Applying a Fuzzy-Based Dynamic Channel Allocation Mechanism to Cognitive Radio Networks

2017 ◽  
Author(s):  
Ying-Hong Wang ◽  
Shou-Li Liao
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Channel Allocation ◽  
Radio Networks ◽  
Allocation Mechanism ◽  
Dynamic Channel Allocation ◽  
Dynamic Channel

Age of Information Minimization of Multichannel Allocation Mechanism for Hybrid Cognitive Radio Networks with Energy Harvesting under Collusion Constraint

2021 ◽  
Author(s):  
Hakan Murat Karaca
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Cognitive Radio Networks ◽  
Channel Allocation ◽  
Radio Networks ◽  
Allocation Mechanism ◽  
Industrial Networks ◽  
Channel Interference ◽  
Promising Solution ◽  
Age Of Information

Abstract Cognitive radio networks (CRNs) with energy harvesting has been a promising solution for wireless industrial networks and seems a promising solution for the spectrum scarcity problem. However, it is critical the wireless spectrum should carefully be managed in order to fullfill the tight requirements on the trustworthy and minimum delayed delivery of information. Motivated by this, in order to represent the freshness of the information, this paper takes into account the metric of age of information (AoI) and multi-channel allocation problem in hybrid cognitive radio networks where secondary transmitters (STs) are able to harvest energy is investigated to maximize allocation performance while minimizing average AOI values. A novel mechanism has been proposed to restrict average AoI values while distributing channels to STs by handling both collusion and energy constraints. STs are prioritized based on a proposed metric and they are able to obtain channels only if the resulting AoI value satisfy proposed conditions. AoI values are computed based on co-channel interference between STs and minimized by decreasing interference levels. For comparison, two algorithms were considered: a greedy mechanism for m-channel allocation of hybrid CRNs with harvesting, but without AOI control and the proposed m-channel allocation schemes based on sorting STs according to the proposed metric and controlling AOI levels based on co-channel interference. The simulations depict that performance of the proposed m-channel allocation method outweighs the greedy algorithm in terms of both AoI minimization and maximization of channel allocation performance, proving the superiority of the proposed algorithm.

scholarly journals Age of Information Minimization of Multichannel Allocation Mechanism for Hybrid Cognitive Radio Networks with Energy Harvesting under Collusion Constraint

2021 ◽  
Author(s):  
HAKAN MURAT KARACA
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Cognitive Radio Networks ◽  
Channel Allocation ◽  
Radio Networks ◽  
Allocation Mechanism ◽  
Industrial Networks ◽  
Channel Interference ◽  
Promising Solution ◽  
Age Of Information

Abstract Cognitive radio networks (CRNs) with energy harvesting has been a promising solution for wireless industrial networks and seems a promising solution for the spectrum scarcity problem. However, it is critical the wireless spectrum should carefully be managed in order to fullfill the tight requirements on the trustworthy and minimum delayed delivery of information. Motivated by this, in order to represent the freshness of the information, this paper takes into account the metric of age of information (AoI) and multi-channel allocation problem in hybrid cognitive radio networks where secondary transmitters (STs) are able to harvest energy is investigated in terms of both maximization of allocation performance while minimizing average AOI values. A novel mechanism has been proposed to restrict average AoI values while distributing channels to STs by handling both collusion and energy constraints. STs are prioritized based on a proposed metric and they are able to obtain channels only if the resulting AoI value satisfy proposed conditions. AoI values are computed based on co-channel interference between STs and minimized by decreasing interference levels. For comparison, two algorithms were considered: a greedy mechanism for m-channel allocation of hybrid CRNs with harvesting, but without AOI control and the proposed m-channel allocation schemes based on sorting STs according to the proposed metric and controlling AOI levels based on co-channel interference. The simulations depict that performance of the proposed m-channel allocation method outweighs the greedy algorithm in terms of both AoI minimization and maximization of channel allocation performance, proving the superiority of the proposed algorithm.

scholarly journals Throughput Optimization of Multichannel Allocation Mechanism under Interference Constraint for Hybrid Overlay/underlay Cognitive Radio Networks with Energy Harvesting

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 330 ◽  
Author(s):  
Hakan Murat Karaca
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Cognitive Radio Networks ◽  
Point Processes ◽  
Channel Allocation ◽  
Radio Networks ◽  
Life Cycles ◽  
Throughput Optimization ◽  
Allocation Mechanism ◽  
Rf Signals

By harvesting energy from ambient radio frequency (RF) signals, significant progress has been achieved in wireless networks self-maintaining their life cycles. Motivated by this and improved spectrum reuse by combined use of overlay/underlay modes of cognitive radio networks (CRNs), this paper proposes a novel multi-channel (m-channel) allocation performance maximization algorithm for low-power mobiles. CRNs, called secondary transmitters (STs), can harvest energy from RF signals by nearby active primary transmitters (PTs). In the proposed scheme, PTs and STs are distributed as independent homogeneous Poisson point processes and contact their receivers at fixed distances. Each PT contains a guard zone to protect its intended receiver from ST interference, and provides RF energy to STs located in its harvesting zone. Prioritization of STs during opportunistic allocation of channels is critical as properties like energy level and harvesting capability improve channel distribution performance. A novel metric is proposed that prioritizes STs based on initial energy levels, harvesting capability, and number of channels through which they can transmit. For comparison, three algorithms were considered: a greedy mechanism for m-channel allocation of hybrid CRNs without harvesting, the proposed m-channel allocation schemes based on maximum independent sets (MIS), and the proposed metric of hybrid CRNs with harvesting capability. The simulations show that the proposed m-channel allocation method based on MIS outperforms the greedy algorithm. The proposed m-channel allocation using the proposed metric on hybrid CRNs with energy harvesting ability produced the best performance of the three methods, proving the superiority of the proposed algorithm.

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