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Use of this web site signifies your agreement to the terms and conditions. Cognitive radio networks Abstract: Cognitive Radio Networks CRNs are emerging as a solution to increase the spectrum utilization by using unused or less used spectrum in radio environments. The basic idea is to allow unlicensed users access to licensed spectrum, under the condition that the interference perceived by the licensed users is minimal.
New communication and networking technologies need to be developed, to allow the use of the spectrum in a more efficient way and to increase the spectrum utilization. This means that a number of technical challenges must be solved for this technique to get acceptance.
Spectrum Sharing is meant to allocate the spectrum holes equitably among the secondary users bearing in mind the usage cost. Spectrum Mobility is to ensure and maintain the seamless communication requirements during the transition to lighter spectrum.
The spectrum sensing function is the most crucial to establish a cognitive radio network. There are some techniques used for spectrum sensing, which are; Primary transmitter detection, cooperative detection and interference detection. The reason that spectrum sensing is the most crucial task is that there are many uncertainties connected while picking up the signals to find the holes in the band like Channel Uncertainty, Noise Uncertainty, Sensing Interference Limit, etc.
So, these uncertainties need to be addressed while solving the problem that is spectrum sensing in cognitive radio networks. Therefore, the major challenge in spectrum sensing is that the secondary users have to detect the presence of the primary users in the licensed spectrum and quit the frequency band as quickly as possible if the corresponding primary radio emerges so that the primary user does not face any interference.
This is the first and most important step in implementing the CR system. The Spectrum sensing techniques are classified into 3 main types, Transmitter Detection Non Cooperative Sensing , Cooperative Sensing and interference based testing. Below are the descriptions of the first two sensing techniques. In transmitter detection there is a further classification into Energy Detection, Matched Filter detection and Cyclostationary feature detection.
The energy detection method detects the primary signal based on the sensed energy. The signal is passed through a band pass filter and is integrated over a time period. The output is tested against a threshold which is predefined.
This reveals whether a primary user is present or absent. A match filter is a linear filter and is used when the secondary user has a prior knowledge of the primary user signal.
It provides more accuracy at the expense of being more complex. Higher sensitivity requirements on the CR user if multiple CR users cooperate in sensing the channel. Therefore it will be shared and compared among various CR users to sense a signal. Often there are multiple choices presented by the spectrum sensing function but it is the function of the spectrum management system to decide which option is the optimum choice. Spectrum management is carried out in two primary steps.
The success of the unlicensed band to accommodate a wide range of wireless devices and services has inspired the FCC Federal Communications Commission in the USA to open up more unlicensed bands. The telecommunications authority in the USA has realized the capability of the CR technology and hopes to open up unlicensed bands which will exploit the inefficiently utilized licensed bands given that the primary users do not undergo interference.
Ways to implement the stages of method will be described in greater detail below. Method may begin at starting block and proceed to stage where controller may receive a beacon message associated with a tag. For example, an active tag e. Using an off-channel scanning architecture, APs in operating environment may operate in a promiscuous mode to gather Wi-Fi telemetry and off-channel packets from neighboring radios i.
During the off-channel scan, the presence of an active tag may be detected based on an Information Element IE e. This communication from Wi-Fi-based active tags may deliver location information and other data to the enabled APs. The beaconing process may not require tags to get associated with the APs and therefore may enable asset tracking to scale e. From stage , where controller receives the beacon message associated with the tag, method may advance to stage where controller may determine, based on information derived from the beacon message, an optimum radio in a network i.
The optimum radio may be associated with an AP that may comprise one of plurality of APs in the network. For example, once a beacon is processed, the presence of a tag may be identified and reported to a central controller entity e. The central control entity may amalgamate information from multiple radios in operating environment to determine attributes comprising, for example, tag information, beaconing range, beaconing pattern, set of frequencies of operation, and programmability.
Tag Information may include Wi-Fi spectrum compliance, tag capabilities such as low frequency receiver, chokepoint detection capabilities, etc. Behavior of the tags may be distinguished based on vendor and capabilities. This information may provide enhanced ability to perform tag classification on the central controller control entity to depict characteristics e.
This may be important to determine a set of neighboring APs that receive signals from a particular tag type. Beaconing pattern, for example, may comprise infrequent burst or scheduled. While active beaconing may enhance a tag's capability to support scale, an aggressive beaconing pattern may contribute to battery drain on a tag. Accordingly, various tags may support diverse beaconing techniques, while some tags may perform bursty beacon transmissions to maximize their reach to many APs in a single transmission.
Regarding set of frequencies of operation, tags may support universal frequencies in 2. This information may be utilized, for example, to determine optimized frequencies for beacon reception and amount of dwell on different set of channels. With respect to programmability, tags may support a diverse set of configurations policies. Tag policies may include transmission interval, channel programmability, RTLS environmental parameters, and other environmental parameters.
Based on the above, embodiments of the disclosure may employ an AP monitoring classifier at the central controller entity, for example, that may determine a radio's monitoring capabilities and whether the presence of a dedicated monitor or multi-spectrum XOR is there. These factors may add bias in candidate determination for tags monitoring services. Embodiment of the disclosure may analyze the above characteristics and may determine an optimal set of radios for tag monitoring service along with its scheduler.
This may allow most of the APs to ignore monitoring of the tags, thus allowing greater efficiency. An AP may support either dedicated monitor role functions e. With other embodiments, AP where a dedicated monitor radio may not be available or their integrated monitor mode radios are optimized for other set of services which cannot facilitate larger dwells and scan requirements for tag monitoring, other processes may perform candidate radio selection for monitoring services.
In this embodiment, for example, client serving radios identified as excessive may bias operation towards 2. In the event, a tag may be monitored by multiple set of APs, built-in monitor capable radios may have higher bias for candidate selection.
With other embodiments, based on the proximity and range of a tag, a single radio capable of 2. A similar beaconing internal may be used on both tags.
Given first tag 's and second tag 's range, a radio capable of 2. In yet another embodiments, a group of radios may be combined together to monitor a single tag if beaconing characteristics are infrequent and bursty. Once controller determines, based on the information derived from the beacon message, the optimum radio in the network to monitor the tag in stage , method may continue to stage where controller may provision the optimum radio associated with the AP in the network to monitor the tag.
For example, embodiments of the disclosure may provision an optimal number of radios that may ensure no-loss in beacon measurements from the active tags. This may include radio capability, active role, and other pending service requests enqueued. Based on the above analysis, a radio in first AP may be provisioned to monitor first tag Radios in twelfth AP and fourteenth AP may be provisioned to monitor second tag A radio in fourteenth AP may be provisioned to monitor third tag Once controller provisions the optimum radio associated with the AP in the network to monitor the tag in stage , method may then end at stage Memory unit may include a software module and a database While executing on processing unit , software module may perform, for example, processes for providing service cognizant radio role assignments as described above with respect to FIG.
Computing device may be implemented using a Wi-Fi access point, a tablet device, a mobile device, a smart phone, a telephone, a remote control device, a set-top box, a digital video recorder, a cable modem, a personal computer, a network computer, a mainframe, a router, a switch, a server cluster, a smart TV-like device, a network storage device, a network relay devices, or other similar microcomputer-based device. Computing device may comprise any computer operating environment, such as hand-held devices, multiprocessor systems, microprocessor-based or programmable sender electronic devices, minicomputers, mainframe computers, and the like.
Computing device may also be practiced in distributed computing environments where tasks are performed by remote processing devices. The aforementioned systems and devices are examples and computing device may comprise other systems or devices. Embodiments of the disclosure, for example, may be implemented as a computer process method , a computing system, or as an article of manufacture, such as a computer program product or computer readable media.
The computer program product may be a computer storage media readable by a computer system and encoding a computer program of instructions for executing a computer process. The computer program product may also be a propagated signal on a carrier readable by a computing system and encoding a computer program of instructions for executing a computer process.
In other words, embodiments of the present disclosure may take the form of a computer program product on a computer-usable or computer-readable storage medium having computer-usable or computer-readable program code embodied in the medium for use by or in connection with an instruction execution system. A computer-usable or computer-readable medium may be any medium that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
The computer-usable or computer-readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. More specific computer-readable medium examples a non-exhaustive list , the computer-readable medium may include the following: an electrical connection having one or more wires, a portable computer diskette, a random access memory RAM , a read-only memory ROM , an erasable programmable read-only memory EPROM or Flash memory , an optical fiber, and a portable compact disc read-only memory CD-ROM.
Note that the computer-usable or computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory. While certain embodiments of the disclosure have been described, other embodiments may exist.
Furthermore, although embodiments of the present disclosure have been described as being associated with data stored in memory and other storage mediums, data can also be stored on or read from other types of computer-readable media, such as secondary storage devices, like hard disks, floppy disks, or a CD-ROM, a carrier wave from the Internet, or other forms of RAM or ROM.
Furthermore, embodiments of the disclosure may be practiced in an electrical circuit comprising discrete electronic elements, packaged or integrated electronic chips containing logic gates, a circuit utilizing a microprocessor, or on a single chip containing electronic elements or microprocessors.
Embodiments of the disclosure may also be practiced using other technologies capable of performing logical operations such as, for example, AND, OR, and NOT, including but not limited to, mechanical, optical, fluidic, and quantum technologies. In addition, embodiments of the disclosure may be practiced within a general purpose computer or in any other circuits or systems.
Embodiments of the disclosure may be practiced via a system-on-a-chip SOC where each or many of the element illustrated in FIG. When operating via an SOC, the functionality described herein with respect to embodiments of the disclosure, may be performed via application-specific logic integrated with other components of computing device on the single integrated circuit chip.
While the specification includes examples, the disclosure's scope is indicated by the following claims. Rather, the specific features and acts described above are disclosed as example for embodiments of the disclosure.
The method of claim 1, wherein determining the optimum radio comprises considering monitoring capabilities of radios in the plurality of APs. The method of claim 1, wherein the information derived from the beacon message comprises tag information. The method of claim 1, wherein the information derived from the beacon message comprises beaconing range of the tag. The method of claim 1, wherein the information derived from the beacon message comprises beaconing pattern of the tag.
The method of claim 1, wherein the information derived from the beacon message comprises a set of frequencies of operation of the tag. The method of claim 1, wherein the information derived from the beacon message comprises a programmability of the tag.
The system of claim 8, wherein the processing unit being operative to determine the optimum radio comprises the processing unit being operative to consider monitoring capabilities of radios in the plurality of APs.
The system of claim 8, wherein the information derived from the beacon message comprises tag information. The system of claim 8, wherein the information derived from the beacon message comprises beaconing range of the tag. The system of claim 8, wherein the information derived from the beacon message comprises beaconing pattern of the tag. The system of claim 8, wherein the information derived from the beacon message comprises a set of frequencies of operation of the tag.
The system of claim 8, wherein the information derived from the beacon message comprises a programmability of the tag. Apple Podcasts Preview. AUG 9, Why product information management PIM is key to your e-commerce success Why product information management PIM is key to your e-commerce success The pandemic has rapidly accelerated consumer adoption of online purchasing.
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