# Context-Aware Spectrum Sharing and Allocation for Multiuser-Based 5G Cellular Networks

Authors: A. Vijay Vasanth; D. Yuvaraj; Prasad Janga; Harsh Pratap Singh; R. Jaikumar; Subbiah Swaminathan; Polamarasetty P. Kumar; Babji Prasad Chapa; D. Y. Varaprasad; S. Chandragandhi; Worku Abera
Journal: Wireless Communications and Mobile Computing
 (2022)

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## Abstract

The number of users of current mobile and cellular networks is constantly increasing. The allocation of spectrum to its users is constantly facing various hurdles. This causes users to leave that network and connect to another network. Thus, those telecom companies are constantly struggling to provide high-speed services to the users. As a result, the demand for 5G networks is currently increasing. Considering these, an algorithm has been proposed here to suit the needs of the users. Its main feature is that it easily identifies the primary and secondary users of the 5G network and creates a spectrum allocation system for them accordingly. Generally, all other methods are designed with the primary user in mind. Furthermore, the spectrum hole calculation that is currently being proposed is done accurately so that the spectrum switching processes required for the secondary user can take place here very quickly so that the secondary user can use the spectrum without any hindrance. The proposed model achieved 93.29% of spectrum blocking, 6.71% of spectrum band dropping, 94.03% bandwidth utilization, 1073 ms end-to-end delay, and 17273 bps of throughput. The proposed model effectively handles the spectrum and intelligent approach to resolve the spectrum hole problems. The existing models are practically faced with these problems. The proposed model spectrum utilization and efficiency were increased compared with the existing models.


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## Body

## 1. Introduction

5G technology is the most anticipated technology across the country. That means 5G is the mobile-based Internet technology for the fifth generation. It is assumed that it will have many times faster download and upload speeds than the fourth-generation technology called 4G. In India in particular, applications for 5G testing are said to focus on health, agriculture, education, and public safety. Similarly, Troy has already approved the use of 5G in the financial sector. Then, the work is to start soon. Although specific bandwidth, quality, and average speeds have been set for 4G technology around the world, it can be said that there are huge differences in Internet speeds between each country. The spectrum sharing is the allocation of existing spectrum space to primary and secondary users without any hassle [1, 2], and many leading companies are competing to introduce this 5G technology. As many people know the benefits of this new 5G technology, your mobile network will be faster and you will be able to download and watch videos instantly. But technologists are hopeful that 5G technology will bring about unprecedented change not only in smartphone use but also in other areas. The primary users will have the pass required to utilize that particular spectrum of data. This is called a license. Users with this license can easily use that spectrum data at any time. These are called license users [3–6]. For example, by incorporating 5G technology into a vehicle, all vehicles traveling on a particular road can exchange information with each other and avoid accidents and fuel wastage. This facilitates the use of sports and entertainment-based live shows, movies, and processors that focus on technologies such as virtual reality and augmented reality in particular.The 5G uses different types of antennas, operates on different radio spectrum frequencies, and connects multiple devices over the Internet, minimizing delays and delivering high speeds. In the absence of the primary user, the secondary space will be leased to the secondary user. This is called spectrum leasing [7–10], and the primary space availability detection methods are called spectrum sensing [2, 11–13]. A new type of mobile network is not new; it is, in some respects, fundamentally different from what already exists. A fundamental difference from 5G’s individual radio frequencies is that 4G networks cannot achieve anything. The radio spectrum is divided into bands and you can go on each channel with unique features. 4G networks use frequencies below 6 GHz, but 5G is likely to use very high frequencies from 30 GHz to 300 GHz. These high frequencies are numerous for a number of reasons; one of the most important of which is supporting the large capacity for very fast data. They are less confusing with existing cellular data, so they can be used for bandwidth requests in the future, which can be used next to other wireless signals without much distraction and interruption. It is very different from 4G towers in that it can drop beam radio waves in places where there is no demand for even extreme data, energy, and electricity to access the Internet in all directions [14–17]. The 5G uses even smaller wavelengths, meaning antennas with precise directional controls will be much smaller than existing antennas. As a base station still uses steering antennas, it will support more than 1000 devices. This means that most users of 5G networks can get very fast, fast data.From a peak speed perspective, 5G is 20 times faster than 4G. It only downloads 20 times over a 5G network, when it only takes 4G (like a movie) to download data. Look another way: you can download more than 10 movies before the first half of a movie is delivered before 4G. The speed of the 5G is up to a maximum of 20 GB/V, while 4G only has 1GB/V [18–23]. These numbers do not refer to devices such as a standard wireless access (FWA) systems that have a direct wireless user between the tower and the user’s device. Speed changes when you move like a car or train. With dynamic spectrum sharing, for the first time, fourth-generation and fifth-generation services can be provided seamlessly within a single spectrum block. 5G is the next-generation mobile Internet service. All work can be done at speeds higher than the current upload and download speed. With the advent of high-speed Internet, users will be able to experience mapping, audiovisual, augmented reality, and computer-generated virtual reality (virtual reality) in real time. Current fourth-generation Internet speeds average 42 megabytes per second. But the telecommunications industry says it can reach speeds of up to 1 gigabyte per second.Qualcomm claims that the fifth-generation bandwidth can provide Internet service at speeds of 10 to 20 times faster than current Internet speeds. This allows you to download an HD movie in less than a minute. However, they usually experience devices with “regular” speeds because there are often many factors that affect bandwidth. Conversely, it is important to look at realistic speeds or the average measured bandwidth [24–28]. The 5G has not been released yet, so we cannot comment on the real-world experience, but at least 5 GB. Daily download speeds are estimated to deliver 100 Mb/s. There are numerous variables that affect speed, but 4G networks are averaged over 10 Mb/s, which is 4 times faster than 5G in the real world.


## 2. Related Works

Yang et al. [1] recommended improved spectrum sharing methods. That is, the unused empty spectrum is calculated first. And based on that calculation, they are given that space on the primary basis which is on the waiting list of the secondary user.Matinmikko et al. [3] calculated the disturbances in shared spectrum systems. Based on that, they identified the primary users who have the appropriate license to use that spectrum. After classifying them, they were assured that spectrum would be allocated to them by that license.Jorswieck et al. [4] calculated that distributed spectrum applications would increase the usability of that cellular network. Spectrum allocation was calculated there based on these calculation methods.Michelusi and Nokleby [5] classified a sensing method that helps to calculate vacancies in the spectrum. Morning spots on that particular wavelength were calculated based on its analysis results. So while it was being calculated whether the primary user was constantly there or not, it was found that the series of interruptions of the second user could also be a nuisance to them.Ai et al. [6] constantly monitored users’ devices. They calculated and analyzed important data such as the power their devices consume when using the bandwidth. Based on these results, it is easy to calculate how much power is required by which device is used.Zhu et al. [7] calculated the spectrum leasing method. This means that the space will be temporarily reserved for the secondary user in the absence of the primary user. Secondary users will be charged for using it. Thus, the benefit to companies is high. But this leasing method will vary depending on the inconvenience to the secondary user when the primary user enters and the extent to which they are prepared for changes in the switching mode.Duan et al. [9] introduced the spectrum sharing system based on interaction. That is, the spectrum is allocated to them based on the interaction of the primary user and the interaction of the secondary user. Priority will be given to the first comer here. Others may need to be on the waiting list. Priority is given to communication here.Goldsmith et al. [29] proposed a spectrum allocation system in brake mode. This means that when a user is utilizing specific spectrum holes their data will be eroded by users elsewhere in it. This will cause a temporary ban. At that point, users will be moved from that location to another location that is blocked. They have elaborated on the consequences of this.


## 3. Proposed Method

This method currently proposed differs from the previous methods of the multiuser management algorithm. That means both primary and secondary users benefit here. Figure1 shows the proposed methodology of spectrum allocation techniques, and also, Figure 2 discusses about the proposed architecture diagram.Figure 1
Proposed spectrum allocation technique.Figure 2
Proposed system block diagram.


### 3.1. Spectrum Sensing Module

Data must first be collected before a spectrum can be allocated. Only on the basis of that information will it be known to whom the spectrum band was given. If it is not assigned to anyone, it can be assigned to the primary or secondary user in the queue. This data management system is called spectrum sensing. With this module, you can see if the spectrum band is available.


### 3.2. User Detection Module

That is, users are required to purchase or use that module for spectrum allocation. In order to allocate the amount they ask for, their size and time of use must first be calculated. Thus, it prevents excessive bandwidth usage of the users. This module usually receives and stores data of primary and secondary users as input. Details of those who need spectrum licenses and those who need spectrum leasing can be obtained from here.


### 3.3. Spectrum Allocation Module

This is where user details and vacant spectrum details are retrieved. Spectrum allocation is the process by which the details obtained and the needs of the user are calculated and allowed to be applied to them.


### 3.4. Spectrum Access Module

Here, the classified spectrum is classified as primary user and secondary user based on their usability. This module allows full-scale spectrum usage for the primary user and a limited amount of usage for the secondary user.Algorithm 1: Multiuser management algorithm (MUMA).
1. Start2. Initialize spectrum sensing input value3. Check the sensing details with the spectrum dataset4.  IF (spectrum=available)5.  Then check if (available=hole)6.       Then send the details to leasing unit7.       Waiting for leasing request from SU8.       Lease the spectrum hole to SU9.       Else10.       Then send the details to licensing unit11.       Waiting for licensing request from PU12.       Provide the license to PU13. End


### 3.5. Spectrum Allocation as per Multiuser Management Algorithm (MUMA)

The input data of the users who log in first is monitored. It is on the basis of these input data’s that it is known whether he is a primary user or a secondary user. And this is where new types of entries without any lentils are calculated. Based on these calculations, their input details are recorded in the database. The entire proposed flow graph is shown in Figure3.Figure 3
Flowchart of the proposed system.Spectrum allocation will be made to them on the basis of those recorded details. Then, it will be calculated whether the spectrum is available for use there. Generally, in other modes, the waiting time of the users may be longer. But in this proposed method, these data will already be calculated and recorded in the database. Based on this, spectrum allocation takes place in two modes, licensing and leasing.All work can be done at speeds higher than the current upload and download speed. With the advent of high-speed Internet, users will be able to experience mapping, audiovisual, augmented reality, and computer-generated virtual reality (virtual reality) in real time. Current fourth-generation Internet speeds average 42 megabytes per second. But the telecommunications industry says it can reach speeds of up to 1 gigabyte per second.The spectrum is allocated to the primary user in the licensing system. In this way, the overall spectrum band can be utilized according to their need. But the leasing system was developed for secondary users. The uniqueness of this is that the spectrum band allocates spectrum droplets to them based on the data bundles so recorded that they detect the existing holes in the spectrum band and record them in the database. Thus, the required spectrum is allocated to all primary and secondary users. The proposed algorithm effectively identified the primary and secondary user groups. This shows the network user groups. These user group functionalities were monitored by the proposed model. This will help here to protect the unwanted usage and vulnerable entries. So, the spectrum was effectively used and the hole usage also switched by the proposed model.


## 3.1. Spectrum Sensing Module

Data must first be collected before a spectrum can be allocated. Only on the basis of that information will it be known to whom the spectrum band was given. If it is not assigned to anyone, it can be assigned to the primary or secondary user in the queue. This data management system is called spectrum sensing. With this module, you can see if the spectrum band is available.


## 3.2. User Detection Module

That is, users are required to purchase or use that module for spectrum allocation. In order to allocate the amount they ask for, their size and time of use must first be calculated. Thus, it prevents excessive bandwidth usage of the users. This module usually receives and stores data of primary and secondary users as input. Details of those who need spectrum licenses and those who need spectrum leasing can be obtained from here.


## 3.3. Spectrum Allocation Module

This is where user details and vacant spectrum details are retrieved. Spectrum allocation is the process by which the details obtained and the needs of the user are calculated and allowed to be applied to them.


## 3.4. Spectrum Access Module

Here, the classified spectrum is classified as primary user and secondary user based on their usability. This module allows full-scale spectrum usage for the primary user and a limited amount of usage for the secondary user.Algorithm 1: Multiuser management algorithm (MUMA).
1. Start2. Initialize spectrum sensing input value3. Check the sensing details with the spectrum dataset4.  IF (spectrum=available)5.  Then check if (available=hole)6.       Then send the details to leasing unit7.       Waiting for leasing request from SU8.       Lease the spectrum hole to SU9.       Else10.       Then send the details to licensing unit11.       Waiting for licensing request from PU12.       Provide the license to PU13. End


## 3.5. Spectrum Allocation as per Multiuser Management Algorithm (MUMA)

The input data of the users who log in first is monitored. It is on the basis of these input data’s that it is known whether he is a primary user or a secondary user. And this is where new types of entries without any lentils are calculated. Based on these calculations, their input details are recorded in the database. The entire proposed flow graph is shown in Figure3.Figure 3
Flowchart of the proposed system.Spectrum allocation will be made to them on the basis of those recorded details. Then, it will be calculated whether the spectrum is available for use there. Generally, in other modes, the waiting time of the users may be longer. But in this proposed method, these data will already be calculated and recorded in the database. Based on this, spectrum allocation takes place in two modes, licensing and leasing.All work can be done at speeds higher than the current upload and download speed. With the advent of high-speed Internet, users will be able to experience mapping, audiovisual, augmented reality, and computer-generated virtual reality (virtual reality) in real time. Current fourth-generation Internet speeds average 42 megabytes per second. But the telecommunications industry says it can reach speeds of up to 1 gigabyte per second.The spectrum is allocated to the primary user in the licensing system. In this way, the overall spectrum band can be utilized according to their need. But the leasing system was developed for secondary users. The uniqueness of this is that the spectrum band allocates spectrum droplets to them based on the data bundles so recorded that they detect the existing holes in the spectrum band and record them in the database. Thus, the required spectrum is allocated to all primary and secondary users. The proposed algorithm effectively identified the primary and secondary user groups. This shows the network user groups. These user group functionalities were monitored by the proposed model. This will help here to protect the unwanted usage and vulnerable entries. So, the spectrum was effectively used and the hole usage also switched by the proposed model.


## 4. Results and Discussion

The proposed algorithm is compared with the existing algorithms in terms of different performance metrics like blocking connectivity, dropping connectivity, bandwidth utilization, throughput, and end-to-end delay of the network. Each performance metric of the proposed algorithm is verified for its efficacy with the existing techniques such as a smart collaborative charging algorithm (SCCA), dynamic spectrum leasing and service selection (DSLSS), cooperative spectrum sharing algorithm (CSSA), and a contract-based spectrum trading scheme (CSTS). The Network Simulator (NS-2) is used for the simulation with the following parameters. This will help the admin to manage both the primary and secondary users. Table1 presents the simulation parameters.Table 1
Simulation parameters.
ParameterValueSimulation duration8000 framesPreamble duration50 msDetection connectivity0.6Frame duration320 msOnline primary users (PU)12No. of secondary users (SU)7Max. interference ratio1.56Permission connectivity0.57


### 4.1. Spectrum Blocking

At the same time, all users are unable to connect a network [13]. To provide sufficient resources for all devices is too expensive and managing the network traffic without congestion is really difficult [12]. Therefore, the networks are likely to face resource shortage issues at times. Here, the blocking helps to filter the primary users. The spectrum blocking is the term, to allow the primary users and filter the random devices in a network. For reserved channel scheme, consider that the total available channels are “s” channels from which “a” channels are reserved. Then, the blocking connectivity is given by
(1)Spectrumblocking=∑b=1aMj,whereMj is the total number of users.Table2 presents the analysis of spectrum blocking between existing SCCA, DSLSS, CSSA, and CSTS and proposed MUMA. From Table 2, if the device does not have user license and device license, then it was sent under security check with network administrator.Table 2
Analysis of spectrum blocking.
No. of usersSpectrum blocking in (%)SCCADSLSSCSSACSTSMUMA10062.5853.2371.1872.7793.5120064.2459.0964.3478.1893.4130064.6957.9563.0579.6793.3440060.1159.0960.9182.9193.2950059.6159.9762.4882.1993.2560059.7761.1764.182.0693.2270060.5162.8265.983.3393.22


### 4.2. Spectrum Dropping

The dropping connectivity is the term to drop all the devices while the network was fully occupied. The random detection of devices is based on priority importance and min–max threshold of a network.(i)
Case 1:averageweight<minthreshold; no dropping users(a)
If an average weight of a queue is under the min threshold, then no devices will be dropped(ii)
Case 2:averageweight>maxthreshold; all users are dropped(a)
If an average weight of a queue is over the max threshold, then all devices will be droppedHere, the priority provides based on the licenses. If the users have licenses, then they are allowed to utilize the resources. Otherwise, they are in queue while they are getting licenses. Assume that the process is ergodic and letxt be its stationary distribution. The main QoS indicators of dropping probabilities are defined, respectively, by the following erotic limit such as
(2)Dxt=droppedusersundertimex,tnonblockarrivalsundertimex,t.Table3 presents the analysis of spectrum dropping between existing SCCA, DSLSS, CSSA, and CSTS and proposed MUMA.Table 3
Analysis of spectrum dropping.
No. of usersSpectrum dropping in (%)SCCADSLSSCSSACSTSMUMA10037.4246.7728.8227.236.4920035.7640.9135.6621.826.5930035.3142.0536.9520.336.6640039.8940.9139.0917.096.7150040.3940.0337.5217.816.7560040.2338.8335.917.946.7870039.4937.1834.116.676.78From Table3, if the device has both user license and device license, then it was paired with the network. When compared with the existing method, the proposed method achieves less dropping connectivity. The primary users do not need to get authentication from network admin.


### 4.3. Utilization of Bandwidth

At a given time, the highest quantity of data transferred over a user is referred the bandwidth. The percentage of consumed bandwidth off the total available bandwidth is called the bandwidth utilization.(3)BUin%=totalmessagestrasmittedandreceivedspeedoftransmission×100.Table4 presents the analysis of bandwidth utilization between existing SCCA, DSLSS, CSSA, and CSTS and proposed MUMA.Table 4
Analysis of bandwidth utilization.
No. of usersBandwidth utilization in (%)SCCADSLSSCSSACSTSMUMA10061.1265.7970.4577.9996.1620060.7964.2969.8676.1295.1230059.4563.1868.8875.2994.9940058.3162.867.6774.3894.0350057.2661.7966.5373.4694.4660056.5560.8665.4272.1393.2270055.2559.8664.7271.2693.11From Table4, primary users are not required any authentication from admin. When compared with the existing method, the proposed method achieves more bandwidth utilization because all the slots are occupied with the primary users. The unused bandwidth is allocated for other new devices while they are getting approved by admin.


### 4.4. End-to-End Delay

The time taken for a message to get transferred across a network user group from source user to end user is called end-to-end delay. This is the ratio of total hops (p) essential for routing to the total users (tu) in the network which is given by
(4)Delayinms=ptu.Table5 presents the analysis of spectrum delay between existing SCCA, DSLSS, CSSA, and CSTS and proposed MUMA.Table 5
Analysis of delay.
No. of usersDelay in (ms)SCCADSLSSCSSACSTSMUMA10034064006486239331359200330538054630380012793003204360444213546117740031023402435533501073500300032004088319098960028952995389026798807002792279237752373799


### 4.5. Throughput

The network throughput is the amount of the data rates that are distributed to all users in a network. It refers to the data flow rate of a communication channel. In wireless environment, throughput is an essential measurement while the data are moving without any traffic simultaneously.(5)Throughputbitssec=∑numberofsuccessfulpackets∗averagepacketsizetotaltimesentindeliveringthatamountofdata.Table6 presents the analysis of throughput between existing SCCA, DSLSS, CSSA, and CSTS and proposed MUMA. When compared with the existing method, the proposed method achieves higher throughput because all the familiar users utilize the higher bandwidth capacity.Table 6
Analysis of throughput.
No. of usersThroughput in (bps)SCCADSLSSCSSACSTSMUMA10013689854011862993317559200135888339116309800174793001348781381142195461737740013385793611355935017273500132837734110889190171896001317875291089086791708070013075732610775837316999In a cutoff region, the proposed model achieved 93.29% of spectrum blocking, 6.71% of spectrum band dropping, 94.03% bandwidth utilization, 1073 ms end-to-end delay, and 17273 bps of throughput. Hence, the proposed algorithm performed effectively in the 5G communication network.


## 4.1. Spectrum Blocking

At the same time, all users are unable to connect a network [13]. To provide sufficient resources for all devices is too expensive and managing the network traffic without congestion is really difficult [12]. Therefore, the networks are likely to face resource shortage issues at times. Here, the blocking helps to filter the primary users. The spectrum blocking is the term, to allow the primary users and filter the random devices in a network. For reserved channel scheme, consider that the total available channels are “s” channels from which “a” channels are reserved. Then, the blocking connectivity is given by
(1)Spectrumblocking=∑b=1aMj,whereMj is the total number of users.Table2 presents the analysis of spectrum blocking between existing SCCA, DSLSS, CSSA, and CSTS and proposed MUMA. From Table 2, if the device does not have user license and device license, then it was sent under security check with network administrator.Table 2
Analysis of spectrum blocking.
No. of usersSpectrum blocking in (%)SCCADSLSSCSSACSTSMUMA10062.5853.2371.1872.7793.5120064.2459.0964.3478.1893.4130064.6957.9563.0579.6793.3440060.1159.0960.9182.9193.2950059.6159.9762.4882.1993.2560059.7761.1764.182.0693.2270060.5162.8265.983.3393.22


## 4.2. Spectrum Dropping

The dropping connectivity is the term to drop all the devices while the network was fully occupied. The random detection of devices is based on priority importance and min–max threshold of a network.(i)
Case 1:averageweight<minthreshold; no dropping users(a)
If an average weight of a queue is under the min threshold, then no devices will be dropped(ii)
Case 2:averageweight>maxthreshold; all users are dropped(a)
If an average weight of a queue is over the max threshold, then all devices will be droppedHere, the priority provides based on the licenses. If the users have licenses, then they are allowed to utilize the resources. Otherwise, they are in queue while they are getting licenses. Assume that the process is ergodic and letxt be its stationary distribution. The main QoS indicators of dropping probabilities are defined, respectively, by the following erotic limit such as
(2)Dxt=droppedusersundertimex,tnonblockarrivalsundertimex,t.Table3 presents the analysis of spectrum dropping between existing SCCA, DSLSS, CSSA, and CSTS and proposed MUMA.Table 3
Analysis of spectrum dropping.
No. of usersSpectrum dropping in (%)SCCADSLSSCSSACSTSMUMA10037.4246.7728.8227.236.4920035.7640.9135.6621.826.5930035.3142.0536.9520.336.6640039.8940.9139.0917.096.7150040.3940.0337.5217.816.7560040.2338.8335.917.946.7870039.4937.1834.116.676.78From Table3, if the device has both user license and device license, then it was paired with the network. When compared with the existing method, the proposed method achieves less dropping connectivity. The primary users do not need to get authentication from network admin.


## 4.3. Utilization of Bandwidth

At a given time, the highest quantity of data transferred over a user is referred the bandwidth. The percentage of consumed bandwidth off the total available bandwidth is called the bandwidth utilization.(3)BUin%=totalmessagestrasmittedandreceivedspeedoftransmission×100.Table4 presents the analysis of bandwidth utilization between existing SCCA, DSLSS, CSSA, and CSTS and proposed MUMA.Table 4
Analysis of bandwidth utilization.
No. of usersBandwidth utilization in (%)SCCADSLSSCSSACSTSMUMA10061.1265.7970.4577.9996.1620060.7964.2969.8676.1295.1230059.4563.1868.8875.2994.9940058.3162.867.6774.3894.0350057.2661.7966.5373.4694.4660056.5560.8665.4272.1393.2270055.2559.8664.7271.2693.11From Table4, primary users are not required any authentication from admin. When compared with the existing method, the proposed method achieves more bandwidth utilization because all the slots are occupied with the primary users. The unused bandwidth is allocated for other new devices while they are getting approved by admin.


## 4.4. End-to-End Delay

The time taken for a message to get transferred across a network user group from source user to end user is called end-to-end delay. This is the ratio of total hops (p) essential for routing to the total users (tu) in the network which is given by
(4)Delayinms=ptu.Table5 presents the analysis of spectrum delay between existing SCCA, DSLSS, CSSA, and CSTS and proposed MUMA.Table 5
Analysis of delay.
No. of usersDelay in (ms)SCCADSLSSCSSACSTSMUMA10034064006486239331359200330538054630380012793003204360444213546117740031023402435533501073500300032004088319098960028952995389026798807002792279237752373799


## 4.5. Throughput

The network throughput is the amount of the data rates that are distributed to all users in a network. It refers to the data flow rate of a communication channel. In wireless environment, throughput is an essential measurement while the data are moving without any traffic simultaneously.(5)Throughputbitssec=∑numberofsuccessfulpackets∗averagepacketsizetotaltimesentindeliveringthatamountofdata.Table6 presents the analysis of throughput between existing SCCA, DSLSS, CSSA, and CSTS and proposed MUMA. When compared with the existing method, the proposed method achieves higher throughput because all the familiar users utilize the higher bandwidth capacity.Table 6
Analysis of throughput.
No. of usersThroughput in (bps)SCCADSLSSCSSACSTSMUMA10013689854011862993317559200135888339116309800174793001348781381142195461737740013385793611355935017273500132837734110889190171896001317875291089086791708070013075732610775837316999In a cutoff region, the proposed model achieved 93.29% of spectrum blocking, 6.71% of spectrum band dropping, 94.03% bandwidth utilization, 1073 ms end-to-end delay, and 17273 bps of throughput. Hence, the proposed algorithm performed effectively in the 5G communication network.


## 5. Conclusion

The proper use of the spectrum typically available on a 5G network ensures that both primary and secondary users benefit. Also, the secondary user may feel some discomfort as the travel time of those users is switched. But it does not have a big impact on the results as it takes less time. They also have the advantage that the speed of the secondary user is equal to the speed of the primary user. Thus, secondary users are found to be running at high speeds. Since it does not affect the spectrum in any way, there is no chance of any curls in its accuracy and bandwidth allocation. Hence, the proposed multiuser management algorithm (MUMA) was comparatively better than the existing algorithms like a smart collaborative charging algorithm (SCCA), dynamic spectrum leasing and service selection (DSLSS), cooperative spectrum sharing algorithm (CSSA), and a contract-based spectrum trading scheme (CSTS).



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*Source: 5309906-2022-07-13.xml*