Game-Theoretic Channel Allocation in Cognitive Radio Networks

Cognitive radio networks provide dynamic spectrum access techniques to support the increase in spectrum demand. In particular, the spectrum sharing among primary and secondary users can improve spectrum utilization in unused spectrum by primary users. In this paper, we propose a novel game theoretic channel allocation framework to maximize channel utilization in cognitive radio networks. We degisn the utility function based on the co-channel interference among primary and secondary users. In addition, we embed the property of the adjacent channel intererence to consider real wireless environment. The results show that the utility function converges quickly to Nash equilibrium and achieves channel gain by up to 25 dB compared to initial assignment

Spectrum sharing models in cognitive radio networks

Spectrum scarcity demands thinking new ways to manage the distribution of radio frequency bands so that its use is more effective. The emerging technology that can enable this paradigm shift is the cognitive radio. Different models for organizing and managing cognitive radios have emerged, all with specific strategic purposes. In this article we review the allocation spectrum patterns of cognitive radio networks and analyse which are the common basis of each model.We expose the vulnerabilities and open challenges that still threaten the adoption and exploitation of cognitive radios for open civil networks.L'escassetat de demandes d'espectre fan pensar en noves formes de gestionar la distribució de les bandes de freqüència de ràdio perquè el seu ús sigui més efectiu. La tecnologia emergent que pot permetre aquest canvi de paradigma és la ràdio cognitiva. Han sorgit diferents models d'organització i gestió de les ràdios cognitives, tots amb determinats fins estratègics. En aquest article es revisen els patrons d'assignació de l'espectre de les xarxes de ràdio cognitiva i s'analitzen quals són la base comuna de cada model. S'exposen les vulnerabilitats i els desafiaments oberts que segueixen amenaçant l'adopció i l'explotació de les ràdios cognitives per obrir les xarxes civils.La escasez de demandas de espectro hacen pensar en nuevas formas de gestionar la distribución de las bandas de frecuencia de radio para que su uso sea más efectivo. La tecnología emergente que puede permitir este cambio de paradigma es la radio cognitiva. Han surgido diferentes modelos de organización y gestión de las radios cognitivas, todos con determinados fines estratégicos. En este artículo se revisan los patrones de asignación del espectro de las redes de radio cognitiva y se analizan cuales son la base común de cada modelo. Se exponen las vulnerabilidades y los desafíos abiertos que siguen amenazando la adopción y la explotación de las radios cognitivas para abrir las redes civiles

Dynamic Channel Allocation in Wireless Networks Using Adaptive Learning Automata

The bandwidth utilization of a single channel-based wireless networks decreases due to congestion and interference from other sources and therefore transmission on multiple channels are needed. In this paper, we propose a distributed dynamic channel allocation scheme for wireless networks using adaptive learning automata whose nodes are equipped with single radio interfaces so that a more suitable channel can be selected. The proposed scheme, adaptive pursuit reward-inaction, runs periodically on the nodes, and adaptively finds the suitable channel allocation in order to attain a desired performance. A novel performance index, which takes into account the throughput and the energy consumption, is considered. The proposed scheme is adaptive in the sense that probabilities in the each step are updated as a function of the error in the performance index. The extensive simulation results in static and mobile environments provide that using the proposed scheme for channel allocation in the multiple channel wireless networks significantly improves the throughput, drop rate, energy consumption per packet and fairness index

Cooperative spectrum sensing using adaptive quantization mapping for mobile cognitive radio networks

Sparsity in spectrum is the result of spectrum underutilization. Cognitive radio (CR) technology has been proposed to address inefficiency of spectrum utilisation through dynamic spectrum access technique. CR in general allows secondary node (SN) users to access the licensed or primary users’ (PU) band without disrupting their activities. In CR cooperative spectrum sensing (CSS), a group of SNs share their spectrum sensing information to provide a better picture of the spectrum usage over the area where the SNs are located. In centralised CCS approach, all the SNs report their sensing information to a master node (MN) through a control reporting channel before the MN decides the spectrum bands that can be used by the SNs. To reduce unnecessary reporting information by the cooperating nodes, orthogonal frequency division multiplexing (OFDM) Subcarrier Mapping (SCM) spectrum exchange information was proposed. In this technique, the detection power level from each secondary SN user is quantized and mapped into a single OFDM subcarrier number before delivering it to the MN. Most researches in cooperative spectrum sensing often stated that the SNs are absolutely in stationary condition. So far, the mobility effect on OFDM based SCM spectrum exchange information has not been addressed before. In this thesis, the benchmarking of SCM in mobility environment is carried out. The results showed that during mobility, the performance of OFDM-based SCM spectrum exchange information degraded significantly. To alleviate the degradation, OFDM-based spectrum exchange information using adaptive quantization is proposed, which is known as Dynamic Subcarrier Mapping (DSM). The method is proposed to adapt to changes in detected power level during mobility. This new nonuniform subcarrier mapping considers the range of received power, threshold level and dynamic subcarrier width. The range of received power is first compressed or expanded depending on the intensity of the received power against a pre-determined threshold level before the OFDM subcarrier number is computed. The results showed that OFDM-based DSM spectrum exchange information is able to enhance the probability of detection for cooperative sensing by up to 43% and reduce false alarm by up to 28%. The DSM spectrum exchange information method has the potential to improve cooperative spectrum sensing for future CR mobile wireless networks