Utility-based joint Power and Rate Control Game with Interference Threshold Elasticity for Cooperative Cognitive Networks

In recent years, channel-hopping-based medium access control protocols have been proposed to improve the capacity in a decentralized multichannel cognitive radio (CR) network without using extra control channels. Each CR user has to stochastically follow a default channel-hopping sequence in order to locate a channel and conduct its frame transmission. In this paper, theoretical analysis is conducted on the probability of channel availability and the average frame delay for primary users (PUs) by considering the impact caused by imperfect sensing of CR users and imperfect synchronization between the primary and CR networks. According to the proposed analytical model with realistic considerations, an optimal channel-hopping sequence (OCS) approach is designed for the CR users based on a dynamic programming technique. It is designed by exploiting the optimal load balance between channel availability and channel utilization within the delay constraints of PUs. By adopting the OCS approach, maximum aggregate throughput of CR users can be achieved while considering PU's quality-of-service (QoS) requirements. Moreover, in addition to the paired CR networks, the logical partition problem that occurs in generalized CR networks will also be addressed. This problem can severely degrade the aggregate throughput due to the decreased probability of connectivity between CR users, especially in a CR network with heavy traffic. Therefore, both wake-up successive contention (WSC) and wake-up counter-reset successive contention (WCSC) algorithms are proposed to increase the number of negotiations by both exploring the blind spot of imperfect sensing and amending the contention mechanisms between CR users. Compared to conventional channel-hopping sequences, numerical results illustrate that the proposed approaches can effectively maximize aggregate throughput for CR users under the QoS requirements of PUs.

In this paper, we propose a new multiple-level power allocation strategy for the secondary user (SU) in cognitive radio (CR) networks. Different from the conventional strategies, where SU either stays silent or transmit with a constant/binary power depending on the busy/idle status of the primary user (PU), the proposed strategy allows SU to choose different power levels according to a carefully designed function of the receiving energy. The way of the power level selection at SU side is optimized to maximize the achievable rate of SU under the constraints of average transmit power at SU and average interference temperature to PU. Simulation results demonstrate that the proposed strategy can significantly improve the throughput of SU compared to the conventional strategies.

Cognitive radio technology is proposed to improve spectrum utilization efficiency through exploiting the unused portions of spectrum in an opportunistic manner. In cognitive radio networks (CRNs), primary users (PUs) are allowed to lease out their unused spectrum to share with cognitive users (CUs). In a CRN consisting of multiple PUs and CUs, the spectrum pricing and resource allocation scheme have to be optimally designed, so that the efficient spectrum sharing among PUs and CUs can be supported and the QoS requirements of both PUs and CUs can be guaranteed. In this paper, we consider the joint spectrum pricing and resource allocation problem of a CRN with imperfect channel condition, i.e., channel state information of the PUs is not fully accessible to the CUs. To characterize the willingness of PUs to share subchannels and the intention of CU on accessing subchannels, a pricing scheme for both PUs and CUs is designed. Addressing the competition of CUs in channel accessing and power allocation, a non-cooperative Game model is formulated. Through solving the Nash equilibrium solution of the Game model, the optimal pricing and resource allocation strategy can be obtained. Numerical results demonstrate the efficiency of the proposed algorithm.

Efficient resource allocation is a major challenge in cognitive radio networks, especially when Cognitive Users (CUs) share the same frequency band with the Primary User. In this paper, we consider minimizing the total power consumption by combining power control, rate control and adaptive modulation. We analyze the existence, uniqueness and Pareto optimality of Nash Equilibrium (NE) in the power control game, and propose an iterative algorithm to find the NE followed by the adjustment of both the transmission rate and modulation scheme based on the convergent power. If compared with previous works, the key feature of the proposed strategy is that each CU can prolong its battery life in energy-constrained networks to support heterogenous services with different transmission rates and modulation schemes requirements. Simulation results are provided to confirm the effectiveness of the proposed method in power saving, improvement of both the transmission rate and the spectral efficiency and the simplicity of implementation.

CooperativeCooperative communication in cognitive radio networks (CRNs) is an emerging communication prototype which offers enhanced reachability and improved capacity. In such mode of communication, the Cognitive Users (CUs) can work as relay nodes for conveying the signal received from the Primary Users (PUs) to required destinations, while satisfying the PUs' and the CUs' minimum rate requirements. The PUs' are motivated to cooperate by the incentive to attain a higher PU rate with low power requirement, while concurrently allowing an access to CUs to share their spectral band. This arrangement is usually called as Overlay CRN. Several schemes are available in the literature which provide efficient spectral access for multiple PUs and CUs in cooperative CRNs. However, in such schemes the PUs enhanced performance does not necessarily translates into a satisfactory performance for the CUs and vice versa. Existing cooperative distribution algorithms such as Pragmatic Distribution Algorithms (PDA) and Conventional Distribution Algorithms (CDA) do not support the transmission rate enhancement for both PUs and CUs simultaneously and an improved performance of one network (PUs or CUs) results into poor performance of the other. In this paper, an improved algorithm namely 'Incremental Pragmatic Distribution Algorithm (IPDA)' is proposed, which attempts to improve the average transmission rate of both CUs and PUs.

Cognitive Radio networks (CRN) enable cognitive users to use portions of the licensed spectrum of the primary users (PU). Dynamic spectrum access (DSA) is a design aspect that facilitates the transmission of cognitive radio (CR) users over idle channels. In many cases, it is not preferable that CR users to be treated equally. Provisioning quality of service (QoS) to some CR users is a challenge in DSA design. In this situation, The CR user traffic is divided into high and low priority classes. Sub-channel reservation (SCR) scheme is the most traditional scheme to provide priority to CR users in admission. In this paper, a new scheme named “low priority bounding” (LPB) scheme is used to provide QoS for CR users. The LPB scheme provides priority by restricting the number of low priority CR users by a threshold. This scheme maintains a suitable level of service to high priority users (as provided by SCR scheme) while improve the level of service for low priority ones. So the revenue gained from LPB scheme is optimized in comparison with SCR scheme. The impact of LPB scheme in the provided QoS is evaluated in terms of blocking probability, service termination rate, and service completion rate. Simulation results are compared with SCR scheme and it shows that the LPB scheme can significantly improve the revenue gained over the traditional SCR scheme.

In this paper, the performance of asecondary user (SU) in an underlay cognitive radio (CR) network over ageneralized-gamma (GG) fading channel in terms of three performance metrics,namely, outage probability, ergodic capacity, and bit error rate (BER), isinvestigated. According to the underlay approach, the transmit power of the SUshould be limited to avoid interference to primary users (PUs). The performancemetrics of the SU in the underlay CR network are theoretically derived and alsoobtained with Monte Carlo simulations for a GG fading channel with different fadingparameters. To demonstrate the effect of limited power on the performancemetrics, three different maximum transmit power levels (Pmax), namely, 10, 20,and 30 dB, are used. The simulation results lead to three conclusions: First,when high values are chosen for the fading parameters (α, c), the fadingchannel gets less distorted and the performance metrics improve. The secondconclusion is that the BER performance gets better as the limited powerincreases. The final conclusion is that the BER performance of SUs improves asthe interference power that PUs can tolerate increases. Cite this article as: Aldırmaz Çolak S.Performance Analysis of a Secondary User in Cognitive Radio overGeneralized-Gamma Fading Channels. Electrica, 2019; 19(2): 166-172.

As the proliferation of wireless handheld devices such as smart phones and tablets grow exponentially, new technologies have to be adopted to efficiently use the radio frequency spectrum. Cognitive Radio(CR) network offers a promising solution to improve spectrum utilization and efficiency by harnessing the available spectrum resources in real-time. However, participants in the CR network can comprise of malicious adversaries who adopt dishonest and non-cooperative strategies to attack the network. In our research, we focus on a critical attack on the CR network: Primary User Emulation (PUE). In a PUE attack, the malicious adversary violates spectrum sharing etiquette by impersonating the primary user at the expense of other unselfish secondary users. To thwart such an attack, we present a strategy to authenticate the primary user, which involves collaborative learning among CR users.

Energy-efficient cooperative cognitive relaying schemes for cognitive radio networks

S Cognitive radio network is a promising wireless network where smart devices are able to opportunistically exploit the spectrum holes and optimize the overall radio spectrum use. The provision of quality of service and mobility management is imperative to providing efficient cognitive radio systems. In this paper, we present a mobility scheme that enables cognitive radio users to seamlessly switch towards the best available spectrum band when moving from one network to another one. On the one hand, our proposal conserves the frequency and the bandwidth needed for users' application. On the other hand, it allows cognitive radio users to have the best band with a good price and a large use duration based on a trading mechanism established between primary and cognitive radio users. Simulation results prove that our approach preserves users' continuity of service during their mobility and ensures high utility for both primary and cognitive radio users.

Resource allocation of cognitive relay networks under continuous transmission mechanism

The performance of cooperative spectrum sensing in cognitive radio (CR) networks depends on the sensing mode, the sensing time and the number of cooperative users. In order to improve the sensing performance and reduce the interference to the primary user (PU), a periodic cooperative spectrum sensing model based on weight fusion is proposed in this paper. Moreover, the sensing period, the sensing time and the searching time are optimized, respectively. Firstly the sensing period is optimized to improve the spectrum utilization and reduce the interference, then the joint optimization algorithm of the local sensing time and the number of cooperative users, is proposed to obtain the optimal sensing time for improving the throughput of the cognitive radio user (CRU) during each period, and finally the water-filling principle is applied to optimize the searching time in order to make the CRU find an idle channel within the shortest time. The simulation results show that compared with the previous algorithms, the optimal sensing period can improve the spectrum utilization of the CRU and decrease the interference to the PU significantly, the optimal sensing time can make the CRU achieve the largest throughput, and the optimal searching time can make the CRU find an idle channel with the least time.

Cognitive Radio Networks (CRNs) is a formidable evolution in wireless technology owing to its potentiality to resolve spectrum scarcity crisis. In CRNs, cognitive radio user’s sense idle spectrum as well as opportunistically entrée sensed spectrum devoid of approved users. The best spectrum is said to be selected opportunistically, shared with other users with no severity to licensed users. Many CRN devices that are fueled by battery possessing constrained energy capacity. Prevailing battery mechanisms yet couldn’t contribute CRN devices works for a long time. Therefore, conservation of energy is mandatory as far as routing in CRN is concerned. In this work a machine learning based method called, Regression Cooperative Spectrum Sensing and Gradient Flying Fox Route Optimization (RCSS-GFFRO) for energy and bandwidth aware data routing with spectrum utilization in CRNs is proposed. Protection of primary users (PUs) as well as optimization of secondary user (SU) transmission included in proposed method. In the proposed method a cooperative spectrum sensing using machine learning (ML) model called, Median Regression function is applied. The Median Regression Cooperative Spectrum Sensing in our work with the bandwidth and energy efficiency ensures acceptable probability of interference to primary users due to secondary user’s access by measuring the relationship between bandwidth and energy efficiency simultaneously. Next, optimal route identification is performed using Gradient Flying Fox Route Optimization algorithm. By applying gradient optimization function minimizes the interference with primary users and increases secondary user performance via sensing time and transmission time parameters with higher routing performance. Simulation estimated with parameters.

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user's QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user's tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.

Although cognitive radio technology improves efficiency of spectrum utilization, primary users usually do not gain from opening up the spectrum in the opportunistic spectrum access, and sometimes even suffer from collisions due to secondary users' imperfect spectrum sensing. However, in this paper, we show that if information secrecy is a concern, primary users could actually be better off by allowing secondary users to cooperatively share the spectrum. Specifically, we propose a new cooperation paradigm in cognitive radio networks that primary users improve secrecy with the help of trustworthy secondary users, in the presence of an intelligent and passive eavesdropper attempting to decode primary users' messages. After deriving the achievable pair of primary users' secrecy rate and secondary users' transmission rate under various circumstances, we model the interaction between primary users and secondary users as a Stackelberg game in which transmission power levels are the key to maximize data rates. Moreover, based on a 2-D representation of how achievable rates depend on power-level regions, we apply equilibrium analysis to understand the optimal strategy of primary and secondary users. Finally, simulation results are presented to verify the performance.