12-10-2012, 03:35 PM
A Cognitive Radio Approach for Usage of Virtual Unlicensed Spectrum
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Abstract
While essentially all of the frequency spectrum is allocated to different applications, observations provide evidence that usage of the spectrum is actually quite limited, particularly in bands above 3 GHz. In this paper we present a Cognitive Radio approach for usage of Virtual Unlicensed Spectrum (CORVUS), a vision of a Cognitive Radio (CR) based approach that uses allocated spectrum in a opportunistic manner to create “virtual unlicensed bands” i.e. bands that are shared with the primary (often licensed) users on a non-interfering basis. Dynamic spectrum management techniques are used to adapt to immediate local spectrum availability. We define the system requirements for this approach, as well as the general architecture and basic physical and link layer functions of CORVUS.
INTRODUCTION
It is commonly believed that there is a crisis of spectrum availability at frequencies that can be economically used for wireless communications. This misconception is strengthened by a look at the FCC frequency chart [1], which shows multiple allocations over all of the frequency bands; which is a situation essentially also true worldwide. This has resulted in fierce competition for use of spectra, especially in the bands below 3 GHz. On the other hand, actual measurements taken in downtown Berkeley (Figure 1) reveal a typical utilization of 0.5% in the 3-4 GHz frequency band. This utilization drops to 0.3% in the 4-5 GHz band. This seems in contradiction to the concern of spectrum shortage, since in fact we have spectrum abundance, and the spectrum shortage is partially an artifact of the regulatory and licensing process.
PREVIOUS WORK
The term Cognitive Radio was first defined by Mitola [5] as “the point in which wireless personal digital assistants (PDAs) and the related networks are sufficiently computationally intelligent about radio resources and related computer-to-computer communications to: (a) detect user communications needs as a function of use context, and (b) to provide radio resources and wireless services most appropriate to those needs.” Thus a CR is able to automatically select the best and cheapest service for a radio transmission and is even able to delay or bring forward certain transmissions depending on the currently or soon to be available resources. The learning and reasoning capabilities of CRs needed to fulfill this goal which would be implemented in software as a high layer functionality have been investigated [4][5]. However, this work lacks a specific radio architecture for physical and link layer that would enable the advanced cognitive techniques.
Recently the term Cognitive Radio has been used in a narrower sense: The FCC suggests [3] that any radio having adaptive spectrum awareness should be referred to as “Cognitive Radio”. More precisely: “A cognitive radio (CR) is a radio that can change its transmitter parameters based on interaction with the environment in which it operates. The majority of cognitive radios will probably be SDRs (Software Defined Radios), but neither having software nor being field programmable are requirements of a cognitive radio.” Implicit in the realization of this type of radio is a high degree of flexibility needed to overcome high variation in channel quality and interference.
SYSTEM ARCHITECTURE
In our system model, SUs form Secondary User Groups (SU Groups) to coordinate their communication. Members of a SU Group use a common control channel for signaling and might communicate with each other in a distributed ad-hoc mode or through a centralized access point. In either mode we assume only a unicast communication, either between a pair of SUs or between a SU and the access point. Direct point-to-point communication between Secondary Users from different SU Group’s or broadcast is not supported.
The traffic pattern for the SUs will be initially assumed to have the following characteristics:
1. Centralized, infrastructure based where there has to be a base station or access point providing connection to a backbone connection, as typically found in Internet access networks.
2. Ad hoc networking covers all kinds of ad-hoc traffic that does not assume any infrastructure. Main purpose is to communicate with each other and exchange information within a SU Group.
SYSTEM FUNCTIONS
Our system design only covers the ISO/OSI layers one (physical layer) and two (link layer). Higher layers will implement standard protocols not specific to cognitive radios and thus are not relevant to our discussion. Figure 3 shows the main building blocks for the deployment of a Cognitive Radio system. We identify six systems functions and two control channels that will implement the core functionality.
Physical Layer Functions
1) Spectrum Sensing: The main function of the physical layer is to sense the spectrum over all available degrees of freedom (time, frequency and space) in order to identify sub-channels currently available for transmission. From this information, SU Links can be formed from a composition of multiple sub-channels. This will require the ability to process a wide bandwidth of spectrum and then perform a wideband spectral, spatial and temporal analysis. Sub-Channels currently used for transmission by SUs have to be surveyed at regular intervals – at least every Δtx – to detect Primary Users activity on those Sub-Channels (“reclaiming the usage of their Sub-Channels”) and if there is activity then those Sub-Channels must be given up
CONCLUSION
In this paper we present the CORVUS system concepts to harness unoccupied frequency bands for the creation of virtual unlicensed spectrum. The motivation for this approach comes from the enormous success of unlicensed bands and the realization that the present strategy of allocation has resulted in much under-utilized spectra.
Cognitive Radios are capable of sensing their spectral environment and locating free spectrum resources. In CORVUS, these radios perform local spectrum sensing but Primary User detection and channel allocation is performed in a coordinated manner. This collaborative (either centralized or distributed) effort greatly increases the system’s ability in identifying and avoiding Primary Users.