Proposed Power Allocation Scheme Research Articles

Power allocation strategy for fuel cell distributed drive electric tractor based on adaptive multi-resolution analysis theory

Fuel cell distributed drive electric tractor (FCDET) provided a novel pathway for the development of green agricultural machinery technology. However, FCDET faced problems such as low traction efficiency, short endurance, and high hydrogen consumption. Relevant studies have shown that reasonable and effective power allocation strategy can improve the efficiency and reduce the energy consumption of fuel cell systems. In this paper, a drive power allocation strategy based on adaptive multi-resolution analysis theory (AMRA) was proposed. The strategy could realize effective decoupling between various energy sources, reduce the problems of frequent start-stop and large power fluctuation for fuel cells. We started with an equivalent circuit model of the fuel cell system, a total efficiency solution model, an energy dissipation model, and a drive motor response model. The first-time reconstruction strategy was based on Tunable Q-factor Wavelet Transform (TQWT) to obtain a subsequence that responds to the oscillatory characteristics of the power signal. The second-time reconstruction strategy took the low-frequency subsequence through Variational Mode Decomposition (VMD) into a number of discrete sub-signals with special sparse properties. Meanwhile, the Sparrow Search Algorithm (SSA) was used to obtain the optimal combined values of the modal decomposition layers and the quadratic penalty factor in the VMD on real time. Finally, the second-time decomposed subsequences and sub-signals were reconstructed according to the frequency characteristics, and the reconstructed power signals were redistributed among the individual energy sources. In order to validate the proposed power allocation strategy, we used the ET504-H prototype as a research object. The power information of plowing and transportation operating conditions was collected in Mengjin test base of China YTO Group. The MATLAB/Simulink-PXI joint simulation platform was set up and the driving motor bench test was carried out in the New Energy Key Laboratory of Henan Province. The results show that the AMRA-based FCDET drive power allocation strategy can effectively improve the energy utilization of the fuel cell system and the economy of the whole tractor operating unit. Compared to the power-following strategy under plowing and transportation conditions, the average efficiency of the fuel cell system was improved by 8.3 % and 3.3 %, the equivalent hydrogen consumption was reduced by 35.6 % and 43.89 %, respectively. The average efficiency of the drive motor was improved by 2.06 % and 2.08 %, the total energy consumption was reduced by 3.73 % and 2.6 %, respectively. This study can provide a theoretical foundation and a novel technical approach for the development of FCDET control system.

Downlink Power Allocation for CR-NOMA-Based Femtocell D2D Using Greedy Asynchronous Distributed Interference Avoidance Algorithm

This paper focuses on downlink power allocation for a cognitive radio-based non-orthogonal multiple access (CR-NOMA) system in a femtocell environment involving device-to-device (D2D) communication. The proposed power allocation scheme employs the greedy asynchronous distributed interference avoidance (GADIA) algorithm. This research aims to optimize the power allocation in the downlink transmission, considering the unique characteristics of the CR-NOMA-based femtocell D2D system. The GADIA algorithm is utilized to mitigate interference and effectively optimize power allocation across the network. This research uses a fairness index to present a novel fairness-constrained power allocation algorithm for a downlink non-orthogonal multiple access (NOMA) system. Through extensive simulations, the maximum rate under fairness (MRF) algorithm is shown to optimize system performance while maintaining fairness among users effectively. The fairness index is demonstrated to be adaptable to various user counts, offering a specified range with excellent responsiveness. The implementation of the GADIA algorithm exhibits promising results for sub-optimal frequency band distribution within the network. Mathematical models evaluated in MATLAB further confirm the superiority of CR-NOMA over optimum power allocation NOMA (OPA) and fixed power allocation NOMA (FPA) techniques.

Performance Analysis of NOMA-Based Hybrid Satellite-Terrestrial Relay Networks With CCI

Hybrid satellite-terrestrial relay networks (HSTRNs) which exploit relay cooperative technology in the integrated system of satellites and terrestrial base stations (BSs) are expected to offer enhanced transmission performance benefited from the spatial gain of independent fading paths. To enable multi-user accessing and resource sharing among users, non-orthogonal multiple access (NOMA) technique can be applied in HSTRNs. In this paper, we consider a NOMA-based HSTRN where a satellite transmits signals to a relay base station (RBS) and a destination ground station (DGS), and RBS also serves a cellular user (CU) and DGS simultaneously by leveraging NOMA scheme. We assume that the satellite shares spectrum with a number of cellular small BSs (SBSs), hence SBSs will cause co-channel interference (CCI) to DGS, RBS and CU. We examine the transmission characteristics of the satellite and terrestrial links, and derive the closed-form expressions of the outage probability (OP) and average symbol error rate (ASER) of DGS and CU, respectively. Specially, we consider the effect of perfect and imperfect successive interference cancellation (SIC) on the ASER performance of CU. Then, considering the stochastic characteristics of satellite links and CCI, we analyze the mean energy efficiency (MEE) of the satellite and propose an optimal power allocation scheme which maximizes the MEE of the satellite and achieves system performance optimization. Simulation results demonstrate the effectiveness of the theoretical analysis and the proposed power allocation scheme.

Performance Analysis and Power Allocation for Cooperative ISAC Networks

To mitigate the overlapping of the radar and communication frequency bands caused by large-scale devices access, we propose a novel integrated sensing and communication (ISAC) system, where a micro base station (MiBS) simultaneously carries out both target sensing and cooperative communication. Concretely, the MiBS, acting as the sensing equipment, can also serve as a full-duplex decode-and-forward relay to assist end-to-end communication. Moreover, nonorthogonal downlink transmission (NO-DLT) is adopted between the macro base station and the Internet of Things devices, so that the spectrum utilization can be further improved. To facilitate the performance evaluation, both the exact and asymptotic outage probabilities, the ergodic rates associated communication, and the probability of successful sensing detection are characterized. Subsequently, a pair of problems of maximizing the receive signal-to-interference-plus-noise ratio of the sensing signal and maximizing the sum rate of communication are formulated that are solved by the classic Lagrangian method while exploiting the associated function monotonicity. Our simulation results demonstrate that: 1) The proposed ISAC NO-DLT system improves both the communication and sensing performance under the same power consumption as noncooperative NO-DLT and 2) the proposed power allocation (PA) schemes are superior to the random PA scheme.

Channel capacity and power allocation of MIMO visible light communication system

In this paper, the channel capacity of the multiple-input multiple-output (MIMO) visible light communication (VLC) system is investigated under the peak, average optical and electrical power constraints. Finding the channel capacity of MIMO VLC is shown to be a mixed integer programming problem. To address this open problem, we propose an inexact gradient projection method to find the channel capacity-achieving discrete input distribution and the channel capacity of MIMO VLC. Also we derive both upper and lower bounds of the capacity of MIMO VLC with the closed-form expressions. Furthermore, by considering practical discrete constellation inputs, we develop the optimal power allocation scheme to maximize transmission rate of MIMO VLC system. Simulation results show that more discrete points are needed to achieve the channel capacity as SNR increases. Both the upper and lower bounds of channel capacity are tight at low SNR region. In addition, comparing the equal power allocation, the proposed power allocation scheme can significantly increase the rate for the low-order modulation inputs.

BER performance analysis of OTFS systems with power allocation

Orthogonal time frequency space (OTFS), as a novel 2-D modulation technique, has been proposed to achieve better BER performances over delay-Doppler channels. In this paper, we propose two different power allocation (PA) algorithms in OTFS systems with zero forcing (ZF) or minimum mean square error (MMSE) equalization, where general formulas with PA are derived in advance under the condition of minimum BER (MBER) criterion. On one hand, a suboptimal MBER power allocation method is put forward to achieve better BER performances, and then analytical BER expressions are derived with proposed PA strategy. Considering the case of MMSE equalization, a combined subsymbol allocation (SA) and PA strategy is raised, where some subsymbols may be abandoned due to worse channel conditions, and then it is proven effectively to improve BER performances through theoretical and simulation results. Furthermore, BER performances with proposed joint SA and PA strategy are also investigated in delay-Doppler channels, where an improved message passing (MP) receiver based on equivalent channel matrix with PA is given.

Self-Sustainable RIS Aided Wireless Power Transfer Scheme

This paper investigates the potential advantages of applying reconfigurable intelligent surface (RIS) in the wireless power transfer (WPT) system and designs an efficient RIS-aided WPT scheme. First, we propose an independent beamforming algorithm. Compared to the existing joint beamforming, the proposed scheme achieves the same performance but is practically much more convenient. Second, we propose an absorb-then-reflect power transfer scheme so that the RIS-aided WPT system can be self-sustainable without external energy supply. Third, we analyze the WPT efficiency of the proposed scheme and derive the minimum required scale of the RIS elements to guarantee a performance gain over the traditional WPT system. Next, we consider the multi-user scenario, and propose power allocation schemes to maximize the energy utility. Finally, the effectiveness of the proposed RIS-aided WPT scheme is verified by simulation results.

Enumeration PCRLB-Based Power Allocation for Multitarget Tracking With Colocated MIMO Radar Systems in Clutter

An effective resource allocation strategy can maximize the remote sensing performance of radar systems, such as target detection and tracking. In this paper, two typical power allocation (PA) strategies are developed for the multi-target tracking (MTT) task in colocated MIMO (C-MIMO) radar systems with the consideration of the clutter. The multi-beam concept and the posterior PDF fusion are adopted by the C-MIMO radar system to obtain the global posterior distribution. Specifically, each radar generates multiple simultaneous beams with controllable power during each interval. To ensure that the limited system resources can be utilized effectively, the online PA scheme is implemented according to the prior knowledge predicted from the tracking cyclic recursive feedback results. The posterior Cramér-Rao lower bound (PCRLB) is derived by enumerating all possible target detection and false alarm occurrence cases, and is utilized as the tracking performance metric since it provides a more accurate lower bound on the target state estimation in clutter. Besides, to solve the computationally expensive problem of this PCRLB caused by enumeration operation, we propose a two-step approximate approach. Then, combined with the system resource configuration, two different types of resource optimization problems are designed, namely, performance maximization for a fixed power budget and direct resource minimization. These formulated PA problems are shown to be non-convex and non-linear. Therefore, we further propose a modified particle swarm optimization (MPSO) algorithm to solve these problems efficiently. Simulation results verify the superiority and effectiveness of the proposed PA strategies in terms of tracking performance in clutter.

Fuzzified power allocation scheme for relay network

This paper presents a new fuzzified power allocation strategy that maximizes achievable secrecy rates while limiting overall transmit power. The fuzzy weight value obtained by determining the rules based on the weights obtained through the sequential update process. Also, it considers the outage probability of multi-source network-coded Device-2-Device (D2D) multicast with predetermined relays in the proposed fuzzified power allocation strategy. Multiple cooperative relays on each hop are also considered, to perform cooperative beamforming in the presence of multiple eavesdroppers. Enhancement in the secrecy rate us also assured along with power allocation. Numerical outcomes are presented to investigate the secrecy capacity obtained by the fuzzy based power allocation in multi-hop Decode & Forward (DF) relay networks and to confirm the enhancement of the proposed power allocation scheme by yielding the secrecy rate as 0.148. From the results, the energy efficiency of the proposed method based on Rayleigh h=1 is 5.74, and it is 4.18%, and 1.92% better than the extant ICBD and NCDMC methods. In addition, the proposed work initially had a very low energy efficiency of 2.6864 (at the ns=8) but eventually reached the highest energy efficiency of 7.194 as it approached the ns=2.

Two-dimensional power allocation scheme for NOMA-based underwater visible light communication systems.

In this work, a two-dimensional power allocation scheme combining fractional transmit power allocation (FTPA) and the sine cosine algorithm (SCA) is proposed for non-orthogonal multiple access (NOMA)-based underwater visible light communication (UVLC) systems. Considering the proposed power allocation scheme, a downlink NOMA-based UVLC system using blue-light-emitting diodes in the deep-sea environment is set up to evaluate the influence of the FTPA coefficient and SCA on system communication performance. The simulation results demonstrate that the two-dimensional power allocation scheme can effectively reduce the impact of user pairing on system performance and improve the system transmission rate compared with the conventional power allocation scheme.

An Efficient Power Allocation Algorithm for Green Reconfigurable Intelligent Surface Assisted Vehicular Network

It is an irreversible trend to build a green and sustainable vehicular network facing with the dramatic increase in urban traffic. Reducing energy consumption has been an important aspect for green transportation. Reconfigurable intelligent surface (RIS) is considered as a promising technology to enhance the communication quality with higher energy efficiency. In this paper, we focus on the RIS-assisted vehicular networks. We obtain the closed-form analytical expressions for outage probability, ergodic achievable rate and average energy efficiency. A series of insights are further explored. Based on these, we discuss the performance under high SNR case, as well as, weak interference case. And then, the approximations in simpler form expressions are provided for each case, respectively. Outage diversity order and high SNR rate slope are also investigated. In addition, we propose a power allocation algorithm to maximize the ergodic achievable sum rate guaranteeing the outage probability and average energy efficiency. Numerical results show that our analytical results agree well with the Monte Carlo simulations in various network configurations. Besides, our proposed power allocation scheme significantly enhances the ergodic achievable sum rate compared with the equal power strategy.

A novel user clustering and a low-complexity power allocation in multi-user and multi-cluster NOMA system via Stackelberg game competition

Non-orthogonal multiple access (NOMA) has drawn wide attentions in multi-user, resource-constrained mobile systems to improve the system spectral efficiency. In the conventional resource assignment approaches, the optimal power allocation solutions are usually performed among multiple clusters, which, however, incur a high computational complexity due to the diversity of multiple users. In this work, we aim at the practical scenarios of multi-user and multi-cluster NOMA networks with the proposed a low-complexity power allocation and a suboptimal user clustering approach. By using Stackelberg game competition, a closed-form solution with no iterative operations is given first to the power allocation problem. The main idea of the authors’ proposed scheme is to have the base station (BS) allocating resources to all the users freely to guarantee their required minimum transmission-rates, and obtaining the maximal revenue through selling the remaining resources. Then, a suboptimal user clustering approach is further proposed to obtain more revenue for selling the resource. Numerical results show that the proposed power allocation scheme approximates the optimal sum-rates performance, but with lower computational floating-point operations (FLOPs) for the multi-user scene. And, the given user clustering scheme can pursue more revenue of the BS.

Resource Allocation for Layered Multicast Video Streaming in NOMA Systems

The application of non-orthogonal multiple access (NOMA) to multi-layer multicast video streaming is envisioned to address the explosively growing demand for capacity which is dominated mostly by multimedia content. In this paper, a joint power allocation and subgrouping scheme is developed to enhance the performance of NOMA-based multi-layer multicast systems. An optimization problem is formulated to maximize the overall sum multicast rate whilst satisfying the maximum transmission power and proportional rate constraints. Due to the complexity of the optimization problem, we first derive two power allocation techniques for the 2-layer case considering arbitrary subgrouping which are based on the iterative implementation and closed-form analysis, respectively. We then generalize the low-complexity closed-form solution for the general multi-layer case. This scheme successively allocates power to each layer stream while assuring that the minimum target rate and proportionality are guaranteed, particularly for the transmission rate of the high-priority base layer stream. A sub-optimal joint power allocation and subgrouping scheme is also designed by incorporating the power allocation scheme into the proposed iterative subgrouping techniques. Simulation results show the effectiveness of the power allocation and subgrouping schemes in enhancing the sum multicast rate performance. In addition, the proposed power allocation scheme ensures substantially higher rates for the base layer stream, which is crucial in robust delivery of standard quality video to all users.

Decentralized Power Allocation for MIMO-NOMA Vehicular Edge Computing Based on Deep Reinforcement Learning

Vehicular edge computing (VEC) is envisioned as a promising approach to process the explosive computation tasks of vehicular user (VU). In the VEC system, each VU allocates power to process partial tasks through offloading and the remaining tasks through local execution. During the offloading, each VU adopts the multi-input multi-output and non-orthogonal multiple access (MIMO-NOMA) channel to improve the channel spectrum efficiency and capacity. However, the channel condition is uncertain due to the channel interference among VUs caused by the MIMO-NOMA channel and the time-varying path loss caused by the mobility of each VU. In addition, the task arrival of each VU is stochastic in the real world. The stochastic task arrival and uncertain channel condition affect greatly on the power consumption and latency of tasks for each VU. It is critical to design an optimal power allocation scheme considering the stochastic task arrival and channel variation to optimize the long-term reward, including the power consumption and latency in the MIMO-NOMA VEC. Different from the traditional centralized deep reinforcement learning (DRL)-based scheme, this article constructs a decentralized DRL framework to formulate the power allocation optimization problem, where the local observations are selected as the state. The deep deterministic policy gradient (DDPG) algorithm is adopted to learn the optimal power allocation scheme based on the decentralized DRL framework. Simulation results demonstrate that our proposed power allocation scheme outperforms the existing schemes.

Spectral and energy efficiencies maximization in downlink NOMA systems

Due to the huge connectivity and ever-growing demands of diverse services and high data rate applications, more effective radio access techniques are required for the next generation wireless systems. Non-orthogonal multiple access (NOMA) is a promising candidate which has been recognized as an effective multiple access technique that notably improves the spectral efficiency (SE). In addition to SE, energy efficiency (EE) is also attracting too much interest nowadays due to the limited power of end users (EU) and internet of things (IoT) devices, and the strict environmental concerns related to global carbon dioxide (CO2) emission of communication devices. However, in fact there is a trade-off relationship between SE and EE. In this paper, the SE-EE trade-off relationship in NOMA-based systems is mathematically modeled and analyzed. On the other hand, in order to attain an elastic SE-EE trade-off relationship, the problem is formulated as an optimization problem with an objective of maximizing the EE under the constraint of satisfying a minimum SE demand. Simulation results confirmed the theoretical findings of this study and further asserted the validation of the proposed power allocation scheme which aims to achieve a more flexible trad-off relationship between SE and EE.

Spectral and Energy Efficiency of ACO-OFDM in Visible Light Communication Systems

In this paper, we study the spectral efficiency (SE) and energy efficiency (EE) of asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) for visible light communication (VLC). Firstly, we derive the achievable rates for Gaussian distributions inputs and practical finite-alphabet inputs. Then, we investigate the SE maximization problems subject to both the total transmit power constraint and the average optical power constraint with the above two inputs, respectively. By exploiting the relationship between the mutual information and the minimum mean-squared error, an optimal power allocation scheme is proposed to maximize the SE with finite-alphabet inputs. To reduce the computational complexity of the power allocation scheme, we derive a closed-form lower bound of the SE. Also, considering the quality of service, we further tackle the non-convex EE maximization problems of ACO-OFDM with the two inputs, respectively. The problems are solved by the proposed Dinkelbach-type iterative algorithm. In each iteration, the interior point algorithm is applied to obtain the optimal power allocation.The performance of the proposed power allocation schemes for the SE and EE maximization are validated through numerical analysis.

Optimal Power Allocation for Channel-Based Physical Layer Authentication in Dual-Hop Wireless Networks.

Channel-based physical-layer authentication, which is capable of detecting spoofing attacks in dual-hop wireless networks with low cost and low complexity, attracted a great deal of attention from researchers. In this paper, we explore the likelihood ratio test (LRT) with cascade channel frequency response, which is optimal according to the Neyman–Pearson theorem. Since it is difficult to derive the theoretical threshold and the probability of detection for LRT, majority voting (MV) algorithm is employed as a trade-off between performance and practicality. We make decisions according to the temporal variations of channel frequency response in independent subcarriers separately, the results of which are used to achieve a hypothesis testing. Then, we analyze the theoretical false alarm rate (FAR) and miss detection rate (MDR) by quantifying the upper bound of their sum. Moreover, we develop the optimal power allocation strategy between the transmitter and the relay by minimizing the derived upper bound with the optimal decision threshold according to the relay-to-receiver channel gain. The proposed power allocation strategy takes advantage of the difference of noise power between the relay and the receiver to jointly adjust the transmit power, so as to improve the authentication performance on condition of fixed total power. Simulation results demonstrate that the proposed power allocation strategy outperforms the equal power allocation in terms of FAR and MDR.

Do not forget the past: A buffer-aided framework for relay based key generation

We address relay-assisted key generation wherein two wireless nodes, that have no direct channel between them, seek the assistance of an intermediate relay to generate secret keys. In a celebrated version of the relay-assisted protocol, as applied by Lai et al., Zhou et al., Wang et al., and Waqas et al., the relay node generates pair-wise keys with the two nodes, and then broadcasts an XOR version of the two keys. Although such protocols are simple and effective, we observe that they face reduction in key rates due to two problems. First, for confidentiality, the relay broadcasts an XOR function of the pair-wise keys thereby pruning the length of the shared key to be the minimum of the key lengths of the pair-wise keys. Secondly, the broadcast phase may also experience outages thereby not being able to share the generated key in every round of the protocol. Identifying these issues, we propose a buffer-aided relaying protocol wherein buffer is used at the relay to store unused secret bits generated in the previous rounds of the protocol so as to provide confidentiality in the subsequent rounds of broadcast. On this buffer-aided protocol, we propose a power-allocation strategy between the phases of key generation and broadcast so as to maximize the throughput and key rate. Rigorous analyses show that buffer-aided relay when implemented along with the proposed power-allocation strategy offer remarkable advantages over existing baselines.

Optimal downlink power allocation schemes for OFDM-NOMA-based Internet of things

With the continuous development of fifth-generation technology, the number of mobile terminal Internet of Things devices has increased exponentially. How to effectively improve the throughput of fifth-generation systems has become a challenge. In the Internet of Things networks, ultra-dense networks and non-orthogonal multiple access technology have drawn extensive attention in recent years, because they can achieve multiplexing from the space domain and power domain. To improve the throughput of the system, this article combines non-orthogonal multiple access with ultra-dense networks technology and considers the orthogonal frequency division multiplexing non-orthogonal multiple access–based ultra-dense networks with multiple base stations and multiple Internet of Things devices. In particular, first, we build the network model and channel model. Second, we construct the downlink transmission rate maximizing problem subject to the total power. Then, to solve this problem, we divide it into three sub-problems: device grouping, inter-sub-band power allocation, and intra-sub-band power allocation problems. Solving these sub-problems, we obtain the optimal power allocation schemes by jointly employing channel-state sorting–pairing algorithm, water-filling algorithm, and convex optimization theory. Finally, numerical simulations are conducted to validate the performance of our proposed optimal downlink power allocation scheme. Experimental results show that the total throughput of the system has been significantly improved.

Secure Multiantenna Transmission With an Unknown Eavesdropper: Power Allocation and Secrecy Outage Analysis

This paper investigates the power allocation problem for secure multiple-input single-output transmission with the injection of artificial noise (AN), in the presence of an unknown eavesdropper (Eve). Two power allocation schemes, the optimal adaptive power allocation (OAPA) and suboptimal fixed power allocation (SFPA) schemes, are proposed to enhance the physical layer security of the considered system. Since the noise power at Eve is unknown, both power allocation schemes are designed for the worst-case scenario in which the noise power at Eve is assumed to be zero, aiming to minimize the secrecy outage probability (SOP). To characterize the performance of the proposed power allocation schemes, approximate closed-form expressions for average SOP under a preset noise power level are derived by applying Gauss-Chebyshev quadrature. We also address the worst-case secrecy outage performance for the proposed OAPA and SFPA schemes. Our analytical and numerical results show that, compared with the exhaustive search method that requires Eve’s prior information, the proposed OAPA scheme exhibits comparable secrecy outage performance without Eve’s prior information. Additionally, the SFPA scheme, also without Eve’s prior information, is capable of achieving almost the same worst-case SOP as the OAPA scheme, with a much lower implementation complexity.