scholarly journals Power allocation in OFDM-based cognitive radio systems using iterative algorithms

2021 ◽  
Author(s):  
Aniqua Tasnim Rahman Antora
Keyword(s):  
Cognitive Radio ◽  
Power Allocation ◽  
Peak Power ◽  
Radio Resource ◽  
Power Constraint ◽  
Power Constraints ◽  
Cognitive Radio Systems ◽  
Water Filling ◽  
Radio Systems ◽  
Water Filling Algorithm

As spectrum scarcity is becoming a serious problem, the worth of finding a general solution for such issue has become even serious due to the rapid development of wireless communications. The main objective of this thesis is to investigate the optimal power allocation procedure that maximizes the capacity in OFDM based Cognitive Radio Systems. The main purpose of the search is to modify the conventional water-filling algorithm applied in general OFDM based Cognitive Radio systems due to the per subchannel power constraints and individual peak power constraints. For Radio Resource Allocation (RRA), one of the most typical problems is to solve power allocation using the Conventional Water- filling. As communication system develops, the structures of the system models and the corresponding RRA problems evolve to more advanced and more complicated ones. In this thesis Iterative Partitioned Weighted Geometric Water-filling with Individual Peak Power Constraints (IGPP), a simple and elegant approach is proposed to solve the weighted radio resource allocation problem with peak power constraint and total subchannel power constraint with channel partitions. The proposed IGPP algorithm requires less computation than the Conventional Water-filling algorithm (CWF). Dynamic Channel Sensing Iterative (DCSI) approach is another algorithm proposed to optimally allocate power for OFDM based Cognitive Radio Systems. DCSI is a innovative concept which will allow us to solve the same problem intelligently with less complexity. It provides straight forward power allocation analysis, solutions and insights with reduced computation over other approaches under the same memory requirement and sorted parameters.

scholarly journals Power allocation in OFDM-based cognitive radio systems using iterative algorithms

2021 ◽  
Author(s):  
Aniqua Tasnim Rahman Antora
Keyword(s):  
Cognitive Radio ◽  
Power Allocation ◽  
Peak Power ◽  
Radio Resource ◽  
Power Constraint ◽  
Power Constraints ◽  
Cognitive Radio Systems ◽  
Water Filling ◽  
Radio Systems ◽  
Water Filling Algorithm

As spectrum scarcity is becoming a serious problem, the worth of finding a general solution for such issue has become even serious due to the rapid development of wireless communications. The main objective of this thesis is to investigate the optimal power allocation procedure that maximizes the capacity in OFDM based Cognitive Radio Systems. The main purpose of the search is to modify the conventional water-filling algorithm applied in general OFDM based Cognitive Radio systems due to the per subchannel power constraints and individual peak power constraints. For Radio Resource Allocation (RRA), one of the most typical problems is to solve power allocation using the Conventional Water- filling. As communication system develops, the structures of the system models and the corresponding RRA problems evolve to more advanced and more complicated ones. In this thesis Iterative Partitioned Weighted Geometric Water-filling with Individual Peak Power Constraints (IGPP), a simple and elegant approach is proposed to solve the weighted radio resource allocation problem with peak power constraint and total subchannel power constraint with channel partitions. The proposed IGPP algorithm requires less computation than the Conventional Water-filling algorithm (CWF). Dynamic Channel Sensing Iterative (DCSI) approach is another algorithm proposed to optimally allocate power for OFDM based Cognitive Radio Systems. DCSI is a innovative concept which will allow us to solve the same problem intelligently with less complexity. It provides straight forward power allocation analysis, solutions and insights with reduced computation over other approaches under the same memory requirement and sorted parameters.

scholarly journals Power allocation in OFDM-based cognitive radio systems

2021 ◽  
Author(s):  
Shibiao Zhao
Keyword(s):  
Cognitive Radio ◽  
Power Allocation ◽  
Optimal Power Allocation ◽  
Power Constraint ◽  
Interference Constraints ◽  
Allocation Algorithm ◽  
Optimal Power ◽  
Water Filling ◽  
Water Filling Algorithm ◽  
Allocation Algorithms

In this thesis, we develop an subcarrier transmission suboptimal power allocation algorithm and an underlay subcarrier transmission optimal power allocation algorithm for the orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems with different statistical interference constraints imposed by different primary users (PUs). Given the fact that the interference constraints are met in a statistical manner, the CR transmitter does not require the instantaneous channel quality feed-back from the PU receivers. First an alternative subcarrier transmission suboptimal algorithm with reduced complexity has been proposed and the performance has been investigated. Presented numerical results show that with our proposed suboptimal power allocation algorithm CR user can achieve 10 percent higher transmission capacity for given statistical interference constraints and a given power budget compared to the traditional suboptimal power allocation algorithms, uniform and water-filling power allocation algorithms. The proposed suboptimal algorithm outperforms traditional suboptimal algorithm, water-filling algorithm and uniform power loading algorithm. Second,We introduce an underlay subcarrier transmission optimal power allocation algorithms which allows the secondary users use the bandwidth used by Pus. And at the same time we consider the individual peak power constraint as the forth constraint added to the objective function which is the transmission capacity rate of the secondary users.Third, we propose suboptimal algorithm using GWF which has less complexity level than traditional water-filling algorithm instead of conventional water-filling algorithm in calculating the assigned power while considering the satisfaction of the total power constraint. The proposed suboptimal algorithm gives an option of using a low complexity power allocation algorithm where complexity is an issue.

scholarly journals Performance of Equal Power Allocation in Multiuser OFDM-Based Cognitive Radio Systems

2008 ◽  
Vol 2008 ◽  
pp. 1-4 ◽  
Author(s):  
Yonghong Zhang ◽  
Cyril Leung
Keyword(s):  
Cognitive Radio ◽  
Power Allocation ◽  
Activity Levels ◽  
Cognitive Radio Systems ◽  
Water Filling ◽  
Radio Systems ◽  
Cr System ◽  
Equal Power Allocation ◽  
Equal Power ◽  
Multiuser Ofdm

The performance difference between a simple equal subchannel power allocation and the optimal water-filling subchannel power allocation schemes is studied for a multiuser OFDM-based cognitive radio (CR) system. It is shown that this difference depends on the average subchannel gain variations among the CR users as well as the activity levels of the primary users.

scholarly journals Power allocation in OFDM-based cognitive radio systems

2021 ◽  
Author(s):  
Shibiao Zhao
Keyword(s):  
Cognitive Radio ◽  
Power Allocation ◽  
Optimal Power Allocation ◽  
Power Constraint ◽  
Interference Constraints ◽  
Allocation Algorithm ◽  
Optimal Power ◽  
Water Filling ◽  
Water Filling Algorithm ◽  
Allocation Algorithms

In this thesis, we develop an subcarrier transmission suboptimal power allocation algorithm and an underlay subcarrier transmission optimal power allocation algorithm for the orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems with different statistical interference constraints imposed by different primary users (PUs). Given the fact that the interference constraints are met in a statistical manner, the CR transmitter does not require the instantaneous channel quality feed-back from the PU receivers. First an alternative subcarrier transmission suboptimal algorithm with reduced complexity has been proposed and the performance has been investigated. Presented numerical results show that with our proposed suboptimal power allocation algorithm CR user can achieve 10 percent higher transmission capacity for given statistical interference constraints and a given power budget compared to the traditional suboptimal power allocation algorithms, uniform and water-filling power allocation algorithms. The proposed suboptimal algorithm outperforms traditional suboptimal algorithm, water-filling algorithm and uniform power loading algorithm. Second,We introduce an underlay subcarrier transmission optimal power allocation algorithms which allows the secondary users use the bandwidth used by Pus. And at the same time we consider the individual peak power constraint as the forth constraint added to the objective function which is the transmission capacity rate of the secondary users.Third, we propose suboptimal algorithm using GWF which has less complexity level than traditional water-filling algorithm instead of conventional water-filling algorithm in calculating the assigned power while considering the satisfaction of the total power constraint. The proposed suboptimal algorithm gives an option of using a low complexity power allocation algorithm where complexity is an issue.

Optimal Cooperative Sensing Assignment and Radio Resource Allocations for Cognitive Radio Systems

2012 ◽  
Vol 12 (1) ◽  
pp. 80-88
Author(s):  
Qionghua Zhu ◽  
Yuan Wu ◽  
Peng Hong ◽  
Liping Qian ◽  
Jingyu Hua ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Cooperative Sensing ◽  
Resource Allocations ◽  
Radio Resource ◽  
Cognitive Radio Systems ◽  
Radio Systems
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