Throughput optimization for dual collaborative spectrum sensing with dynamic scheduling

2017 ◽  
Vol 31 (19-21) ◽  
pp. 1740089 ◽  
Author(s):  
Cuimei Cui ◽  
Dezhi Yang
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Optimization Algorithm ◽  
Ad Hoc ◽  
Dynamic Scheduling ◽  
Throughput Optimization ◽  
Shadow Fading ◽  
Average Throughput ◽  
Collaborative Spectrum Sensing ◽  
Sensing Time

Cognitive radio technology is envisaged to alleviate both spectrum inefficiency and spectrum scarcity problems by exploiting the existing licensed spectrum opportunistically. However, cognitive radio ad hoc networks (CRAHNs) impose unique challenges due to the high dynamic scheduling in the available spectrum, diverse quality of service (QOS) requirements, as well as hidden terminals and shadow fading issues in a harsh radio environment. To solve these problems, this paper proposes a dynamic and variable time-division multiple-access scheduling mechanism (DV-TDMA) incorporated with dual collaborative spectrum sensing scheme for CRAHNs. This study involves the cross-layered cooperation between the Physical (PHY) layer and Medium Access Control (MAC) layer under the consideration of average sensing time, sensing accuracy and the average throughput of cognitive radio users (CRs). Moreover, multiple-objective optimization algorithm is proposed to maximize the average throughput of CRs while still meeting QOS requirements on sensing time and detection error. Finally, performance evaluation is conducted through simulations, and the simulation results reveal that this optimization algorithm can significantly improve throughput and sensing accuracy and reduce average sensing time.

scholarly journals Evolutionary Game Theory-Based Collaborative Sensing Model in Emergency CRAHNs

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Sasirekha GVK ◽  
Jyotsna Bapat
Keyword(s):  
Game Theory ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Evolutionary Game Theory ◽  
Ad Hoc ◽  
Evolutionary Game ◽  
Autonomous Systems ◽  
Simulation Models ◽  
Signal To Noise ◽  
Collaborative Spectrum Sensing

Game theory has been a tool of choice for modeling dynamic interactions between autonomous systems. Cognitive radio ad hoc networks (CRAHNs) constituted of autonomous wireless nodes are a natural fit for game theory-based modeling. The game theory-based model is particularly suitable for “collaborative spectrum sensing” where each cognitive radio senses the spectrum and shares the results with other nodes such that the targeted sensing accuracy is achieved. Spectrum sensing in CRAHNs, especially when used in emergency scenarios such as disaster management and military applications, needs to be not only accurate and resource efficient, but also adaptive to the changing number of users as well as signal-to-noise ratios. In addition, spectrum sensing mechanism must also be proactive, fair, and tolerant to security attacks. Existing work in collaborative spectrum sensing has mostly been confined to resource efficiency in static systems using request-based reactive sensing resulting in high latencies. In this paper, evolutionary game theory (EGT) is used to model the behavior of the emergency CRAHNS, providing an efficient model for collaborative spectrum sensing. The resulting implementation model is adaptive to the changes in its environment such as signal-to-noise ratio and number of users in the network. The analytical and simulation models presented validate the system design and the desired performance.

Spectrum Sensing in Emergency Cognitive Radio Ad Hoc Networks

2013 ◽  
pp. 86-102
Author(s):  
Sasirekha GVK ◽  
Jyotsna Bapat
Keyword(s):  
Cognitive Radio ◽  
Ad Hoc Networks ◽  
Spectrum Sensing ◽  
Ad Hoc ◽  
Cognitive Radios ◽  
Distributed Architectures ◽  
Emergency Situations ◽  
Collaborative Spectrum Sensing ◽  
Military Applications ◽  
Hoc Networks

Ad hoc networks are infrastructure less networks which are self organizing and adaptive. Such networks can be used in emergency situations like disaster management and military applications. Usage of cognitive radios as the wireless terminals in ad hoc networks in emergency situations has distinct advantages. Better bandwidth, interoperability, avoidance of interference, and ant-jamming capabilities are a few such advantages. Ad hoc networks with cognitive radios are wireless terminals used in emergency situations and can be referred to as Emergency Cognitive Radio Ad Hoc Networks (Emergency CRAHNs). In this chapter, the authors discuss emergency CRAHNs and the specific requirements that must be met by the spectrum sensing mechanism used by them. In particular, the authors discuss collaborative spectrum sensing methodology; where in multiple cognitive radios operate together such that reliability of spectrum sensing in improved. This collaborative sensing in ad hoc networks can be either of centralized or distributed architectures, both of which are discussed in this chapter.

Spectrum Sensing in Emergency Cognitive Radio Ad Hoc Networks

2013 ◽  
pp. 944-960
Author(s):  
Sasirekha GVK ◽  
Jyotsna Bapat
Keyword(s):  
Cognitive Radio ◽  
Ad Hoc Networks ◽  
Spectrum Sensing ◽  
Ad Hoc ◽  
Cognitive Radios ◽  
Distributed Architectures ◽  
Emergency Situations ◽  
Collaborative Spectrum Sensing ◽  
Military Applications ◽  
Hoc Networks

Ad hoc networks are infrastructure less networks which are self organizing and adaptive. Such networks can be used in emergency situations like disaster management and military applications. Usage of cognitive radios as the wireless terminals in ad hoc networks in emergency situations has distinct advantages. Better bandwidth, interoperability, avoidance of interference, and ant-jamming capabilities are a few such advantages. Ad hoc networks with cognitive radios are wireless terminals used in emergency situations and can be referred to as Emergency Cognitive Radio Ad Hoc Networks (Emergency CRAHNs). In this chapter, the authors discuss emergency CRAHNs and the specific requirements that must be met by the spectrum sensing mechanism used by them. In particular, the authors discuss collaborative spectrum sensing methodology; where in multiple cognitive radios operate together such that reliability of spectrum sensing in improved. This collaborative sensing in ad hoc networks can be either of centralized or distributed architectures, both of which are discussed in this chapter.

scholarly journals Optimization of Collaborative Spectrum Sensing Mechanism for Cognitive Radio

2014 ◽  
Vol 8 (1) ◽  
pp. 14-18
Author(s):  
Zhigang Wen ◽  
Mingjun Mu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Cost ◽  
Communication Systems ◽  
Emerging Technology ◽  
Passive Detection ◽  
Sensing Mechanism ◽  
Collaborative Spectrum Sensing ◽  
Passive Sensing ◽  
Sensing Time

Cognitive radio (CR) is an emerging technology that helps efficiently use spectrum. In this paper, a collaborative spectrum sensing mechanism is proposed which combines passive detection and sensing service compensation. Theoretical analysis and simulations show that this method not only reduces the energy cost and the passive sensing time, but also maintains fairness in the CR communication systems.

scholarly journals Efficient Approximations for Optimization of N-Out-of-K Rule for Heterogeneous Cognitive Radio Networks

2021 ◽  
Vol 11 (7) ◽  
pp. 3083
Author(s):  
Youheng Tan ◽  
Xiaojun Jing
Keyword(s):  
Cognitive Radio ◽  
Computational Complexity ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Closed Form Expression ◽  
Sampling Point ◽  
Mutual Cooperation ◽  
Communication Time ◽  
Sensing Time

Spectrum sensing (SS) has attracted much attention due to its important role in the improvement of spectrum efficiency. However, the limited sensing time leads to an insufficient sampling point due to the tradeoff between sensing time and communication time. Although the sensing performance of cooperative spectrum sensing (CSS) is greatly improved by mutual cooperation between cognitive nodes, it is at the expense of computational complexity. In this paper, efficient approximations of the N-out-of-K rule-based CSS scheme under heterogeneous cognitive radio networks are provided to obtain the closed-form expression of the sensing threshold at the fusion center (FC), where the false alarm probability and its corresponding detection probability are approximated by the Poisson distribution. The computational complexity required to obtain the optimal sensing threshold at the FC has greatly decreased and theoretical derivations state that the approximation error is negligible. The simulations validate the effectiveness of the proposed scheme.

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