Claims:We claim:
1. A system for sharing spectrum sensing load in a radio network, the system comprising:
a radio frequency (RF) unit (102) configured to receiveradio frequency (RF) signals from a cognitive radio network (302);
a GPS unit (104) configured to determine geo-coordinatesof each of plurality of cognitive radio nodes (304);
a processing unit (114) comprising:
a spectrum sensing module (108) configured to calculate received signal strength (RSS) values for each of a frequency band of interest of the cognitive radio network (302);
a channel property estimation module (116) configured to
calculate a probability of detection (Pd) valuesfor each ofthe frequency band of interest of the cognitive radio network, and
share the calculated Pd values and the geo-coordinates valuesamong the plurality of the cognitive radio nodes (304);
a cooperative sensing module (118) configured to
consolidate the received Pd values and calculate a consolidated energy (CE) matrix,
receive the geo-coordinates values and calculate a geo-correlation (GC) matrix, and
create one or more clusters having a common set of frequencies of the cognitive radio nodes based on the CE matrix and the GC matrix; and
a MAC and Network module (112) configured to allocate frequency-bands among a common cognitive radio nodes within the created clusters, uniformly in a distributed manner.
2. The system as claimed in claim 1, whereincalculation of the Pdvalues is based on the RSS values.
3. The system as claimed in claim 1, wherein calculation of the consolidated energy (CE) matrix is based on the received Pd values.
4. The system as claimed in claim 1, wherein calculation of the GC matrix is based on the received geo-coordinates values.
5. The system as claimed in claim 1, wherein allocation of the frequency-bands among the common cognitive radio nodes within the created clusters, uniformly in a distributed manner is performed without the need of any central entity or a base station.
6. The system as claimed in claim 1, wherein the creation of clusters is formed with the common cognitive radio nodes those can sense and determine the channel occupancy of the same set of frequency bands and those having high geo-correlation among other members of the common cognitive radio nodes.
7. The system as claimed in claim 1, wherein the processing unit (114) further calculates a seed-based sensing matrix per cluster.
8. The system as claimed in claim 7, where the seed-based sensing matrix per cluster is based on:
a number ofthe cognitive radio nodes (304) participating in the spectrum sensing,
a number of frequencies for sensing in that particular cluster, and
a number of times each of the frequency bands is to be sensed.
9. The system as claimed in 7, wherein the seed-based unique sensing matrix derived at each cluster ensures that all frequency bands to be sensed by equal number of member-radio in a cluster and sensing load is equally shared among the member-radios of the clusters.
10. The system as claimed in claim 1, wherein the clustersinclude an overlapping cluster or a non-overlapping cluster.
11. The system as claimed in claim 10, wherein in the non-overlapping cluster, allocation of the frequency bands in a uniform manner is achieved by the seed-based sensing matrix.
12. The system as claimed in claim 10, wherein in the overlapping clusters, uniform load sharing of the spectrum sensing is decided by the common cognitive radio members (304) in adjacent clusters, the common members vote for choosing the frequency band to be sensed before the generation of the sensing matrix to ensure the balanced sensing load.
13. A method for sharing spectrum sensing load in a radio network, the method comprising:
receiving, by a radio frequency (RF) unit (102), a radio frequency (RF) signals from a cognitive radio network (302);
determining, by a GPS unit (104), geo-coordinatesof each of plurality of a cognitive radio node (304);
calculating, by a spectrum sensing module (108) of a processing unit (114), a received signal strength (RSS) values for each of a frequency band of interest of the cognitive radio network (302);
calculating, by a channel property estimation module (116) of the processing unit (114), a probability of detection (Pd) valuesfor each of the frequency band of interest of the cognitive radio network (302);
sharing, by the channel property estimation module (116) of the processing unit (114),the calculated Pd values and the geo-coordinates values among the plurality of the cognitive radio nodes (202);
consolidating, by a cooperative sensing module (118) of the processing unit (114), the received Pd values and calculating a consolidated energy (CE) matrix;
receiving, by the cooperative sensing module (118) of the processing unit (114), the geo-coordinates values and calculating a geo-correlation (GC) matrix;
creating, by the cooperative sensing module (118) of the processing unit (114), one or more clusters having a common set of frequencies of the cognitive radio nodes based on the CE matrix and the GC matrix; and
allocating, by a MAC and Network module (112) of the processing unit (114), frequency-bands among a common cognitive radio node within the created clusters, uniformly in a distributed manner.
14. The method as claimed in claim 13, whereincalculating, by the channel property estimation module, the Pdvalues is based on the RSS values.
15. The method as claimed in claim 13, wherein calculating, by the cooperative sensing module (118), the consolidated energy (CE) matrix is based on the received Pd values.
16. The method as claimed in claim 13, wherein calculating, by cooperative sensing module (118), the GC matrix is based on the received geo-coordinates values.
17. The system as claimed in claim 13, wherein, calculating, by the processing unit, a seed-based sensing matrix per cluster.

Dated this 17th day of March, 2021

FOR BHARAT ELECTRONICS LIMITED
(By their Agent)

D. MANOJ KUMAR (IN/PA-2110)
KRISHNA & SAURASTRI ASSOCIATES LLP
, Description:FORM – 2

THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003

COMPLETE SPECIFICATION
(SEE SECTION 10, RULE 13)

A SYSTEM AND METHOD FOR DISTRIBUTED SHARING OF SPECTRUM SENSING LOAD IN COGNITIVE RADIO AD-HOC NETWORK

BHARAT ELECTRONICS LIMITED
WITH ADDRESS AT OUTER RING ROAD, NAGAVARA,
BANGALORE,
KARNATAKA, 560045

THE FOLLOWING SPECIFICATION PARTICULARLY DESCRIBES THE INVENTION AND THE MANNER IN WHICH IT IS TO BE PERFORMED

TECHNICAL FIELD
The present invention relates generally to spectrum sensing in a radio network. The invention, more particularly, relates to a systemand method fordistributed sharing of spectrum sensingload in a Cognitive Radio Ad-Hoc Networks (CRAHN).
BACKGROUND
Radio spectrum is a limited natural resource. Governments licensing policies generally allocate these radio spectrums such that only the incumbent users/licensees can use that spectrum. These licensing policies create an apparent scarcity of the radio spectrum for new emerging radio technologies. Various paradigms of Cognitive radio technology, e.g., interweave, underlay, and overlay, have the capability to deal with this issue, thereby creating an additional spectrum opportunity to fulfill the demand of the radio spectrum. In the interweave paradigm, the cognitive radio sense the radio spectrum, already licensed to some user, in a periodic manner to exploit any spectrum opportunity available. The vacant spectrum or the spectrum opportunity can be utilized by the unlicensed users.
There are many conventional solutions that exist for spectrum sensing, for example, one of a conventional solution is proposed in US20120163355A1 titled “Cognitive Radio Cooperative Spectrum Sensing Method And Fusion Center Performing Cognitive Radio Cooperative Spectrum Sensing” disclosesa cognitive radio (CR) cooperative spectrum sensing method and a fusion center (FC) performing CR cooperative spectrum sensing. The CR cooperative spectrum sensing method includes receiving, at an FC, local spectrum sensing information about a predetermined frequency band from each of N secondary users (SUs) in a predetermined zone, determining, at the FC, the optimum number of SUs for determining whether the predetermined frequency band is being used by a primary user (PU) on the basis of the received local spectrum sensing information, and performing cooperative spectrum sensing on the basis of local spectrum sensing information received from the optimum number of SUs in the predetermined zone. The method is implemented by the FC. Accordingly, the method and FC find how many SUs are needed to determine that a frequency of a PU is being used in a corresponding-channel situation, thereby enabling efficient communication.
Another conventional solution is proposed in US9148885B2 titled “Distributed assignment of frequency channels to transceivers over dynamic spectrum”discloses systems and methods of operating a wireless network including allocating and assigning frequency channels using a dynamic and distributed process. For example, a network node in an ad- hoc wireless network will assign frequency channels to one or more of its transceivers based on at least one of a list of allowed frequency channels and a neighbor-frequency channel list.
Another conventional solution is proposed in US7826850B2 titled “Frequency band allocation device and method” discloses a frequency band allocation device. The frequency band allocation device comprises a frequency band selection unit (1161, 1162) for selecting usable frequency bands from a dedicated frequency band, a registered frequency band and an unlicensed frequency band; and a frequency band allocation unit (1163) for allocating a frequency band out of the selected usable frequency bands to an uplink and downlink, so as to satisfy user required Quality of Service (QoS).
Another conventional solution is proposed in WO2010033333A2 titled “Method and apparatus for distributed sensing management and control within a cognitive radio network” discloses a technique for spectrum sensing management and control for a secondary communication system seeking to utilize another communication system's spectrum is provided (600). Sensor control data is sent from a base station to subscriber units (604). Sensing measurements are taken and sent back to the base station for ranking (608) as sensed feedback information. Comparisons of the sensed feedback information are made to each other and to thresholds aligned with the types of measurements taken (610). An initial ranked channel list is generated (612). Weighting of the initial ranking list and secondary ranking list is followed by re-ranking the channels according to the weighting into a final ranking list (612). The final ranking list is transmitted to the mobile units to enable operation within the other communication system's spectrum within interfering with that system (614). The weighting is based on the type of sensing measurement taken as opposed to the channel.
However, the above-provided conventional solutions for spectrum sensing phenomena can be misled in the presence of deep fading and shadowing. This problem can be minimized by implementing multiple Cognitive radios to sense the spectrums independently and then share their information to get the final decision about spectrum vacancy. Furthermore, the frequency bands available for sensing may be fixed but the availability of Cognitive radios for sensing in the ad-hoc network environment may vary. A radio user may leave the network because of some reasons like battery got discharged or weak network/coverage, etc. At the same time, a radio user may join the network and agreed to cooperate with other radios in finding spectrum vacancies. Butthe allocation of spectrum bands among radios for sensing may not be fixed to cope with the possible hack and attack by the invaders.
Thus, there is a need for an invention that solves one or more of the aforesaid problems and provides a cognitive radio system and method with distributed cooperation for spectrum sensing in a radio network.
SUMMARY OF THE INVENTION
This summary is provided to disclose a cognitive radio system and method for spectrum sensing and distributed sharing the spectrum sensing load among cognitive radios in a radio network. This summary is neither intended to identify essential features of the present invention nor is it intended for use in determining or limiting the scope of the present invention.
In an embodiment, the present invention describes a method for spectrum sensing load in a radio network. The method includes receiving, by a radio frequency(RF unit), a radio frequency (RF) signals from a cognitive radio network. The method further includes determining, by a GPS unit, geo-coordinates values of each of a plurality of cognitive radio nodes. The method further includes calculating, by a spectrum sensing module of a processing unit, a received signal strength (RSS) values for each of a frequency band of interest of the cognitive radio network. The method further includes calculating, by a channel property estimation module of the processing unit, probability of detection (Pd) valuesfor each of the frequency band of interest of the cognitive radio network. The method further includes sharing, by the channel property estimation module of the processing unit,the calculated Pd values, and the geo-coordinates values among the plurality of the cognitive radio nodes. The method further includes consolidating, by a cooperative sensing module (118) of the processing unit, the received Pd values and calculating a consolidated energy (CE) matrix,receiving the geo-coordinates values and calculating a geo-correlation (GC) matrix, andcreating one or more clusters having a common set of frequencies of the cognitive radio nodes based on the CE matrix and the GC matrix. The method further includes allocating, by a MAC and Network moduleof the processing unit, frequency-bands among a common cognitive radio node within the created clusters, uniformly in a distributed manner.
The method also includes creating, by MAC and Network module of the processing unit, one or more clusters having cognitive radio nodesthose have the capacity to sense the common set of frequencies based on the consolidated energy (CE) matrix and the geo-correlation (GC) matrix. The method also includes calculating, by the processing unit, a seed-based sensing matrix, and allocating, by the processing unit, frequency-bands among the common cognitive radio nodes within the created clusters, uniformly in a distributed manner.
In another embodiment, the present invention describes a cognitive radio system for spectrum sensing load in a radio network. The system comprising a radio frequency (RF) unit configured to receiveradio frequency (RF) signals from a cognitive radio network. The system further includes a GPS unit configured to determine geo-coordinatesof each of plurality of cognitive radio nodes. The system further includes a processing system. The processing system includes a spectrum sensing module configured to calculate received signal strength (RSS) values for each of a frequency band of interest of the cognitive radio network. The processing system further includes a channel property estimation module. The channel property estimation module calculates a probability of detection (Pd) valuesfor each of the frequency band of interest of the cognitive radio networkandshare the calculated Pd values and the geo-coordinates values among the plurality of the cognitive radio nodes. The processing system further includes a cooperative sensing module. The cooperative sensing moduleconsolidates the received Pd values and calculate a consolidated energy (CE) matrix, receive the geo-coordinates values and calculate a geo-correlation (GC) matrix, and create one or more clusters having a common set of frequencies of the cognitive radio nodes based on the CE matrix and the GC matrix. The processing system further includes a MAC and Network module configured to allocate frequency-bands among a common cognitive radio nodes within the created clusters, uniformly in a distributed manner.
In another embodiment of the present invention,for sensing the spectrum occupancy in a radio network, allocation of the frequency bands among network-enabled cognitive radio nodes through a distributed cooperative approach is disclosed. The system includes a plurality of cognitive radio nodes. Each of the plurality of the cognitive radio nodes comprising a radio frequency (RF) unit, a GPS unit, and a processing unit. The RF unit is configured to receive RF signals from the radio network. The GPS unit of the present system is configured to determine geo-coordinates of the cognitive radio node. After determining, channel property estimation module of the processing unit shares the geo-coordinates values of each of the cognitive radio nodeamong the plurality of the cognitive radio nodes, and then calculate a geo-correlation (GC) matrix upon receiving the geo-coordinates values. Further, the processing unit of the present system derives various parameters required information of clusters. The processing unit is configured to calculate a probability of detection (Pd) values for each of the frequencies of the received RF signals of the radio network. Further, the calculated Pd values are shared by the processing unit among the plurality of the cognitive radio nodes in the radio network. A consolidatedenergy matrix (CE) is calculated based on the received Pd values. The processing unit further, create one or more clusters having a common set of frequencies of the cognitive radio nodes based on the consolidated energy (CE) matrix and the geo-correlation (GC) matrix. The processing unit of the present system further calculates a seed-based sensing matrix and allocates frequency-bands for spectrum sensing among the common cognitive radio nodes within the created clusters, uniformly in a distributed manner.
BRIEF DESCRIPTION OF ACCOMPANYING DRAWINGS
The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to reference like features and modules.
Figure 1 illustrates a blockdiagramdepicting a hardware architecture ofa cognitive radio system, according to an embodiment of the present invention.
Figure2 illustrates a schematic diagram depicting a pictorial view of geo-located cognitive radio nodes, according to an embodiment of the present invention.
Figure3 illustrates a flow diagramdepicting creation of clusters, according to an exemplary implementation of the present invention.
Figure4 illustrates a schematic diagram depictingan over-lapped clustering scenario, according to an exemplary embodiment of the present disclosure.
Figure5 illustrates a flow chart depicting a method for spectrum sensing in a radio network, according to an exemplary implementation of the present invention.
It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative methodsembodying the principles of the present disclosure. Similarly, it will be appreciated that any flow charts, flow diagrams, and the like represent various processes that may be substantially represented in a computer-readable medium and so executed by a computer or processor, whether or not such computer or processor is explicitly shown.
DETAILED DESCRIPTION
The various embodiments of the present inventiondescribea system and method for spectrum sensing in a radio network. The method and the system allocate frequency bands among network-enabled cognitive radio nodes for sensing the spectrum occupancy, through a distributed cooperative approach.
In the following description, for purpose of explanation, specific details are outlined to provide an understanding of the present disclosure. It will be apparent, however, to one skilled in the art that the present disclosure may be practiced without these details. One skilled in the art will recognize that embodiments of the present disclosure, some of which are described below, may be incorporated into a number of systems.
However, the systems and methodsare not limited to the specific embodiments described herein. Further, structures and devices shown in the figures are illustrative of exemplary embodiments of the presentlydisclosureand are meant to avoid obscuring the presentlydisclosure.
It should be noted that the description merely illustrates the principles of the present invention. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described herein, embody the principles of the present invention. Furthermore, all examples recited herein are principally intended expressly to be only for explanatory purposes to help the reader in understanding the principles of the invention and the concepts contributed by the inventor to furthering the art and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, andembodiments of the invention, as well as specific examples thereof, are intended to encompass equivalents thereof.
In one of the exemplary implementations, the novel aspects of the present invention are disclosed. The system and method of the present invention describe allocating frequency bands among network-enabled cognitive radio nodes for sensing the spectrum occupancythrough a distributed cooperative approach. The method of clustering agroup of cognitive radio nodes is equipped with the hardware of an amplifier, an antenna, and processors that perform the radio functionalities. In an embodiment, the radio functionalities include, but are not limited to, radio frequency carrier reception/transmission, modulation, voice/data processing, and sensing the spectrum occupancy. The present invention further provides the system of combing the radios based on a trust index that is ameliorating the spectrum sensing efficiency based on RSS (Received Signal Strength), Pd(Probability of Detection), and Geo-Location.
In one of the implementations, the present invention describes a method for sharing spectrum sensing load in a radio network. The method includes receiving, by a radio frequency(RF unit), a radio frequency (RF) signals from a cognitive radio network. The method further includes determining, by a GPS unit, geo-coordinates values of each of a plurality of cognitive radio node. The method further includes calculating, by a spectrum sensing module of a processing unit, an RSS (received signal strength) values for each of a frequency band of interest of the cognitive radio network. The method further includes calculating, by a channel property estimation module of the processing unit, a probability of detection (Pd) valuesfor each of the frequency band of interest of the cognitive radio network. The method further includes sharing, by the channel property estimation module of the processing unit,the calculated Pd values, and the geo-coordinates values among the plurality of the cognitive radio nodes. The method further includes consolidating, by a cooperative sensing module of the processing unit, the received Pd values and calculating a consolidated energy (CE) matrix,receiving the geo-coordinates values and calculating a geo-correlation (GC) matrix, andcreating one or more clusters having a common set of frequencies of the cognitive radio nodes based on the CE matrix and the GC matrix. The method further includes allocating, by a MAC and Network module of the processing unit, frequency-bands among a common cognitive radio node within the created clusters, uniformly in a distributed manner.
In another implementation of the present invention, the method further includes sharing, by channel property estimation module of the processing unit, the geo-coordinate values of each of the cognitive radio node among the plurality of the cognitive radio nodes, and calculating, by a cooperative sensing module of the processing unit, a geo-correlation (GC) matrix upon receiving the geo-coordinates values of each of plurality of the cognitive radio nodes. The method further includes calculating, by a processing unit, a probability of detection (Pd) values for each of frequencies of the received RF signals of the radio network. The method further includes sharing, by the processing unit, the calculated Pd values among the plurality of the cognitive radio nodes in the radio network, and consolidating the received Pd values, and calculating a consolidated energy (CE) matrix. The method further includes creating, by the processing unit, one or more clusters having a common set of frequencies of the cognitive radio nodes based on the consolidated energy (CE) matrix and the geo-correlation (GC) matrix. The method also includes calculating, by the processing unit, a seed-based sensing matrix, and allocating, by the processing unit, frequency-bands among the common cognitive radio nodes within the created clusters, uniformly in a distributed manner.
In another implementation, the present invention describescalculating, by the channel property estimation module, the Pd values is based on the RSS valuesof the received RF signals.
In another implementation, the present invention describes the method of calculating, by the cooperative sensing module, the consolidated energy (CE) matrix is based on the received Pd values.
In another embodiment, the present invention describes the allocation of the frequency-bands among the common cognitive radio nodes within the created clusters, uniformly in a distributed manner without the need of any central entity or a base station.
In another embodiment, the present invention describes the creation of clusters. The creation of clusters is formed with the common cognitive radio nodes that can sense and determine the channel occupancy of the same set of frequency bands and those having high geo-correlation among other members of the common cognitive radio nodes.
In another embodiment, the present invention describes a processing unit. The processing unit of the present system calculates a seed-based sensing matrix per cluster. The seed-based sensing matrix per cluster is based on:a number of the cognitive radio nodes participating in the spectrum sensing,a number of frequencies for sensing in that particular cluster, anda number of times each of the frequency bands are to be sensed.The seed-based unique sensing matrix derived at each cluster ensures that all frequency bands to be sensed by equal number of member-radio in a cluster and sensing load is equally shared among the member-radios of the cluster.
In another embodiment, the present invention discloses a overlapping cluster and non-overlapping cluster. In the non-overlapping cluster, allocation of the frequency bands in a uniform manner is achieved by the seed-based sensing matrix, whereas in the overlapping clusters, uniform load sharing of the spectrum sensing is decided by the common cognitive radio members in adjacent clusters, the common members vote for choosing the frequency band to be sensed before the generation of the sensing matrix to ensure the balanced sensing load.
In another implementation, the present invention describes that the seed-based sensing matrix is calculated for the amelioration of the spectrum sensing in the radio network with peer cognitive radio nodes of the radio network. The radio network is a cognitive radio Ad-hoc network (CRAHN).
In another embodiment, the present invention describes a cognitive radio system for spectrum sensing in a radio network. For sensing the spectrum occupancy in a radio network, allocation of the frequency bands among network-enabled cognitive radio nodes through a distributed cooperative approach is applied. The system includes a plurality of cognitive radio nodes. Each of the plurality of the cognitive radio nodes comprising a radio frequency (RF) unit, a GPS unit, and a processing unit. The RF unit is configured to receive RF signals from the radio network. The GPS unit of the present system is configured to determine the geo-coordinates value of a cognitive radio node. After determining, by a channel property estimation module of the processing unit, shares the geo-coordinates values of the cognitive radio node, and then calculates a geo-correlation (GC) matrix upon receiving the geo-coordinates values from the plurality of the cognitive radio nodes in the network. Further, the processing unit of the present system derives various parameters required information of the clusters. The processing unit is configured to calculate a probability of detection (Pd) values for each of frequencies of the received RF signals of the radio network. Further, the calculated Pd values are shared among the plurality of the cognitive radio nodes in the radio network. The processing unit further consolidates the received Pd values and calculate a consolidated energy matrix (CE) based on the received Pdvalues. The processing unit further, creates one or more clusters having cognitive radio nodes those have the capacity to sense the common set of frequencies,based on the consolidated energy (CE) matrix and the geo-correlation (GC) matrix. The processing unit of the present system further calculates a seed-based sensing matrix and allocates the frequency-bands among the common cognitive radio nodes within the created clusters, uniformly in a distributed manner.
In another embodiment, the present invention describes the calculation of the GC matrix. The GCmatrix is calculated by each of the plurality of the cognitive radio nodes.
In another embodiment, the present invention describes that the common cognitive radio nodes those have the capacity to sense the common set of frequencies form a cluster. The nodes of the cluster are further filtered based on their respective geo-coordinate values. The filtered cognitive radio nodes having high geo-correlation among other member-radios of the cluster.
In another embodiment, the present invention describes the seed-based sensing matrix is calculated per cluster. The seed-based sensing matrix calculated per cluster is based on a number of cognitive radio nodes participating in spectrum sensing, a number of frequencies for sensing in that particular cluster, and a number of times each of the frequency bands is to be sensed.
In another embodiment, the present invention describes channel sensing. In the channel sensing, the probability of detection,Pd, and the probability of false alarm, Pf, are significant indicators for measuring the spectrum sensing accuracy. Here, Pd is defined as the probability that the spectrum is sensed busy/occupied when it is actually busy/occupied. Pfis defined as the probability that the spectrum is sensed busy/occupied when it is actually vacant. In an embodiment, an energy detection method is performed by the cognitive radio nodes to sense the channel occupancy in which the RSS is used for determining whether the channel is occupied or not. If the RSS is above a threshold, then the channel is defined as an occupied channel. The threshold of determining the channel occupancy is chosen and agreed among the cognitive radio nodes. Every node in a radio network is configured to estimate itsPdbased on the RSS value for every chosen frequency of the RF signals of the spectrum.
In an embodiment, the Pdvalue of each spectrum determined by each cognitive radio node is shared among other cognitive radio nodes. Upon receiving the Pd values from all the other cognitive radio nodes, each cognitive radio node consolidates the received Pdvalue and calculatea consolidated energy (CE) matrix. Every cognitive radio node sharesitself geo-coordinates values among other cognitive radio nodes. Upon receiving the geo-coordinates values from all the other cognitive radio nodes, each cognitive radio nodes calculate a geo-correlation (GC) matrix.
In another embodiment, the technical advantages of the present invention are disclosed. The system and method guarantee the uniformity in distributing frequency bands among the plurality of the cognitive radio nodes of a clustered group, such that all the cognitive radio nodes in that devised group equally share the spectrum sensing load and each of the frequency bands in the RF signals to be sensed by a nearly equal number of cognitive radio nodes in cooperation.
Another advantage of the present invention provides robustness of a frequency allocation strategy. The robustness is achieved by varying the frequency bands allocation in every cycle while maintaining the uniformity among sensed bands and cooperating cognitive radio nodes.
Figure 1 illustrates a block diagram depicting a hardware architecture of a cognitive radio system.
The architecture includes aradio frequency (RF) board (101) and a baseband and network processing board/or processing unit (114). In an embodiment, each cognitive radio node includesthe RF board (101). The RF board (101) of thecognitive radio node,but not limited to, consists of a flexible antenna system, an RF unit (102), a GPS unit (104), an analog-to-digital and digital-to-analog convertermodule (106).
In an embodiment, the RF unit (102) consists of a bank of an RF chain that can be adapt/change according to the requirement. A particular RF chain gets configured depending upon, but is not limited to,the frequency band of interest, corresponding bandwidth, and modulation scheme. In another embodiment, the RF unit (102) is configured to receive/transmit in the frequency range from 30 MHz (Megahertz)to 1GHz (Gigahertz). The RF unit (102) consists of a bank of filters, and the A/D/A (Analog to digital convertor and Digital to analog converter)module (106). The A/D/A module (106) is configured to filter the data of the desired frequency range.
In an embodiment, the cognitive radio node works in two modes, namely a sensing mode and a communication mode. In the sensing mode, the cognitive radio node performs only spectrum sensing and in the communication mode, the cognitive radio node sends or receives data among peer cognitive radio nodes. In the sensing mode, the RF data gets filtered, at the GPS unit(104) andthe A/D/A module (106),is sent to aspectrum sensing module (108) of the baseband & network board (114), where the spectrum occupancy sensing is carried out. In the communication mode, the RF data filtered at the GPS unit(104)and the A/D/A (106),is sent to a baseband module (110) of the baseband & network processing board/unit (114).
Further, the GPS unit (104)of the RF board (101) is configured to determine a geo-coordinate value of each of the plurality of cognitive radio nodes (304). Further, the analog-to-digital and digital-to-analog converters module (106) are part of the RF unit (102) and are configured for the corresponding conversion of the signal.
The baseband and network processing board/unit(114)is configured to perform all the signal processing activities of the cognitive radio node.The baseband and network processing unit (114) includes the baseband module (110), the spectrum sensing module (108), a channel property estimation module (116), a cooperative spectrum sensing module (118), and a MAC and network processing module (112).
The baseband module (110) is configured to modulate/demodulate the RF signals and coding. Further, the spectrum sensing module (108) is configured to monitor the availability of the signal in the spectrum and/or frequency bands of interest, thereby finding the spectrum occupancy. The MAC and network processing module(112) of the radio node is configured to establish the network and communication between the radio nodes.
Figure 2 illustrates a schematic diagram depicting a pictorial view of geo-located cognitive radio nodes. A plurality of the cognitive radio nodes (202) monitors the availability of the signals in the spectrum or the radio network or the frequency of interest, for spectrum sensing.
Figure 3 illustrates a flow diagramdepicting the creationof clusters. In Figure 3, the cognitive radio system comprising the plurality of the cognitive radio nodes (304)present in the spectrum/frequency-band of the interest/radio network, as shown at a block (302). In an embodiment, the plurality of the cognitive radio nodes (304) refers tomore than one cognitive radio node, and these nodes are present in the radio network or the network of interest, as shown at the block (302). A cognitive radio node (304) operates in a MANET (Mobile Ad-Hoc network) scenario, and this network is known as CRAHN (cognitive radio Ad-Hoc network). In an embodiment, the network considered in the present inventionis a CRAHN network. In theCRAHN, any radio network can self-join and self-form with the network. In such theCRAHN, the spectrum sensing is exercised for dynamically choosing an un-occupied channel for ameliorating the transmission efficiency of the radios. The spectrum occupancy is sensed by all the cognitive radio nodes (304) in the CRAHN. The sensed information is shared among all the cognitive radio nodes (304).
In an embodiment, the cognitive radio node (304) of the system consists of the RF unit (102), the processing unit (114), and the GPS unit (104). The RF unit (102) in the front end of each of the cognitive radio node(304) is configured to receive the RF signal from the spectrum/ or the radio network/or the frequency band of interest (302).
The received signals are transmitted from the RF unit (102) of each of the cognitive radio node (304) towards the processing unit (114). A spectrum sensing module (108) of the processing unit (114) is configured to calculate received signal strength (RSS) values for each of a frequency band of interest of the cognitive radio network (302), and, a channel property estimation module (116) of the processing unit (114) is configured to calculate a probability of detection (Pd) valuesfor each of the frequency band of interest of the cognitive radio network (302), as shown at block (306). In an embodiment, the Pdis defined as the probability that the spectrum is sensed busy/occupied when it is actually busy/occupied.
Each of the cognitive radio (304) calculates the average Pdinformation for each spectrum as below:
d_(i,j)=?_(k=1)^M¦(P_(d,i,j) (k))/M,where i=1,2,……N and j=1,2…..S
where ‘M’ is time statistics. The sensing information is collected for ‘M’ times ‘N’ is the number of radio nodes in a cluster. ‘S’ is the frequency band for sensing. P_(d,i,j) (k) represents the probability of detection for jth frequency band by ith radio node at kth time instant.
The Pd values and the geo-coordinates valuesare subsequently shared among all the plurality of the cognitive radio nodes (304), by a channel property estimation module (116) of the processing unit (114), as shown at a block (308). Based on the Pd values, the consolidated energy matrix (CE) is calculated by a cooperative sensing module (118) of the processing unit(114), as shown at a block (310), that is finally used in the creation of the clusters, as shown at a block (318).
Further, the system of the present invention includes the GPS unit (104). The GPS unit (104) is configured to determine the geo-coordinates values of the cognitive radio node(202),as shown at a block (312). Further, sharing of the geo-coordinates values of each of the cognitive radio node (304) among the plurality of the cognitive radio nodes (202) is performed by the channel property estimation module (116), as shown at a block (314). Further, calculation of a geo-correlation (GC) matrix having GC matrix values upon receiving the geo-coordinates values is performed by the cooperative sensing module (118),as shown at a block (316),that are finally used in the refining the creation of the clusters. The geo-correlation matrix is calculated based on the nearness/co-location of the cognitive radio nodes (202).
Each of the cognitive radio node (304) estimates the GC matrix with respect to their geo-coordinates values. The correlation coefficient of the geo-coordinates between other nodes (202) in the network (302) is defined as ?_(a,i), where ‘a’ is the index of the self-node and ‘ i’ is all the other nodes (202) in the network (302). The geo-correlation matrix (GC) is as shown below:

The diagonal matrix ?_(a,a), which is self-correlated, and the elements below the diagonal is not considered. A threshold ‘? ‘can be chosen as per the user requirements. For every row member, if the ?_(a,i)> ?, thenodes are grouped with node ‘a’. The same is applied to every row member.
Upon receiving the GC matrix and CE matrix, the clusters of the cognitive radio nodes(304) are formed based on the GC matrix and CE matrix.The cognitive radio nodes (304) are grouped into various clusters for spectrum sensing. The set of radio nodes (304) that sense the same set of frequencies forms a cluster. The clusters formed may be overlappingor non-overlapping cluster. The overlapping clusters mean some of the radio nodes are shared/common in more than one cluster. Similarly, in non-overlapping clusters, the radio nodes are not shared/common with any other clusters.
In another embodiment, a seed-based sensing matrix is derived by each of the cognitive radio node(304) within the cluster. The the seed-based sensing matrix per cluster is based on:a number of the cognitive radio nodes (304) participating in the spectrum sensing,a number of frequencies for sensing in that particular cluster, anda number of times each of the frequency bands is to be sensed.
The sensing matrix, finally, allocates the frequency bands to the cognitive radio nodes (304) for sensing at a particular instant. The seed-based sensing matrix guarantees the uniformity and fairness of sensing load among the cognitive radio nodes(304) and the frequency bands.
In an exemplary implementation of the present invention, the creationof the clusters is disclosed. The processing unit (114) of each of the cognitive radio node (304) executes aclustering algorithm. A cluster is createdin three steps:
At step 1:A member cognitive radio node (304) of the cluster is decided based on the consolidated energy (CE) matrix.
Every cognitive radio node (304) calculates the average Pdinformation for each spectrum of each cognitive radio node (304) as below:
d_(i,j)=?_(k=1)^M¦(P_(d,i,j) (k))/M,where i=1,2,……N and j=1,2…..S
where ‘M’ is time statistics. The sensing information is collected for ‘M’ times, ‘N’ is the number of nodes in a cluster. ‘S’ is the frequency band for sensing. P_(d,i,j) (k) represents the probability of detection for jth frequency band by ith radio node at a kth time instant.
Table 1a is a P_dmatrix of node’1’ and Table 1b is P_d matrix for ‘ith’ the node. The consolidated Pdvalues for all ‘i nodes Vs all ‘S’ frequencies of interest are illustrated in Table 1c.
Table 1a: For the cognitive radio node (304) number 1

Table 1a

Table 1b: For the ithnode

Table 1b
Table 1c: CE matrix for all the cognitive radio nodes (202)

Table 1c
The node is picked for sensing a particular spectrum for which d_(i,j)>?. The value of ‘?’can be chosen between 0.7 to 0.9, depending upon the user requirements. The radio nodes that sense the same set of frequencies are grouped.
At step 2:The member cognitive radio node (304) of the cluster is decided based on the Geo-Correlation matrix.Every radio node (304) estimates the correlation matrix with respect to their geo-coordinates values.
The correlation coefficient of geo-coordinates between other nodes (304) in the network (302) is defined as ?_(a,i), where ‘a’ is the index of the self-node and ‘i’ is all the other nodes (304) in the network (302). The geo-correlation matrix (GC) is as shown below:

The diagonal matrix ?_(a,a), that is self-correlated and the elements below the diagonal is not considered.
A threshold ‘?’ can be chosen as per the user requirements.
For every row members if the ?_(a,i)> ?, those nodes are grouped with node ‘a’.
The same is applied to every row member. Finally, common nodes are combined to yield a cluster.
At step 3:Combining the common member cognitive radio nodes in the cluster of both CE and a correlation method is finalized.
Group of common members of both the methods of Step 1 &Step 2 is merged to yield a cluster.
In another exemplary implementation of the present invention, an illustration for spectrum sensing is disclosed. In the illustration, the CRAHN of 16 nodes is considered. The number of spectrums to be scanned is considered to be 8. After sharing Pdvalues by all the cognitive radio nodes, each of the cognitive radio node constitutes CE matrix as shown in Table 2 below.

Table 2
With reference to Table 2, clustering is formedas below:
Nodes 1 to 5 sense F1, F3, F5;
Node 5 sense F2;
Nodes 6 to 10 sense F2 and F4, F6;
N9 and N10 sense F7 and F8 also
Nodes 11 to 16 sense F7 and F8;
N11 and N12 sense F3 and F5 also N13 sense F3, F5 and F2, F6 also, N14 sense F2, F6 also.
Cluster 1 is formed with nodes that sense F1, F3, F5.
Cluster 2 is formed with nodes that sense F2, F4, F6.
Cluster 3 is formed with nodes that sense F7, F8.
The example illustration of clustering for the CE matrix of Table 2 iscalculated as per the information based in Figure 4.
Once the cluster is formed, each of the cognitive radio nodes know its cluster number. The radio nodes of the cluster sense the frequencies associated with the respective cluster.
Figure 4 illustrates a schematic diagram depicting an over-lapped clustering scenario. In the case of the overlapping cluster scenario, the allocation of the cognitive radio nodes (304) is revised based on the sensing load of the cognitive radio nodes (304).
The cluster (402) consists of frequencies F1, F3, and F5 for sensing. Cognitive radio nodes N1, N2, N3, N4, N5, N11, N12, and N13 are capable to sense these frequency bands. The cognitive radio nodes N5 and N13 are also capable of sensing F2, F4, and F6 allocated to the cluster (404). The cognitive radio nodes N11, N12, and N13 are also capable of sensing F7 and F8 allocated to the cluster (406).
The cluster (404) consists of the frequencies F2, F4, and F6 for sensing. The cognitive radio nodes N5, N6, N7, N8, N9, N10, N13, and N14 are potentially capable to sense these frequency bands. Radio nodes N5 and N13 are also capable to sense the F1, F3, and F5 allocated to the cluster (402). The cognitive radio nodes N9, N10, N13, and N14 are also capable of sensing F7 and F8 allocated to the cluster (406).
Further, the cluster (406) consists of the frequencies F7 and F8 for sensing. The cognitive radio nodes N9, N10, N11, N12, N13, N14, N15, and N16 are potentially capable to sense these frequency bands. The radio nodes N11, N12, and N13 are also capable of sensing the F1, F3, and F5 allocated to the cluster (402). Furthermore, the cognitive radio nodes N9, N10, N13, and N14 are also capable of sensing the frequencies F2, F4, and F6 allocated to the cluster (404).
In an exemplary implementation of the present invention, the two possibilities of clustering are as follows.
Case 1: Non-overlapping cluster:
In the non-overlapping cluster, there is no common cognitive radio node in any of the clusters. The sensing of spectrum bands designated for the same cluster is shared uniformly among the cognitive radio nodes (304) of the same cluster. Not all the radio nodes of the same cluster sense all the bands provided in a particular cluster, rather the sensing job is distributed among the cognitive radio nodes (304) such that uniformity and fairness are guaranteed. The spectrum bands, provided for sensing in a particular cluster, are sensed by the equal number of the cognitive radio nodes (304). Also, the numbers of spectrum bands allotted for sensing among the cognitive radio nodes (304) are equally distributed such that no cognitive radio node (304) is largely or less loaded. Uniformity in bands distribution among the cognitive radio nodes (304) guarantees the fairness and equal load distributions.
In an ad-hoc wireless scenario, any cognitive radio node (304) may join or leave a particular sector. Hence, for assuring fairness in spectrum sensing, in such a dynamic scenario, a unique seed number that generates the sensing matrix. In order to determine the sensing matrix, the following four parameters are shared among the cognitive radio nodes (304) of the network (302):
a unique seed number;
a number of the radio nodes participating in sensing;
a number of spectrum bands for sensing in that particular cluster; and
number of times each band to be sensed.
Based on the above four parameters, each radio node (304) of a cluster calculatesa sensing matrix that confirms who will sense what.
The virtue of the sensing matrix is that it is the same at all the cognitive radio nodes (304) in a particular cluster at a particular instant of time. Hence, which radio node (304) is sensing which frequency bands in a particular sensing interval is not required to share among radio nodes (304), thereby the sharing overhead is reduced. The creation of the same sensing matrix at all the radio nodes (304) in theparticular cluster at a particular instant of time is achieved because of the same unique seed shared among the cognitive radio nodes (304). This seed value is also changed randomly to get robustness against any possible attacks. Only overhead is that the newly generated seed value is needed to be shared securely among all participating radio nodes (304).
For example, in a sector, there are 16 numbers of bands for sensing by 12 number of available radio nodes. Further, it is decided that suppose each band is sensed by 3 radio nodes. The seed value is assumed to be 1945 and it is shared among all the 12 radio nodes. The sensing matrix created by the method and system proposed in the presentinvention is detailed in Table 3 shown below.
Bands

Radios f1 f2 f3 f4 f5 f6 f7 f8 f9 f10 f11 f12 f13 f14 f15 f16
Radio 1
Radio 2
Radio 3
Radio 4
Radio 5
Radio 6
Radio 7
Radio 8
Radio 9
Radio 10
Radio 11
Radio 12

Table 3
In Table 3, f1 to f16 represents the 16 number of bands for sensing. In Table 3, “1” denotes that the corresponding band in a column is sensed by a corresponding radio node in the row. “0” denotes otherwise. From Table 3, it can be observed that each radio is sensing 4 number of frequency bands and each band is sensed by 3 number of radio nodes. In this way, the load of sensing among radios and number of times a particular band is sensed are fairly distributed.
In another situation, when the number of frequency bands sensed, the number of radio nodes available for sensing, and the number of times each band is required to be sensed are not in proper combination, then the load of sensing among radio nodes or the number of times a band is to be sensed may differ by 1 or 2, which will be averaged out in subsequent sensing cycle. For example, this scenario may arise when the number of frequency bands sensed, the number of radio nodes available for sensing, and the number of times each band is required to be sensed are 15, 11, and 4, respectively. In this case, the load distribution among radio nodes and the number of times a band is sensed is said to be fair in some sensing duration. The system and method take care of all such possible situations.
Case 2: Overlapping cluster:
In the overlapping cluster, same nodes can be part of two or more clusters. In such a case, the node which is part of two or more clusters can give its priority to sense the selected frequency bands of clusters, ensuring fairness in contributing equally for spectrum sensing. The choice of priority can be decided based on the load of the node. The common node can choose the frequencies of clusters before the calculation of the sensing matrix and hence the load of the common node is balanced.
In an embodiment, all radio nodes (304) share their sensing information with all other radio nodes (304) who are involved in sensing of the same frequency band. All radio nodes (304) then combine the sensing decisions about a particular frequency band to take the final decision about occupancy/vacancy.
Figure5 illustrates a flowchart depicting a method for spectrum sensing in a radio network, according to an exemplary implementation of the present invention.
A flow chart (500) as shown in Figure 5 is explained below with reference to Figure 3 as described above.
At step 502,receiving, by a radio frequency (RF) unit (102), a radio frequency (RF) signals from a cognitive radio network (302). In an embodiment, an RF unit (102) is configured to receive radio frequency (RF) signals from the radio network (302).
At step 504, determining, by a GPS unit (104), geo-coordinates of each of plurality of a cognitive radio node (304). In an embodiment, a GPS unit (104) is configured to determine a geo-coordinates values of each of plurality of cognitive radio node (304).
At step 506, calculating, by a spectrum sensing module (108) of a processing unit (114), an RSS (received signal strength) values for each of a frequency band of interest of the cognitive radio network (302). In an embodiment, a spectrum sensing module (108) is configured to calculate an RSS (received signal strength) values for each of a frequency band of interest of the cognitive radio network (302).
At step 508,calculating, by a channel property estimation module (116) of the processing unit (114), a probability of detection (Pd) valuesfor each of the frequency band of interest of the cognitive radio network (302). In an embodiment, a channel property estimation module (116) is configured to calculate a probability of detection (Pd) valuesfor each of the frequency band of interest of the cognitive radio network (302).
At step 510, sharing, by the channel property estimation module (116) of the processing unit (114), the calculated Pd values and the geo-coordinates values among the plurality of the cognitive radio nodes (202).In an embodiment, the channel property estimation module (116) is configured to share the calculated Pd values and the geo-coordinates values among the plurality of the cognitive radio nodes (202).
At step 512, consolidating, by a cooperative sensing module (118) of the processing unit (114), the received Pd values and calculating a consolidated energy (CE) matrix. In an embodiment, a cooperative sensing module (118) is configured to consolidate the received Pd values and calculating a consolidated energy (CE) matrix.
At step 514, receiving, by the cooperative sensing module (118) of the processing unit (114), the geo-coordinates values and calculating a geo-correlation (GC) matrix. In an embodiment, the cooperative sensing module (118) is configured to receive the geo-coordinates values and calculating a geo-correlation (GC) matrix.
At step 516,creating, by the cooperative sensing module (118) of the processing unit (114), one or more clusters having a common set of frequencies of the cognitive radio nodes based on the CE matrix and the GC matrix. In an embodiment, the cooperative sensing module (118) is configured to create one or more clusters having a common set of frequencies of the cognitive radio nodes based on the CE matrix and the GC matrix.
At step 518, allocating, by a MAC and Network module (112) of the processing unit (114), frequency-bands among a common cognitive radio node within the created clusters, uniformly in a distributed manner. In an embodiment, the MAC and Network module (112) is configured to allocate frequency-bands among a common cognitive radio node within the created clusters, uniformly in a distributed manner.
The foregoing description of the invention has been set merely to illustrate the invention and is not intended to be limiting. Since modifications of the disclosed embodiments incorporating the substance of the invention may occur to a person skilled in the art, the invention should be construed to include everything within the scope of the invention.