Two-way spectrum sharing protocol in overlay cognitive radio network

2017 ◽  
Author(s):  
Said Emam ◽  
M. E. Celebi
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sharing ◽  
Cognitive Radio Network ◽  
Radio Network

Spectrum Trading Analyze in the Spectrum Sharing Framework in Cognitive Radio Networks

2019 ◽  
Vol 10 (1) ◽  
pp. 1-18
Author(s):  
Prince Semba Yawada ◽  
Mesmin J. Mbyamm Kiki ◽  
Mai Trung Dong
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sharing ◽  
Cognitive Radio Network ◽  
Radio Networks ◽  
Radio Network ◽  
Primary Operator ◽  
Bertrand Model ◽  
Competitive Prices ◽  
Effective Design

The effective design of a cognitive radio network must take into account economic and technical aspects. This article presents a commercial formulation of the spectrum by the primary operators who decide to sell a part of their spectrum to a group of cognitive users in order to earn money and to promote the efficient use of the spectrum. Three systems of spectrum pricing are compared and suggested, such as the cooperative price based on the optimization of the profits, the market equilibrium, and the competitive prices focused on the competition of Bertrand. The Bertrand model examines the influences of certain parameters of the system such as the quality of the channel based on the Nash equilibrium and the substitutability of the spectrum. The differences in the various aspects of these systems of pricing are presented through the graphs. The authors note through the obtained result that the profit of the primary operator depends not only on the demand quantity of the spectrum but also on the behavior of the primary operators.

scholarly journals Capacity optimization for radio resource allocation in cognitive networks

2021 ◽  
Author(s):  
Mohamed Elalem
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sharing ◽  
Cognitive Radio Network ◽  
Radio Spectrum ◽  
Opportunistic Spectrum Access ◽  
Effective Capacity ◽  
Radio Network ◽  
Spectrum Access ◽  
Primary Users ◽  
Access Model

With the rapid development of wireless services and applications, the currently radio spectrum is becoming more crowded. How to accommodate more wireless services and applications within the limited radio spectrum becomes a big challenge faced by modern society. Cognitive radio (CR) is proposed as a promising technology to tackle this challenge by introducing secondary users (SUs) to opportunistically or concurrently access the spectrum allocated to primary users (PUs). Currently, there are two prevalent CR models: the spectrum sharing model and the opportunistic spectrum access model. In the spectrum sharing model, the SUs are allowed to coexist with the PUs as long as the interferences from SUs do not degrade the quality of service (QoS) of PUs to an unacceptable level. In the opportunistic spectrum access model, SUs are allowed to access the spectrum only if the PUs are detected to be inactive. These two models known as underlay and overlay schemes, respectively. This thesis studies a number of topics in CR networks under the framework of these two schemes. First, studied cognitive radio transmissions under QoS delay constraints. Initially, we focused on the concept: effective capacity for cognitive radio channels in order to identify the performance in the presence of QoS constraints. Both underlay and overlay schemes are studied taking into consideration the activity of primary users, and assuming the general case of channel fading as Gamma distribution. For this setting, we further proposed a selection criterion by which the cognitive radio network can choose the adequate mode of operation. Then, we studied the cognitive radio transmissions focusing on Rayleigh fading channel and assumed that no prior channel knowledge is available at the transmitter and the receiver. We investigated the performance of pilot-assisted transmission strategies. In particular, we analyzed the channel estimation using minimum mean-square-error (MMSE) estimation, and analyzed efficient resource allocation strategies. In both cases, power allocations and effective capacity optimization were obtained. Effective capacity and interference constraint were analyzed in both single-band and multi-band spectrum sensing settings. Finally, we studied optimal access probabilities for cognitive radio network using Markov model to achieve maximum throughput for both CR schemes.

Basic Spectrum Sensing Techniques

2019 ◽  
pp. 70-84
Author(s):  
Bhuvaneswari P. T. V. ◽  
Bino J.
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Spectrum Sharing ◽  
Cognitive Radio Network ◽  
Radio Spectrum ◽  
Spectrum Management ◽  
Radio Network ◽  
Spectrum Band ◽  
Radio Systems ◽  
Networking Technology

Cognitive radio network (CRN) is an upcoming networking technology that can utilize both radio spectrum and wireless resources efficiently based on the information gathered from the past experience. There are two types of users in CRN, namely primary and secondary. PUs (PU) have the license to operate in certain spectrum band while the secondary (SU) or cognitive radio (CR) users do not have the license to operate in the desired band. However, they can opportunistically utilize the unused frequency bands. Spectrum sensing, spectrum management, spectrum sharing, and spectrum mobility are the four major functions of cognitive radio systems. The main objective of spectrum sensing is to provide better spectrum access to CR users, without causing any harmful interference to PUs. Sensing accuracy is considered as the most important factor to determine the performance of cognitive radio network. In this chapter, the challenges and requirement involved in spectrum sensing are detailed. Further, various spectrum sensing basic techniques are also discussed in detail.

scholarly journals A Graph Convolutional Network-Based Deep Reinforcement Learning Approach for Resource Allocation in a Cognitive Radio Network

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5216
Author(s):  
Di Zhao ◽  
Hao Qin ◽  
Bin Song ◽  
Beichen Han ◽  
Xiaojiang Du ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Reinforcement Learning ◽  
Cognitive Radio ◽  
Spectrum Sharing ◽  
Cognitive Radio Network ◽  
Radio Network ◽  
Model Learning ◽  
Secondary Users ◽  
Convolutional Network ◽  
Optimal Resource

Cognitive radio (CR) is a critical technique to solve the conflict between the explosive growth of traffic and severe spectrum scarcity. Reasonable radio resource allocation with CR can effectively achieve spectrum sharing and co-channel interference (CCI) mitigation. In this paper, we propose a joint channel selection and power adaptation scheme for the underlay cognitive radio network (CRN), maximizing the data rate of all secondary users (SUs) while guaranteeing the quality of service (QoS) of primary users (PUs). To exploit the underlying topology of CRNs, we model the communication network as dynamic graphs, and the random walk is used to imitate the users’ movements. Considering the lack of accurate channel state information (CSI), we use the user distance distribution contained in the graph to estimate CSI. Moreover, the graph convolutional network (GCN) is employed to extract the crucial interference features. Further, an end-to-end learning model is designed to implement the following resource allocation task to avoid the split with mismatched features and tasks. Finally, the deep reinforcement learning (DRL) framework is adopted for model learning, to explore the optimal resource allocation strategy. The simulation results verify the feasibility and convergence of the proposed scheme, and prove that its performance is significantly improved.

Sign in / Sign up

Export Citation Format

Share Document