Cognitive network

About: Cognitive network is a research topic. Over the lifetime, 4213 publications have been published within this topic receiving 107093 citations.

Resource Allocation Techniques in Cooperative Cognitive Radio Networks

Abstract: In the past decade, cognitive radio and cooperative communication techniques have been proposed in the literature for efficiently utilizing the radio resources. Cognitive radio is an emerging technology intended to enhance the utilization of the radio frequency spectrum. The cooperative communication system, with the same total power and bandwidth of legacy wireless communication systems, can increase the data rate of the future wireless communication system. A combination of cognitive radio with cooperative communication can further improve the future wireless network performance. Efficient resource allocation in cooperative cognitive radio network (CRN) is essential in order to meet the challenges of future wireless networks. In this article, a survey of resource allocation in cooperative CRN is presented. We discuss the taxonomy of objectives and protocols used in the literature for resource allocation in cooperative CRN. This paper also highlights the use of power control, cooperation types, network configurations and decision types used in cooperative CRN. Finally, directions for future research are outlined.

The Primary Exclusive Region in Cognitive Networks

Abstract: In this paper, we consider a cognitive network in which a single primary transmitter communicates with primary receivers within an area of radius RO, called the primary exclusive region (PER). Inside this region, no cognitive users may transmit. Outside the PER, provided that the cognitive transmitters are at a minimal distance isinp from a primary receiver, they may transmit concurrently with the primary user. We determine bounds on the primary exclusive radius RO and the guard band isinp to guarantee an outage performance for the primary user. Specifically, for a desired rate CO and an outage probability beta, the probability that the primary user's rate falls below CO is less than beta. This performance guarantee holds even with an arbitrarily large number of cognitive users uniformly distributed with constant density outside the primary exclusive region.

Cognitive Radio and Networking Research at Virginia Tech

Abstract: More than a dozen Wireless @ Virginia Tech faculty are working to address the broad research agenda of cognitive radio and cognitive networks. Our core research team spans the protocol stack from radio and reconfigurable hardware to communications theory to the networking layer. Our work includes new analysis methods and the development of new software architectures and applications, in addition to work on the core concepts and architectures underlying cognitive radios and cognitive networks. This paper describes these contributions and points towards critical future work that remains to fulfill the promise of cognitive radio. We briefly describe the history of work on cognitive radios and networks at Virginia Tech and then discuss our contributions to the core cognitive processing underlying these systems, focusing on our cognitive engine. We also describe developments that support the cognitive engine and advances in radio technology that provide the flexibility desired in a cognitive radio node. We consider securing and verifying cognitive systems and examine the challenges of expanding the cognitive paradigm up the protocol stack to optimize end-to-end network performance. Lastly, we consider the analysis of cognitive systems using game theory and the application of cognitive techniques to problems in dynamic spectrum sharing and control of multiple-input multiple-output radios.

Opportunistic Cooperation in Cognitive Femtocell Networks

Abstract: We investigate opportunistic cooperation between unlicensed secondary users and legacy primary users in a cognitive radio network. Specifically, we consider a model of a cognitive network where a secondary user can cooperatively transmit with the primary user in order to improve the latter's effective transmission rate. In return, the secondary user gets more opportunities for transmitting its own data when the primary user is idle. This kind of interaction between the primary and secondary users is different from the traditional dynamic spectrum access model in which the secondary users try to avoid interfering with the primary users while seeking transmission opportunities on vacant primary channels. In our model, the secondary users need to balance the desire to cooperate more (to create more transmission opportunities) with the need for maintaining sufficient energy levels for their own transmissions. Such a model is applicable in the emerging area of cognitive femtocell networks. We formulate the problem of maximizing the secondary user throughput subject to a time average power constraint under these settings. This is a constrained Markov Decision Problem and conventional solution techniques based on dynamic programming require either extensive knowledge of the system dynamics or learning based approaches that suffer from large convergence times. However, using the technique of Lyapunov optimization, we design a novel greedy and online control algorithm that overcomes these challenges and is provably optimal.