Position location techniques and applications - Part 4: Toward the cognitive radio paradigm

[Part one begins a discussion of the basic evolution of wireless networks and how position location could be considered from the networking point of view. Part two offers a general overview of wireless mobile ad hoc networks and sensor networks. Part three introduces some aspects of mobility that need to be considered to balance the capacity–coverage trade-off that mobility causes.]

5.3 TOWARD THE CR PARADIGM FOR POSITION LOCATION
Cognitive radio (CR) is a new paradigm that emerged from studying the problem of spectrum scarcity or the efficient use of the RF spectrum. It was found that large portions of the spectrum are unused formuch of the time. The main idea is for intelligent devices to sense the spectrum to find and use unoccupied portions without causing interference affecting other authorized users. The device would also be able to perform frequency hopping in order to leave the frequency free to primary users assigned to such an RF band, or it could modify its transmission characteristics (power, modulation, coding, etc.) to coexist with such primary users.

These ideas were proposed for the first time in Mitola [50]. In this section, we present the concept of CR together with some recent results in the area of PL. We also present selected technologies that will certainly ease the process of achieving this new paradigm.

5.3.1 The Concept of Cognitive Radio
Even though a clear definition of CR has not been recognized, we can point to certain concepts produced in recent years and separate from a cognitive radio feature.

For example, CR as a paradigm for wireless communications represents the use of devices in a network where both the devices and the network could change or adapt their characteristics to achieve higher efficiency levels. The particular adaptation takes place based on sensing the environment variables of interest such as RF spectrum occupancy, traffic, and location awareness.

We can see that the devices in this paradigm will learn to adapt according to their sensing of the environment in order to maintain or improve quality of service (QoS) and reduce interference to other devices or services. To achieve such paradigm and device features, two avenues have been used (i.e., SDR and spectrum sharing).

The idea behind spectrum sharing is to organize spectrum access in order to assign resources on demand and location bases. Also, the process could be managed by the network and end users instead of regulatory entities. The Federal Communications Commission (FCC) reports that in the United States a large percentage of the spectrum that has already been allocated is underutilized.

Sharing is seen as a possibility with the new paradigm due to device adaptability to several of the environment parameters such as bandwidth, frequency, power, interference, coding, and synchronization. The device will also be able to use this under utilized spectrum if it also adapts itself in terms of technologies, packet formats, packet lengths, and protocols. This self-adaptability derives from the concept of SDR, as device characteristics are changed from the inside [51].

The success of spectrum sharing will come together with methods to achieve almost no interference to primary users in the selected frequency band. The quantification of such interference is also an issue, and a performance measure to achieve this has been proposed with the definition of interference temperature, in Haykin [33], where issues such as cooperation, power control, and dynamic spectrum management are also discussed. CR needs certain capabilities to reach such goals, among which location plays an important role of sensing the specific environment.

At some spatial points, for example, a CR is aware of technologies such as cellular coverage, range of WLAN signals or areas defined by Bluetooth technology. Hence, a CR has sensors for location information with learning and intelligent algorithms to adapt itself by reconfiguring according to the environment. The disadvantages that are evident at this point in time are the complexity of the hardware necessary to achieve the sensing, complexity and computational requirements to achieve intelligence, and communications cost incurred in the sensing, learning, decision-making, and reconfiguring phases. Research is currently focused on CR combined with multiuser detection, ultra wideband (UWB) communications, and cooperative diversity. A survey of these mixes can be found in Glisic [26].

As discussed previously, awareness is important for CR, especially location for the device to use local parameters to sense the environment and reconfigure itself to adapt to changing conditions. Realization of these tasks is known as location awareness [8, 9]. Application of these location-awareness techniques is in LBS, characterization of the environment, network optimization assisted locally, and transceiver optimization. In addition, a location awareness architecture is introduced in Celebi and Arslan [8], where the estimation of position is a relevant issue in order to carry out the CR paradigm.

Positioning applications in CR systems can help in monitoring the environment to conduct dynamic spectrum access, which is fundamental to achieving optimization at the network level. Also, traffic monitoring can help provide LBS services to traffic commuters, and the sensing of some parameters will make the device adapt to channel conditions by changing its transceiver.

It is important to note that CRs will form cognitive wireless networks that will work cooperatively with other technologies such as Bluetooth, CDMA, WiMAX, and satellite. The issue is to adapt in order to achieve interoperability. The potential of location techniques for CR devices is higher since the latter can use traditional techniques, such as those discussed in Chapters 2, 3 and 4, based on the estimation of position, or newsensing techniques and scene analysis;some postprocessing such as video and image information can also be used.

A cognitive radio positioning system with two modes is also discussed in Celebi and Arslan [8], where bandwidth determination and dynamic spectrum management are used. Considering a channel with an estimated distance error of σ, an observation period containing K symbols, a signal-to-noise ratio of γ, and a signal propagation speed of ν, we can determine the required effective bandwidth β; as follows [8]:

This required effective bandwidth is used by the dynamic spectrum access to find and provide to the CR system a bandwidth to carry out the positioning algorithm; an estimate of the location is obtained afterward. There are also applications of location awareness such as location-assisted handoffs and location-assisted network optimization, discussed as well in Celebi and Arslan [8].