A database-assisted TV white space network can achieve the goal of green cognitive communication by effectively reducing the energy consumption in cognitive communications. The success of such a novel network relies on a proper business model that provides incentives for all parties involved. In this paper, we propose an integrated spectrum and information market for a database-assisted TV white space network, where the geo-location database serves as both the spectrum market platform and the information market platform. We study the interactions among the database, the spectrum licensee, and unlicensed users by modelling the system as a three-stage sequential decision process. In Stage I, the database and the licensee negotiate regarding the commission for the licensee to use the spectrum market platform. In Stage II, the database and the licensee compete for selling information or channels to unlicensed users. In Stage III, unlicensed users determine whether they should buy exclusive usage right of licensed channels from the licensee or information regarding unlicensed channels from the database. Analyzing such a three-stage model is challenging due to the co-existence of both positive and negative network externalities in the information market. Despite of this, we are able to characterize how the network externalities affect the equilibrium behaviors of all parties involved. We analytically show that in this integrated market, the licensee can never get a market share more than half. Our numerical results further show that the proposed integrated market can improve the network profit up to 87 , compared with a pure information market.
Most of the existing studies on green cognitive communications aimed at addressing the technical issues. For example, Hafeez and Elmirghani in @cite_32 presented a new licensed shared access spectrum sharing scheme to increase the energy efficiency in a network. Palicot in @cite_14 demonstrated how to achieve green radio communications by employing cognitive radio technology. Ji in @cite_19 proposed a platform to explore TV white space in order to achieve green communications in cognitive radio network. Successful commercialization of new green cognitive technology, however, not only relies on sound engineering, but also depends on the proper design of a business model that provides sufficient incentives to the involved parties such as spectrum licensees and the network operators. The joint study of technology and business issues is relatively under explored in the current green cognitive radio literature.
@cite_19 @cite_14 @cite_32
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In this paper, Cognitive Radio (CR) is proposed as an efficient technology to meet the Green communications concept. First of all, the concept of "green communications" is extended to the radio communications world. The main topics, described for example in the call for papers of the first Greencom09 Workshop include energy-efficient network, protocols, devices and energy management. But to reduce the global CO2 emission to protect our environment is not the sole way to address this green concept in wireless communications. The proper use and the optimal sharing of spectrum resources is also a very important topic. In this paper the electromagnetic waves can be considered as a pollution for other users and we shall also deal with this problem. Sustainable development should also address the human aspects both from the social and the health point of views. This paper demonstrates that CR may be a very good technology for dealing with the green radio communication, by describing in detail several examples. Cognitive radio is an emerging technology that aims for efficient spectrum usage by allowing unlicensed (secondary) users to access licensed frequency bands under the condition of protecting the licensed (primary) users from harmful interference. The latter condition constraints the achievable throughput of a cognitive radio network, which should therefore access a wideband spectrum in order to provide reliable and efficient services to its users. In this paper, we study the problem of designing the optimal sensing time and power allocation strategy, in order to maximize the ergodic throughput of a cognitive radio that employs simultaneous multiband detection and operates under two different schemes, namely the wideband sensing-based spectrum sharing (WSSS) and the wideband opportunistic spectrum access (WOSA) scheme. We consider average transmit and interference power constraints for both schemes, in order to effectively protect the primary users from harmful interference, propose two algorithms that acquire the optimal sensing time and power allocation under imperfect spectrum sensing for the two schemes and discuss the effect of the average transmit and interference power constraint on the optimal sensing time. Finally, we provide simulation results to compare the two schemes and validate our theoretical analysis. The deployment of cognitive radio networks enables efficient spectrum sharing and opportunistic spectrum access. It also presents new challenges to the classical problem of interference management in wireless networks. This paper develops an axiomatic framework for power allocation in cognitive radio networks based on four goals: QoS protection to primary users, opportunism to secondary users, admissibility to secondary users, and autonomous operation by individual users. Two additional goals, licensing and versatility, which are desirable rather than essential, are also presented. A general class of Duo Priority Class Power Control (DPCPC) policies that satisfy such goals is introduced. Through theoretical analysis and simulation, it is shown that a specific interference-aware power-control algorithm reaches such goals. Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a software-defined radio, is defined as an intelligent wireless communication system that is aware of its environment and uses the methodology of understanding-by-building to learn from the environment and adapt to statistical variations in the input stimuli, with two primary objectives in mind: spl middot highly reliable communication whenever and wherever needed; spl middot efficient utilization of the radio spectrum. Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks. 1) Radio-scene analysis. 2) Channel-state estimation and predictive modeling. 3) Transmit-power control and dynamic spectrum management. This work also discusses the emergent behavior of cognitive radio.