSI) of satellite or terrestrial links is unavailable. In this context, we investigate the impact of imperfect CSI of both desired satellite link and harmful terrestrial interference link on the power control scheme in cognitive satellite terrestrial networks. By adopting a pilot-based channel estimation of satellite link and a back-off interference power constraint of terrestrial interference link, a novel power control scheme is presented to maximize the outage capacity of the satellite user while guaranteeing the communication quality of primary terrestrial user. Extensive numerical results quantitatively demonstrate the effect of various system parameters on the proposed power control scheme in cognitive satellite terrestrial networks with imperfect CSI.

Multi-pair massive MIMO amplify-and-forward relaying system with low-resolution ADCs: performance analysis and power control

In this paper, we focus on a general multi-pair massive MIMO amplify-and-forward (AF) relaying system where the relay antennas employ low-resolution analog-to-digital converters (ADCs) to reduce the hardware cost. First, considering the effect of low quantization on channel estimation, a tight closed form approximation of the system ergodic achievable rate is derived. Second, some asymptotic analysis is presented to reveal the impacts of the system parameters on the achievable rate. Particularly, the generalized power scaling schemes are characterized. The results indicate that in some cases, when the number of relay antennas grows without bound, the impact of the finite resolution ADCs on data transmission can be eliminated. To enhance the achievable rate of the quantized systems, the optimal user and relay power control schemes are proposed. Furthermore, to reap all the benefits of low-resolution ADCs, another power control scheme is also designed to minimize the total power consumption while guaranteeing the quality-of-service (QoS) requirement of each user, which can help draw some useful insights into the optimal ADC resolution from power saving perspectives. The simulation results confirm the accuracy of our theoretical analysis and the effectiveness of the proposed power control schemes.

Distributed Power Control Schemes for In-Band Full-Duplex Energy Harvesting Wireless Networks

This paper studies two power control problems in energy harvesting wireless networks where one hybrid base station (HBS) and all user equipments (UEs) are operating in in-band full-duplex mode. We consider minimizing the aggregate power subject to the quality of service requirement constraint, and maximizing the aggregate throughput. We address these two problems by proposing two distributed power control schemes for controlling the uplink transmit power by the UEs and the downlink energy harvesting signal power by the HBS. In our proposed schemes, the HBS updates the downlink transmit power level of the energy-harvesting signal so that each UE is enabled to harvest its required energy for powering the operating circuit and transmitting its uplink information signal with the power level determined by the proposed schemes. We show that our proposed power control schemes converge to their corresponding unique fixed points starting from any arbitrary initial transmit power. We will show that our proposed schemes well address the stated problems, which is also demonstrated by our extensive simulation results.

Control approach of a connected PV system under grid faults

This paper proposes a flexible power control of a three-phase grid-connected PV system which fulfills the PV converter operations under normal conditions and symmetrical grid voltage sags. This control approach can be configured in the PV converters and flexibly change from one to another mode during operation. In normal operation mode, a Maximal Power Point Tracking (MPPT) algorithm and PQ-control loop have been designed around the converters. Their aim is to maximize the PV power and to inject into the grid a current with low harmonic distortion, as well as energy at unity power factor. Under grid voltage dips, the PQ-control strategy has been changed within the grid voltage sag levels and the inverter rating currents. The MPPT control is deactivated, and the PV power has been reduced to the target value delivered by the inverter at the Point of Common Coupling. Case studies with simulations and experimental results have verified the effectiveness and flexibilities of the proposed power control strategy to release the advanced features.

Full-Duplex Massive MIMO AF Relaying With Semiblind Gain Control

This paper proposes an amplify-and-forward-based massive multiple-input–multiple-output full-duplex relaying (AF-MM-FDR) protocol, where multiple source–destination pairs communicate simultaneously with a common full-duplex relay. A zero-forcing (ZF)-based relay transceiver design with semiblind gain control is presented, considering the problem of relay oscillation. The asymptotic expression of end-to-end signal-to-interference-plus-noise power (SINR) is derived under the general power scaling scheme. The scaling behaviors of echo interference (EI) and effective channel estimation error are determined. Scaling results show that the deployment of very large antenna arrays at the relay has the potential to eliminate the effect of EI due to the full-duplex operation, if the power scaling scheme is selected properly. Moreover, based on the asymptotic analysis, a low-complexity power control scheme is proposed to optimize the spectral efficiency of AF-MM-FDR. Simulation results show that the proposed power control scheme improves the spectral–energy efficiency tradeoff of AF-MM-FDR significantly.

A non-iterative resource allocation strategy for device-to-device communications in underlaying cellular networks

We develop a joint spectrum sharing and power control strategy to increase the admissible number of device-to-device (D2D) links in an underlaying cellular network while guaranteeing the quality-of-service (QoS) of both D2D links and cellular users (CUs). The proposed spectrum sharing algorithm, termed as interference-filling (IF), examines whether the SINR requirements of all the existing CUs and D2D users can be met if a new D2D pair is admitted. In the sequel, two power control schemes are proposed to check the resultant interference level and increase the transmit power of the admitted D2D pairs group-by-group to further improve the system throughput. IF algorithm is based on the ordering statistics of the interference amounts from D2D transmitters to CUs, thus neither grid searching nor iteration is needed. Furthermore, the two proposed power control schemes are in closed-forms. These two favorable properties make the proposed strategy cost-effective and computationally efficient. Numerical results show the effect of the proposed IF and power control schemes in term of admissible D2D pairs and system sum rate.