Number Of Resource Blocks Research Articles

Towards 5G new radio sidelink communications: A versatile link-level simulator and performance evaluation

Sidelink in cellular networks enables direct exchange of data packets between devices without the need for network infrastructure, resulting in various benefits, including communication in out-of-coverage areas and possible decrease in latency by a considerable extent. Thus, sidelink is a favorable choice for applications like public safety communications and Vehicle-to-Everything (V2X) communications. As 4G Long Term Evolution (LTE) advanced to 5G New Radio (NR) under the Third Generation Partnership Project (3GPP), several new features were introduced to sidelink, such as two-stage Sidelink Control Informations (SCIs), data and control multiplexing, and feedback-based Hybrid Automatic Repeat Request (HARQ) with a configurable maximum number of transmissions. To conduct extensive NR sidelink link-level evaluations, a comprehensive simulation platform is essential. In this paper, we introduce the first publicly accessible 5G NR Link-Level Simulator (LLS) that supports major 5G NR sidelink features and complies with the 3GPP standards. This MATLAB-based simulator allows for flexible control over various Physical Layer (PHY) configurations, facilitating customized simulations on algorithm development and performance evaluations. We discuss the simulator’s structure and the sidelink features implemented in detail and evaluate the 5G NR sidelink performance using the developed simulator. Our simulation results indicate that the Block Error Rate (BLER) curves are insensitive to error-prone 2nd-stage Sidelink Control Information (SCI2) and number of Resource Blocks (RBs) allocated; however, the sidelink communication range is sensitive to the deployment environment. We also highlight the need for a careful choice of numerology, device power class and HARQ configuration to balance performance metrics for a variety of services based on 5G NR sidelink deployment scenarios.

EETSQ: Energy Efficient Task Scheduling based on QoS Parameters in Cloud Computing Environment

Now a day, energy consumption is the big challenge in heterogeneous cloud computing environment that needs to be considered. Cloud service provider also needs to satisfy customer’s Quality of Service (QoS) for better utilization. An energy efficient task scheduling based on QoS parameter has been proposed to address above said challenge. Firsty, all the incoming tasks are categorized into four classes based on some special attributes and prioritize according to importance of the classes. Secondly, Physical Machines (PMs) type confirmation list is selected based on the number of resource blocks and then select one PM that has maximum QoS value. All the Virtual Machines (VMs) on selected PM are prioritized according to their weight. Experimental evaluation done on CloudSim shows the effectiveness and efficiency of proposed approach.

QoS-Aware User Scheduling in Crowded XL-MIMO Systems Under Non-Stationary Multi-State LoS/NLoS Channels

Ensuring that the quality-of-service (QoS) requirements are satisfied in wireless communications systems with high user density is challenging due to the limitations on the transmit power budget and the number of resource blocks. In this paper, we propose a QoS-aware joint user scheduling and power allocation technique to enhance the number of served users in the downlink of crowded extra-large scale massive multiple-input multiple-output (XL-MIMO) with minimum QoS requirements guarantee. The proposed technique is constituted by two sequential procedures: the clique search-based scheduling (CBS) algorithm for user scheduling followed by optimal power allocation with transmit power budget and minimum achievable rate per user constraints.We propose a generalized non-stationary multi-state channel model based on spherical wave propagation assuming that users under line-of-sight (LoS) and non-LoS (NLoS) transmission coexist in the same communication cell. This is done to accurately evaluate the proposed technique in realistic XL-MIMO scenarios. Numerical results reveal that the proposed CBS algorithm provides fair coverage over the whole cell area, achieving remarkable numbers of scheduled users with satisfied QoS requirements when users under the LoS and NLoS channel states coexist in the communication cell.

Meta-Scheduling Framework With Cooperative Learning Toward Beyond 5G

In this paper, we propose a novel meta-scheduling framework with cooperative learning that fully exploits a functional split structure of the base station (BS) consisting of a central unit (CU) and digital units (DUs). To this end, we first design a meta-scheduling policy structure to find a scheduling strategy that can be applied to any BS regardless of BS-specific characteristics such as the number of users, various quality-of-service requirements, and the number of resource blocks. In the proposed framework, the CU only needs to manage objective-specific meta-scheduling policies in a centralized manner while each DU performs scheduling in a decentralized manner by simply using the policy at the CU without any responsibility to manage or train policies. Besides, the policies at the CU can be cooperatively trained using the experiences obtained from all DUs. Therefore, the proposed framework not only provides computational efficiency but also supports network scalability. We show via experiments that the proposed meta-scheduling framework achieves competitive performances compared with the near-optimal conventional schedulers tailored to each BS even though it manages and exploits only one meta-scheduling policy for each objective. Furthermore, our meta-scheduling framework effectively adapts to the change of BS-specific characteristics.

Analysis on The Effect of Channel Bandwidth Occupying in LTE Frequency Band on Throughput

The maximum channel capacity of a 4G LTE network will be directly correlated to the channel bandwidth that occupies a certain radio frequency on that network. The number of Resource Blocks (RB), subcarriers, and Resource Elements (RE) as channel resources available to serve users concurrently will depend on the bandwidth channel sizes. Mobile service providers in Indonesia provide scalable channel bandwidth LTE 4G networks on a variety of frequency bands, including adjacent and non-adjacent bands. In this study, it was examined how to channel bandwidth, which changes at 10MHz, 15MHz, and 20MHz, affects throughput to give user equipment the best possible performance (UE). This study makes use of actual measurement data from installed and active eNodeB or cells obtained via the drive test approach. According to the test, each channel's maximum throughput varies, however, there is no linear relationship found between channel bandwidth expansion and throughput. The 20MHz channel bandwidth, which is located in the 2300MHz frequency band, has a maximum throughput value of 64666.80 kbps.

Load Based Carrier Aggregation Algorithm for LTE Advanced

Long Term Evolution (LTE) supports transmission bandwidth upto 20MHz. Nowadays the multimedia rich applications connects billions of users worldwide. These services demands more number of Resource Blocks (RBs) to satisfy the Quality of Service (QoS) requirements and that can increase the data traffic in multifold. This crunch has led the Mobile Network Operators (MNOs) to increase the transmission bandwidth in order to fulfil the QoS requirements of the different services. In Release10, Third Generation Partnership Project (3GPP) provides a provision for MNOs to use Carrier Aggregation (CA) scheme in LTE-Advanced to aggregate upto five Components Carriers (CCs) of existing LTE carriers at the eNB to increase the transmission bandwidth upto 100MHz. Further, this scheme allows a User Equipment (UE) to transmit and receive data packets simultaneously on multiple CCs based on UE capability to meet the service requirements. However, the CC selection and efficient RBs utilization plays a vital role to optimize the system performance. Hence, in this paper using QualNet 8.2 network simulator the Load Based Carrier Aggregation Algorithm (LBCAA) is proposed for LTE-Advanced to aggregate the CCs of the existing LTE carriers at the eNB based on cell load in order to increase the transmission bandwidth to handle the data traffic growth. The simulations results illustrated that the proposed LBCAA for LTE-Advanced outperforms in the achieved average unicast received throughput, average unicast end-to-end delay and jitter as compared to LTE.

Toward Efficient Hierarchical Federated Learning Design Over Multi-Hop Wireless Communications Networks

Federated learning (FL) has recently received considerable attention and is becoming a popular machine learning (ML) framework that allows clients to train machine learning models in a decentralized fashion without sharing any private dataset. In the FL framework, data for learning tasks are acquired and processed locally at the edge node, and only the updated ML parameters are transmitted to the central server for aggregation. However, because local FL parameters and the global FL model are transmitted over wireless links, wireless network performance will affect FL training performance. In particular, the number of resource blocks is limited; thus, the number of devices participating in FL is limited. Furthermore, edge nodes often have substantial constraints on their resources, such as memory, computation power, communication, and energy, severely limiting their capability to train large models locally. This paper proposes a two-hop communication protocol with a dynamic resource allocation strategy to investigate the possibility of bandwidth allocation from a limited network resource to the maximum number of clients participating in FL. In particular, we utilize an ordinary hierarchical FL with an adaptive grouping mechanism to select participating clients and elect a leader for each group based on its capability to upload the aggregated parameters to the central server. Our experimental results demonstrate that the proposed solution outperforms the baseline algorithm in terms of communication cost and model accuracy.

A Comparative Analysis of Wi-Fi Offloading and Cooperation in Small-Cell Network

Small cells deliver cost-effective capacity and coverage enhancement in a cellular network. In this work, we present the interplay of two technologies, namely Wi-Fi offloading and small-cell cooperation that help in achieving this goal. Both these technologies are also being considered for 5G and B5G (Beyond 5G). We simultaneously consider Wi-Fi offloading and small-cell cooperation to maximize average user throughput in the small-cell network. We propose two heuristic methods, namely Sequential Cooperative Rate Enhancement (SCRE) and Sequential Offloading Rate Enhancement (SORE) to demonstrate cooperation and Wi-Fi offloading, respectively. SCRE is based on cooperative communication in which a user data rate requirement is satisfied through association with multiple small-cell base stations (SBSs). However, SORE is based on Wi-Fi offloading, in which users are offloaded to the nearest Wi-Fi Access Point and use its leftover capacity when they are unable to satisfy their rate constraint from a single SBS. Moreover, we propose an algorithm to switch between the two schemes (cooperation and Wi-Fi offloading) to ensure maximum average user throughput in the network. This is called the Switching between Cooperation and Offloading (SCO) algorithm and it switches depending upon the network conditions. We analyze these algorithms under varying requirements of rate threshold, number of resource blocks and user density in the network. The results indicate that SCRE is more beneficial for a sparse network where it also delivers relatively higher average data rates to cell-edge users. On the other hand, SORE is more advantageous in a dense network provided sufficient leftover Wi-Fi capacity is available and more users are present in the Wi-Fi coverage area.

Peal factor of signals of 5G mobile service systems

This article discusses the possible formats of signals of 5G mobile communication networks (NR, IMT-2020): configurations of the number of resource blocks and frequency shifts of subcarriers. modulation schemes, organizations of the physical level, as well as the broadband signals of these networks and, as a result, the need for introducing a margin on the linearity of the transceiver’s paths to eliminate distortion or the manifestation of blocking effects when the signal interferes with third-party means. We analyze the characteristics of the dynamic range of the signals from IMT-2020 ground mobile systems and make a conclusion about the noise-like signals. To find the ratio of the maximum amplitude to its average value and a given ratio not exceeded with a given probability, the Matlab mathematical models were used. We infer that the law of probability distribution of the module of the instantaneous amplitude of the 5G signals corresponds to the distribution characteristic of narrow-band radio noise. Based on the study, the peak factor of the signal of the IMT-2020 ground mobile systems for various variations is obtained and a sufficient level of power reserve is provided to ensure, with high probability, the transmission of the 5G signals through radio paths, eliminating signal distortion. The results of this study were applied in the examination of the electromagnetic compatibility of radio electronic devices of cellular mobile communications with existing and promising electronic means of civil and special purposes and in the study of the protection of ground satellite stations from the effects of radio electronic means of IMT-2020 cellular mobile telecommunication networks located at border territories.

Research of the total spectral density of signals in the LTE up-link

This article is devoted to the analysis of the total spectral radiation density of LTE subscriber terminals. The LTE network uses orthogonal frequency division multiple access (OFDMA) technology for downlink communications, and multiple access technology with single-carrier frequency division multiple access (SC-FDMA) for uplink communications. In a downlink, the occupied radio frequency band is determined by the number of resource blocks and the size of the step of placement of subcarrier oscillations in the frequency domain. Features of the technologies used for organizing multiple access in LTE networks determine the nature of the spectral density of the total radio signal. Thus, in a downlink, the spectral density approaches uniformity, since the power distribution in the spectral region does not depend on the number and location of resource blocks allocated to the subscriber, and also does not depend on the territorial location of the subscriber itself. For an uplink, the determination of spectral density characteristics is not so unambiguous, since they depend on a number of factors (traffic parameters, the nature of radio conditions, etc.). Тo conduct a detailed analysis of the spectral radiation density of a set of LTE subscriber terminals, a scheme of the measuring unit was developed and experimental studies of the spectral density were conducted on the basis of the BSUIR research laboratory. The article presents spectrograms of a set of signals in the uplink of the LTE communication network, obtained for different time intervals and different places of observation. The conclusion is made about the possibility of using an equivalent uniform spectral density to describe interference effects from groupings of subscriber terminals of LTE communication networks.

Physical Layer Detection of Malicious Relays in LTE-A Network Using Unsupervised Learning

For Long Term Evolution Advanced (LTE-A) network, although there exist many studies that focus on improving the performance with relays, security issues are often neglected. Due to the broadcast nature of wireless channels, relay nodes in LTE-A network may act maliciously, affect communication, reduce quality, and cause delays. Recently, physical (PHY) layer security has attracted researchers to provide secure communication and data privacy. In this study, we propose using unsupervised learning approach at the destination node to detect malicious relay attacks in cooperative LTE-A network based on received source signal in the PHY layer. Outlier detection algorithms such as one class support vector machine (OCSVM), local outlier factor (LOF) and isolation forest ( $i$ Forest) are applied to detect various malicious relay behaviors such as garbling, regenerative, and false data injection type attacks. As input to these algorithms, feature vectors are constructed by using amplitude, phase, and relative phase information of modulated baseband symbols. The performance of the outlier detectors are evaluated with respect to precision, accuracy, and under the area curve (AUC) measures under changing signal-to-noise ratio (SNR) levels, different modulation types, allocated number of resource blocks (RBs), and varying data size. The results demonstrate the effectiveness of our proposed outlier detection approach for detecting malicious relays in the LTE-A network. Accuracy and precision of the algorithms are observed to be above 90% for 10 dB and larger SNR levels for the relay attack scenarios considered here. AUC values for all algorithms for all SNR levels is also above 0.9 for the attack detection cases, and the performance of the LOF algorithm with 0.95 and above AUC values is superior to other algorithms. The results verify the contribution of this study, which is the demonstration of the effectiveness of one class outlier detection approaches for detecting malicious relays in the LTE-A network.

On the Impact of Satellite Communications Over Mobile Networks: An Experimental Analysis

Future telecommunication systems are expected to co-exist with different backhauling nodes such as terrestrial or satellite systems. Satellite connectivity can add flexibility to backhauling networks and provide an alternative route for transmission. This paper presents experimental comparisons of satellite and terrestrial cellular networks and evaluates their performances in terms of different Key Performance Indicators (KPIs) including Channel Quality Index (CQI), Modulation Coding Scheme (MCS) index, Downlink throughput, Frame Utilization (FU) and number of Resource Block (RB) utilization ratios. Our experimental satellite network system uses a real satellite backhaul deployment and works in Ka band (with two specific sub-bands on 19 Ghz in downlink and 29 Ghz in uplink). As a benchmark, we compare our system with live terrestrial network in which backhaul connection is cellular backhaul. Our experiments reveal three main observations: First observation is that there exists FU and number of RB utilization problems in the satellite link even though there exists a single test user equipment (UE) with high CQI and MCS index values. Second observation is that in satellite link relatively low number of Protocol Data Units (PDUs) are generated at Radio Link Controller (RLC) layer compared to the Packet Data Convergence Control (PDCP) layer. Finally, our third observation concludes that the excessive existence of PDCP PDUs can be due to existence of General Packet Radio Service (GPRS) Tunneling Protocol-User Plane (GTP-U) accelerator where an optimal balance between the caching size and the number of UEs using satellite eNodeB is needed. For this reason, our experimental results reveal the existence of a trade-off between the supported number of users on satellite link and the GTP-U acceleration rate.

Sector-Based Radio Resource Allocation (SBRRA) Algorithm for Better Quality of Service and Experience in Device-to-Device (D2D) Communication

The mounting content sharing among users has resulted in a considerable rise in wireless data traffic, pressurizing the cellular networks to undergo a suitable upheaval. A competent technology of the fifth-generation networks (5G) for efficiently supporting proximity-based applications is Device-to-Device (D2D) communication, underlaying cellular networks. Significant advances have been made till date, for allocating resources to D2D users in cellular networks, such that sharing of spectral resources between cellular and D2D users is carried out in a coordinated manner. In this paper, a sector-based radio resource allocation (SBRRA) algorithm for resource block allocation to D2D pairs has been proposed, where the number of resource blocks (RBs) is allocated to each D2D pair in an adaptive manner, based on the demanded application by each pair. Different applications demand a varying number of RBs, in accordance with their priority. This algorithm focusses on the use of sectored antennas at the base station, for a better performance and low complexity. Extensive simulations are carried out, considering real-time scenario, for ensuring satisfactory Quality of Service (QoS) and Quality of Experience (QoE) by the users. The efficiency of the proposed scheme is proved by comparing it with the RB allocation using Hidden Markov Model (HMM).

Self-Organized Resource Allocation for Femtocell Network to Mitigate Downlink Interference

In this paper, we consider the femto users and their mutual interference as graph elements, nodes and weighted edges, respectively. The total bandwidth is divided into a number of resource blocks (RBs) and these are assigned to the femto user equipment (FUEs) using a graph coloring algorithm. In addition, resources blocks are assigned to the femto users to avoid inter-cell interference. The proposed scheme is compared with the traditional scheduling schemes in terms of throughput and fairness and performance improvement is achieved by exploiting the graph coloring scheme.

Efficient Resource Scheduling by Exploiting Relay Cache for Cellular Networks

In relay-enhanced cellular systems, throughput of User Equipment (UE) is constrained by the bottleneck of the two-hop link, backhaul link (or the first hop link), and access link (the second hop link). To maximize the throughput, resource allocation should be coordinated between these two hops. A common resource scheduling algorithm, Adaptive Distributed Proportional Fair, only ensures that the throughput of the first hop is greater than or equal to that of the second hop. But it cannot guarantee a good balance of the throughput and fairness between the two hops. In this paper, we propose a Two-Hop Balanced Distributed Scheduling (TBS) algorithm by exploiting relay cache for non-real-time data traffic. The evolved Node Basestation (eNB) adaptively adjusts the number of Resource Blocks (RBs) allocated to the backhaul link and direct links based on the cache information of relays. Each relay allocates RBs for relay UEs based on the size of the relay UE’s Transport Block. We also design a relay UE’s ACK feedback mechanism to update the data at relay cache. Simulation results show that the proposed TBS can effectively improve resource utilization and achieve a good trade-off between system throughput and fairness by balancing the throughput of backhaul and access link.

Statistically controlled opportunistic resource block sharing for femto cell networks

In this paper, we propose an efficient interference management technique which controls the number of resource blocks (or subcarriers) shared with other cells based on statistical interference levels among cells. The proposed technique tries to maximize average throughput of a femto cell user under a constraint on non-real time control of a femto cell network while guaranteeing a target throughput value of a macro cell user. In our proposed scheme, femto cells opportunistically use resource blocks allocated to other cellsif the required average user throughputis not attained with the primarily allocated resource blocks. The proposed method is similar to the underlay approach in cognitive radio systems, but resource block sharing among cells is statistically controlled. For the statistical control, a femto cell sever constructs a table storing average mutual interference among cells and periodically updates the table. This statistical approach fully satisfies the constraint of non-real time control for femto cell networks. Our simulation results show that the proposed scheme achieves higher average femto user throughput than conventional frequency reuse schemes for time varying number of users.