In this paper, we propose and study a new jointloadbalancing(LB)andpowerallocation(PA)scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF access point (AP) and multiple VLC APs. An iterative algorithm is proposed to distribute users on APs and distribute the powers of the APs on their users. In the PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for total achievable data rate maximization. In this subproblem, we propose a new efficient algorithm that finds optimal dual variables after formulating them in terms of each other. This new algorithm provides faster convergence and better performance than thetraditionalsubgradientmethod.Inaddition,itdoesnot dependonthestepsizeortheinitialvaluesofthevariables, which we look for, as the subgradient does. Then, we start withtheuseroftheminimumdatarateseekinganotherAP thatoffersahigherdatarateforthatuser.Userswithlower dataratescontinuereconnectingfromoneAPtoanotherto balancetheloadonlyifthistravelincreasesthesummation of the achievable data rates and enhances the system fairness.TwoapproachesareproposedtohavethejointPAand LB performed: a main approach that considers the exact interference information for all users, and a suboptimal approach that aims to decrease the complexity of the first approach by considering only the approximate interference information of users. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.

/pdf/joint-optimization-of-power-allocation-and-load-balancing-3k9kwg16td.pdf

Joint optimization of power allocation and load balancing for hybrid VLC/RF networks

As the complexities of wireless technologies increase, novel multidisciplinary approaches for the spectrum sharing/management are required with inputs from the technology, economics and regulations. Recently, the cognitive radio technology comes into action to handle the spectrum scarcity problem. To identify the available spectrum resource, decision on the optimal sensing and transmission time with proper coordination among the users for spectrum access are the important characteristics of spectrum sharing methods. In this paper, we have technically overviewed the state-of-the-art of the various spectrum sharing techniques and discussed their potential issues with emerging applications of the communication system, especially to enhance the spectral efficiency. The potential advantages, limiting factors, and characteristic features of the existing cognitive radio spectrum sharing domains are thoroughly discussed and an overview of the spectrum sharing is provided as it ensures the channel access without the interference/collision to the licensed users in the spectrum.

An overview of spectrum sharing techniques in cognitive radio communication system

Cognitive radio networks (CRN), in their quest to become the preferred next-generation wireless communication paradigm, will depend heavily on their ability to efficiently manage the limited resources at their disposal in meeting the demands of their numerous users and driving their operations. As a result, a considerable amount of research work has been recently dedicated to investigating and developing resource allocation (RA) models that capture the essentials of CRN. The various ideas put forward by researchers to address RA problems in CRN have been somewhat diverse, and somehow, there seem to be no links that bring cohesion and clarity of purpose and ideas. To address this problem and bridge the gap, in this paper, a comprehensive study on the prevalent techniques developed for addressing RA problems in CRN is carried out, with an intent to put some structure, relevance and meaning to the various solution approaches. The solution models are therefore grouped and/or classified based on certain outstanding criteria, and their strengths and weaknesses highlighted. Open-ended problems are identified, and suggestions for improving solution models are given. The study therefore gives good directions for further investigations on developing RA solutions in CRN.

/pdf/solving-resource-allocation-problems-in-cognitive-radio-3rrvehjom4.pdf

Solving resource allocation problems in cognitive radio networks : a survey

In previous study, deep learning and autoencoder have been applied for data detection of NOMA systems, rather than the resource allocation of OFDMA/NOMA systems. In previous work, we proposed the use of non-deep-learning-based cross-layer resource allocation for OFDMA/NOMA video communication systems. In this paper, we apply a deep neural network and supervised learning to an OFDMA subcarrier assignment and NOMA user grouping problem in downlink video communication systems. The resource allocation results from our previous work are used as training data at the training stage. At the testing stage, we propose a conversion algorithm to map the result of the sigmoid activation function (values between [0,1]) of the output layer of the DNN to either zero (unassigned) or one (assigned), in order to meet two hard constraints. The PSNR performance is very close (within 0.2dB) to that but has lower complexity, due to the non-iterative approach used in the testing stage of the DNN.

/pdf/deep-learning-aided-cross-layer-resource-allocation-of-ofdma-45xnj4gm10.pdf

Deep-Learning-Aided Cross-Layer Resource Allocation of OFDMA/NOMA Video Communication Systems

The popularity and convergence of wireless communications have resulted in continuous network upgrades to support the increasing demand for bandwidth. However, given that wireless communication systems operate on radio-frequency waves, the health effects of electromagnetic (EM) emission from these systems are increasingly becoming a concern due to the ubiquity of mobile communication devices. To address these concerns, we propose two schemes (offline and online) for minimizing the EM emission of users in the uplink of orthogonal frequency-division multiplexing (OFDM) systems, while maintaining an acceptable quality of service (QoS). We formulate our offline EM reduction scheme as a convex optimization problem and solve it through water filling. This is based on the assumption that the long-term channel state information (CSI) of all the users is known. Given that, in practice, long-term CSI of all the users cannot always be available, we propose our online EM emission reduction scheme, which is based on minimizing the instantaneous transmit energy per bit of each user. Simulation results show that both of our proposed schemes significantly minimize the EM emission when compared with the benchmark classic greedy spectral efficiency (SE)-based scheme and an energy efficiency (EE)-based scheme. Furthermore, our offline scheme proves to be very robust against channel prediction errors.

/pdf/electromagnetic-emission-aware-schedulers-for-the-uplink-of-3339ru3wco.pdf

Electromagnetic Emission-Aware Schedulers for the Uplink of OFDM Wireless Communication Systems

A gradient-based method is designed for power allocation in orthogonal-frequency-division-multiplexing (OFDM) -based cognitive radio networks. The resource allocation problem subject to a mutual interference constraint is considered. We utilize the gradient descent approach to allocate power to subcarriers in cognitive radio (CR) networks. The proposed gradient-based power allocation method with a well-designed step size can approximate the optimal solution within a few iterations. Due to the derived equation for power allocation in an adaptive manner, the proposed method is feasible for adaptive power allocation in time-varying channels. The analysis for the selection of the step size is presented in this paper. For comparison purposes, a greedy power-loading method requiring numerous iterations is also designed for this power allocation problem. The proposed gradient-based method and the greedy power-loading method both have a computational complexity of O(N), but the proposed gradient-based method requires far fewer iterations. As demonstrated in the simulation results, the proposed gradient-based method with the adaptive step size has a fast rate to achieve a near-optimal solution within an extremely small number of iterations and has quite a low computational complexity of O(N).

Adaptive Gradient-Based Methods for Adaptive Power Allocation in OFDM-Based Cognitive Radio Networks

Previously, a scheme in [1] is proposed for the subcarrier, bit, and power allocation problem to minimize the total transmit power for multiuser orthogonal frequency division multiplexing systems in downlink transmission. However, it is a batch mode which may not be so efficient in terms of computational complexity for slowly time-varying channel environments. The solution of the current frame can be obtained with slight modification from that of the previous frame in an adaptive fashion. By utilizing this property, we propose a scheme to obtain the solution in the adaptive fashion, which offers comparable performance with a reduced complexity compared to the previously proposed method and other existing suboptimal methods. Based on a derived expression composed of the channel gains, the numbers of assigned subcarriers, and the data rates along with the new proposed processing procedures, the proposed adaptive scheme is able to track the channel variation for the solution adjustment in a faster speed compared to the original batch mode method. Simulation results reveal that the proposed adaptive scheme has the competitive performance compared with those of the optimal and the existing schemes while the computational complexity and the number of iterations are both reduced.

An Adaptive Allocation Scheme in Multiuser OFDM Systems with Time-Varying Channels

Orthogonal frequency division multiplex-based femtocell networks in downlink with two-tier interference are considered in this paper. In order to satisfy the quality of service of macrocell users, a capacity maximization problem with the total and the upper power constraints by allocating power to subcarriers for a user in femtocell systems becomes important. In this paper, the optimal power allocation is derived by using the Lagrangian technique. Based on the analysis of the Karush-Kuhn-Tucker conditions, subcarriers can be classified into two sets with different power allocation strategies according to the upper power constraint. One set of subcarriers is allocated with upper power, and the other set of subcarriers is processed by using the waterfilling approach. A direct linear search scheme is presented to achieve the optimal performance by finding the threshold over the channel states of all subcarriers to determine the two sets. In order to reduce the computational load, a reduced complexity scheme is designed for the optimal solution by utilizing the relationship of the allocated power in the two sets of subcarriers. Unlike the schemes in iterative manners, a fast power allocation scheme with a near-optimal performance is also developed. Simulation results reveal that the proposed schemes outperform the existing scheme. The efficacy of the proposed schemes is demonstrated in the simulations.

Power Allocation Schemes in OFDM-Based Femtocell Networks

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Wei-Chen Pao

Author Tools

Chat about Author

Papers

Adaptive Gradient-Based Methods for Adaptive Power Allocation in OFDM-Based Cognitive Radio Networks

An Adaptive Allocation Scheme in Multiuser OFDM Systems with Time-Varying Channels

Power Allocation Schemes in OFDM-Based Femtocell Networks