scholarly journals Retraction Note to: Throughput maximization of multichannel allocation mechanism under interference constraint for hybrid overlay/underlay cognitive radio networks with energy harvesting

2021 ◽  
Author(s):  
Hakan Murat Karaca
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Throughput Maximization ◽  
Allocation Mechanism ◽  
Interference Constraint ◽  
Underlay Cognitive Radio

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.

Auction-Based Throughput Maximization in Cognitive Radio Networks Under Interference Constraint

2013 ◽  
Vol 72 (2) ◽  
pp. 1259-1275 ◽  
Author(s):  
Hakan Murat Karaca ◽  
Tolga Kurt ◽  
Salih Zafer Dicle ◽  
Emin Anarim
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Throughput Maximization ◽  
Interference Constraint
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