Frequency Resources Research Articles

BigTrustScheduling: Trust-aware big data task scheduling approach in cloud computing environments

Big data task scheduling in cloud computing environments has gained considerable attention in the past few years, due to the exponential growth in the number of businesses that are relying on cloud-based infrastructure as a backbone for big data storage and analytics. The main challenge in scheduling big data services in cloud-based environments is to guarantee minimal makespan while minimizing at the same time the amount of utilized resources. Several approaches have been proposed in an attempt to overcome this challenge. The main limitation of these approaches stems from the fact that they overlook the trust levels of the Virtual Machines (VMs), thus risking to endanger the overall Quality of Service (QoS) of the big data analytic process, which includes not only heartbeat frequency ratio and resource consumption, but also security challenges such as intrusion detection, access control, authentication, etc. To overcome this limitation, we propose in this work a trust-aware scheduling solution called BigTrustScheduling that consists of three stages: VMs’ trust level computation, tasks priority level determination, and trust-aware scheduling. Experiments conducted on a real Hadoop cluster environment using real-world datasets collected from the Google Cloud Platform pricing and Bitbrains task and resource requirements show that our solution minimizes the makespan by 59% compared to the Shortest Job First (SJF), by 48% compared to the Round Robin (RR), and by 40% compared to the improved Particle Swarm Optimization (PSO) approaches in the presence of untrusted VMs. Moreover, our solution decreases the monetary cost by 58% compared to the SJF, by 47% compared to the RR, and by 38% compared to the improved PSO in the presence of untrusted VMs. The results in this work can be applicable to other problems. This would be possible through tuning the corresponding metrics in the formulation of the problem and solution, as will as in the experimental environment. In fact, the trust model can be extended to other environments including cloud computing, IoT, parallel computing, etc.

Prediction and Communication Co-Design for Ultra-Reliable and Low-Latency Communications

Ultra-reliable and low-latency communications (URLLC) are considered as one of three new application scenarios in the fifth generation cellular networks. In this work, we aim to reduce the user experienced delay through prediction and communication co-design, where each mobile device predicts its future states and sends them to a data center in advance. Since predictions are not error-free, we consider prediction errors and packet losses in communications when evaluating the reliability of the system. Then, we formulate an optimization problem that maximizes the number of URLLC services supported by the system by optimizing time and frequency resources and the prediction horizon. Simulation results verify the effectiveness of the proposed method, and show that the tradeoff between user experienced delay and reliability can be improved significantly via prediction and communication co-design. Furthermore, we carried out an experiment on the remote control in a virtual factory, and validated our concept on prediction and communication co-design with the practical mobility data generated by a real tactile device.

Interference Avoidance Using TDMA-Beamforming in Location Aware Small Cell Systems

It is ascertained that the current communication systems will not be able to support the future network demands due to the increasing traffic, limitation of frequency resources, and high level of interference. Recently, beamforming techniques have been introduced to reduce the interference by redirecting the transmission towards the desired users only. While such beamforming enables better interference mitigation and improved network performance, the concerns on its effectiveness in dense deployment environments are arising. In this paper, the prospect of interference avoidance in location aware small cell environments using time division multiple access (TDMA) and beamforming is studied. The interference is reduced by identifying the aggressor small cell and transmit the beams towards the desired users at different times. Simulation results show that the proposed scheme is able to enhance the signal to interference plus noise ratio (SINR) by approximately 18 dB, enhance the user throughput by about 10 Mbps in comparison to small cell on/off control scheme with a discovery signal (SCon/off-DS), and improve the fairness index to about 95% in comparison to the baseline scheme. It is believed that the presented results promote the proposed scheme as an efficient interference management paradigm for the fifth generation (5G) communication systems.

Low Complexity User Selection and Power Allocation for Uplink NOMA Beamforming Systems

In this paper, we develop user selection and power allocation methods for NOMA systems equipped with multi-antenna to enhance the sum capacity of the uplink. The system has the base station (BS) with $$ N $$ antenna supporting 2N users in the same spectrum resource simultaneously, and successive interference cancellation (SIC) is applied at the BS. Because the superposition of multiple users in transmission within the same frequency resource block leads to the interference among users, we derive a user set selection algorithm and a suboptimal power control to mitigate the interference effect and to maximize the sum capacity. The user set selection algorithm is first applied by comparing the designed indicator which balances the factors affecting the sum capacity of the uplink. Second, the derived suboptimal power assignment algorithm is utilized with power control factors where four cases are evaluated. The simulation results show that the proposed schemes can significantly improve the sum capacity than the existing methods.

Network slicing - enabled RAN management for 5G: Cross layer control based on SDN and SDR

Having already entered the initial phase of the 5th generation networks (5G) era, the network ecosystems have already begun comprising a plethora of coexisting 3GPP and non-3GGP Radio Access Technologies (RATs). Deployment scenarios envision a multi-layer use of macro, micro and femto-cells, where multi-mode end devices, supporting different applications, are served by heterogeneous access technologies. At the same time, this heterogeneous environment results in an abstract pool of resources, moving away from the traditional cell concept and exposing the network administrator with the collective resources in time, frequency, and space. An imperative need is thus created, to obtain an overview of the network and radio conditions in order to respond in an optimal way. The concepts of Software Defined Networking (SDN) and Software Defined Radio (SDR), when applied in a coordinated and sophisticated manner, may prove of utmost importance towards addressing the aforementioned challenges. The concept of network slicing -that enables the creation of several virtual networks with diverse characteristics, on top of common infrastructure- further reinforces the flexibility and dynamicity of the network. To this end, we present and evaluate a Cross Layer Controller (CLC), which acts on top of well-established SDN and SDR technologies, and monitors in real-time the conditions in the radio environment, as well as the transport network traffic, in a unified way; based on this dynamic input, CLC enforces sophisticated, end-to-end resource allocation policies and pairing mechanisms between network slices from different network segments, highlighting thus, the feature of cross layer resource management and dynamic adaptation. The experimentation results demonstrate the considerable gains acquired from the proposed solution.

Joint mode selection and power control for D2D underlaid cellular networks

Device-to-Device (D2D) communication is a new paradigm proposed in cellular networks, which promises several benefits to the network providers as well as end users. Firstly, it improves spectral efficiency (SE) of cellular networks by re-using the same frequency resources occupied by cellular users. In fact, mobile users cellular networks use high data rate services (e.g., video sharing, gaming, proximity aware social networking etc.), in which they could potentially be in range for direct communications (i.e., D2D). Secondly, D2D can enhance energy efficiency (EE), since the mobile terminals use less transmission power when communicating directly between each other. Thirdly, D2D communication can also reduce communication delay and increase network throughput, due to its short distance communication. This paper investigates the future challenges in order to improve the network throughput by proposing a joint mode selection (MS) and centralized power control (PC), which maximizes the sum rate of D2D links. To keep the interference under control, coverage probabilities are studied in this paper for both cellular and D2D users, while a signal-to-interference-plus-noise ratio (SINR) threshold is maintained for more than one CUE. Based on the latter assumption, this paper provides two sufficient conditions to ensure the existence of the Pareto optimal power, that should be verified by both Cellular User Equipment (CUE) and D2D User Equipment (DUE) during the MS process. The mathematical expressions of these two sufficient conditions are proved. Then, the PC approach is deduced based on two derived sufficient conditions. Two joint MS and PC algorithms are proposed in this paper and compared in terms of coverage probability and total power consumption with a conventional algorithm for both CUE and DUE.

Pilot Contamination Mitigation for Wideband Massive MIMO Systems

This paper proposes a novel joint channel estimation and beamforming approach for multicell wideband massive multiple input multiple output (MIMO) systems. With the proposed channel estimation and beamforming approach, we determine the number of cells $N_{c}$ that can utilize the same time and frequency resource while mitigating the effect of pilot contamination. The proposed approach exploits the multipath characteristics of wideband channels. Specifically, when the channel has a maximum of $L$ uncorrelated multipath taps (or correlated multipath taps satisfying modest criteria which is valid in most practical scenarios), it is shown that $N_{c}=L$ cells can estimate the channels of their user equipments (UEs) and perform beamforming while mitigating the effect of pilot contamination. The proposed approach can also be applied for general correlated multipath taps, and achieves good performance for this scenario as well. In a typical long term evolution (LTE) channel environment having delay spread $T_{d}=4.69\,\,\mu \text{s}$ and channel bandwidth $B=5$ MHz, we have found that $L=36$ cells can use this band. In practice, $T_{d}$ is constant for a particular environment and carrier frequency, and hence $L$ increases as the bandwidth increases. All the analytical expressions have been validated, and the superiority of the proposed design over the existing ones is demonstrated using extensive numerical simulations both for correlated and uncorrelated channels. The proposed channel estimation and beamforming design is linear and simple to implement.

PSU17 ECONOMIC ANALYSIS OF SUGAMMADEX FOR REVERSAL OF NEUROMUSCULAR BLOCKADE IN LAPAROSCOPIC SURGERY IN CHINA

Neuromuscular blockade and artificial pneumoperitoneum (AP) are important factors to ensure general anesthesia laparoscopic surgery successful. However, residual neuromuscular blockade (rNMB) and AP can lead many potential complications, such as airway obstruction, hypoxemia, respiratory failure, muscular weakness, nausea / vomit, and shoulder pain. The aim of this study was to estimate cost-effectiveness analysis of sugammadex versus neostigmine for reversal of neuromuscular blockade in laparoscopic surgery in China. A decision tree model was developed in Microsoft Excel based on a time horizon of laparoscopic surgery related hospitalization duration. 1,000 patients were simulated by using sugammadex or neostigmine within the model. The model outcome included rNMB / AP related complications frequency and healthcare resource utilization. Clinical efficacy, safety data and cost data were collected from the published literature and 30 physicians’ interview. The total complications frequency occurred in sugammadex group were less than in the neostigmine group, 621 times versus 1294 times, respectively. Although the sugammadex group was associated with a higher medication cost, the costs related to complications treatment, hospitalization and adverse event in sugammadex group were lower than those in neostigmine group. When compared with neostigmine group, sugammadex group costs a total ¥128.56 more to avoid one rNMB / AP related complication. In comparison, the weighted average cost of each rNMB / AP related complications was ¥932.14. One way sensitivity analysis confirmed the robustness of the model results by varying up or down 10% for all model parameters. This economic analysis indicated that, compared with neostigmine group, sugammadex group patients will have slightly higher overall costs but achieve better clinical outcomes by avoiding 674 times of rNMB / AP related complications. This evidence can be used to support clinical decision makers to make informed decisions for treating individual patient to achieve overall better patient outcomes.

Research on millimeter wave spectrum planning for 5G

In order to allocate reasonable frequency resources in millimeter wave band for 5th-Generation (5G), this paper summarizes the position and consideration of USA and China. It analyses the feasibility of sharing and compatibility in 24.25-27.5GHz, 66-71GHz, 81-86GHz with Monte-Carlo simulation. There is a high possibility to allocate 24.75-27.5GHz, 66-71 GHz and 81-86 GHz to 5G in ITU and China. But the commercial deployment in millimeter wave in China will be delayed 1-2 years because of industry bottleneck.

Technology Support for Smart Computational Grid (SCG) in Future Wireless Systems

The communication grid is an emerging infrastructure that will fundamentally change the way we think – and use – computing. Communication grid is used by analogy with the electric power grid, as an infrastructure that provides pervasive access to electricity. Like the computer and a small number of other advances had a dramatic impact on human capabilities and utilization of the scarce frequency resource, it is believed that allowing all components of our information technology infrastructure – computational capabilities, databases, sensors, and people – to be shared flexibly as true collaborative tools, the Smart Computational Grid (SCG) will have a similar transforming effect, allowing new classes of applications to emerge. Improvement in spectrum usage achieved by CR technology and associated collaborative computations on white spaces. Every spectrum hole includes several channels. Implementing collaborative algorithms over the channels help track changing environment parameters and managed to achieve smooth handoffs, which is maximized to offer services ranging from low-data-rate non-rea-time applications to high-speed real-time multimedia applications. With virtualization, the heterogeneous wireless access networks complement each other to deliver maximal signal strength, wider coverage, efficient data rate, low latency and reduced loss rate. Keywords: computation, detection, grid, sensing, virtualization DOI : 10.7176/CEIS/10-7-04 Publication date: November 30th 2019

METHOD OF FORECASTING THE CONDITION OF RADIO-ELECTRONIC SITUATION OF MULTIPLE SYSTEMS IN THE CONDITIONS OF UNCERTAINTY

The task of forecasting future values of the time series based on its previous values is the basis for planning in the economy, trade, energy and technical fields. Forecasting of a radio-electronic situation in the conditions of shortage of radio-frequency resource is a very important component of modern high-tech military conflicts, the transport basis of which are multi-antenna radio-emitting means. For this purpose, an analysis of the known methods of forecasting the radio-electronic situation is carried out in that article. It is established that nowadays there are many models of time series prediction, namely: regression and autoregressive models, neural network models, exponential smoothing models, Markov-based models, classification models, etc. Based on the above analysis, it is found that the most appropriate for use in the prediction problems of the electronic environment of multi-antenna communication systems are time series prediction methods, which are based on autoregressive models. The article proposes a technique for predicting the condition of the radio-electronic environment, which allows to increase the noise immunity of communication systems in the conditions of deliberate interference and the unsteady nature of the predicted process, in order to ensure electromagnetic compatibility and increase the efficiency of use of radio frequency resource by complexes. To solve the scientific problem, we use the general scientific methods of analysis and synthesis of complex technical systems, the theory of noise immunity of radio engineering systems and methods of mathematical modeling. It is advisable to use this technique while assessing the electronic environment and identifying measures to enhance the security of communications systems. The calculations show that the use of this method allows to reduce the error of the forecast by an average of 20%. It is advisable to practically implement the proposed methodology while developing software for programmable radio stations.

Dynamic spectrum refarming for GERAN/EUTRAN considering GERAN voice traffic

This research article has been conducted for the efficient use of frequency spectrum in multi-RAT cellular network using dynamic spectrum refarming (DSR). For this purpose, two overlapping networks, GERAN and EUTRAN, and their voice and data traffic statistics are taken into consideration. Our investigation of hourly traffic changes in the voice service in the GERAN and the data service in the EUTRAN (which are the dominant services of each of these networks), indicates that these changes are approximately orthogonal. This issue is the main motivation for use of DSR methods, including DSR without inband/guardband (I/G) overlay and DSR with I/G overlay, for efficient assignment of frequency resources to GERAN and EUTRAN. In this paper, the main focus is on the process of performing DSR with I/G overlay in a real network and its challenges. For this purpose, we used a nonlinear autoregressive neural network to predict the traffic changes of voice service in the GERAN. By this method, the prediction error is less than 6.5% in the peak hours. Also, a method for efficient use of GERAN and EUTRAN carrier numbers (ARFCN and EARFCN, respectively) has been proposed to reduce the mutual interference in DSR with I/G overlay. The results show the significant impact of the DSR with I/G overlay on increasing the EUTRAN average bit rate compared to the classic spectrum refarming method (168% in downlink and 146% in uplink).

Analysis of frequency resource for FHSS mode

Introduction: When the radio frequency spectrum is as busy as it is today, it is especially important to ensure effective functioningof radio systems under various signal and interfering conditions. One of the research fields is radio frequency resource management.Purpose: Developing a system of proposals for choosing a frequency resource for radio system operation in the mode of frequencyhoppingspread spectrum (FHSS). Results: On the basis of the developed analytical apparatus, we have specified the conditions forpreliminary testing of working frequencies in the direct response mode in FHSS radio channels. Practical conditions are substantiatedfor achieving the required performance indicators from the parameters of the preliminary frequency testing process. A statementis proved that determines how the improvement of timely message delivery in a radio link with a pseudo-random adjustment of theoperating frequency depends on the growth of the array of allocated frequencies and on the speed of the program adjustment. A featureof the newly developed theoretical approaches is the formalization of radio system performance indicators based on the ratio of the timewithout taking into account the preliminary testing processes to the time required to implement the test mode with a fixed amount of aninformation message. The chosen criterion for selecting a frequency group is the permissible level of errors in the received test sequencewhose evaluation determines the group of specified unsuitable frequencies. On the basis of the conducted simulation, we have revealedthe relationships between the number of unsuitable frequencies and the gains provided by the timeliness of information transfer,depending on the performance indicators found during the testing of the working frequencies. Practical relevance: The developedsolutions, in their entirety, provide a better timeliness of message delivery in radio systems in FHSS mode.

FFR TEKNİĞİ KULLANILAN ÇOK HÜCRELİ LTE-A SİSTEMLERİNDE KAYNAK ATAMA ALGORİTMALARININ KARŞILAŞTIRILMASI

The purpose of resource allocation in LTE-A (Long Term Evolution Advanced) systems is that the time frequency resource can be used effectively by the users according to specific parameters. Scheduling algorithms are used to efficiently allocate system resources among users. In this study, when allocating frequency among cells in multi-cell LTE-A systems, the Fractional Frequency Reuse (FFR) technique, a static ICIC (Intercell Interference Coordination) technique, was first used for GPF (Generalized Proportional Fair) and AMM (Arithmetic Mean Method) schedulers. BCQI (Best Channel Quality Indicator, RR (Round Robin) and PF (Proportional Fair), AMM and GPF schedulers were compared in terms of mean user throughput, edge user throughput, peak user throughput and fairness. As a result of the simulations, it was observed that GPF schedulers increased edge user throughputs and system fairness compared to other schedulers in case of using FFR in multicellular LTE-A systems.

Алгоритм визначення електромагнітної сумісності для рішення задач частотного планування

The intensive development of the telecommunications sector is directly connected with the introduction of the latest radio technologies and communication systems, the emergence of new services and communications. In these conditions, the provision of the requirements for the radio frequency resource of all categories of users is carried out at the expense of redistribution of already mastered and further development of new frequency ranges. Redistribution of frequencies, in turn, leads to an increase in supply on already developed ranges, which is due to the growth of the number of existing radio electronic devices, and to the complication of electromagnetic environment. The development of new ranges dictates the need to allocate radio frequency bands for the latest radio technologies, systems and communication standards. In these conditions, the task of controlling the PCR and ensuring the electromagnetic compatibility of radio electronic devices and emitters are of great practical importance.These tasks can be solved only with the implementation of the appropriate scientific and methodical apparatus of radio monitoring, the application of which would enable the efficient use of radio frequency resource in modern conditions. Therefore, the topic of the thesis is relevant.The paper presents the reasons for the occurrence of interference in the work of radio electronic devices in a complicated electronic environment, examines the modern scientific and methodical apparatus of radio monitoring with the definition of the electromagnetic environment at this location for the solution of frequency scheduling of RES.Ref. 5, fig. 2.

Spatio-Radio Resource Management and Hybrid Beamforming for Limited Feedback Massive MIMO Systems

In this paper, a joint spatio–radio frequency resource allocation and hybrid beamforming scheme for the massive multiple-input multiple-output (MIMO) systems is proposed. We consider limited feedback two-stage hybrid beamformimg for decomposing the precoding matrix at the base-station. To reduce the channel state information (CSI) feedback of massive MIMO, we utilize the channel covariance-based RF precoding and beam selection. This beam selection process minimizes the inter-group interference. The regularized block diagonalization can mitigate the inter-group interference, but requires substantial overhead feedback. We use channel covariance-based eigenmodes and discrete Fourier transforms (DFT) to reduce the feedback overhead and design a simplified analog precoder. The columns of the analog beamforming matrix are selected based on the users’ grouping performed by the K-mean unsupervised machine learning algorithm. The digital precoder is designed with joint optimization of intra-group user utility function. It has been shown that more than 50 % feedback overhead is reduced by the eigenmodes-based analog precoder design. The joint beams, users scheduling and limited feedbacK-based hybrid precoding increases the sum-rate by 27.6 % compared to the sum-rate of one-group case, and reduce the feedback overhead by 62.5 % compared to the full CSI feedback.

Application Research of Multi-Mode Relay in Future Heterogeneous Networks

The fast increase of users in existing mobile networks requires more base stations (BSs) to bear more communication traffic. Future heterogeneous network is considered to be a promising candidate architecture to meet the demands of wireless networks under scarcity of radio frequency (RF) resources. In this paper, we present a multi-mode relay (MMR) model based on two-way relay technology, which is applied to heterogeneous hierarchical wireless networks (HHWN), and set up a system model of HHWN with 3 tiers, 2 users between the macrocell, and the picocell as the multi-mode relay (MMR). Specifically, we consider the new system with unequal relay emission power situation, which is usually researched in the traditional literature with equal relay emission powers. Based on this idea, we define the two-way SINR ratio, derive the mathematical formulas of outage error probability with channel estimation errors, and verify theoretical expressions by data simulations. For further comparison, several experiments are implemented to illuminate the effect on outage probability among different levels of relay emission power, noise power, and signal power. Furthermore, several conclusions are obtained, which have some meanings for implementing MMR in future heterogeneous networks.

Energy‐efficient resource allocation in D2D communications for energy harvesting–enabled NOMA‐based cellular networks

SummaryIn this paper, we propose an energy‐efficient power control and harvesting time scheduling scheme for resource allocation of the subchannels in a nonorthogonal multiple access (NOMA)–based device‐to‐device (D2D) communications in cellular networks. In these networks, D2D users can communicate by sharing the radio resources assigned to cellular users (CUs). Device‐to‐device users harvest energy from the base station (BS) in the downlink and transmit information to their receivers. Using NOMA, more than one user can access the same frequency‐time resource simultaneously, and the signals of the multiusers can be separated successfully using successive interference cancellation (SIC). In fact, NOMA, unlike orthogonal multiple access (OMA) methods, allows sharing the same frequency resources at the same time by implementing adaptive power allocation. Our aim is to maximize the energy efficiency of the D2D pairs, which is the ratio of the achievable throughput of the D2D pairs to their energy consumption by allocating the proper subchannel of each cell to each device user equipment (DUE), managing their transmission power, and setting the harvesting and transmission time. The constraints of the problem are the quality of service of the CUs, minimum required throughput of the subchannels, and energy harvesting of DUEs. We formulate the problem and propose a low‐complexity iterative algorithm on the basis of the convex optimization method and Karush‐Kuhn‐Tucker conditions to obtain the optimal solution of the problem. Simulation results validate the performance of our proposed algorithm for different values of the system parameters.

Multiuser Massive MIMO-OFDM System Incorporated with Diverse Transformation for 5G Applications

Wireless systems and standards are now progressing towards the implementation of fifth generation (5G) to combat with an expected and explosive growth of demands of wireless services in future. Consequently, the orthogonal frequency division multiple access (OFDMA) technology is being utilised for the uplink and downlink transmission to afford the high spectral efficiency in fading environments. However, the 5G implementation requires additional improvements to meet the futuristic stress. This work proposes an innovative solution that combines OFDMA technology with multi-user massive multiple input multiple output (MIMO) technology to meet the required elevated data rates as desired by the growing application needs of 5G. Massive MIMO is capable to fulfil the vision of 5G to realize a huge number of base stations equipped with a large number of terminals to be served in the same time–frequency resource without severe inter-user interference. Furthermore, the proposed system is demonstrated incorporation with discrete wavelet transform, and fractional Fourier transforms. The evaluated outcomes exemplify a considerable improvement in spectral efficiency and BER performance in contrast with the earlier reported work.

A resource allocation and cell association algorithm for energy efficiency in HetNets

SummaryAiming at further improving the energy efficiency of system while meeting the data rate requirement of the users, in this paper, a network energy efficiency optimization problem by jointly optimizing the resource allocation of macrocells and small cells is formulated and proven to be an NP‐hard problem, which cannot be worked out by direct methods in polynomial time. Considering the effectiveness of the modified particle swarm optimization (MPSO) algorithm, an MPSO‐based resource allocation and cell association algorithm is employed to solve the proposed joint optimization problem where the frequency resource partitioning of the macrocells, the transmission power, and the cell‐association bias of the small cells are jointly optimized. During the implementation of the optimization algorithm, the cell association alters with the transmission power and cell‐association bias adjustment, and the small cells where there are no active users associating with them will be turned off. The data rate requirement of the users is an indispensable metric in the communication system. Taking no account of the data rate requirement of the users, the frequency resource partitioning and cell association alteration will deteriorate the data rate of a few of users. Under such circumstances, we take the users' data rate requirement as a constraint of the joint optimization problem. The system level simulation results show that, by jointly optimizing the resource allocation of macrocells and small cells while guaranteeing the users' data rate requirement, the energy efficiency and system throughput can be further improved, and energy consumption can be further reduced.