Protocol Design and Stability Analysis of Cooperative Cognitive Radio Users

A single cognitive radio transmitter--receiver pair shares the spectrum with two primary users communicating with their respective receivers. Each primary user has a local traffic queue, whereas the cognitive user has three queues; one storing its own traffic while the other two are relaying queues used to store primary relayed packets admitted from the two primary users. A new cooperative cognitive medium access control protocol for the described network is proposed, where the cognitive user exploits the idle periods of the primary spectrum bands. Traffic arrival to each relaying queue is controlled using a tuneable admittance factor, while relaying queues service scheduling is controlled via channel access probabilities assigned to each queue based on the band of operation. The stability region of the proposed protocol is characterized shedding light on its maximum expected throughput. Numerical results demonstrate the performance gains of the proposed cooperative cognitive protocol.Comment: Accepted in WCNC 201

Interference-Based Optimal Power-Efficient Access Scheme for Cognitive Radio Networks

In this paper, we propose a new optimization-based access strategy of multipacket reception (MPR) channel for multiple secondary users (SUs) accessing the primary user (PU) spectrum opportunistically. We devise an analytical model that realizes the multipacket access strategy of SUs that maximizes the throughput of individual backlogged SUs subject to queue stability of the PU. All the network receiving nodes have MPR capability. We aim at maximizing the throughput of the individual SUs such that the PU's queue is maintained stable. Moreover, we are interested in providing an energy-efficient cognitive scheme. Therefore, we include energy constraints on the PU and SU average transmitted energy to the optimization problem. Each SU accesses the medium with certain probability that depends on the PU's activity, i.e., active or inactive. The numerical results show the advantage in terms of SU throughput of the proposed scheme over the conventional access scheme, where the SUs access the channel randomly with fixed power when the PU is sensed to be idle

Optimal Spectrum Access for Cognitive Radios

In this paper, we investigate a time-slotted cognitive setting with buffered primary and secondary users. In order to alleviate the negative effects of misdetection and false alarm probabilities, a novel design of spectrum access mechanism is proposed. We propose two schemes. First, the SU senses primary channel to exploit the periods of silence, if the PU is declared to be idle, the SU randomly accesses the channel with some access probability $a_s$. Second, in addition to accessing the channel if the PU is idle, the SU possibly accesses the channel if it is declared to be busy with some access probability $b_s$. The access probabilities as function of the misdetection, false alarm and average primary arrival rate are obtained via solving an optimization problem designed to maximize the secondary service rate given a constraint on primary queue stability. In addition, we propose a variable sensing duration schemes where the SU optimizes over the optimal sensing time to achieve the maximum stable throughput of the network. The results reveal the performance gains of the proposed schemes over the conventional sensing scheme. We propose a method to estimate the mean arrival rate and the outage probability of the PU based on the primary feedback channel, i.e., acknowledgments (ACKs) and negative-acknowledgments (NACKs) messages.Comment: arXiv admin note: substantial text overlap with arXiv:1206.615

To Sense or Not To Sense

A longer sensing time improves the sensing performance; however, with a fixed frame size, the longer sensing time will reduce the allowable data transmission time of the secondary user (SU). In this paper, we try to address the tradeoff between sensing the primary channel for $\tau$ seconds of the time slot proceeded by randomly accessing it and randomly accessing primary channel without sensing to avoid wasting $\tau$ seconds in sensing. The SU senses primary channel to exploit the periods of silence, if the primary user (PU) is declared to be idle the SU randomly accesses the channel with some access probability $a_s$. In addition to randomly accesses the channel if the PU is sensed to be idle, it possibly accesses it if the channel is declared to be busy with some access probability $b_s$. This is because the probability of false alarm and misdetection cause significant secondary throughput degradation and affect the PU QoS. We propose variable sensing duration schemes where the SU optimizes over the optimal sensing time to achieve the maximum stable throughput for both primary and secondary queues. The results reveal the performance gains of the proposed schemes over the conventional sensing scheme, i.e., the SU senses the primary channel for $\tau$ seconds and accesses with probability 1 if the PU is declared to be idle. Also, the proposed schemes overcome random access without sensing scheme. The theoretical and numerical results show that pairs of misdetection and false alarm probabilities may exist such that sensing the primary channel for very small duration overcomes sensing it for large portion of the time slot. In addition, for certain average arrival rate to the primary queue pairs of misdetection and false alarm probabilities may exist such that the random access without sensing overcomes the random access with long sensing duration

Cooperation and Underlay Mode Selection in Cognitive Radio Network

In this research, we proposes a new method for cooperation and underlay mode selection in cognitive radio networks. We characterize the maximum achievable throughput of our proposed method of hybrid spectrum sharing. Hybrid spectrum sharing is assumed where the Secondary User (SU) can access the Primary User (PU) channel in two modes, underlay mode or cooperative mode with admission control. In addition to access the channel in the overlay mode, secondary user is allowed to occupy the channel currently occupied by the primary user but with small transmission power. Adding the underlay access modes attains more opportunities to the secondary user to transmit data. It is proposed that the secondary user can only exploits the underlay access when the channel of the primary user direct link is good or predicted to be in non-outage state. Therefore, the secondary user could switch between underlay spectrum sharing and cooperation with the primary user. Hybrid access is regulated through monitoring the state of the primary link. By observing the simulation results, the proposed model attains noticeable improvement in the system performance in terms of maximum secondary user throughput than the conventional cooperation and non-cooperation schemes

On Orthogonal Band Allocation for Multi-User Multi-Band Cognitive Radio Networks: Stability Analysis

In this work, we study the problem of band allocation of $M_s$ buffered secondary users (SUs) to $M_p$ primary bands licensed to (owned by) $M_p$ buffered primary users (PUs). The bands are assigned to SUs in an orthogonal (one-to-one) fashion such that neither band sharing nor multi-band allocations are permitted. In order to study the stability region of the secondary network, the optimization problem used to obtain the stability region's envelope (closure) is established and is shown to be a linear program which can be solved efficiently and reliably. We compare our orthogonal allocation system with two typical low-complexity and intuitive band allocation systems. In one system, each cognitive user chooses a band randomly in each time slot with some assignment probability designed such that the system maintained stable, while in the other system fixed (deterministic) band assignment is adopted throughout the lifetime of the network. We derive the stability regions of these two systems. We prove mathematically, as well as through numerical results, the advantages of our proposed orthogonal system over the other two systems.Comment: Conditional Acceptance in IEEE Transactions on Communication

A hierarchy of happiness? Mokken scaling analysis of the Oxford Happiness Inventory

The items of the Oxford Happiness Inventory (OHI, a self-report assessment of happiness, are subjected to an analysis for hierarchy among its items. By using Mokken scaling analyses we can assess whether items can reliably be ordered between persons as severity indicators on a latent trait; in this case, a latent trait of Happiness. OHI item-level data from 1024 participants were entered into the Mokken Scaling Procedure (MSP) seeking reliable scales with H > 0.30. 12 OHI items formed a reliable and statistically significant hierarchy. However, the MSP values indicate a 'weak' scale. The 'most difficult' (happiest) item on the scale is 'feeling energetic' and the 'least difficult' (least happy) is 'I have fun'. Items in the scale are consistent with what is already known about both happiness and low mood. The reduction in the OHI's items from 29 to 12 in the Mokken scale may have utility making it more accessible to participants as well as identifying items with reliably different levels of 'difficulty'. (C) 2010 Elsevier Ltd. All rights reserved

Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence

IEEE Access Volume 3, 2015, Article number 7217798, Pages 1512-1530 Open Access Cognition-based networks: A new perspective on network optimization using learning and distributed intelligence (Article) Zorzi, M.a , Zanella, A.a, Testolin, A.b, De Filippo De Grazia, M.b, Zorzi, M.bc a Department of Information Engineering, University of Padua, Padua, Italy b Department of General Psychology, University of Padua, Padua, Italy c IRCCS San Camillo Foundation, Venice-Lido, Italy View additional affiliations View references (107) Abstract In response to the new challenges in the design and operation of communication networks, and taking inspiration from how living beings deal with complexity and scalability, in this paper we introduce an innovative system concept called COgnition-BAsed NETworkS (COBANETS). The proposed approach develops around the systematic application of advanced machine learning techniques and, in particular, unsupervised deep learning and probabilistic generative models for system-wide learning, modeling, optimization, and data representation. Moreover, in COBANETS, we propose to combine this learning architecture with the emerging network virtualization paradigms, which make it possible to actuate automatic optimization and reconfiguration strategies at the system level, thus fully unleashing the potential of the learning approach. Compared with the past and current research efforts in this area, the technical approach outlined in this paper is deeply interdisciplinary and more comprehensive, calling for the synergic combination of expertise of computer scientists, communications and networking engineers, and cognitive scientists, with the ultimate aim of breaking new ground through a profound rethinking of how the modern understanding of cognition can be used in the management and optimization of telecommunication network