CTH01-3: A Low-complexity Adaptive Subcarrier, Bit, and Power Allocation Algorithm for OFDMA Systems

2006 ◽  
Author(s):  
Long Gao ◽  
Shuguang Cui ◽  
Feifei Li
Keyword(s):  
Power Allocation ◽  
Low Complexity ◽  
Allocation Algorithm

scholarly journals Power Allocation Algorithm for an Energy-Harvesting Wireless Transmission System Considering Energy Losses

Algorithms ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 25
Author(s):  
Su Zhao ◽  
Gang Huang ◽  
Qi Zhu
Keyword(s):  
Energy Harvesting ◽  
Power Allocation ◽  
Online Algorithm ◽  
Optimization Methods ◽  
Low Complexity ◽  
Transmission System ◽  
Wireless Transmission ◽  
Energy Losses ◽  
Average Throughput ◽  
Allocation Algorithm

For an energy-harvesting wireless transmission system, considering that a transmitter which can harvest energy from nature has two kinds of extra energy consumption, circuit consumption and storage losses, the optimization models are set up in this paper for the purpose of maximizing the average throughput of the system within a certain period of time for both a time-invariant channel and time-varying channel. Convex optimization methods such as the Lagrange multiplier method and the KKT (Karush–Kuhn–Tucker) condition are used to solve the optimization problem; then, an optimal offline power allocation algorithm which has a three-threshold structure is proposed. In the three-threshold algorithm, two thresholds can be achieved by using a linear search method while the third threshold is calculated according to the channel state information and energy losses; then, the offline power allocation is based on the three thresholds and energy arrivals. Furthermore, inspired by the optimal offline algorithm, a low-complexity online algorithm with adaptive thresholds is derived. Finally, the simulation results show that the offline power allocation algorithms proposed in this paper are better than other algorithms, the performance of the online algorithm proposed is close to the offline one, and these algorithms can help improve the average throughput of the system.

The Waterfilling Based Subcarrier and Power Allocation for OFDM Cognitive Radio Networks

2012 ◽  
Vol 601 ◽  
pp. 406-412
Author(s):  
Yue Huai Ma ◽  
Dong Mei Zhang ◽  
You Yun Xu
Keyword(s):  
Cognitive Radio ◽  
Power Allocation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Cognitive Radio Network ◽  
Low Complexity ◽  
Radio Networks ◽  
Secondary Users ◽  
Allocation Algorithm ◽  
Primary Network ◽  
Primary Receiver

In this paper, the subcarrier and power allocation problem for the orthogonal frequency division multiplexing (OFDM) cognitive radio network which coexists with the primary network is studied. Specifically, in consideration of both transmit power constraints of secondary users and interference power constraint at each primary receiver. A cognitive waterfilling (CWF) power allocation algorithm which based upon the classical waterfilling mechanism is proposed for the single SU and multi-PU scenario. As for the multi-SU and multi-PU case, we present an efficient joint subcarrier and power allocation algorithm called MS-CWF algorithm with low complexity. Simulation results show the effectiveness of the proposed CWF and MS-CWF algorithms.

scholarly journals An Efficient Resource Allocation Algorithm for OFDM-Based NOMA in 5G Systems

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1399 ◽  
Author(s):  
Omar A. Saraereh ◽  
Amer Alsaraira ◽  
Imran Khan ◽  
Peerapong Uthansakul
Keyword(s):  
Resource Allocation ◽  
Power Allocation ◽  
Multiple Access ◽  
Low Complexity ◽  
System Capacity ◽  
Resource Allocation Algorithm ◽  
Allocation Algorithm ◽  
User Grouping ◽  
Power Domain ◽  
Efficient Resource

Non-orthogonal multiple access (NOMA) has become the key technology in the future 5G wireless networks. It can achieve multi-user multiplexing in the transmit power domain by allocating different power, which can effectively improve the system capacity and spectral efficiency. Aiming at the problem of high computational complexity and improving system capacity in non-orthogonal multiple access (NOMA) based on orthogonal frequency division multiple access (OFDMA) for 5G wireless cellular networks, this paper proposes an improved low complexity radio resource allocation algorithm for user grouping and power allocation optimization. The optimization model is established with the goal of maximizing system capacity. Through the step-by-step optimization idea, the complex non-convex optimization problem is decomposed into two sub-problems to be solved separately. Firstly, all users are grouped based on the greedy method, and then the power allocation is performed on the sub-carriers of the fixed group. Simulation results show that the proposed algorithm has better system capacity than the existing state-of-the-art algorithms and reduced complexity performance.

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