Wireless Cellular Networks Research Articles

Accurate Path-Loss Estimation for Wireless Cellular Networks

In addition to its rule in achieving acceptable system performance, accurate path-loss estimation leads to realize a simple and precise estimation of cellular networks financial feasibility. In other words, in cellular networks, while accurate path-loss estimation helps to achieve a reasonable cost, inaccurate path-loss estimation could either lead to reduce the cost but degrade the performance, or improve the performance but increase the cost. Thus accurate path loss estimation becomes a very crucial and desirable goal. To this end, different models were introduced in the literature for achieving the aforementioned goal; however, each model sought to be a valid choice in a specific environment. Therefore, our main objective in this paper was to provide an insight to the cellular network designers to simplify the decision-making process. A number of widely used path-loss estimation models that work in different environments, such as Free-space model, Two-ray model, Okumura/Hata model, COST 231 model, and Indoor model were reviewed and analyzed. This significantly would assist any cellular network designer to select an appropriate model according to its working environment, and thus realize the desirable accurate path-loss estimation. Matlab was used to perform this analysis. The analysis drove us to enter into implicit comparisons between the aforementioned models. Going through these comparisons, it is concluded that although an increase in the level of complexity is encountered when using models with large number of correction factors, more accurate path-loss estimation can be achieved.

Compact wideband hybrid fractal antenna loaded on AMC reflector with enhanced gain for hybrid wireless cellular networks

A wideband hybrid fractal monopole antenna loaded with artifical magnetic conductor (AMC) is proposed. Using a hybrid fractal generator, the monopole antenna achieves self-similarity compactness, reduced size and good wideband performances. The ground is semi-elliptic and has defected steps aiming to improve impedance matching and X-pol. reduction. The AMC reflector has 3× 3 array of cesaro shaped unit cells looped in a square metallic conductor. The AMC enhances radiation gain with back-lobe reduction. The AMC unit cell produce a 00 phase reflection at fAMC = 4.5 GHz and then loaded to optimize antenna performance. To validate the design, a prototype antenna is fabricated and measured. The antenna operates from (3.7–7.0) GHz with 61.68% impedance bandwidth, realized gain of (8.7–13.8) dBi, and radiation efficiency > 82.5%. The proposed antenna leverages on compactness, low-profile AMC height and good boresight radiation gain, which shows its potential for hybrid wireless cellular networks.

Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks

With growth in the number of smart devices and advancements in their hardware, in recent years, data-driven machine learning techniques have drawn significant attention. However, due to privacy and communication issues, it is not possible to collect this data at a centralized location. Federated learning is a machine learning setting where the centralized location trains a learning model over remote devices. Federated learning algorithms cannot be employed in the real world scenarios unless they consider unreliable and resource-constrained nature of the wireless medium. In this paper, we propose a federated learning algorithm that is suitable for cellular wireless networks. We prove its convergence, and provide a sub-optimal scheduling policy that improves the convergence rate. We also study the effect of local computation steps and communication steps on the convergence of the proposed algorithm. We prove, in practice, federated learning algorithms may solve a different problem than the one that they have been employed for if the unreliability of wireless channels is neglected. Finally, through numerous experiments on real and synthetic datasets, we demonstrate the convergence of our proposed algorithm.

Time of Arrival Ranging and Localization Algorithm in Multi-Path and Non-Line-of-Sight Environments in OFDM System

Time of Arrival (TOA) is a widely used wireless cellular network ranging technology. How to perform accurate TOA estimation in multi-path and non-line-of-sight (NLOS) environments and then accurately calculating mobile terminal locations are two critical issues in positioning research. For NLOS identification, it can be performed in the TOA measurement part and the position calculation part, respectively. In this paper, for the above two steps, two schemes for mitigating NLOS errors are proposed. First of all, a TOA ranging method based on clustering theory is proposed to solve the problem of line of sight (LOS) path estimation in multi-path channels. We model TOA ranging as a Gaussian mixture model and illustrate how LOS and NLOS can be measured and identified based on non-parametric Bayesian methods when the wireless transmission environment is unknown. Moreover, for NLOS propagation channels, this paper proposes a user location estimator based on the maximum a posteriori (MAP) criterion. Combined with the TOA estimation and user location computation scheme proposed in this paper, the terminal's positioning accuracy is improved. Experiments show that the TOA measurement and localization algorithms presented in this paper have good robustness in complex wireless environments.

Evaluation of Development Level and Technical Contribution of Recent Technologies Adopted to Meet the Challenges of 5G Wireless Cellular Networks

The evolution of the global wireless market is accompanied by an increased need in terms of speed and number of users, lower latency, better coverage, better spectral efficiency and quality of service, etc. To meet these needs, 5G has recently been introduced as an effective solution which targets, via the large scale deployment of symmetric antennas, a wide variety of sectors such as energy, health, media, industry, transport and especially wireless cellular networks which are among the most important pillars of modern societies. Multiple Input, Multiple Output (MIMO) systems, which have been extended to “Massive MIMO” mode and which consist of increasing the number of radiating elements involved in the transmission and reception of the radio link, are a very promising solution for improving the spectral efficiency of wireless communication systems (WCSs). Motivated by the aforementioned developments, the present paper investigates the increased capacity of MIMO systems to improve transmission in WCSs using 5G. It carefully focuses on the evaluation of the development level and technical contribution of MIMO systems and millimeter wave (mmWave) bands in 5G wireless cellular networks (WCNs) and gives important recommendations.

Ruin Theory for Energy-Efficient Resource Allocation in UAV-Assisted Cellular Networks

Unmanned aerial vehicles (UAVs) can provide an effective solution for improving the coverage, capacity, and the overall performance of terrestrial wireless cellular networks. In particular, UAV-assisted cellular networks can meet the stringent performance requirements of the fifth generation new radio (5G NR) applications. In this article, the problem of energy-efficient resource allocation in UAV-assisted cellular networks is studied under the reliability and latency constraints of 5G NR applications. The framework of ruin theory is employed to allow solar-powered UAVs to capture the dynamics of harvested and consumed energies. First, the surplus power of every UAV is modeled, and then it is used to compute the probability of ruin of the UAVs. The probability of ruin denotes the vulnerability of draining out the power of a UAV. Next, the probability of ruin is used for efficient user association with each UAV. Then, power allocation for 5G NR applications is performed to maximize the achievable network rate using the water-filling approach. Simulation results demonstrate that the proposed ruin-based scheme can enhance the flight duration up to 61% and the number of served users in a UAV flight by up to 58%, compared to a baseline SINR-based scheme.

Performance analysis on a cooperative transmission scheme of multicast and NOMA in cache‐enabled cellular networks

Caching popular contents at base stations (BSs) can effectively avoid redundant data traffic and improve backhaul capacity. Techniques such as multicast (MC) and non-orthogonal multiple access (NOMA) can significantly improve spectral efficiency by delivering popular contents to multiple users using a single channel. Therefore, we propose a cooperative transmission scheme of MC and NOMA in cache-enabled wireless cellular networks. First, we derive the probability mass function (PMF) of the number of channels in the MC mode as well as the joint PMF of the number of channels and number of NOMA users in the NOMA mode. Second, we analyse the successful transmission probabilities of the two modes by utilising tools from stochastic geometry. Finally, with the derived probabilities using the two modes, we obtain the total successful transmission probability based on probability theory. The quasi-closed form expression of the successful transmission probability is obtained in a special case, where the noise is neglected, and the path-loss exponent is set to be four. Simulation results validate the accuracy of the analysis and demonstrate the performance gain due to the proposed cooperative transmission scheme of MC and NOMA.

QoS Aware Multi-Path Routing using Link Scheduling Algorithm

Objective: The demand for Cellular based multimedia services is growing day by day, in order to fulfill such demand the present day cellular networks needs to be upgraded to support excessive capacity calls along with high data accessibility. Analysis of traffic and huge network size could become very challenging issue for the network operators for scheduling the available bandwidth between different users. In the proposed work a novel QoS Aware Multi Path scheduling algorithm for smooth CAC in wireless mobile networks. The performance of the proposed algorithm is assessed and compared with existing scheduling algorithms. The simulation results show that the proposed algorithm outperforms existing CAC algorithms in terms of throughput and delay. The CAC algorithm with scheduling increases end-to-end throughput and decreases end-to-end delay. Methods: The key idea to implement the proposed research work is to adopt spatial reuse concept of wireless sensor networks to mobile cellular networks. Spatial reusability enhances channel reuse when the node pairs are far away and distant. When Src and node b are communicating with each other, the other nodes in the discovered path should be idle without utilizing the channel. Instead the other nodes are able to communicate parallelly the end-to-end throughput can be improved with acceptable delay. Incorporating link scheduling algorithms to this key concept further enhances the end-to-end throughput with in the turnaround time. So, in this research work we have applied spatial reuse concept along with link scheduling algorithm to enhance end-to-end throughput with in turnaround time. The proposed algorithm not only ensures that a connection gets the required bandwidth at each mobile node on its way by scheduling required slots to meet the QoS requirements. By considering the bandwidth requirement of the mobile connections, the CAC module at the BS not only considers the bandwidth requirement but also conforming the constrains of system dealy and jitter are met. Result: To verify the feasibility and effectiveness of our proposed work, with respect to scheduling the simulation results clearly shows the throughput improvement with Call Admission Control. The number of dropped calls is significantly less and successful calls are more with CAC. The percentage of dropped calls is reduced by 9 % and successful calls are improved by 91%. The simulation is also conducted on time constraint and ratio of dropped calls are shown. The total time taken to forward the packets and the ration of dropped calls is less when compared to non CAC. On a whole the CAC with scheduling algorithms out performs existing scheduling algorithms. Conclusion: In this research work we have proposed a novel QoS aware scheduling algorithm that provides QoS in Wireless Cellular Networks using Call Admission Control (CAC). The simulation results show that the end-to-end throughput has been increased by 91% when CAC is used. The proposed algorithm is also compared with existing link scheduling algorithms. The results reveal that CAC with scheduling algorithm can be used in Mobile Cellular Networks in order to reduce packet drop ratio. The algorithm is also used to send the packets within acceptable delay.

Energy-Efficient Resource Allocation in C-RANs with Capacity-Limited Fronthaul

Cloud Radio Access Network (C-RAN) is a key architecture for 5G cellular wireless network that aims at improving spectral and energy efficiency of the network by uniting traditional RAN with cloud computing. In this paper, a novel resource allocation scheme that optimizes the network energy efficiency of a C-RAN is designed. First, an energy consumption model that characterizes the computation energy of the BaseBand Unit (BBU) is introduced based on empirical results collected from a programmable C-RAN testbed. Then, an optimization problem is formulated to maximize the energy efficiency of the network, subject to practical constraints including Quality of Service (QoS) requirement, radio remote head transmit power, and fronthaul capacity limits. The formulated Network Energy Efficiency Maximization (NEEM) problem jointly considers the tradeoff among the network accumulated data rate, BBU power consumption, fronthaul cost, and beamforming design. To deal with the non-convexity and mixed-integer nature of the problem, we utilize successive convex approximation methods to transform the original problem into the equivalent Weighted Sum-Rate (WSR) maximization problem. We then propose a provably-convergent iterative method to solve the resulting WSR problem. Extensive simulation results coupled with real-time experiments on a small-scale C-RAN testbed show the effectiveness of our proposed resource allocation scheme and its advantages over existing approaches.

5G Energy Efficiency Overview

It is a critical requirement for the future of 5G communication networks to provide high speed and significantly reduce network energy consumption. In the Fifth Generation (5G), wireless cellular networks, smartphone battery efficiency, and optimal utilization of power have become a matter of utmost importance. Energy-efficient networks along with an energy-saving strategy in mobile devices play a vital role in the mobile revolution. The goal of energy efficiency, apart from its ecological value, is also associated with the reduction of operational expenses for mobile network operators, as well as with greater customer satisfaction thanks to increased battery life. Battery and power are an area of significant challenges considering that smartphones are nowadays equipped with advanced technological network features and interfaces. These features require a lot of simultaneous power to make decisions and to transfer information between devices and networks to provide the best user experience. Furthermore, to meet the demands of increased data capacity, data rate, and to provide the best quality of service, there is a need to adopt energy-efficient architectures. The new strategies should not only focus on wireless base stations, which consumes most of the power, but it should also take into consideration the other power consumption elements for future mobile communication networks, including User Equipment (UE). In this paper, we do an overview of power consumption and improvements made so far on the networks and user equipment side and provide our proposals on how to overcome these power- European Scientific Journal, ESJ ISSN: 1857-7881 (Print) e - ISSN 1857-7431 January 2021 edition Vol.17, No.3 www.eujournal.org 316 hungry issues on the newly 5G systems.

Effective Energy Adaptive and Consumption in Wireless Sensor Network Using Distributed Source Coding and Sampling Techniques

Multimedia is the process of handling multiple medium of messages over network with high rate data services in wireless cellular area networks. Communication is the process of exchanging information form one service to another. In wireless networks are significantly growth of affecting network performance and energy consumption. The major problem is end to end delay in each node and meets the quality of services. The followings are considered for implementing wireless sensor network such as reduces the network delay, propagation delay and energy consumption. The senor node can sense the encoding value and reduce the network traffic delay using mitigation method. This paper propose a unique approach to provide simple routing services with reduced traffic delay, end to end delay network performance and to achieve better performance using Distributed Source Coding and Effective Energy Consumption methods. In this paper we use optimal early detection algorithm for improving network performance and energy consumption problem. An iterative Shannon fano and Tuker method is used for finding optimal solution of each node values. Network Simulator-3 is used for simulating network environments and setup the experiments. Our proposed method shows high data rate, good performance and low energy consumptions. The results compare with existing methodologies and performance is good.

Edge caching in blockchain empowered 6G

The sixth generation (6G) of wireless cellular networks is expected to incorporate the latest developments in network infrastructure and emerging advances in technology. In the age of 6G, edge caching technology will evolve towards intelligence, dynamics, and security. However, the security problems of edge caching, including data tampering and eavesdropping, are seldomly considered in most literatures. In this paper, we consider the two-hop edge caching where the blockchain and physical layer security technologies are adopted to prevent data from being tampered with and eavesdropped. We design blockchain-based framework to guarantee the reliability of important data such as the frequency of contents and jointly optimize content caching probability and redundancy rate to maximize the secure transmission probability. Extensive simulation shows that our optimization scheme can significantly improve the secure transmission probability of edge cache network, whether facing the threat of independent eavesdropping or joint eavesdropping.

Crowdsensing-Assisted Path Loss Estimation and Management of Dynamic Coverage in 3D Wireless Networks With Dense Small Cells

Emerging vertical applications enabled by connected devices and smart infrastructures have created an ever-increasing demand for high data rates over 5th-Generation (5G) and beyond wireless networks. Deployment of dense small cells (SCs) and millimeter wave (mmWave) communication systems have become inevitable in future wireless networks. Consequently, it is more accurate to model such networks in the 3D space due to the spatially distributed nature of the SCs, locations of the devices, radio resources and propagation environment. Accurate estimation of location-specific path loss parameters is then essential for efficient utilization of radio resources and management of dynamic coverage in 3D SC networks. In the paper, a framework for location-specific path loss estimation is developed for efficient radio resource management, based on the principle of crowdsensing together with Linear Algebra (LA) and machine learning (ML) techniques considering 2.5 GHz and 28 GHz bands. The corresponding procedure for capturing dynamic coverage of a SC base station (BS) serving to an arbitrary cluster is proposed and examined based on its 3D propagation characteristics. Results show that the accuracy of 3D channel parameter estimation using gradient descent ML techniques is superior compared to LA technique and can achieve over 98% estimation accuracy. It is shown that using the proposed process, parameters can be extrapolated for the slightly extended 3D communication distances from the cluster boundary for the worst-case locations of devices based on already estimated propagation parameters with accuracy over 74% for certain distances. Although numerical results are presented for a single amorphous 3D cell of a wireless network, the framework given in the paper can be extended to any arbitrary 3D wireless cellular network.

Optimal Power Allocation in Downlink Non-Orthogonal Multiple Access (NOMA)

Fifth generation of wireless cellular networks promise to enable better services anytime and anywhere. Non-orthogonal multiple access (NOMA) stands as a suitable multiple accessing scheme due to the ability to allow multiple users to share the same radio resource simultaneously via different domains (power, code, etc.). Through the introduced power domain, users multiplexed at the radio resource within different power levels. This paper studies power allocation in downlink NOMA, an optimization problem formulated that aims to maximize the system's sum rate. To solve the problem, a genetic algorithm based power allocation (GAPA) was proposed that uses genetic algorithm (GA) that employs heuristics to search for suitable solutions. The performance of the proposed power allocation algorithm compared with full search power allocation (FSPA) that gives an optimal performance. Results show that GAPA reaches a performance near to FSPA with lower complexity. In addition, GAPA simulated with various user paring algorithms. Channel state sorting based user pairing with GAPA achieves the best performance comparing to random user pairing algorithm and exhaustive user pairing.

An Optimal Deployment Framework for Multi-Cloud Virtualized Radio Access Networks

Virtualized radio access networks (vRAN) are emerging as a key component of wireless cellular networks, and it is therefore imperative to optimize their architecture. vRANs are decentralized systems where the Base Station (BS) functions can be split between the edge Distributed Units (DUs) and Cloud computing Units (CUs); hence they have many degrees of design freedom. We propose a framework for optimizing the number and location of CUs, the function split for each BS, and the association and routing for each DU-CU pair. We combine a linearization technique with a cutting-planes method to expedite the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">exact</i> problem solution. The goal is to minimize the network costs and balance them with the criterion of centralization, i.e., the number of functions placed at CUs. Using data-driven simulations we find that multi-CU vRANs achieve cost savings up to 28% and improve centralization by 77%, compared to single-CU vRANs. Interestingly, we see non-trivial trade-offs among centralization and cost, which can be aligned or conflicting based on the traffic and network parameters. Our work sheds light on the vRAN design problem from a new angle, highlights the importance of deploying multiple CUs, and offers a rigorous optimization tool for balancing costs and performance.

Capacity Limits of Full-Duplex Cellular Network

This paper aims to characterize the capacity limits of a wireless cellular network with a full-duplex (FD) base-station (BS) and half-duplex user terminals, in which three independent messages are communicated: the uplink message $m_1$ from the uplink user to the BS, the downlink message $m_2$ from the BS to the downlink user, and the device-to-device (D2D) message $m_3$ from the uplink user to the downlink user. From an information theoretical perspective, the overall network can be viewed as a generalization of the FD relay broadcast channel with a side message transmitted from the relay to the destination. We begin with a simpler case that involves the uplink and downlink transmissions of $(m_1,m_2)$ only, and propose an achievable rate region based on a novel strategy that uses the BS as a FD relay to facilitate the interference cancellation at the downlink user. We also prove a new converse, which is strictly tighter than the cut-set bound, and characterize the capacity region of the scalar Gaussian FD network without a D2D message to within a constant gap. This paper further studies a general setup wherein $(m_1,m_2,m_3)$ are communicated simultaneously. To account for the D2D message, we incorporate Marton's broadcast coding into the previous scheme to obtain a larger achievable rate region than the existing ones in the literature. We also improve the cut-set bound by means of genie and show that by using one of the two simple rate-splitting schemes, the capacity region of the scalar Gaussian FD network with a D2D message can already be reached to within a constant gap. Finally, a generalization to the vector Gaussian channel case is discussed. Simulation results demonstrate the advantage of using the BS as relay in enhancing the throughput of the FD cellular network.

Managing the Interference for Down-Link in LTE Using Fractional Frequency Reuse

Long Term Evolution has developed a new radio technology called femtocell or Femto Base station, which is well-suited to improve cellular network capacity and mobile coverage to indoor user's areas. Providing additional capacity and coverage expansion through FBSs could lead to large interference in a cellular radio communication network. In this paper, we proposed an efficient resource allocation scheme based on Fraction Frequency Reuse (FFR) for interference mitigation, where the entire spectrum is shared among network entities. FFR mechanism aims to reduce co-tier and cross-tier downlink interferences by allocating non-overlapping sets of bands to the user equipment at different geographic locations. The main purpose of this work is to compare two main types of FFR schemes, respectively, Strict FFR and Soft Frequency Reuse with the proposed scheme. The three types of FFR schemes were explained and evaluated with Monte-Carlo simulation based on some performance metrics, namely, sum-rate, spectral efficiency, and outage probability. Simulation results showed that the impacts of the proposed scheme are significantly high in comparison with two other methods. The proposed scheme proved to enhance spectral efficiency, reduced the outage probability, and increased the sum rate for all the users.

An overview of massive MIMO localization techniques in wireless cellular networks: Recent advances and outlook

The massive multiple-input-multiple-output (mMIMO) antenna systems are well known for their capability to achieve high spectral efficiency in wireless communication systems thanks to millimeter waves (mmWaves) which allow a large number of antennas to be deployed at the base stations (BSs). Aside from communication-based services, mMIMO BSs are presently being exploited for location estimation of user equipment due to their high angular resolution, low-cost implementation, and excellent performance in the indoor and clutter urban environments where line-of-sight may not be available. Although various mMIMO localization solutions have been proposed, there are still pressing issues yet to be resolved. To this end, this article first provides an overview of recent and relevant state-of-the-art survey papers on localization. Further to this, we provide various foundational background concepts based on the existing localization techniques applicable to mMIMO localization systems. Furthermore, we discuss various methods under each technique and we also identify some critical factors to be considered in a practical radio environment. Based on these techniques, we provide a comprehensive review of recent works on mMIMO localization. Finally, we suggest key research directions to be addressed in the future and also we discuss key enabling technologies that will enhance the performance of localization systems in 6G communication networks.

A Distributed Power Control Algorithm for Energy Efficiency Maximization in Wireless Cellular Networks

In this paper, we propose a distributed power control algorithm for addressing the global energy efficiency (GEE) maximization problem subject to satisfying a minimum target SINR for all user equipments (UEs) in wireless cellular networks. We state the problem as a multi-objective optimization problem which targets minimizing total power consumption and maximizing total throughput, simultaneously, while a minimum target SINR is guaranteed for all UEs. We propose an iterative scheme executed in the UEs to control their transmit power using individual channel state information (CSI) such that the GEE is maximized in a distributed manner. We prove the convergence of the proposed iterative algorithm to its corresponding unique fixed point also shown by our numerical results. Additionally, simulation results demonstrate that our proposed scheme outperforms other algorithms in the literature and performs like the centralized algorithm executed in the base station and maximizes the GEE using the global CSI.

Design of a Four-Element Array Antenna for 5G Cellular Wireless Networks

This paper proposes the design of a four-element array planar antenna based on a single antenna that combines the Double Positive (DPS) and Epsilon Negative (ENG) materials. The single antenna consists of a microstrip segment (which is equivalent to a DPS material) connected to a grounded microstrip segment (which is equivalent to an ENG material). T-Junction power dividers with one-input and two-output ports are used for feeding the two-element and the four-element array antennas. The proposed array antenna is designed to operate optimally at 30GHz frequency under Finite Element Method (FEM)-based simulation. The obtained simulation results show that the proposed array antennas have good radiation performances, in which the four-element array antenna has a -10dB bandwidth ranging from 28.7 to 33.4GHz and 12.9dBi gain.