EFFECT OF MATRIX PARTITIONING ON SECOND ORDER STATISTICS OF FADING CHANNELS IN IOT-ENABLED MOBILE COMMUNICATION SYSTEMS

Abstract

The present invention relates to a method for analyzing the effect of matrix partitioning on second order statistics of fading channels in IoT-enabled mobile communication systems. The method comprises of: derive expressions for the level crossing rate (LCR) and average fade duration (AFD) using a novel matrix partitioning approach applied to a two-branch selection combining (SC) system; and compare the proposed methodology with existing characteristic function-based approaches, including the impact of Gaussian fluctuation effects. This system utilizes a horizontally aligned linear antenna array at the mobile station, a common configuration in IoT networks. The analysis demonstrates that the alignment of the antennas in relation to the motion direction has a substantial impact on the Linear Characteristic Ratio (LCR) and Area Frequency Distribution (AFD). Antennas positioned perpendicular to the motion direction exhibit a lower reliance on antenna spacing. The loss of common reflection (LCR) is reduced by parallel alignment, yet, the average frequency distribution (AFD) may be compromised, especially for antennas that are closely together. An evaluation is conducted to compare the proposed methodology with existing characteristic function-based approaches, including the impact of Gaussian fluctuation effects. In situations often found in communication networks facilitated by the Internet of Things (IoT), the results indicate that the matrix partitioning approach yields enhanced performance in terms of Linear Compressive Ratio (LCR) and Average Frequency Distribution (AFD). This work provides significant insights on optimizing antenna designs to improve the reliability of communication in IoT architectural systems.

Specification

Description:Field of the Invention
The present invention relates to the technical field of telecommunications, and more particular to a method for analyzing the effect of matrix partitioning on second order statistics of fading channels in IoT-enabled mobile communication systems.
Background of the Invention
In order to enhance the precision of second-order statistical measurements in fading channels, a one-of-a-kind method is presented here. The level crossing rate (LCR) and the average fade duration (AFD) are two important measurements that fall under this category. These mobile communication systems are made possible by the Internet of Things (IoT), and the objective of this method is to achieve the highest possible level of performance for these systems. The phenomenon known as channel fading, which results in variations in signal intensity, is one of the most significant obstacles that wireless communication must overcome. The presence of mobile devices and sensors connected to the Internet of Things is a particularly difficult challenge in these kinds of scenarios. In the proposed invention, a matrix partitioning technique is presented. This approach successfully reduces the Linear Channel Reduction (LCR) and increases the Adaptive Frequency Distribution (AFD), which ultimately results in an increase in the reliability and efficiency of data transmission in Internet of Things (IoT) networks.
In Indian Patent application no. IN2022221027256, presents innovative approaches that integrate wireless communication signals with IoT technology to enhance the navigation and steering capabilities of mobile robots. The primary goal of this study is to provide a dynamic picture of wireless signals inside a specified context. Potentially included in this wireless transmission are a number of radio frequency (RF) signals, including Bluetooth, Wi-Fi, and others with similar characteristics. Using cartographic representation as a navigational aid allows mobile robots to successfully navigate and function in tough or unfamiliar situations. Reason being, robots can find their way around. In addition to the data on the previously listed parameters, this system additionally sends data on the characteristics of the signal's intensity and quality, which it analyses and updates continuously. When discovered in this condition, it is known as a state of continuous analysis. To achieve this goal, sensors are strategically distributed throughout the environment and connected to the Internet of Things (IoT). These autonomous systems use the information they have gathered to do a timely analysis of their pathways. They are equipped with mapping algorithms and communication interfaces. Their overall efficiency is enhanced because of their exceptional obstacle-navigating and trajectory-correcting abilities. In some cases, traditional navigation technologies, like GPS, could give you the wrong information. When these systems are in use for navigation in places where there is a lot of signal interference, for instance, this may happen. This technology is very useful when put to use in cases like these.
The use of the Internet of Things (IoT) in conjunction with the integration of real-time mapping. In the framework of this invention, the Internet of Things (IoT) is used in order to construct a map of wireless communication signals that is not only dynamic but also continually updated. This map is a result of the innovation. Robotic navigation systems that are traditional, on the other hand, are dependent on maps or sensors that are already in existence and are stationary. In contrast to the situation that was discussed before, this pertains to the opposite of that. Real-time data is easily accessible to mobile robots, which enables them to adapt to the ever-changing conditions of their settings. This allows mobile robots to be more environmentally friendly. The fact that they are able to manage situations that are not only difficult but also constantly changing inside themselves is therefore improved as a consequence of this specific predicament.
The utilization of extant wireless communication networks, such as Wi-Fi or Bluetooth, is a notable strategy. This is due to the fact that it makes use of current networks rather than needing the building of unique equipment. Specifically, this is due to the fact that it utilizes networks that already exist. One of the most significant advantages is that this is the case. Taking into consideration the fact that this is the circumstance, one of the most important techniques is to make advantage of the wireless infrastructure that has already been developed. The ease with which the system may be implemented in a wide range of diverse circumstances contributes to the cost-effectiveness of the system, which in turn contributes to the total profitability of the system. In order to do this, the amount of extra hardware that has to be added during the installation process is decreased.
The scalability and flexibility of the system, which are two of the most essential aspects of the system, make it feasible to use the system at a broad variety of spatial scales, ranging from modest interior settings to enormous industrial zones. This is because the system is able to accommodate a wide range of spatial scales. Scalability and adaptability are two of the properties that are considered to be among the most important characteristics. The fact that it is reliant on the Internet of Things also means that it is able to communicate with other intelligent devices in a way that is absolutely seamless from one device to the next. Consequently, this helps to contribute to the construction of an operational environment that is connected with a greater number of connections and is associated with a higher level of intelligence.
Mobile robots are able to enhance their navigation algorithms by continually refining them using the data that they get from the Internet of Things network. This innovation integrates learning and adaptive processes, which allows mobile robots to improve their navigation algorithms. The innovation is what makes this scenario conceivable. Because of the invention that was developed, it was possible for this innovation to really take place. The use of this iterative learning technique leads to an enhancement in the effectiveness of navigation, which eventually results in an increase in performance over a wide range of operational circumstances.
In another Indian Patent application no. 202411047663, Using the Internet of Things (IoT), the innovation that is referred to as "IoT-Based Camera for Healthcare Management" incorporates cameras into the infrastructure of hospitals with the purpose of actively monitoring and managing healthcare facilities. This is accomplished via the use of webcams. Using cutting-edge technology, these security cameras are now able to capture and send both still photographs and video in real time to medical specialists. This capability was previously unattainable. It is because of the use of these cameras that this capability has been made available. The aims of this effort are to ensure the security of the company, to monitor the circumstances of the surrounding environment, and to keep a close check on patients even when the person is not physically present. Continuous monitoring can be carried out with the help of this technology, which also makes it possible to quickly identify any potential issues that may arise and to put solutions into action in a timely manner. The methods for governance and decision-making in the healthcare sector become more effective as a result of this, which ultimately leads to an increase in the quality of care that is offered to patients over the whole of their treatment course or treatment period.
The system that was referred to as "IoT-Based Camera for Healthcare Management" had a number of essential goals, one of which was to promote the construction of automated data interchange and real-time monitoring in healthcare settings or surrounds. The implementation of the Internet of Things (IoT) proved to be of considerable help within the framework of the deployment procedure. This healthcare camera system was painstakingly built with the sole goal of improving both the quality of care that is delivered to patients as well as the management of the institution. This was accomplished by adding features that allow for quicker response times and continual monitoring. The "Smart Camera-Integrated Fuzzy Enhanced Image Fusion System," on the other hand, is designed to improve the quality of the photographs taken in a variety of lighting conditions. On the other hand, this technology was created as a specific means of enhancing the care that is provided to patients. One thing that should be brought to your attention is the fact that this is in direct contrast to the primary goal of the system, which is to enhance the overall picture quality in a broad variety of lighting circumstances.
The suggested system distinguishes itself by the following distinctive features:
By providing a matrix partitioning method that is both comprehensive and logical, the goal of this invention is to provide an alternative to the standard diversity techniques and approaches that are based on characteristic functions. When compared to the conventional techniques and strategies for diversity, this stands in stark contrast. By using this strategy, the covariance matrix is broken down into components that are more readily manageable, taking into consideration the levels of the signals. In order to accomplish this objective, we want to put our innovation into practice as the mechanism by which we will do so.
Throughout the process of constructing the solution that is recommended, the challenges that are brought about by linked branch signals have been taken into significant consideration and taken into account. When it comes to circumstances that take place in the real world and need a wireless connection, the challenges that were outlined before are often encountered. This innovative strategy offers a solution that is more long-lasting, which is necessary in order to solve the problems that are associated with fading channels. The optimization of the form of the antenna and the inclusion of Gaussian fluctuation effects are the techniques by which this aim is accomplished. The occurrence of this event may be attributed to the strengthening that was included into the design of the antenna.
Before the Internet of Things can be included into communication networks, there are a significant number of factors that need to be taken into consideration, including the following: In contrast to past research that focused on wireless communication systems of a more general nature, the current breakthrough is one that has been designed specifically for networks that are made feasible by the Internet of Things (IoT). This is a significant advancement in the field of wireless communication. On the other hand, this is completely and utterly in direct contrast to the findings of the study that was carried out before to this one. As a result of the fact that it takes into account the distinctive qualities of Internet of Things devices, such as their adaptability and portability in terms of deployment across a variety of environments, the matrix partitioning paradigm is an exceptional choice for effectively satisfying the requirements of contemporary communication. Because it takes into consideration the qualities that set Internet of Things devices apart from other types of devices, this is the result. As a consequence of this, it is an extraordinarily advantageous option that needs to be taken into account while contemplating the means by which to satisfy the requirements of contemporary communication practices.
Drawings
Fig.1 illustrates the process diagram of the present invention
Detailed Description of the Invention
The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention as defined in the claims.
In any embodiment described herein, the open-ended terms "comprising," "comprises," and the like (which are synonymous with "including," "having" and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of," consists essentially of," and the like or the respective closed phrases "consisting of," "consists of, the like. As used herein, the singular forms "a", "an", and "the" designate both the singular and the plural, unless expressly stated to designate the singular only.
The goal of this idea is to maximize the efficiency with which navigational data may be sent to mobile robots via the use of wireless communication signals." When it comes to executing automatic robot navigation, wireless networks are used, and the results are both innovative and successful. It is important to note that this is not the same as systems that rely on visualization markers or global positioning systems (GPS).
The capability of the system to continuously modify itself in real time and collect new knowledge distinguishes it from other technologies that are presently available with comparable capabilities. Through the use of this feature, the system is able to distinguish itself from other technologies. By making use of this function, which improves navigation, the effectiveness of the system is certain to stay uncompromised even in the face of obstructions or changes in the environment that surrounds it. The occurrence of this circumstance continues regardless of whether or not the capabilities are put into action.
Because it removes the need for a significant investment in new infrastructure throughout the installation process, the cutting-edge technology is more economically efficient than conventional wireless networks. This is accomplished by eliminating the need for the investment. Because of this quality, it is a more economical choice than similar alternatives. This is the reason why the technology is now capable of being implemented in an efficient manner for the first time. This application is particularly attractive to a wide variety of enterprises since it combines cutting-edge technology with an application that is both efficient and cost-effective. The emergence of this phenomena may be traced back to the combination of the two components.
The seamless connection that exists between the system and devices that are linked to the Internet of Things makes it possible for the system to improve its capacity to provide navigation map updates that are both permanent and very quick. As a consequence of this, the system may be able to react more effectively to changes in its environment by using adaptive processes. It is one of the few navigation systems that are now available and exhibits such high levels of integration, which results in greater efficiency and flexibility. This navigation system is one of the few systems that exists. At the moment, there is a limited selection of navigation systems that are available for use.
This breakthrough integrates Wi-Fi, Bluetooth, and radio frequency (RF) signals in order to create a navigation map of the region that is both dynamic and updated in real time. With the help of this geographical paradigm, mobile robots are able to navigate terrain that is both complicated and dynamic. Unlike traditional guiding systems, this idea makes use of data collected from the Internet of Things (IoT) in real time in order to regularly update the map.
One of the most notable aspects of the invention is the inclusion of the Internet of Things. For the purpose of providing mobile robots with information, pervasive wireless Internet of Things (IoT) sensors in the environment assess the strength and quality of signals. The link allows robots to rapidly make judgments and adjust their approach in response to changes in the environment, which ultimately results in an improvement in the adaptability of the robots.
The technique that has been suggested makes use of the wireless communication infrastructure that already exists, eliminating the need for additional apparatus. Currently available methods for network signal mapping and processing make the technology economically feasible for use in both tiny interior areas and big industrial complexes.
The cutting-edge design makes use of complex algorithms to provide mobile robots with assistance in gathering data about their surroundings and effectively navigating. Robotic systems make use of adaptive learning in order to save energy, improve their trajectory, and avoid obstacles. The effectiveness of the system is improved by its use.
The system has a great degree of scalability and versatility, which enables it to be suitable for a broad variety of sizes and needs. It is possible for the system to provide services to both small office buildings and massive industrial complexes on the same scale. The abundance of communication channels that it offers makes it easier to integrate with other intelligent devices that are part of the Internet of Things.
Improvements in reliability under challenging circumstances: This technology performs very well in restricted locations that have large physical obstacles, particularly in situations where traditional navigation systems may have difficulty. When mobile robots are operating in difficult situations, the navigation capabilities of these robots may be improved by using wireless signal mapping rather than optical or GPS systems.
The precision of mobile robot navigation is significantly improved as a consequence of this innovation, which combines a dynamic map of wireless communication signals with a real-time map of those signals. Significant advancements have been made in mobile robot navigation as a result of this breakthrough. This specific map has been included into the system as a whole with their inclusion. This method is able to adapt to changes in the surrounding environment, which results in navigation that is more precise and reliable. This is particularly true in areas that are difficult to access or that are sealed off. This is in contrast to traditional systems, which are unable to adapt to these changes since they are reliant on fixed maps or GPS.
Using sensors that are linked to the Internet of Things (IoT) in order to continuously monitor and update the signal map, this technology makes it feasible for mobile robots to react in real time to changes that occur in their surroundings. This technology also makes it possible for mobile robots to communicate with one another. It is essential for robots to have the capacity to adapt in order for them to be able to properly perform in dynamic situations. These conditions are characterized by the presence of shifting obstacles or the introduction of new items. The introduction of new things is another pointer that indicates the presence of dynamic circumstances. Robots are able to make quick alterations to the paths that they have specifically established for themselves as a result of this.
Due to the fact that the innovation takes use of the wireless communication infrastructure that already exists, such as Wi-Fi and Bluetooth, it avoids the need for extra hardware installations that are expensive. In addition to this, it does this by making use of the infrastructure that is already in place. The result is an efficient use of the resources that are at one's disposal. This strategy not only lowers the overall costs that are associated with deployment, but it also makes it simpler to incorporate it into pre-existing systems without causing any disturbances to the operations of those systems. This is because the method decreases the total costs that are connected with deployment. As a consequence of this, it has been shown that commercial and industrial organizations are able to make a choice that is financially viable.
Because the system has a high degree of scalability and flexibility, it is possible to be used in a wide range of environments, ranging from limited interior spaces to enormous industrial zones. This is because the system is able to scale up and adapt to new circumstances. This enables the system to be deployed in almost any area, which is a significant advantage. Due to the fact that the system is constructed using Internet of Things technology, it is feasible for it to simply grow by including new Internet of Things devices or by responding to changing communication signals. Because the system is being created, this is now something that can be accomplished. The fact that the system is able to accommodate both of these options makes this a possibility that may be considered within the realm of possibilities. as a consequence of this, it is able to give versatility for a broad range of applications and jobs as a result of this.
The standard navigation systems, such as the Global Positioning System (GPS), provide a number of benefits to its users or users. They are able to work more effectively under challenging settings that are characterized by a large degree of interference, which is one of the benefits that they provide. There are a number of situations that may be classified into this category. Some examples of these scenarios are locations that are surrounded by dense physical barriers or interior spaces. Because of this technological innovation, a solution to these challenges is supplied, and that answer is the mapping of wireless signals that are less impacted by the impediments that are being addressed. Therefore, this guarantees that the robot will continue to guide itself in a dependable and consistent way even when it is confronted with challenging circumstances.
The robot's navigation route is changed in a methodical manner in order to attain the goal of achieving lower energy consumption. Making advantage of real-time signal mapping is the means by which this is performed. This specific activity is conducted in order to achieve the goal of enhancing energy efficiency, which is the aim. Not only does this contribute to the reduction of the amount of energy that is consumed, but it also adds to the reduction of the amount of movement that is not necessary, which in turn helps to the attainment of energy efficiency. This very high degree of efficiency not only results in a sizeable decrease in the overall running expenses of mobile robots, but it also helps to extend the lifetime of the batteries that are used to power them.
The ongoing creation of a real-time map of wireless communication transmission networks has resulted in important advancements in the area of dynamic signal mapping. These advancements have been made possible as a consequence of the ongoing construction of the map. The fact that the map is being updated on a regular basis is one of the likely explanations for this progress. After that particular point has been successfully completed, this map will be subjected to regular revisions. When weighed against other significant accomplishments, this accomplishment has a significant amount of weight and significance. As a consequence of this, the availability of this attribute reduces the need for individuals to make use of extra equipment or maps that are already in existence in order to provide them with direction. The occurrence of this evolution may have occurred for a number of reasons, one of which is because it has the potential to enhance the accuracy of navigation, which is the goal that was intended to be accomplished.
It is feasible to create a system that is entirely networked by integrating mobile robots with devices that are connected to the Internet of Things (IoT) in a way that is both coordinated and seamless. It is possible to refer to this approach as a pragmatic one. The rapid exchange of information is made simpler as a result of this, and the capabilities necessary for independent decision-making are made feasible as a result of this. The cognitive capacities of the navigation system are enhanced as a consequence of this link, which allows the system to efficiently handle tasks that are growing more complex and to operate independently. As a result, the system is able to work independently.
With respect to its technical capabilities, the system has achieved a great deal, particularly in the innovative area of adaptive learning, which has contributed significantly to the field. Notable accomplishments may be found in both of these areas. It is without a doubt the most significant achievement that has been achieved. Due to the presence of these characteristics, the system has the capability to gradually enhance its navigation algorithms by gathering information from the environment that it is surrounded by. Because it leads to gains in both performance and efficiency, the approach of recurrent learning is particularly effective in situations that are dynamic. This is because it leads to increases in both performance and efficiency. These developments are the result of the approach that was adopted, which led to their respective production.
This innovation seeks to improve Rayleigh fading channel second-order statistics by using a unique matrix partitioning method. LCR and AFD are crucial statistics in this study. Wireless communication signal behavior representation is improved by partitioned covariance matrices. This situation works best for systems with tightly spaced antennas. The suggested strategy outperformed characteristic function-based methods. Therefore, it investigated various antenna designs and Gaussian variations.
Simulations revealed that the matrix partitioning approach may increase antenna frequency distribution (AFD) and lower loss control ratio (LCR), which might provide satisfactory results. This is helpful when antenna direction and distance matter. This statistical accuracy increase helps wireless communication networks' efficiency and reliability. IoT-supported networks need steady signal strength, therefore this is beneficial.
The present method found that matrix partitioning improves wireless communication network efficiency and dependability. The matrix splitting technique was carefully reviewed before arriving here. Both current and future network topologies may profit from this technology.
Advantages of the present Invention
1. As a consequence of the innovation, there has been a significant enhancement in the effectiveness of navigation, especially in regions where conventional techniques are unable to overcome obstacles. With the existence of barriers or interference from other signals, wireless signal mapping has the potential to deliver a very high degree of precision and dependability. This is particularly true in situations when there are many signals.
2. The use of pre-existing wireless networks for the purpose of signal mapping provides a significant economic benefit by reducing the costs that are involved with the operation of infrastructure. The use of the system by industrial firms, which would not need the construction of costly new infrastructure, would make it possible for sophisticated robotic navigation to be utilized in a wider variety of industries. This will result in a higher number of industrial businesses integrating the system into their operations.
3. The technology reduces the amount of energy that is used as well as the expenses associated with operations by optimizing the pathways that robots take and removing any excess movement. Restricting any motion that is not necessary is one way to accomplish this goal. Through the use of an extraordinary degree of efficiency, businesses have the potential to accomplish cost savings within a constrained amount of time. Not only does this make the idea more technically better, but it also makes it substantially more appealing from an economic one.
, Claims:1. A method for analyzing the effect of matrix partitioning on second order statistics of fading channels in IoT-enabled mobile communication systems, comprises of:
• derive expressions for the level crossing rate (LCR) and average fade duration (AFD) using a novel matrix partitioning approach applied to a two-branch selection combining (SC) system;
• compare the proposed methodology with existing characteristic function-based approaches, including the impact of Gaussian fluctuation effects.
2. The method for analyzing the effect of matrix partitioning on second order statistics of fading channels in IoT-enabled mobile communication systems as claimed in the claim 1, wherein system
• integrates Wi-Fi, Bluetooth, and radio frequency (RF) signals in order to create a navigation map of the region that is both dynamic and updated in real time;
• Enable mobile robots to navigate terrain that is both complicated and dynamic. Unlike traditional guiding systems, this idea makes use of data collected from the Internet of Things (IoT) in real time in order to regularly update the map; and
• pervasive wireless Internet of Things (IoT) sensors in the environment assess the strength and quality of signals.
3. The method for analyzing the effect of matrix partitioning on second order statistics of fading channels in IoT-enabled mobile communication systems as claimed in the claim 1, wherein the present available methods for network signal mapping and processing make the technology economically feasible for use in both tiny interior areas and big industrial complexes.
4. The method for analyzing the effect of matrix partitioning on second order statistics of fading channels in IoT-enabled mobile communication systems as claimed in the claim 1, wherein cutting-edge design makes use of complex algorithms to provide mobile robots with assistance in gathering data about their surroundings and effectively navigating, and robotic systems make use of adaptive learning in order to save energy, improve their trajectory, and avoid obstacles. The effectiveness of the system is improved by its use.
5. The method for analyzing the effect of matrix partitioning on second order statistics of fading channels in IoT-enabled mobile communication systems as claimed in the claim 1, wherein the system exhibits a high degree of scalability and versatility, making it suitable for a wide range of applications and varying operational needs.

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