Performance Of Cellular Networks Research Articles

RTTV-TCP: Adaptive congestion control algorithm based on RTT variations for mmWave networks

Internet applications such as video gaming virtual/ augmented reality necessitate efficient fifth-generation (5G) millimeter-wave (mmWave) cellular networks. The Transmission Control Protocol (TCP) is an essential protocol for network connectivity. However, TCP faces challenges in efficiently utilizing the available bandwidth of 5G mmWave cellular networks while maintaining low latency, mainly due to constraints like Non-Line of Sight (NLoS) conditions. This paper introduces Round-Trip-Time Variations-TCP (RTTV-TCP), enhancing TCP performance in 5G mmWave cellular networks. Simulation scenarios for a 5G mmWave cellular network have been conducted to evaluate RTTV-TCP’s performance, comparing it to legacy TCP variants such as NewReno, HighSpeed, CUBIC, Bottleneck Bandwidth and Round-trip propagation time (BBR), FB-TCP (Fuzzy Based-TCP). The results demonstrate that RTTV-TCP achieves higher average throughput than these TCP variants while maintaining the same level of delay in 5G mmWave cellular networks. RTTV-TCP outperforms NewReno and CUBIC by a very significant margin, demonstrating a 208% improvement compared to HighSpeed and a 6% increase compared to BBR protocol in the worst Packet Error Rate (PER) scenario and when the buffer size matches the Bandwidth Delay Product (BDP).

Subchannel assignment for social-assisted UAV cellular networks using dynamic hypergraph coloring

Device-to-Device (D2D) communication when used in conjugation with Unmanned Aerial Vehicle (UAV) Femtocell and unlicensed spectrum can effectively tackle the ever-increasing mobile data demands. However, D2D communication raises security and privacy concerns among users due to the absence of a centralized entity such as a base station. Therefore, exploring social connections among users becomes imperative to enable secure and trustworthy D2D communication. This paper seeks to improve the performance of a social-assisted UAV cellular network augmented by D2D communication by proposing a novel subchannel assignment technique employing hypergraph coloring. Considering the real-world scenario, we incorporate the user/UAV mobility by using dynamic hypergraph coloring for subchannel assignment instead of the static one. Our proposed technique shifts a set of cellular users from the licensed to the unlicensed band based on their social connection with other co-channel D2D users. Additionally, we assign subchannels to different users to optimize the throughput while minimizing overall interference. Our proposed technique demonstrates significant improvements in system throughput, energy efficiency, and interference efficiency compared to conventional techniques. For our proposed technique, we observed improvements of 69%, 42%, and 15% in the per user system throughput when compared with the conventional techniques (graph, hypergraph, and dynamic-hypergraph, respectively). Moreover, our technique achieves higher per user energy efficiency by 120%, 70%, and 25%, and higher per user interference efficiency by 92%, 43%, and 22%, respectively, compared to graph, hypergraph, and dynamic-hypergraph techniques.

Cellular network-based IIoT architecture for time-critical control tasks of building automation

Industrial Internet of Things (IIoT) adopting emerging cellular networks attracted great attention in various industrial fields, including the building sector. However, the capability of IIoT and the performance of cellular networks when applie for building automation (BA), especially for time-critical control tasks, are not effectively evaluated yet. The potential impacts of network constraints on the control performance also need further investigation for the alternative architecture. These fundamental questions have not been addressed sufficiently yet. This study therefore proposes a cellular network-based IIoT architecture as a newly-proposed and recommendable solution for building automation systems. The architecture consists of smart field-level devices embedded with cellular network-enabled IoT controllers and a configured cellular network. Performance of the latest cellular networks, including 4th generation (4G) and 5th generation (5G) networks, are experimentally tested under different conditions. A typical building time-critical control task is selected to assess the capability of proposed architecture. The results show that the proposed IIoT architecture adopting 4G and 5G networks has good capability for the time-critical control tasks.

Fairness aware deep reinforcement learning for grant-free NOMA-IoT networks

Next generation networks have special areas related with the Internet of Things (IoT) to improve the performance of cellular networks in terms of throughput. Grant-free non-orthogonal multiple access (GF-NOMA) seems a feasible solution, letting machine type communication (MTC) devices transmits their packets when they ready to transmit. GF-NOMA increases the spectral efficiency by using the superimposing signals with different power levels over the same time and frequency resources. However, the main drawbacks of GF-NOMA are randomness and the management of power level selection of MTC devices. In 6G-IoT networks, the intelligence should be met to random access. It is time to design new access methods to solve the GF-NOMA issues that should be between the randomness and fully coordinated medium access. Deep-Q-Network (DQN) has become a very hot research topic in recent years that let the MTC devices to make a smart decision in an intelligent way to improve the throughput. Selfishness is an undesirable behavior of DQN for GF-NOMA system where the resources have different cost. In this study, we develop a novel learning framework for power domain GF-NOMA. The goal of our learning framework is to maximize the throughput considering fairness in power consumption which provides long-life to the IoT network. The learning algorithm push the MTC devices to exchange the resources between each other over time. The results show that the proposed method outperform the NOMA scheme with random selection in terms of throughput and increase the fairness index when the DQN with selfish behavior is employed.

Clustered jamming and antenna beam-width fluctuations for UAV-assisted cellular networks

Jamming devices have the capability to deliberately disrupt legitimate communications. Clustered jamming pertains to the deployment of jammers that are concentrated within specific clusters to amplify the interference. This paper models the impact of clustered jamming interference on unmanned aerial vehicles (UAV)-assisted cellular networks, taking into account fluctuations of the 3-dimensional (3D) beam-width of low altitude platform (LAP) antennas. The distribution of UAVs and macro base station (MBS) is modeled by independent 3D and 2D homogeneous Poisson point processes, respectively, while jammers are modeled using an independent Matern cluster process. Antenna 3D beam-width fluctuations are modeled according to Normal distribution. The modeling centers on the probability of association as well as coverage and spectral efficiency for line-of-sight LAP, non-line-of-sight LAP, and MBS links. This modeling investigation is conducted under multiple jamming clusters and the antenna 3D beam-width fluctuations of UAV. Analytical expressions are derived to characterize association, coverage, and SE performance in the context of clustered jamming and UAV beam-width variation. The obtained results indicate that UAV-assisted cellular networks experience a notable decline in the proximity of clustered jammers. Furthermore, this performance degradation is significantly exacerbated when the antenna 3D beam-width exhibits fluctuations. Consequently, to enhance the performance of UAV-assisted cellular networks, it is imperative for system designers to consider the implementation of robust anti-jamming techniques.

Joint Uplink and Downlink EMF Exposure: Performance Analysis and Design Insights

Installing more base stations (BSs) into the existing cellular infrastructure is an essential way to provide greater network capacity and higher data rate in the 5th-generation cellular networks (5G). However, a non-negligible amount of population is concerned that such network densification will generate a notable increase in exposure to electric and magnetic fields (EMF) over the territory. In this paper, we analyze the downlink, uplink, and joint downlink&uplink exposure induced by the radiation from BSs and personal user equipment (UE), respectively, in terms of the received power density and exposure index. In our analysis, we consider the EMF restrictions set by the regulatory authorities such as the minimum distance between restricted areas (e.g., schools and hospitals) and BSs, and the maximum permitted exposure. Exploiting tools from stochastic geometry, mathematical expressions for the coverage probability and statistical EMF exposure are derived and validated. Tuning the system parameters such as the BS density and the minimum distance from a BS to restricted areas, we show a trade-off between reducing the population's exposure to EMF and enhancing the network coverage performance. Then, we formulate optimization problems to maximize the performance of the EMF-aware cellular network while ensuring that the EMF exposure complies with the standard regulation limits with high probability. For instance, the exposure from BSs is two orders of magnitude less than the maximum permissible level when the density of BSs is less than 20 BSs/km2.

Maximizing Signal Quality for One Dimensional Cells In Mobile Communications

In this work, the cellular network performance based on other cell interference predictions is presented. It presents a mathematical model of co-channel interference analysis in hexagonal and linear cell shapes through a log-distance propagation model to investigate the effect of path loss exponent value on the received signal quality of the downlink. Simulation results obtained show that as the power exponent value increase, the interfering signals attenuation is increased resulting in received signal quality improvement. The signal-to-interference ratio (SIR) received by subscribers close to the cell edge will be less due to the contribution of the near-interfering cells especially when multiple layers of interfering cells are considered. The simulations confirmed that the impact of multi tiers of interfering cells cannot be ignored in systems of small cluster size as they may contribute to system performance degradation.

MISO System with Intelligent Reflecting Surface-Assisted Cellular Networks

This paper proposes an architecture based on Intelligent Reflecting Surfaces (IRSs) to improve the performance of future cellular networks. Specifically, we investigate the use of IRSs in combination with statistical Channel State Information (CSI) to enhance the coverage of Base Stations (BSs) in Multiple-Input Single-Output (MISO) systems. Furthermore, we exploit IRSs to reduce the complexity of the proposed architecture, and therefore the total cost, by reducing the number of required antennas at the transmitters (i.e., BSs). At first, we consider a Rayleigh fading channel between the transmitter and the receiver, and we assume the existence of a Line of Sight (LoS) between the BS and the IRS, as well as between the IRS and the destination. In the second part, we investigate the case of a Single-User Multiple-Input Single-Output (SU-MISO) system, where we study the benefits of IRSs in terms of coverage of the BS; then, we formulate a problem for a Multi-User Multiple-Input Single-Output (MU-MISO) system where the IRS is considered as a block of resources that can assist a certain number of users. The problem of managing the IRS resources is formulated as a nonlinear integer problem. We solve the optimization problem using an exhaustive search and propose two low-complexity heuristic algorithms. The performance of the system is evaluated with respect to a variable number of users, the position of the IRS, the required SNR, and the size of the cell. Simulation results corroborate the proposed approach and show that the introduction of the IRS in the network architecture enhances the overall performance of the network, extends the coverage area, enhances users’ satisfaction, and improves the SNR value, while optimizing the required number of antennas at the BS.

The Effect of Sand and Dust Storms (SDSs) and Rain on the Performance of Cellular Networks in the Millimeter Wave Band

The Effect of Sand and Dust Storms (SDSs) and Rain on the Performance of Cellular Networks in the Millimeter Wave Band

Modeling and Analysis of UAV-Assisted Mobile Network with Imperfect Beam Alignment

With the rapid development of emerging 5G and beyond (B5G), Unmanned Aerial Vehicles (UAVs) are increasingly important to improve the performance of dense cellular networks. As a conventional metric, coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment. In recent years, stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems. In this paper, an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed. An assumption was considered that all users are distributed according to Poisson Cluster Process (PCP) around base stations, in particular, Thomas Cluster Process (TCP). Using this model, the impact of beam alignment errors on the coverage probability was investigated. Initially, the Probability Density Function (PDF) of directional antenna gain between the user and its serving base station was obtained. Then, association probability with each tier was achieved. A tractable expression was derived for coverage probability in both Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) condition links. Numerical results demonstrated that at low UAVs altitude, beam alignment errors significantly degrade coverage performance. Moreover, for a small cluster size, alignment errors do not necessarily affect the coverage performance.

A dynamic policy for selecting D2D mobile relays

User-to-network relaying via Device-to-Device (D2D) communications is a promising technique for improving the performance of cellular networks. Since in practice the users serving as relays are mobile, a dynamic relay selection scheme is required to meet the requirements of communications and optimize the system performance In this paper, we propose a dynamic relay selection policy that maximizes the performance of cellular networks (e.g. throughput, reliability, coverage) under cost constraints (e.g. transmission power). We represent the relays’ dynamics as a Markov Decision Process (MDP) and, to limit the signaling overhead, we assume that only the locations of selected relays are observable. Therefore, the dynamic relay selection process is modeled as a Constrained Partially Observable Markov Decision Process (CPOMDP). Since finding the exact solution of such a framework is intractable, we develop a point-based value iteration solution and evaluate its performance. Furthermore, with the aim to reduce the complexity of the solution we prove the submodularity property of the reward and cost value functions and deduce a greedy solution that is scalable with the number of discovered relays. For the multi-user scenario, a distributed approach is introduced in order to reduce further the complexity and overhead of the proposed solution. We provide simulation results of a scenario where throughput is maximized under energy constraint and show the gain achieved by the proposed relay selection policy with respect to traditional cellular networks.

Evaluation of cellular network performance involving the LTE 1800 band and LTE 2100 band using the drive test method

In the 4G Network on the cellular system, the possibility of high traffic increase is a big problem for users, the proposed solution is to reduce the possibility of full traffic and decrease the quality of the cellular system by dividing the frequency channel into several parts. The purpose of this paper is to study the effect of network optimization on the value of Key Performance Indicator (KPI) in the LTE 1800 and LTE 2100 bands. KPI values, In the LTE 1800 and LTE 2100 bands tested using the drive test method using the Telkomsel sim card provider, the results show that the LTE 2100 band on the TML 013 site has a very high CSSR number compared to the band LTE 1800 which is 99.73% after optimization. The results showed that the LTE band 2100 is better than the LTE band 1800 in terms of KPI Summary.

On the Power-Splitting Relaying Protocol for SWIPT with Multiple UAVs in Downlink NOMA-IoT Networks

Unmanned aerial vehicle (UAV) communication and non-orthogonal multiple access (NOMA) are two promising technologies for wireless 5G networks and beyond. The UAVs can be used as flying base stations to form line-of-sight communication links to the Internet of things devices (IDs) and to enhance the performance of usual terrestrial cellular networks. Moreover, the UAVs can also be deployed as flying relay nodes for forwarding data from a base station (BS) to the IDs. On the other hand, non-orthogonal resource sharing for many concurrent users is exploited in NOMA, thus improving spectrum efficiency (SE) and supporting massive connections. The NOMA combined with energy harvesting (EH) in an amplify-and-forward (AF) with cooperative UAV systems is researched. Specifically, the UAVs act as rotary-wing relays to forward data from the BSs to two IDs. This paper focuses on the analysis of outage probabilities (OPs), system throughput, and energy efficiency (EE) for two IDs. Besides, we also do the asymptotic analysis of OPs at high signal-to-noise ratios (SNRs). Furthermore, this paper also inspects the impacts of the UAV-based relaying on the OP, system throughput, and EE of the proposed NOMA scheme. The derived asymptotic expansions show that the suggested model can enhance user fairness and the analytical results match the simulation results.

Fine-Grained Analysis of Reconfigurable Intelligent Surface-Assisted mmWave Networks

Reconfigurable intelligent surfaces (RISs) have emerged as a promising technology for millimeter wave (mmWave) networks. In this paper, we utilize tools from stochastic geometry to study the performance of a RIS-assisted mmWave cellular network. Specifically, the locations of the base stations (BSs) and the midpoints of the blockage are modeled as two independent Poisson point processes (PPPs), where the blockages are modeled by a Boolean model and a fraction of the blockages are coated with RISs. The particular characteristics of mmWave communications, i.e., directional beamforming and different path loss laws for line-of-sight (LOS) and non-line-of-sight (NLOS) propagation, are incorporated into our analysis. We derive analytical expressions for the success probability and the area spectral efficiency. The success probability under the special case where the blockage parameter is sufficiently small is also derived. Numerical results demonstrate that better coverage performance and higher energy efficiency can be achieved by a large-scale deployment of RISs. In addition, the tradeoff between the BS and RIS densities is investigated and the results show that the RISs can indeed enable the traditional networks to improve the success probability, especially for the cell-edge region, with limited power consumption.

Physical Layer Security in Multi-Antenna Cellular Systems: Joint Optimization of Feedback Rate and Power Allocation

This paper comprehensively studies the physical layer security in frequency division duplex multi-antenna cellular systems, where the multi-antenna base stations (BSs), legitimate users (LUs), and eavesdroppers are all randomly located. Each BS employs artificial-noise (AN)-aided multi-user linear beamforming with limited channel state information feedback. Based on the stochastic geometry theory, we first derive an analytical expression of a lower bound on the ergodic secrecy rate (ESR) of the typical LU without assuming asymptotes for any system parameter. We then develop a tight closed-form approximation on the optimal number of feedback bits to maximize a lower bound on the per-user net ESR, which takes into consideration the cost of uplink spectral efficiency for limited feedback. Moreover, the power allocation coefficient between message-bearing signals and AN can be optimized by using a bisection search method. Our main finding is that, the optimum number of feedback bits scales linearly with the path-loss exponent and the number of antennas, and scales logarithmically with the channel coherence time. The derived analytical results can also provide system-level insights into the ESR performance of the multi-antenna random cellular networks with limited feedback and the optimal system design. Numerical results are also presented to verify the obtained results.

Energy-efficient full-duplex D2D for SWIPT-empowered underlay cellular networks using a deep neural network

Close-packed small-cell networks enables a device-to-device (D2D) user equipment (DUE) to harvest energy from an ambient source, which increases the energy efficiency of the devices. Conceptually, full-duplex (FD) communications can double spectral efficiency compared to traditional half-duplex (HD) communications. However, the use of FD mode increases self-interference, which impacts spectral capacity and energy efficiency. In this paper, we study the performance of full-duplex D2D underlay cellular networks, where D2D devices decipher information and harvest energy simultaneously using SWIPT technology. Specifically, we build an optimization model to maximize the energy efficiency of the system, and obtain global- and sub-optimal solutions from the exhaustive search (ES) algorithm and the gradient search (GS) with barrier algorithm, respectively. In addition, we design deep neural networks (DNN) algorithm for the optimization model and evaluate the performance of the proposed DNN algorithm compared to the ES and GS algorithms. From the results, we confirm that the FD mode outperforms the HD mode in terms of energy efficiency and sum-rate and the proposed DNN algorithm can achieve near-global-optimal solution.

Analysis of Signal Quality, Voice Service, and Data Access on Telkomsel And Indosat Providers in Pakisjaya District

Quality in communication is very important in activities in this modern era. It is expected that the expected network quality against network quality is actually not expected. Measurement of network performance is important to refer for users to choose the right operator for service providers to improve the quality of their service Drive Test Method is a method used to measure cellular network performance. The purpose of this study is to study the results of research between service providers. The parameters used in this analysis are Receive Signal Code Power (RSCP), Cell ID, Signal Noise Ratio (SNR), Upload Rate, and Download Rate. This parameter is used for the measurement process of the Drive Test method. While the tool used to collect the value of each Drive Test parameter by using an Android-based application, GNet Track Pro. The measurement results with GNet Track Pro are then processed with the Google Earth application as a measurement area. Research data collected in this analysis were 60 cases, with each village 20 data collected to continue processing with the Drive Test method. In this study, Telkomsel chose to excel in voice services with 150 successful numbers of 150 attempted calls. While Indosat excels in providing data access services and special signals in the village of Tanjungbungin.

Modeling D2D Underlaying Cellular Network for Hotspot Communications with Poisson Cluster and Hole Processes

This paper develops a new approach to the modeling and analysis of device-to-device (D2D) underlaying multi-tier cellular network for dense hotspot communications, which consists of macro base stations (MBSs), pico BSs (PBSs), femto BSs (FBSs). A typicl user equipment (UE) can work either in D2D mode or cellular mode. Considering the dense hotspot communications, this work employs Poisson point process (PPP) to model the locations of MBSs and PBSs, and uses Poisson cluster process (PCP) to model the ones of UEs and FBSs. The locations of PBSs are also modeled as the centers of hotspots, referred to as the centers of PCPs. UEs and FBSs cluster around the common parent process PBSs. To guard the cluster-edge UEs, the clustered-UE classification and modified fractional frequency reuse (FFR) are jointly used, by which both the UEs and FBSs are classified two sets, cluster-center UEs and cluster-edge UEs, cluster-center FBSs and cluster-edge FBSs, respectively. The total frequency band is divided into two orthogonal segments, one of which is shared by D2D devices, cluster-edge FBSs, and PBSs, and the other segment of which is shared by cluster-center FBSs and MBSs. For such clustered multi-tier network, by using the methods from PPP, PCP, and PHP, this paper presents a tractable approach for modeling and analyzing the performance of cellular and D2D networks and gives the statistical descriptions of the experienced interferences at a typical D2D or cellular receiver by using the approximated Poisson hole processes (PHP) theory. This yields the derivations of the coverage probabilities of both the D2D receivers and cellular destinations. In additon, during the analysis of cellular UEs, to derive the coverage probabilities, this paper specially constructs one UE association criterion as well as the derivations of both the association probabilities and the statistical descriptions of association distances for cluster-center and cluster-edge UEs. The simulations results exploit the effect of various network parameters on the network performance and give the insights in terms of the proposed schemes as well as the comparison between cluster-center and cluster-edge UEs.

Impact of Blocking Correlation on the Performance of mmWave Cellular Networks

In mmWave networks, a large or nearby object can obstruct multiple communication links, which results in spatial correlation in the blocking probability between a user and two or more base stations (BSs). This paper characterizes this blocking correlation and derives its impact on the signal-to-interference-plus-noise ratio (SINR) of a mmWave cellular network. We first present an exact analysis of a 1D network and highlight the impact of blocking correlation in the derived expressions. Gaining insights from the 1D analysis, we develop an analytical framework for a 2D network where we characterize the sum interference at the user by considering the correlation between the blocking of serving and interfering links. Using this, we derive the SINR coverage probability. Via simulations, we demonstrate that including blockage correlation in the analysis is required for accurate characterization of the system performance, in particular when the blocking objects tend to be large.

On the Performance of Underlay Device-to-Device Communications

This paper comprehensively investigates the performance of the D2D underlaying cellular networks where D2D communications are operated concurrently with cellular networks provided that the aggregate interference measured on licensed users is strictly guaranteed. In particular, we derive the outage probability (OP), the average rate, and the amount of fading (AoF) of the D2D networks in closed-form expressions under three distinct power allocation schemes, i.e., the path-loss-based, equal, and random allocation schemes. It is noted that the considered networks take into consideration the impact of the intra-D2D networks, the inter-interference from the cellular networks and background noise, thus involving many random variables and leading to a complicated mathematical framework. Moreover, we also reveal the behavior of the OP with respect to the transmit power based on the rigorous mathematical frameworks rather than the computer-based simulation results. The derived framework shows that increasing the transmit power is beneficial for the OP of the D2D users. Regarding the cellular networks, the coverage probability (Pcov) of the cellular users is computed in closed-form expression too. Monte Carlo simulations are given to verify the accuracy of the proposed mathematical frameworks. Our findings illustrate that the power allocation method based on prior path-loss information outperforms the other methods in the average sum rate.