scholarly journals A Resource Allocation Evolutionary Algorithm for OFDM Based on Karush-Kuhn-Tucker Conditions

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Hai-Lin Liu ◽  
Qiang Wang
Keyword(s):  
Resource Allocation ◽  
Evolutionary Algorithm ◽  
Power Allocation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Resource Scheduling ◽  
Computer Experiments ◽  
Kkt Conditions ◽  
Subcarrier Allocation ◽  
Frequency Division ◽  
Step Method

For orthogonal frequency division multiplexing (OFDM), resource scheduling plays an important role. In resource scheduling, power allocation and subcarrier allocation are not independent. So the conventional two-step method is not very good for OFDM resource allocation. This paper proposes a new method for OFDM resource allocation. This method combines evolutionary algorithm (EA) with Karush-Kuhn-Tucker conditions (KKT conditions). In the optimizing process, a set of subcarrier allocation programs are made as a population of evolutionary algorithm. For each subcarrier allocation program, a power allocation program is calculated through KKT conditions. Then, the system rate of each subcarrier allocation program can be calculated. The fitness of each individual is its system rate. The information of optimizing subcarrier and power allocation can be interacted with each other. So, it can overcome the shortcoming of the two-step method. Computer experiments show the proposed algorithm is effective.

scholarly journals Mobile Fog Computing-Assisted Resource Allocation for Two-Hop SWIPT OFDM Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaofei Di ◽  
Yu Zhang ◽  
Tong Liu ◽  
Shaoli Kang ◽  
Yue Zhao
Keyword(s):  
Resource Allocation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Fog Computing ◽  
Achievable Rate ◽  
Fast Time ◽  
Power Splitting ◽  
Frequency Division ◽  
Decode And Forward ◽  
Subcarrier Pairing ◽  
Receiver Architecture

The mobile fog computing-assisted resource allocation (RA) is studied for simultaneous wireless information and power transfer (SWIPT) two-hop orthogonal frequency division multiplexing (OFDM) networks, where a decode-and-forward (DF) relay first harvests energy from signals emitted by a source and then helps the source to forward information to its destination by using the harvested energy. Power splitting (PS) strategy is adopted at the relay and a different PS (DPS) receiver architecture is proposed, where the PS factors of all subcarriers are different. A RA problem is formulated to maximize the system’s achievable rate by jointly optimizing subcarrier pairing, power allocation, and PS factors. Since the RA problem is a nonconvex problem and is difficult to solve, an efficient RA algorithm is designed. As the wireless channels are fast time-varying, the computation is performed in mobile fog node close to end nodes, instead of remote clouds. Results demonstrate that the achievable rate is significantly increased by using the proposed RA algorithm. It is also found that the computation complexity of RA algorithm of DPS receiver architecture is much lower than the existing identical PS (IPS) receiver architecture, and thus the proposed DPS architecture is more suitable for computation-constrained fog system.

QoS-Constrained Resource Allocation Scheduling for LTE Network

2015 ◽  
Vol 4 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Hung-Chin Jang ◽  
Yun-Jun Lee
Keyword(s):  
Resource Allocation ◽  
Data Transmission ◽  
Orthogonal Frequency Division Multiplexing ◽  
Transmission Rate ◽  
High Mobility ◽  
System Throughput ◽  
Frequency Division ◽  
High Data ◽  
Single Carrier ◽  
Allocation Method

The goal of LTE (Long Term Evolution) is to provide high data transmission rate, scalable bandwidth, low latency, high-mobility, etc. LTE employs OFDM (Orthogonal Frequency Division Multiplexing) and SC-FDMA (Single Carrier - Frequency Division Multiple Access) for downlink and uplink data transmission, respectively. As to SC-FDMA, there are two constraints in doing resource allocation. First, the allocated resource blocks (RBs) should be contiguous. Second, those of the allocated RBs are forced to use the same modulation technique. The aim of this research is to propose a QoS-constraint resource allocation scheduling to enhance data transmission for uplink SC-FDMA. The proposed scheduling is a three-stage approach. In the first stage, it uses a time domain scheduler to differentiate user equipment (UE) services according to their distinct QoS service requirements. In the second stage, it uses a frequency domain scheduler to prioritize UE services based on channel quality. In the third stage, it limits the number of times of modulation downgrade of RBs allocation in order to enhance system throughput. In the simulations, the proposed method is compared to fixed sub-carrier dynamic resource allocation method and adaptive dynamic sub-carrier resource allocation method. Simulation results show that the proposed method outperforms the other two methods in terms of throughput, transmission delay, packet loss ratio, and RB utilization.

scholarly journals Novel Resource Allocation Techniques for Downlink Non-Orthogonal Multiple Access Systems

2020 ◽  
Vol 10 (17) ◽  
pp. 5892 ◽  
Author(s):  
Zuhura J. Ali ◽  
Nor K. Noordin ◽  
Aduwati Sali ◽  
Fazirulhisyam Hashim ◽  
Mohammed Balfaqih
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Power Allocation ◽  
Multiple Access ◽  
High Capacity ◽  
Kkt Conditions ◽  
Optimal Power Allocation ◽  
User Pairing ◽  
Optimal Power ◽  
Sum Rate

Non-orthogonal multiple access (NOMA) plays an important role in achieving high capacity for fifth-generation (5G) networks. Efficient resource allocation is vital for NOMA system performance to maximize the sum rate and energy efficiency. In this context, this paper proposes optimal solutions for user pairing and power allocation to maximize the system sum rate and energy efficiency performance. We identify the power allocation problem as a nonconvex constrained problem for energy efficiency maximization. The closed-form solutions are derived using Karush–Kuhn–Tucker (KKT) conditions for maximizing the system sum rate and the Dinkelbach (DKL) algorithm for maximizing system energy efficiency. Moreover, the Hungarian (HNG) algorithm is utilized for pairing two users with different channel condition circumstances. The results show that with 20 users, the sum rate of the proposed NOMA with optimal power allocation using KKT conditions and HNG (NOMA-PKKT-HNG) is 6.7% higher than that of NOMA with difference of convex programming (NOMA-DC). The energy efficiency with optimal power allocation using DKL and HNG (NOMA-PDKL-HNG) is 66% higher than when using NOMA-DC.

scholarly journals Energy consumption index minimized resource allocation in hybrid energy multiuser OFDM system with distributed antennas

2018 ◽  
Vol 17 ◽  
pp. 03015
Author(s):  
Huanhuan MAO ◽  
Pengcheng Zhu ◽  
Jiamin Li
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Energy Harvesting ◽  
Power Allocation ◽  
Base Station ◽  
Mixed Integer ◽  
Subcarrier Allocation ◽  
Ofdm System ◽  
Consumption Index ◽  
Distributed Antennas

Energy harvesting is one of the promising option for realization of green communication and has been a growing concern recently. In this paper, we address the downlink resource allocation in OFDM system with distributed antennas with hybrid power supply base station, where energy harvesting and non-renewable power sources are used complementarily. A joint subcarrier and power allocation problem is formulated for minimizing the net Energy Consumption Index (ECI) with system Quality of Service (QoS) and bit error rates constraint. The problem is a 0-1 mixed integer nonlinear programming problem due to the binary subcarrier allocation variable. To solve the problem, we design an algorithm based on Lagrange relaxation method and fraction programming which optimizes the power allocation and subcarrier allocation iteratively in two nests. Simulation results show that the proposed algorithm converges in a small number of iterations and can improve net ECI of system greatly.

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