Clusters-based rendezvousing approach for scheduling the flash crowd transmissions over cognitive radio networks

Implementation of cognitive radio networks for optimum spectrum utilization through feed forward backpropagation artificial neural network

The competitive coexistence of a large number of secondary users in heterogeneous cognitive radio networks (CRN) is a challenging issue. In this paper, we address this issue by developing an efficient approach to analyze the competition among the secondary users. Based on the Markov model bank that we developed recently, we can change the evaluation of the secondary user throughput into studying a special root of a polynomial that is much more simplified. Under this framework, we study the competition among the secondary users in three special cases: homogeneous CRN with identical secondary users, heterogeneous CRN with a group of identical secondary users plus an outlier, and heterogeneous CRN with two different groups of secondary users. In each case, we derive the polynomial, prove the uniqueness of the root, and derive the throughput of each secondary user based on the root. Furthermore, we derive closed-form approximate solutions to the root, based on which constrained optimization can be formulated to study the optimal competition strategies for the secondary users. The optimization results are in water-filling principles and can be derived in closed-form expressions. Simulations are conducted to verify the analysis results.

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.

In this paper a local geometry alignment algorithm is presented for locating the primary users (PUs) and Secondary users (SUs) in cognitive radio network. Based on the estimated distance between PUs and SUs for the neighbors within certain communication range, the relative configuration of all the users in the network is obtained initially and is refined finally to get the global position of every user in the network. The localization performance of the proposed approach is compared to multidimensional scaling and principal component analysis. Furthermore the lower bound on error i.e., the Cramer Rao lower bound (CRLB) is also derived to check the performance of the proposed algorithm.

The radio frequency (RF) spectrum is a limited and precious resource. The continuing deployment of a diverse range of new wireless services into an already crowded RF spectrum requires a new way to accommodate these services. This increasing demand for the spectrum is in contrast with the inefficient use of the RF spectrum in some licensed bands, which high ights an opportunity for accessing the RF spectrum with cognitive radio (CR) networks. In CR networks, a secondary user group (the unlicensed users) is allowed to opportunistically access temporarily unused licensed bands of the primary users (licensed users), i.e., the spectrum holes. Accessing the spectrum band in such a manner poses many research challenges including finding the band vacancies, protecting the primary system from interference, allocating vacant bands among the secondary users, and sharing the spectrum bands among multiple CR networks. To address these issues, this dissertation proposes a new dynamic spectrum access framework for CR networks, including methods for the spectrum sensing, agile spectrum evacuation, spectrum allocation, and spectrum sharing. For spectrum sensing, a weighted combining scheme is introduced that intelligently assigns weights to the energy measurements of a number of CRs and then combines these values to decide if the primary user is currently using a band. This scheme exhibits a better detection accuracy and spectrum utilization. The agile spectrum evacuation scheme allows uninterrupted use of a licensed band by a CR until the primary transmitter returns when the CR quickly evacuates. This is a major innovation because until now a CR must interchange sensing and transmitting in a licensed band, creating a trade-off between spectrum utilization and unavoidable interference caused to the primary user. To allow the fair and fast allocation of available bands among CRs a collaborative framework for allocating multiple bands simultaneously among multiple CRs is proposed. This framework exhibits a significant superiority over conventional approaches in terms of an improved throughput and spectrum utilization, and reduced interference loss and collisions. Finally, a scheme to facilitate spectrum sharing among multiple CR networks is created by utilizing various game theoretic approaches for different configurations of band access. For each game, the Nash Equilibrium is defined and attained in most cases. Collaboration among the CR networks is also investigated through repeated games and it is shown that a cooperative method results in a much better sharing of the RF spectrum. Comprehensive performance analyses including mathematical formulations and experimental evaluations are provided, with the proposed dynamic spectrum access framework exhibiting a superior performance over existing techniques.

Cognitive radio networking is emerging paradigm for future generation wireless networks in which cognitive radio users (also known as secondary users) dynamically access the RF spectrum opportunistically without creating harmful interference to primary users. In this paper, the waiting probability of secondary users in the cognitive radio network is analyzed. We consider a cognitive radio network where multiple secondary users (SUs) contend for spectrum access using time division multiple access over idle primary user (PU) channels. Using queue dynamics as Poisson driven stochastic process, we characterize the waiting probability of secondary users. Generally speaking, in practical systems, secondary users of cognitive radio network would have no knowledge of activities of other users, thus the probability of being idle or contention probabilities of SUs' in cognitive radio network have to be assigned according to the available local information. Our focus is on SUs waiting probability analysis, for which a systematic understanding is lacking. Simulation results show that the use of multiple channels and/or multiple slots leads to significant delay reduction and transmission fairness.

We consider a cooperation scenario between primary users and untrusted secondary users in cognitive radio networks. The secondary users are willing to help the primary users to relay the primary users' messages in reward for being allowed to share the primary users' spectrum bands. However, the primary users might be reluctant to accept this help, since the secondary users are untrustworthy and may try unauthorized decoding of the primary users' messages. This paper will answer the question: when is this cooperation mutually beneficial for primary and secondary users? Taking an approach of information-theoretic secrecy, such as coding techniques for wiretap channels, the primary users can allow the secondary users to sense and relay the message, while ensuring that the secondary users are ignorant of the primary users' messages. We characterize an achievable secrecy rate of primary users with a rate of the secondary users' communication. From the derived rate pairs, an optimization problem is formulated such that the secondary transmitter distributes its transmit power to maximize its data rate while providing a higher secrecy rate to the primary users. We demonstrate that this cooperation can provide a positive secrecy rate, even when a non-cooperative scheme achieves a zero secrecy rate.

With the employment of cognitive radio technology, dynamic spectrum management has the potential to solve the underused spectrum problem. In this paper, we introduce and compare two periodic sensing and transmission schemes for secondary users (SUs) in cognitive radio networks. In an attempt to maximize the exploitation of spectrum opportunities in these two schemes, we analyze three metrics of SUs, namely, channel utility, collision rate and sensing overhead. Optimizations of SU's slot period are analyzed under single-SU single-channel scenario. The proposed schemes are applicable to any i.i.d. ON-OFF channel distribution.

In our work, for the purpose of controlling the retransmission behavior of secondary users (SUs) in cognitive radio networks (CRNs) with hierarchical SUs, we set a feedback probability for the interrupted lower priority SUs (SU2). Whether an interrupted SU2 packet leaves the system depends on this feedback probability. This feedback probability is a system parameter associated with the amount of packets in the system. An adjustment factor is introduced to control the impact of the amount of packets on the feedback probability. By establishing a Markov chain model, we obtain some expressions of related performance metrics. Finally, by operating numerical experiments, we analyze the impact of the adjustment factor on different performance indicators of SU2.

Cognitive Radio Networks (CRNs) deal with opportunistic spectrum access in order to fully utilize the scarce of spectrum resources, with the development of cognitive radio technologies to greater utilization of the spectrum. Now-a-days Cognitive Radio (CR) is a promising concept for improving the utilization of limited radio spectrum resources for future wireless communications and mobile computing. In this paper we propose two approaches. At first we propose a trust aware model to authenticate the secondary users (SUs) in CRNs which provides a reliable technique to establish trust for CRNs. Secondly, we propose stochastic approach to show the free spectrum availability for SUs in CRNs. To evaluate the proposed approaches, we have modeled and analyzed steady state availability depending on Markov model for free spectrum by adopting QoS characteristics in cognitive radio networks.

Cognitive radio is an emerging technique to improve the utilization of the scarce radio frequency spectrum, which is characterized by the dynamic spectrum access of the secondary users coexisting with the primary users. In cognitive radio network, secondary users strive for temporally unused spectrum access opportunities offered by primary services; as a result, the opportunistic nature of the spectrum utilization among secondary users leads to great threats to primary users. Considering the fact that the cognitive ability of secondary users in cognitive radio network are similar to the intelligent behaviors of ant colonies in biological environment. Therefore, in this paper, the dynamic spectrum access problem is modeled as an adaptive task assignment in ant colonies. Furthermore, we propose to use the ACO algorithm to assign a set of secondary users to a given number of available spectrum bands owned by a special primary service subject to minimal cost constraint. So the basic idea of the ACO algorithm is to let each secondary user distributively select a spectrum band with a good enough quality and without interfering with the primary users, meanwhile minimize spectrum cost of the primary service. Performance evaluation has also been conducted and the results recorded after 100 runs have shown the optimal spectrum assignment.

The next generation networks intend to have features like device to device (D2D) connectivity, energy efficiency and spectral efficiency. This paper presents problem formulation for maximization of energy efficiency of cognitive radio assisted D2D networks subject to compliance of transmit powers of cellular users and interference constraints of primary users of broadcast network. Cognitive radio network (CRN) users are cellular users comprising of cellular and D2D users. Cellular users can opt any of the cellular or D2D mode. These CRN users opportunistically utilize spectrum of television (TV) white spaces. The problem thus formulated is NP-complete. Mesh adaptive direct search (MADS) algorithm has been used to find $$\varepsilon $$ -optimal solution. The results of MADS are compared with the global optimal solution obtained by exhaustive search algorithm (ESA). The simulation results reveal that MADS’ performance is equally good as that of ESA in most of the cases. MADS outperforms ESA in terms of energy efficiency comparison. Simulation results compare results of utility value, spectral efficiency and admission of CRN users with two types of utilities, i.e., utility with maximization of energy efficiency and utility without maximization of energy efficiency. Results testify that utility with maximization of energy efficiency outperforms its counterpart utility. MADS is also ideal algorithm as it has low computational complexity as compared to ESA. Computational complexity of ESA increases exponentially as numbers of users increase making MADS obvious choice for real life networks comprising of large number of cellular users.

Cognitive radio is a revolutionary paradigm to migrate the spectrum scarcity problem in wireless networks. In cognitive radio networks, collaborative spectrum sensing is considered as an effective method to improve the performance of primary user detection. For current collaborative spectrum sensing schemes, secondary users are usually assumed to report their sensing information honestly. However, compromised nodes can send false sensing information to mislead the system. In this paper, we study the detection of untrustworthy secondary users in cognitive radio networks. We first analyze the case when there is only one compromised node in collaborative spectrum sensing schemes. Then we investigate the scenario that there are multiple compromised nodes. Defense schemes are proposed to detect malicious nodes according to their reporting histories.We calculate the suspicious level of all nodes based on their reports. The reports from nodes with high suspicious levels will be excluded in decision-making. Compared with existing defense methods, the proposed scheme can effectively differentiate malicious nodes and honest nodes. As a result, it can significantly improve the performance of collaborative sensing. For example, when there are 10 secondary users, with the primary user detection rate being equal to 0.99, one malicious user can make the false alarm rate (Pf ) increase to 72%. The proposed scheme can reduce it to 5%. Two malicious users can make Pf increase to 85% and the proposed scheme reduces it to 8%.

Cognitive Radio Networks (CRNs) provide a solution for the spectrum scarcity problem facing the wireless communications community. To be able to utilize CRNs in practical applications, a certain level of quality-of-service (QoS) should be guaranteed to the secondary users (SUs) in such networks. In this paper, we propose a packet scheduling scheme that orders the SUs' transmissions according to the packet dropping rates and the number of packets queued waiting for transmission. A medium access control (MAC) protocol, based on the mentioned scheduling scheme, is proposed for a centralized CRN. In addition, the scheduling scheme is adapted for a distributed CRN, by introducing a feature that allows SUs to organize access to the available spectrum without the need for a central unit. Extensive simulation results are presented to evaluate the proposed protocols, in comparison with other MAC protocols designed for CRNs. The results demonstrate the effectiveness of our proposed protocols to guarantee the required QoS for voice packet transmission, while maintaining fairness among SUs.

SummarySpectrum handoff (SH) in the cognitive radio network (CRN) is considered as a key challenging area to enhance the performance of secondary users (SUs) in CRN. If the primary user is detected, the SU may pause and stay on the same channel or may perform SH to another idle channel. An accurate and precise handoff decision improves the overall throughput and quality of experience of end‐users. In this paper, we introduce a new SH algorithm and continuous short‐sensing strategy to improve the overall throughput of SUs. In addition, we have derived the minimum length of the target channel sequence based on network‐specific parameters like desired call dropping probability. Further, an optimum channel search time is obtained to minimize the handoff delay. The simulation result shows that the proposed scheme improves the overall throughput of CRN, and the mean opinion score of different video applications increases by 10%, 4.6%, and 1% for rapid motion, gentle walk, and slight motion types of video applications. In the case of VoIP applications, the maximum simultaneous call is improved by 2 times in the case of G.711, 1.72 times in the case of G.729, and 1.66 times in the case of iLBC.