The present disclosure relates to a communication system, and more specifically relates to a method and a system for providing a contiguous slot in an unlicensed band of radio slot.
BACKGROUND
[0002] Wireless communication networking has become a backbone of today's portable modern world. Over the past few decades, deployment of wireless communication networks has increased dramatically. The wireless communication networks enable users to have access to various services such as voice-based services, video services, messaging services, broadcasting services, and the like. Currently, the wireless communication networks face multiple challenges and consistent efforts are being made to resolve them. Some of these challenges include management of wireless communication networks in an inefficient way, limited spectrum problem, bounced signals, interference of co-channels, wireless fidelity interference, changing conditions, and the like. One of the problems faced most consistently by wireless network operators is the interference problem. Multiple researches have been done and techniques have been designed to find the best interference free channel. Further, separately there have been multiple Wi-Fi radio chipset hardware model which could combine the channel as instructed but none of these have any solution to provide a complete solution in a wireless ecosystem. In an example, Cisco Meraki Enterprise-class 802.1 lac Aps with hardware model MR53 and Ruckus wireless, ChannelFly model are used for finding a best interference free channel. Similarly, a wireless network operating in same or similar one or more unlicensed bands have to suffer traffic or congestion and one or more unreliable connection issues that create problems for existing wireless network sharing at same channel.
[0003] In this era of rising deployment of the wireless communication networks, interference in unlicensed (i.e., Ultra Broadband Radio (UBR)) bands (such as 2.4 GHz and 5.8 GHz) has taken a toll. The interference degrades performance of the wireless communication networks at all level. Throughput

becomes about one-fifth due to interference in the wireless communication networks. The interference in the wireless communication networks leads to frustrating customer experience, dropped connection, operational in-efficiencies, higher field visits, and higher operational expenditure (OPEX). Currently, the wireless network operators are either purchasing expensive licensed band or deploying even more costly fibre links with below 100 Mbps capacity. On the other hand, the wireless network operators want higher throughput in the wireless communication networks and that too at a lower cost and to achieve higher throughput.
[0004] For example, a prior art reference "US20160302200A1" discloses a method and an apparatus for communicating over a wireless communication network. One communication device includes a processor configured to allocate, or receive allocation of, at least a portion of a first sub-band of a channel and at least a portion of a second sub-band of the channel for use by the communication device. The communication device further includes a plurality of encoders configured to independently encode first and second data for wireless transmission over the first and second sub-bands, respectively. The communication device further includes a transmitter configured to transmit the independently encoded first and second data over the first and second sub-bands, respectively.
[0005] Another prior art reference "Non-contiguous Channel Bonding for TV White Space Usage with NC-OFDM Transmission: Jianwen Gao, Et. Al." discloses a contiguous channel bonding for using more than one channels together in a TV white space in the IEEE 802.22-specified wireless regional area network system. In order to support more flexible channel usage, the method investigates non-contiguous channel bonding as a potential extended feature of IEEE 802.22 standard. In the method, a transceiver structure with non-contiguous orthogonal frequency-division multiplexing (OFDM) (NC-OFDM) transmission to support non-contiguous channel bonding is presented.
[0006] The existing methods disclose about bonding of non-contiguous slots in licensed as well as unlicensed spectrum to create a contiguous channel for

allocation. But there exists no method and system disclosing an interference free channel allocation by bonding non-contiguous slots in an unlicensed spectrum based on an interference score. Thus, there exists a need for an interference free channel allocation by bonding the non-contiguous slots in the unlicensed spectrum based on the interference score.
[0007] Any references to methods, apparatus or documents of the prior art are not to be taken as constituting any evidence or admission that they formed, or form part of the common general knowledge.
OBJECT OF THE DISCLOSURE
[0008] A principal object of the present disclosure is to disclose a method and a cloud intelligence engine for providing a contiguous slot in an unlicensed band of radio slot.
[0009] Another object of the present disclosure is to provide an interference free channel allocation in unlicensed spectrum.
[0010] Another object of the present disclosure is provide an interference free channel allocation by bonding non-contiguous slots in the unlicensed spectrum based on an interference score. Thus, high bandwidth requirement can be catered using the unlicensed band of the radio slots.
[0011] Another object of the present disclosure is to determine interference free non-contiguous slots and combine them to create a continuous slot to provide interference free channel slot, which may be allocated to a communications service provider (CSP).
[0012] Another object of the present disclosure is to provide an affordable gigabit wireless broadband solution in the unlicensed band using the cloud intelligence engine (e.g., interference avoidance cloud platform).
[0013] Another object of the present disclosure is to dynamically change a channel without any performance degradation.

SUMMARY
[0014] In a first aspect, a method for providing a contiguous slot in unlicensed band of radio slots is disclosed. The method includes selecting a plurality of non-contiguous slots in the unlicensed band of radio slots. Further, the method includes determining an interference score for each of the plurality of non-contiguous slots. Further, the method includes creating the contiguous slot by combining at least two non-contiguous slots based on the determined interference score. Further, the method includes allocating the at least two combined non-contiguous slots from the plurality of non-contiguous slots as the contiguous slot. The at least two non-contiguous slots in the unlicensed band of radio slots have lowest interference scores among the plurality of non-contiguous slots. Further, the method includes determining the interference score for each of the plurality of non-contiguous slots based on at least one interference key performance indicator (KPI). Further, the method includes scoring each slot based on the at least one interference KPI at a first time interval. The first time interval is a current time. Further, the method includes scoring each slot based on the at least one interference KPI at a second time interval. The second time interval is a historical time before the current time. Further, the method includes calculating a total score for each slot based on the scores of each slot at the first time interval and the second time interval. Further, the method includes determining the interference score for each of the plurality of non-contiguous slots based on the at least one interference KPI. Further, the method includes scoring each slot based on the at least one interference KPI at a first time interval. The first time interval is a current time. Further, the method includes scoring each slot based on the at least one interference KPI at a plurality of second time intervals. The plurality of second time intervals includes a plurality of historical time intervals before the current time. Further, the method includes calculating a total score for each slot based on the scores of each slot at the first time interval and the plurality of second time intervals. Further, the method includes providing a first threshold for interference score for each of the plurality of non-contiguous slots. Further, the method includes selecting the at least two non-contiguous slots having

interference scores above the first threshold to create the contiguous slot by combining the selected at least two non-contiguous slots.
[0015] The interference score is determined after every first time interval. The number of non-contiguous slots to be combined to create the contiguous slot is based on channel required by a user of a customer premises equipment. The plurality of non-contiguous slots include at least one of 5 MHz slots, 10 MHz slots, 15 MHz slots, 20 MHz slots, 40 MHz slots, and 60 MHz slots. A maximum of four non-contiguous slots are combined to create the contiguous slot for allocation. The at least one interference KPI is determined by at least one of a spectrum analyzer output, a link outage duration count, a syslog data with connection disconnection, retransmission of a packet, drop in received signal, and a link utilization.
[0016] In a second aspect, a cloud intelligence engine for providing a contiguous slot in an unlicensed band of radio slots is disclosed. The cloud intelligence engine includes an artificial intelligence (AI) based interference mitigation and avoidance controller coupled with a processor and a memory. The AI based interference mitigation and avoidance controller may be configured to select a plurality of non-contiguous slots in the unlicensed band of radio slots. Further, the AI based interference mitigation and avoidance controller may be configured to determine an interference score for each of the plurality of non-contiguous slots. Further, the AI based interference mitigation and avoidance controller may be configured to create the contiguous slot by combining at least two non-contiguous slots based on the determined interference score. Further, the AI based interference mitigation and avoidance controller may be configured to allocate the at least two combined non-contiguous slots from the plurality of non-contiguous slots as the contiguous slot.
[0017] These and other aspects of the embodiments herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions, while indicating preferred embodiments and numerous specific details thereof, are given by way of illustration and not of

limitation. Many changes and modifications may be made within the scope of the embodiments herein without departing from the spirit thereof, and the embodiments herein include all such modifications.
BRIEF DESCRIPTION OF FIGURES
[0018] The method and the system are illustrated in the accompanying drawings, throughout which like reference letters indicate corresponding parts in the various drawings. The embodiments herein will be better understood from the following description with reference to the drawings, in which:
[0019] FIG. 1 illustrates an example overview of a network management system providing a gigabit wireless solution to a plurality of customer premises.
[0020] FIG. 2 illustrates an example of a wireless communication network environment in which the network management system provides the gigabit wireless solution in an unlicensed band using a cloud intelligence engine.
[0021] FIG. 3 illustrates an example of the wireless communication network environment in which the network management system provides the gigabit wireless solution in the unlicensed band using the cloud intelligence engine based on a slot interference score.
[0022] FIG.4 is a block diagram of the cloud intelligence engine.
[0023] FIG. 5 is an example illustration in which the cloud intelligence engine creates the contiguous slot by combining two non-contiguous slots based on a determined interference score.
[0024] FIG. 6 illustrates an architecture of hardware of a base station.
[0025] FIG. 7 is a flow chart illustrating a method for providing a contiguous slot in the unlicensed band of the radio slots.
DETAILED DESCRIPTION
[0026] In the following detailed description of embodiments of the invention, numerous specific details are set forth in order to provide a thorough understanding of the embodiment of invention. However, it will be obvious to a person skilled in the art that the embodiments of the invention may be practiced

with or without these specific details. In other instances, well known methods, procedures and components have not been described in details so as not to unnecessarily obscure aspects of the embodiments of the invention.
[0027] Furthermore, it will be clear that the invention is not limited to these embodiments only. Numerous modifications, changes, variations, substitutions and equivalents will be apparent to those skilled in the art, without parting from the scope of the invention.
[0028] The accompanying drawings are used to help easily understand various technical features and it should be understood that the embodiments presented herein are not limited by the accompanying drawings. As such, the present disclosure should be construed to extend to any alterations, equivalents and substitutes in addition to those which are particularly set out in the accompanying drawings. Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are generally only used to distinguish one element from another.
[0029] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. Also, the various embodiments described herein are not necessarily mutually exclusive, as some embodiments can be combined with one or more other embodiments to form new embodiments. The term "or" as used herein, refers to a non-exclusive or, unless otherwise indicated. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein can be practiced and to further enable those skilled in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0030] The present disclosure discloses a method and a system for providing a contiguous slot in an unlicensed band of radio slots. The method includes selecting a plurality of non-contiguous slots in the unlicensed band of

radio slots and determining an interference score for each of the plurality of non-contiguous slots. Further, the method includes creating the contiguous slot by combining at least two non-contiguous slots based on the determined interference score and allocating the at least two combined non-contiguous slots from the plurality of non-contiguous slots as the contiguous slot.
[0031] Referring now to the drawings, and more particularly to FIGS. 1 through 8.
[0032] FIG. 1 illustrates an example (100) overview of a network management system (108) providing a gigabit wireless solution to a plurality of customer premises (102a-102c). In the example (100), number of the plurality of customer premises is 3. Alternatively, the number of the plurality of customer premises may vary. Each of the plurality of customer premises (102a-102c) may include a plurality of customer premises equipment (206) (as shown in the FIG. 2). The plurality of customer premises equipment (206) may include wireless fidelity routers and a multiport Ethernet switch. The plurality of subscribers may be present inside each of the plurality of customer premises having one or more communication devices.
[0033] Each of the one or more communication devices may be a portable communication device. The portable communication device may include, but not limited to, a laptop, a smartphone, a tablet, a palmtop, a flexible device, an Internet of things (IoT) device, a smart watch and any wearable communication device. Alternatively, each of the one or more communication devices may be a fixed communication device. The fixed communication device may include, but not limited to, a desktop, a workstation, a smart television (TV) and a mainframe computer. In the example (100), the plurality of customer premises equipment (206) of each of the plurality of customer premises may be wirelessly connected with a base station (104) through a plurality of channels. Number of the plurality of channels may be 4. Alternatively, the number of the plurality of channels may vary. The base station (104) may communicate with a switch/convertor (106). The detailed operations and functions of the base station (104) are explained in FIG. 6. The base station (104) and a customer-provided equipment (CPE interface) (not

shown) may be interfaced, through air, with the channels chosen as per channel selection techniques. In an example, the CPE may assign channels to Wi-Fi access points connected to it via an Ethernet and each Wi-Fi access points may serve various users through a wireless interface.
[0034] FIG. 2 illustrates an example (200) of a wireless communication network environment in which the network management system (108) provides the gigabit wireless solution in an unlicensed band using a cloud intelligence engine (202). The wireless communication network environment may include the plurality of customer premises equipment (206), the base station (104) and the switch/convertor (106). In addition, the wireless communication network environment may include the network management system (108) and the cloud intelligence engine (202). The above stated elements of the wireless communication network environment may operate coherently and synchronously to provide the gigabit wireless solution in the unlicensed band using the cloud intelligence engine (202). The customer premises equipment (206) may be operated with a spectrum analyser (204) and a packet sniffer (208).
[0035] The plurality of customer premises equipment (206) may correspond to a terminal and associated equipment located at the customer premise (102) of corresponding subscriber of a plurality of subscribers. A customer premises equipment (206) may include telephones, routers, network switches, residential gateways (RG), set-top boxes, fixed mobile convergence products, home networking adapters, Internet access gateways, and the like.
[0036] The base station (104) may perform wireless communication with the plurality of customer premises equipment (206). For example, the base station (104) may perform the wireless communication with the customer premises equipment (206) that is positioned within a cell, which is a communication area of the base station (104). Specifically, the base station (104) may transmit a downlink signal to the plurality of customer premises equipment (206) and may receive an uplink signal from the plurality of customer premises equipment (206). In an example, the base station (104) may correspond to a base station of a small cell (hereinafter referred to as a "small base station"). In another example, the

base station (104) may correspond to a base station of a macro cell (hereinafter referred to as a "macro base station").
[0037] The base station (104) and the plurality of customer premises equipment (206) may be operated based on a wireless chipset. The base station (104) may be capable of bonding at least two channels of the plurality of channels to accommodate higher bandwidth scenario for the gigabit wireless solution. The base station (104) may combine more than two channels chosen on the basis of the proposed method. The base station (104) may include a spectrum analyzer (212) and a sniffer sensor (not shown) to sense the channel condition at the same time. The spectrum analyser (212) may be coupled with a packet sniffer (210).
[0038] The network management system (108) may be integrated with the cloud intelligence engine (202). Alternatively, in order to get an interference score of each base station, the cloud intelligence engine (202) may be installed separately in synchronization with the network management system (108). The cloud intelligence engine (202) may compute channel/interference score for each of the plurality of channels. The network management system (108) may bond the at least two channels of the plurality of channels. In addition, the network management system (108) may work through instructions given by the cloud intelligence engine (202) or embedded programming in the base station (104). The channel/interference score is a score provided to each of the channel slot signifying magnitude of interference within each of the channel slot. The interference score may denote intensity of channel availability to be allocated for usage by a user of the customer premises equipment (206).
[0039] The network management system (108) may receive the spectrum table from the base station (104) for a pre-configured period of time. The pre-configured period of time may be defined by the base station (104). In addition, the network management system (108) may obtain a plurality of key performance indicators (KPI) associated with the base station (104). The KPI may be, for example, but not limited to, a Reference Signal Receive Power (RSRP), a Reference Signal Received Quality (RSRQ), a Received Signal Strength Indicator (RSSI), or the like. Further, the network management system (108) may fetch a

syslog data from the base station (104). The cloud intelligence engine (202) may compute the channel/interference score based on analyses of the spectrum table, the plurality of key performance indicators and the syslog data using a plurality of hardware-run procedures. In addition, the cloud intelligence engine (202) may compute the channel/interference score for each of the base station (104). Further, the cloud intelligence engine (202) may compute the channel/interference score for each of the plurality of channels. The channel/interference score corresponds to weighted sum of real-time interference level and historic interference level.
[0040] The network management system (108) may trigger switching between the plurality of channels using interference mitigation and avoidance without performance degradation. The network management system (108) may trigger the switching using the switch/convertor (106) based on link specifications and severity of services. A trigger mechanism is categorized into a periodic based trigger or an event based trigger. In an example, the network management system (108) may use the periodic based trigger when combined interference score is summarized over a long period of time and a non-service time (maintenance hour) for minimal service impact. In another example, the network management system (108) may use the event-based trigger if the plurality of channels are flapping due to high outage issue or frequent disconnection.
[0041] The trigger mechanism may be configured as per link specifications and severity of services. Further, the trigger mechanism may continuously maintain the connection even for millisecond time for an application (e.g., banking application or the like).
[0042] The network management system (108) may alert/notify about the link that has throughout lower than a threshold throughout to initiate one or more proactive maintenance actions. In addition, the network management system (108) may determine a link quality for each of the links of the wireless communication network environment based on real-time RF condition and real-time throughput. Further, the network management system (108) may define a threshold throughout based on the real-time RF condition and the real-time throughput.

[0043] The network management system (108) may evaluate the channel/interference score for the plurality of channels at area/cluster level. The evaluation of the channel/interference score for the plurality of channels at the area/cluster level may be based on network design data and changing frequency of any channel. The network design data may include Latitude, longitude, azimuth, Tx power and the like. The evaluation of the channel/interference score for the plurality of channels at the area/cluster level may avoid possibility of getting any interference through nearby areas/clusters.
[0044] The cloud intelligence engine (202) may select the plurality of non-contiguous slots in the unlicensed band of the radio slots. The plurality of non-contiguous slots may be, for example, but not limited to, 5 MHz slots, 10 MHz slots, 15 MHz slots, 20 MHz slots, 40 MHz slots, and 60 MHz slots. After selecting the plurality of non-contiguous slots in the unlicensed band of the radio slots, the cloud intelligence engine (202) may determine the interference score for each of the plurality of non-contiguous slots. The interference score may be determined after every first time interval.
[0045] Based on the determined interference score, the cloud intelligence engine (202) may create the contiguous slot by combining at least two non-contiguous slots. The contiguous slot may be a combination of two or more channel slots which are free from interference. The contiguous slot may act as a continuous channel which may be allocated to a consumer service provider for consumption as a continuous channel. Further, the cloud intelligence engine (202) may allocate the at least two combined non-contiguous slots from the plurality of non-contiguous slots as the contiguous slot. The at least two non-contiguous slots in the unlicensed band of the radio slots may have lowest interference scores among the plurality of non-contiguous slots.
[0046] Further, the cloud intelligence engine (202) may determine the interference score for each of the plurality of non-contiguous slots based on at least one interference key performance indicator (KPI). Further, the cloud intelligence engine (202) may score each slot based on the at least one interference KPI at a first time interval. The first time interval may be a current

time. Further, the cloud intelligence engine (202) may score each slot based on the at least one interference KPI at a second time interval. The second time interval may be a historical time before the current time. Further, the cloud intelligence engine (202) may calculate a total score for each slot based on the scores of each slot at the first time interval and the second time interval.
[0047] Alternatively, the cloud intelligence engine (202) may determine the interference score for each of the plurality of non-contiguous slots based on the at least one interference KPI. Further, the cloud intelligence engine (202) may score each slot based on the at least one interference KPI at the first time interval. The first time interval may be the current time. Further, the cloud intelligence engine (202) may score each slot based on the at least one interference KPI at a plurality of second time intervals. The plurality of second time intervals may include a plurality of historical time intervals before the current time. Further, the cloud intelligence engine (202) may calculate the total score for each slot based on the scores of each slot at the first time interval and the plurality of second time intervals.
[0048] Further, the cloud intelligence engine (202) may provide a first threshold for interference score for each of the plurality of non-contiguous slots. Further, the cloud intelligence engine (202) may select the at least two non-contiguous slots having interference scores above the first threshold to create the contiguous slot by combining the selected at least two non-contiguous slots.
[0049] Unlike conventional systems, the proposed cloud intelligence engine (202) may be used to perform interference free, throughput aware dynamic channel allocation by selecting non-contiguous slots out of complete spectrum and then channel bonding using a standard radio unit architecture modified to support unlicensed band channels. The non-contiguous slots are channel slots which are not continuous or in continuation with each other in unlicensed spectrum band. These slots are required to be allocated to the user as continuous slots, which require bonding of the non-contiguous slots.
[0050] The cloud intelligence engine (202) may compute interference score for each slot periodically using AI (artificial intelligence) based techniques.

Based on computed score, the cloud intelligence engine (202) may assign non-contiguous slots with minimum interference score.
[0051] The cloud intelligence engine (202) may provide high bandwidth application use case with realization of 40 MHz/80 MHz of system bandwidth, however aggregation of smaller discontinuous bands like 5 MHz /10 MHz /15 MHz may also be possible. Based on the proposed method, high bandwidth may be achieved through non-contiguous cloud based channel bonding solutions. In an example, the cloud intelligence engine (202) may bond four independent streams. In the proposed method, the data transmission and channel sensing may be performed at same time. The cloud intelligence engine (202) may change the channel without any performance degradation.
[0052] FIG. 3 illustrates an example (300) of the wireless communication network environment in which the network management system (108) provides the gigabit wireless solution in the unlicensed band using the cloud intelligence engine (202) based on the slot interference score. The operations and functions of the network management system (108) and the cloud intelligence engine (202) are explained in conjunction with FIG. 2.
[0053] Referring to FIG. 3, the cloud intelligence engine (202) may evaluate the channel/interference score for each of the plurality of channels based on two levels. The two levels may include the real-time interference level and the historic interference level. The evaluation of the channel/interference score for the real-time interference level may be based on the plurality of key performance indicators. The plurality of key performance indicators may include output of the spectrum analyser (212), link outage duration count, and the syslog data with connection disconnection. In addition, the plurality of key performance indicators may include retransmission of packet, drop in received signal, link utilization and the like.
[0054] The evaluation of the channel/interference score for the historic interference level may be based on a plurality of factors. The plurality of factors may include past interference trend, aggregation of the historic data using a proprietary machine-learning algorithm and baselines for each of the plurality of

channels. The baselines for each of the plurality of channels may be defined so that indexing of each of the plurality of key performance indicators is measured.
[0055] In an example, the baselines may be defined for each slot to measure indexing of each KPI and correct score may be provided to get a final score. The network design data may be a combination of lat/long, azimuth and distance and appropriate channel indexing may be determined based on that cluster.
[0056] FIG. 4 is a block diagram of the cloud intelligence engine (202). The cloud intelligence engine (202) may include an artificial intelligence (AI) based interference mitigation and avoidance controller (402), a communicator (404), a memory (406), and a processor (408). The processor (408) may be coupled with the AI based interference mitigation and avoidance controller (402), the communicator (404) and the memory (406).
[0057] The AI based interference mitigation and avoidance controller (402) may select the plurality of non-contiguous slots in the unlicensed band of the radio slots. After selecting the plurality of non-contiguous slots in the unlicensed band of the radio slots, the AI based interference mitigation and avoidance controller (402) may determine the interference score for each of the plurality of non-contiguous slots. Based on the determined interference score, the AI based interference mitigation and avoidance controller (402) may create the contiguous slot by combining at least two non-contiguous slots. The contiguous slot may be a combination of two or more channel slots which are free from interference. The contiguous slot may act as a continuous channel which may be allocated to the consumer service provider for consumption as a continuous channel. Further, the AI based interference mitigation and avoidance controller (402) may allocate the at least two combined non-contiguous slots from the plurality of non-contiguous slots as the contiguous slot. The at least two non¬contiguous slots in the unlicensed band of radio slots may have the lowest interference scores among the plurality of non-contiguous slots.
[0058] Further, the AI based interference mitigation and avoidance controller (402) may determine the interference score for each of the plurality of

non-contiguous slots based on the at least one interference key performance indicator (KPI). Further, the AI based interference mitigation and avoidance controller (402) may score each slot based on the at least one interference KPI at the first time interval. The first time interval may be the current time. Further, the AI based interference mitigation and avoidance controller (402) may score each slot based on the at least one interference KPI at the second time interval. The second time interval may be the historical time before the current time. Further, the AI based interference mitigation and avoidance controller (402) may calculate the total score for each slot based on the scores of each slot at the first time interval and the second time interval.
[0059] Alternatively, the AI based interference mitigation and avoidance controller (402) may determine the interference score for each of the plurality of non-contiguous slots based on the at least one interference KPI. Further, the AI based interference mitigation and avoidance controller (402) may score each slot based on the at least one interference KPI at the first time interval. The first time interval may be the current time. Further, the AI based interference mitigation and avoidance controller (402) may score each slot based on the at least one interference KPI at the plurality of second time intervals. The plurality of second time intervals may include the plurality of historical time intervals before the current time. Further, the AI based interference mitigation and avoidance controller (402) may calculate the total score for each slot based on the scores of each slot at the first time interval and the plurality of second time intervals.
[0060] The AI based interference mitigation and avoidance controller (402) may provide the first threshold for the interference score for each of the plurality of non-contiguous slots. Further, the AI based interference mitigation and avoidance controller (402) may select the at least two non-contiguous slots having the interference scores above the first threshold, to create the contiguous slot by combining the selected at least two non-contiguous slots.
[0061] The AI based interference mitigation and avoidance controller (402) may be implemented by analog or digital circuits such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive

electronic components, active electronic components, optical components, hardwired circuits, or the like, and may optionally be driven by firmware.
[0062] The processor (408) may be configured to execute instructions stored in the memory (406) and to perform various processes. The communicator (404) may be configured for communicating internally between internal hardware components and with external devices via one or more networks. The memory (406) may store instructions to be executed by the processor (408). The memory (406) may also store the interference score, the interference KPI, the current interference level, the historical interference level, and the slot interference score. The current interference level may be determined by one or more the spectrum analyser output, the link outage duration count, the syslog data with connection disconnection, the retransmission of packet, the drop in received signal, and the link utilization. The historical interference level may provide past interference trends. The historical interference level may be used for baseline for interference for each channel slot.
[0063] At least one of the plurality of modules may be implemented through an AI model. A function associated with AI may be performed through the non-volatile memory, the volatile memory, and the processor. The processor (408) may include one or more processors. The one or more processors may be a general purpose processor, such as a central processing unit (CPU), an application processor (AP), or the like, a graphics-only processing unit such as a graphics processing unit (GPU), a visual processing unit (VPU), and/or an Al-dedicated processor such as a neural processing unit (NPU).
[0064] The one or more processors control the processing of the input data in accordance with a predefined operating rule or artificial intelligence (AI) model stored in the non-volatile memory and the volatile memory. The predefined operating rule or artificial intelligence model is provided through training or learning. Here, being provided through learning means that, by applying a learning algorithm to a plurality of learning data, a predefined operating rule or AI model of a desired characteristic is made. The learning may be performed in a device itself, and/or may be implemented through a separate server/system.

[0065] The AI model may consist of a plurality of neural network layers. Each layer has a plurality of weight values, and performs a layer operation through calculation of a previous layer and an operation of a plurality of weights. Examples of neural networks include, but are not limited to, convolutional neural network (CNN), deep neural network (DNN), recurrent neural network (RNN), restricted Boltzmann Machine (RBM), deep belief network (DBN), bidirectional recurrent deep neural network (BRDNN), generative adversarial networks (GAN), and deep Q-networks.
[0066] The learning algorithm is a method for training a predetermined target device (for example, a robot) using a plurality of learning data to cause, allow, or control the target device to make a determination or prediction. Examples of learning algorithms include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.
[0067] Unlike conventional systems, the AI based interference mitigation and avoidance controller (402) may be used to perform interference free, throughput aware dynamic channel allocation by selecting non-contiguous slots out of complete spectrum and then channel bonding using a standard radio unit architecture modified to support unlicensed band channels. The AI based interference mitigation and avoidance controller (402) may compute the interference score for each slot periodically using AI based techniques. Based on the computed score, the AI based interference mitigation and avoidance controller (402) assigns non-contiguous slots with the minimum interference score.
[0068] Although FIG. 4 shows various hardware components of the cloud intelligence engine (202) but it is to be understood that other alternatives are not limited thereon. In other implantations, the cloud intelligence engine (202) may include less or more number of components. Further, the labels or names of the components are used only for illustrative purpose and does not limit the scope of the invention. One or more components can be combined together to perform same or substantially similar function in the cloud intelligence engine (202).

[0069] FIG. 5 is an example illustration in which cloud intelligence engine creates the contiguous slot by combining two non-contiguous slots based on the determined interference score. Based on the proposed method, the cloud intelligence engine (202) may select four non-contiguous slots (e.g., slot 3, slot 8, slot 13, and slot 19) and bond the four non-contiguous slots to create 40MHz/80MHz/160MHz channel. This results in an increased throughput performance.
[0070] Referring now to FIG. 6, there is provided a more detailed block diagram of an architecture of hardware of the base station (104) of FIG. 1. The base station (104) may include an antenna (632), the spectrum analyser (212) and the packet sniffer (210) for spectrum sensing configured in receive mode to capture the complete unlicensed band spectrum. The base station (104) may support any 4 independent streams across the unlicensed bands.
[0071] The base station (104) may include a baseband processing block (602) and a radio frequency block (604) that have embedded feature to generate spectrum table at a pre-configured period of time. In an example, the pre-configured period of time is one minute. The baseband processing block (602) and the radio frequency block (604) may generate the spectrum table in an embedded random-access memory that is sent to the cloud intelligence engine (202). The baseband processing block (602) and the radio frequency block (604) may be configured for instant channel change with the plurality of channels in case of any severe interference case or outage.
[0072] The radio frequency block (604) may include radio protocols and the spectrum analyser (212). The radio frequency block (604) may utilize the radio protocols to facilitate communication through the antenna (632). The spectrum analyser (212) facilitates dynamic spectrum optimization with information from the base station (104). With the information, the spectrum analyser (212) may optimize local spectrum by informing the base station (104) to avoid channels that may be subjected to the interference.
[0073] In an example, the radio protocols may include simple network management protocol version 3 (hereinafter referred to as a "SNMPV3". The

SNMPV3 is used in a user datagram protocol (UDP) layer/ a transmission control protocol (TCP) layer to send the spectrum table to the cloud intelligence engine (202). Further, the SNMPV3 signals communications between the plurality of customer premises equipment (206) and the network management system (108).
[0074] In another example, the radio protocols may include capture aware channel access protocol. In addition, the capture aware channel access protocol may be used if capacity is limited for link due to the usage of the SNMPV3. The capture aware channel access protocol may facilitate sensing of channel condition and data transmission of the plurality of channels simultaneously.
[0075] The base station (104) may include a router. In general, the router corresponds to device that transfers data packets between computer networks. The router has an application of access, core and distribution. The router is compatible to run Linux-based firmware. The Linux-based firmware includes Tomato, OpenWrt and DD-WRT. The Linux-based firmware embeds the radio protocols and a plurality of embedded features. The plurality of embedded features is used to support Gigabit connectivity requirement. The plurality of embedded features includes antenna technology like multi-user, multiple input, multiple output (Mu-MEVIO), 256 Quadrature Amplitude Modulation (QAM), Adaptive Modulation and Beam forming. The base station (104) may include a bonding driver. The bonding driver may be used to achieve an optimal latency requirement. The optimal latency requirement may be less than 1 millisecond. Alternatively, the optimal latency requirement may vary.
[0076] The base station (104) may include the baseband processing block (602) and the radio frequency block (604), both provided as separate chips or distinct physical units. The baseband processing block (602) may include a microcontroller (606) and a plurality of peripheral interfaces (608) that complement the radio frequency block (604). The plurality of peripheral interfaces (608) include but may not be limited to a double data rate (DDR) interface, an Ethernet interface, and a universal asynchronous receiver/transmitter interface. The radio frequency block (604) may have a transmit path for transmitting a transmit signal. The radio frequency block (604) may include a first RFFE (624),

a second RFFE (626), a third RFFE (628) and a fourth RFFE (630). Each of the first RFFE (624), the second RFFE (626), the third RFFE (628) and the fourth RFFE (630) may correspond to radio frequency front end circuit that has amplification circuitry for the transmitted and received signals. Each of the first RFFE (624), the second RFFE (626), the third RFFE (628) and the fourth RFFE (630) may include a power amplifier and a low noise amplifier.
[0077] The power amplifier and the low noise amplifier of the first RFFE (624) may specifically be tuned for a 2.4 GHz Tx/Rx (616). The power amplifier and the low noise amplifier of the second RFFE (626) may specifically be tuned for a first 5.8 GHz Tx/Rx (618). The power amplifier and the low noise amplifier of the third RFFE (628) may specifically be tuned for a second 5.8 GHz Tx/Rx (620). The power amplifier and the low noise amplifier of the fourth RFFE (630) may specifically be tuned for a third 5.8 GHz Tx/Rx (622). The transmit signal may be amplified by the power amplifier prior to transmission over the antenna (632). More transmit paths may be provided for more transmit channels/bands, depending on the application.
[0078] The baseband processing block (602), having various radio frequency (RF) functions, may typically be implemented on a field-programmable gate array (FPGA) or a system-on-chip (SoC) (610). The baseband processing block (602) may include heavy duty or highly intensive digital functions, which processes a digital signal prior to providing the digital signal to the radio frequency block (604). The baseband processing block (602) includes a power (612) and a clock (614). Generally, wider bandwidth means higher amount of data traffic, wider serial link, and faster the interface has to be clocked. The microcontroller (606) may control power levels for closed-loop system operation of the baseband processing block (602).
[0079] FIG. 7 is a flow chart (700) illustrating a method for providing the contiguous slot in the unlicensed band of the radio slots. The operations (702-708) are performed by the AI based interference mitigation and avoidance controller (402). At step (702), the method includes selecting the plurality of non-contiguous slots in the unlicensed band of the radio slots. At step (704), the method includes

determining the interference score for each of the plurality of non-contiguous slots. At step (706), the method includes creating the contiguous slot by combining two or more non-contiguous slots based on the determined interference score. At step (708), the method includes allocating the at least two or more combined non-contiguous slots from the plurality of non-contiguous slots as the contiguous slot.
[0080] The proposed method may be used to perform interference free, throughput aware dynamic channel allocation by selecting non-contiguous slots out of complete spectrum and then channel bonding using the standard radio unit architecture modified to support the unlicensed band channels.
[0081] In the proposed method, the cloud intelligence engine (202) may compute interference score for each slot periodically using AI based techniques. Based on the computed score, the cloud intelligence engine (202) may assign the non-contiguous slots with the minimum interference score. In the proposed method, allocation of channel slots with low interference or no interference is achieved. Further, high bandwidth requirement may be catered using the unlicensed band of the radio slots.
[0082] The various actions, acts, blocks, steps, or the like in the flow chart (700) may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some of the actions, acts, blocks, steps, or the like may be omitted, added, modified, skipped, or the like without departing from the scope of the invention.
[0083] The embodiments disclosed herein can be implemented using at least one software program running on at least one hardware device and performing network management functions to control the elements.
[0084] It will be apparent to those skilled in the art that other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention. While the foregoing written description of the invention enables one of ordinary skill to make and use what is considered presently to be the best mode thereof, those of ordinary skill will understand and appreciate the existence of variations,

combinations, and equivalents of the specific embodiment, method, and examples herein. The invention should therefore not be limited by the above described embodiment, method, and examples, but by all embodiments and methods within the scope of the invention. It is intended that the specification and examples be considered as exemplary, with the true scope of the invention being indicated by the claims.
[0085] The methods and processes described herein may have fewer or additional steps or states and the steps or states may be performed in a different order. Not all steps or states need to be reached. The methods and processes described herein may be embodied in, and fully or partially automated via, software code modules executed by one or more general purpose computers. The code modules may be stored in any type of computer-readable medium or other computer storage device. Some or all of the methods may alternatively be embodied in whole or in part in specialized computer hardware.
[0086] The results of the disclosed methods may be stored in any type of computer data repository, such as relational databases and flat file systems that use volatile and/or non-volatile memory (e.g., magnetic disk storage, optical storage, EEPROM and/or solid state RAM).
[0087] The various illustrative logical blocks, modules, routines, and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. The described functionality can be implemented in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosure.
[0088] Moreover, the various illustrative logical blocks and modules described in connection with the embodiments disclosed herein can be

implemented or performed by a machine, such as a general purpose processor device, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components or any combination thereof designed to perform the functions described herein. A general purpose processor device can be a microprocessor, but in the alternative, the processor device can be a controller, microcontroller, or state machine, combinations of the same, or the like. A processor device can include electrical circuitry configured to process computer-executable instructions. In another embodiment, a processor device includes an FPGA or other programmable device that performs logic operations without processing computer-executable instructions. A processor device can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Although described herein primarily with respect to digital technology, a processor device may also include primarily analog components. A computing environment can include any type of computer system, including, but not limited to, a computer system based on a microprocessor, a mainframe computer, a digital signal processor, a portable computing device, a device controller, or a computational engine within an appliance, to name a few.
[0089] The elements of a method, process, routine, or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor device, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of a non-transitory computer-readable storage medium. An exemplary storage medium can be coupled to the processor device such that the processor device can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor device. The processor device and the storage medium can reside in an ASIC. The ASIC can reside in a user

terminal. In the alternative, the processor device and the storage medium can reside as discrete components in a user terminal.
[0090] Conditional language used herein, such as, among others, "can," "may," "might," "may," "e.g.," and the like, unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain alternatives include, while other alternatives do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more alternatives or that one or more alternatives necessarily include logic for deciding, with or without other input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular alternative. The terms "comprising," "including," "having," and the like are synonymous and are used inclusively, in an open-ended fashion, and do not exclude additional elements, features, acts, operations, and so forth. Also, the term "or" is used in its inclusive sense (and not in its exclusive sense) so that when used, for example, to connect a list of elements, the term "or" means one, some, or all of the elements in the list.
[0091] Disjunctive language such as the phrase "at least one of X, Y, Z," unless specifically stated otherwise, is otherwise understood with the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain alternatives require at least one of X, at least one of Y, or at least one of Z to each be present.
[0092] While the detailed description has shown, described, and pointed out novel features as applied to various alternatives, it can be understood that various omissions, substitutions, and changes in the form and details of the devices or algorithms illustrated can be made without departing from the scope of the disclosure. As can be recognized, certain alternatives described herein can be embodied within a form that does not provide all of the features and benefits set forth herein, as some features can be used or practiced separately from others.

CLAIMS
We claim:

1. A method for providing a contiguous slot in unlicensed band of radio slots,
comprising:
selecting, by a cloud intelligence engine (202), a plurality of non-contiguous slots in the unlicensed band of the radio slots;
determining, by the cloud intelligence engine (202), an interference score for each of the plurality of non-contiguous slots;
creating, by the cloud intelligence engine (202), the contiguous slot by combining at least two non-contiguous slots based on the determined interference score; and
allocating, by the cloud intelligence engine (202), the at least two combined non-contiguous slots from the plurality of non-contiguous slots as the contiguous slot.
2. The method of claim 1, wherein the at least two combined non-contiguous
slots in the unlicensed band of the radio slots have lowest interference scores among the plurality of non-contiguous slots.
3. The method of claim 1, further comprising:
determining, by the cloud intelligence engine (202), the interference score for each of the plurality of non-contiguous slots based on at least one interference key performance indicator (KPI);
scoring, by the cloud intelligence engine (202), each slot based on the at least one interference KPI at a first time interval, wherein the first time interval is a current time;
scoring, by the cloud intelligence engine (202), each slot based on the at least one interference KPI at a second time interval, wherein the second time interval is a historical time before the current time; and

calculating, by the cloud intelligence engine (202), a total score for each slot based on the scores of each slot at the first time interval and the second time interval.
4. The method of claim 1, further comprising:
determining, by the cloud intelligence engine (202), the interference score for each of the plurality of non-contiguous slots based on the at least one interference key performance indicator (KPI);
scoring, by the cloud intelligence engine (202), each slot based on the at least one interference KPI at a first time interval, wherein the first time interval is a current time;
scoring, by the cloud intelligence engine (202), each slot based on the at least one interference KPI at a plurality of second time intervals, wherein the plurality of second time intervals includes a plurality of historical time intervals before the current time; and
calculating, by the cloud intelligence engine (202), a total score for each slot based on the scores of each slot at the first time interval and the plurality of second time intervals.
5. The method of claim 1, further comprising:
providing, by the cloud intelligence engine (202), a first threshold for interference score for each of the plurality of non-contiguous slots; and
selecting, by the cloud intelligence engine (202), the at least two non-contiguous slots having interference scores above the first threshold, to create the contiguous slot by combining the selected at least two non-contiguous slots.
6. The method of claim 1, wherein the interference score is determined after
every first time interval.

7. The method of claim 1, wherein a number of non-contiguous slots to be
combined to create the contiguous slot is based on channel required by a user of a customer premises equipment (206).
8. The method of claim 1, wherein the plurality of non-contiguous slots include
at least one of 5 MHz slots, 10 MHz slots, 15 MHz slots, 20 MHz slots, 40 MHz slots, and 60 MHz slots.
9. The method of claim 1, wherein a maximum of four non-contiguous slots are
combined to create the contiguous slot for allocation.
10. The method of claim 1, wherein the at least one interference KPI is determined by at least one of a spectrum analyzer output, a link outage duration count, a syslog data with connection disconnection, retransmission of packet, drop in received signal, and a link utilization.
11. A cloud intelligence engine (202) for providing a contiguous slot in unlicensed band of radio slots, comprising:
a processor (408);
a memory (406) storing at least one of a slot interference score, an interference key performance indicator (KPI), a current interference level, and a historical interference level; and
an artificial intelligence (AI) based interference mitigation and avoidance controller (402), coupled with the processor (408) and the memory (406) configured to:
select a plurality of non-contiguous slots in the unlicensed band of radio slots;
determine an interference score for each of the plurality of non-contiguous slots;
create the contiguous slot by combining at least two non-contiguous slots based on the determined interference score; and

allocate the at least two combined non-contiguous slots from the plurality of non-contiguous slots as the contiguous slot.
12. The cloud intelligence engine (202) of claim 11, wherein the at least two combined non-contiguous slots in the unlicensed band of the radio slots have lowest interference scores among the plurality of non-contiguous slots.
13. The cloud intelligence engine (202) of claim 11, wherein the AI based interference mitigation and avoidance controller (402) is configured to:
determine the interference score for each of the plurality of non-contiguous slots based on at least one interference key performance indicator (KPI);
score each slot based on the at least one interference KPI at a first time interval, wherein the first time interval is a current time;
score each slot based on the at least one interference KPI at a second time interval, wherein the second time interval is a historical time before the current time; and
calculate a total score for each slot based on the scores of each slot at the first time interval and the second time interval.
14. The cloud intelligence engine (202) of claim 11, wherein the AI based
interference mitigation and avoidance controller (402) is configured to:
determine the interference score for each of the plurality of non-contiguous slots based on the at least one interference key performance indicator (KPI);
score each slot based on the at least one interference KPI at a first time interval, wherein the first time interval is a current time;
score each slot based on the at least one interference KPI at a plurality of second time intervals, wherein the plurality of second time intervals includes a plurality of historical time intervals before the current time; and

calculate a total score for each slot based on the scores of each slot at the first time interval and the plurality of second time intervals.
15. The cloud intelligence engine (202) of claim 11, wherein the AI based
interference mitigation and avoidance controller (402) is configured to:
provide a first threshold for interference score for each of the plurality of non-contiguous slots; and
select the at least two non-contiguous slots having interference scores above the first threshold, to create the contiguous slot by combining the selected at least two non-contiguous slots.
16. The cloud intelligence engine (202) of claim 11, wherein the interference score is determined after every first time interval.
17. The cloud intelligence engine (202) of claim 11, wherein a number of non-contiguous slots to be combined to create the contiguous slot is based on channel required by a user of a customer premises equipment (206).
18. The cloud intelligence engine (202) of claim 11, wherein the plurality of non-contiguous slots include at least one of 5 MHz slots, 10 MHz slots, 15 MHz slots, 20 MHz slots, 40 MHz slots, and 60 MHz slots.
19. The cloud intelligence engine (202) of claim 11, wherein a maximum of four non-contiguous slots are combined to create the contiguous slot for allocation.
20. The cloud intelligence engine (202) of claim 11, wherein the at least one interference KPI is determined by at least one of a spectrum analyzer output, a link outage duration count, a syslog data with connection disconnection, retransmission of packet, drop in received signal, and a link utilization.