Dynamic Subcarrier Allocation Research Articles

Novel EBBDSA based Resource Allocation Technique for Interference Mitigation in 5G Heterogeneous Network

Telecom operators have applied the cell association and load balancing technique with femtocell (HeNB) in urban dense 5G Heterogeneous networks (HetNets) for reducing loads of macrocells (MeNBs) and improving the total capacity. However, this deployment creates an interference scenario; mainly, the problem occurs severely from the users of the connected and autonomous vehicle in MeNBs coverage to HeNBs coverage. The main reason is that deploying HeNBs in MeNBs applies the co-subchannels by HeNB and MeNB, leading to severe cross-tier interference (CSI) in the OFDMA subcarrier. Due to this CSI occurrence, the spectral efficiency, Signal to Interference Noise Ratio (SINR), and system outages affect severely. As a result, the MeNB User Equipment (MUEs) and HeNB User Equipment (HUEs) suffer from service disruption, and the entire system’s performance degrades. This challenge has attracted the attention of many researchers and the telecom industries. As a result, several interferences controlling methods such as enhanced frequency allocation strategies, power management, control technique, resource scheduling, spectrum sharing, and Cognitive Radio (CR) techniques have been suggested for 5G communications. However, the study suggests that downlink interference is still challenging in dense urban zones, especially in multilevel and high-rise complex buildings. This paper proposes the EBBDSA-CSI technique where a novel Evolutionary Biogeography-based Dynamic Subcarrier Allocation (EBBDSA) algorithm is introduced for reducing the cross-tier Subcarriers interference (CSI) issues in MeNB and HeNB. The system-level simulation results suggest that the proposed algorithm reduces the system outage to 88.1%, and total spectral efficiency achieves 83.6% compared to the existing techniques.

Dynamic Subcarrier Assignment in OFDMA-PONs Based on Deep Reinforcement Learning

Orthogonal Frequency Division Multiplexing Access Passive Optical Networks (OFDMA-PONs), a solution for the next-generation optical access network, allows multiple optical network units (ONUs) to dynamically share subcarriers (SCs) to support efficient bandwidth allocation. In uplink transmission, multiple ONUs can share orthogonal low bit rate SCs to transmit data at different time slots (TSs) during the transmission cycle. In this paper, the dynamic subcarrier allocation (DSA) scheme based on deep reinforcement learning (DRL) is proposed for various ONU bandwidth requests. The novel scheme jointly allocates time slots, subcarriers, and modulation formats in a dynamic and flexible manner. The ONU can save transmit power by using a lower order modulation format while meeting the delay requirement. The simulation part demonstrates how the proposed DRL-based DSA scheme can be adapted to various situations, including 1) variation in the size of ONU bandwidth requests, and 2) variation in the weight of different indicators. The extensive simulation results show that, for the first time, the proposed DRL-based DSA algorithm achieves optimal traffic latency with substantial power saving, compared with the traditional two-dimensional DSA algorithms.

Joint Resource Optimization for UAV-Enabled Multichannel Internet of Things Based on Intelligent Fog Computing

Due to flexible scheduling, and better transmission channel, unmanned aerial vehicle (UAV) can improve transmit performance of Internet of Things (IoT). In this paper, we propose an UAV-enabled multichannel IoT based on intelligent fog computing, where UAV as a relay forwards IoT's information to the data center under the control of fog computing base station in the case of terrestrial channel fading. The IoT's throughput are maximized by jointly optimizing subcarrier, power of IoT, and UAV, and UAV trajectory, subject to the constraints of information causality, maximum transmit power, and maximum UAV speed. The subcarriers are dynamically allocated according to their channel gains, the water filling algorithm is adopted to optimize the power for UAV, and IoT by fixing UAV trajectory, and the optimal UAV trajectory is achieved with successive convex approximation under the fixed power allocation. Then a jointly iterative optimization on subcarrier, power, and trajectory is presented to get the optimal solution. In addition, we propose a fairness optimization scheme to maximize the minimum transmit rate of IoT nodes. The simulations indicate the IoT with mobile UAV, and dynamic subcarrier allocation may achieve better transmit performance, and the fairness optimization can decrease the rate difference of nodes effectively.

Energy-efficient resource allocation for multi-RAT networks under time average QoS constraint

In this paper, we propose an energy-efficient resource allocation algorithm for multiple radio access technologies (multi-RAT) networks, where the user equipments (UEs) transmit data over multiple radio interfaces for exploiting the complementary advantages of different RATs. In this scenario, the resource allocation is formulated as a stochastic energy efficiency (EE) maximization problem. More specifically, the time average quality of service constraint is considered to provide the flexible resource allocation over the time-varying fading channels. The virtual queue is introduced for each UE to deal with the time average transmission requirement. By adopting Lyapunov optimization technique and fractional programming theory, the non-concave EE maximization is converted into a mixed integer nonlinear optimization (MINO) problem. After that, the continuity relaxation and Lagrange dual methods are used to find the solution of the MINO problem. Then, we develop an EE-based dynamic joint subcarrier and power allocation algorithm, which does not require any prior knowledge of the channel state information. In addition, the performance bounds of the EE and virtual queue are provided. Our simulation results show that the performance of the proposed algorithm is better than other general algorithms.

A Novel Semi-Distributed OFDMA for Indoor Visible Light Communications

In this paper, a novel OFDMA architecture based on the characteristics of the indoor visible light communication network is introduced. It is characterized by a microcell structure and frequent terminal switching. The OFDM proposed in this paper adopts DCO-OFDM modulation technology, which is determined by the consideration of the nonlinear and non-negative signal transmission characteristics of LEDs, and the SLM algorithm is also introduced to reduce PAPR. The simulation results demonstrate that the SLM algorithm can effectively reduce the PAPR of DCO-OFDM, which increases the probability that the signal in the entire system is lower than the PAPR threshold. Compared with the SLM algorithm, its CDF probability is increased by about 40%, and the SNR is also improved by 2.5 dB. The proposed OFDMA is a semi-distributed structure that is controlled by the DME to allocate subcarriers to each AP, and each has the ability to allocate subcarriers independently. Based on this architecture, an idea of dynamic subcarrier allocation is proposed, and uses the optical power received by the terminal as the SIR index to allocate different subcarriers to different SIR terminals and optimize the utilization of resources. The results of the modeling and simulation indicate that when the subcarrier allocation algorithm and method of reducing PAPR via SLM are combined, the BER of the system is significantly improved; when the SNR is 13 dB, the BER can be reduced to less than 10-6. This method can help the system reach the perfect communication target with a lower SNR, allowing the system to achieve better BER performance with less power consumption.

Performance of flexi-grid networks with dynamic and contiguous resource allocation

Abstract Flexi-grid networks with orthogonal frequency-division multiplexing has recently been proposed in optical networks, which can provide flexible capacity granularity. We investigate the network performance under dynamic subcarrier allocation methods. The performance measurements, including blocking probability and average link efficiency, are considered by simulations. The results demonstrate the performance profiles of three scenarios, and show that the performance of the network with first fit method is better than that with next fit one in a single fiber link; the traffic requests in one connection can influence the performance of related connections; the blocking probability of connection with multiple alternative paths is smaller than that of connection with just one path.

Joint subcarrier and power allocation for Multi-UAV systems

This paper investigates subcarrier and power allocation in a multi-UAV OFDM system. The study considers a practical scenario, where certain subcarriers are unavailable for dynamic subcarrier allocation, on account of pre-allocation for burst transmissions. We first propose a novel iterative algorithm to jointly optimize subcarrier and power allocation, so as to maximize the sum rate of the uplink transmission in the multi- UAV OFDM system. The key idea behind our solution is converting the nontrivial allocation problem into a weighted mean square error (MSE) problem. By this means, the allocation problem can be solved by the alternating optimization method. Besides, aiming at a lower-complexity solution, we propose a heuristic allocation scheme, where subcarrier allocation and transmit power allocation are separately optimized. In the heuristic scheme, closed- form solution can be obtained for power allocation. Simulation results demonstrate that in the presence of stretched subcarrier resource, the proposed iterative joint optimization algorithm can significantly outperform the heuristic scheme, offering a higher sum rate.

Control-Data Separation Architecture for Dual-Band mmWave Networks: A New Dimension to Spectrum Management

The exponential growth in global mobile data traffic, especially with regards to the massive deployment of devices envisioned for fifth generation (5G) mobile networks, has given impetus to exploring new spectrum opportunities to support the new traffic demands. The millimeter wave (mmWave) frequency band is considered as a potential candidate for alleviating the spectrum scarcity. Moreover, the concept of multi-tier networks has gained popularity, especially for dense network environments. In this paper, we deviate from the conventional multi-tier networks and employ the concept of control-data separation architecture (CDSA), which comprises of a control base station (CBS) overlaying the data base station (DBS). We assume that the CBS operates on the sub-6 GHz single band, while the DBS possesses a dual-band mmWave capability, i.e., 26 GHz unlicensed band, and 60 GHz licensed band. We formulate a multi-objective optimization (MOO) problem, which jointly optimizes conflicting objectives: the spectral efficiency (SE) and the energy efficiency (EE). The unique aspect of this paper includes the analysis of a joint radio resource allocation algorithm based on Lagrangian Dual Decomposition (LDD) and we compare the proposed algorithm with the maximal-rate (maxRx), dynamic sub-carrier allocation (DSA) and joint power and rate adaptation (JPRA) algorithms to show the performance gains achieved by the proposed algorithm.

Enabling radioprotection capabilities in next generation wireless communication systems: An ecological green approach

AbstractIn future fifth‐generation and beyond radio systems, access points equipped with massive antennas will be deployed to support the increased communication demands. As a result, radio environments will become more dense and users will be exposed to higher electromagnetic field (EMF) radiation from wireless devices than today. This paper proposes to take preemptive action toward protecting the public health from potential EMF‐related ill effects by examining radiation‐aware solutions for future green wireless communication systems from the radio resource scheduling perspective. Our efforts focus on correlating the transmit power levels of the wireless system with the operands used to express the EMF dosimetry metrics known as maximum permissible exposure and specific absorption rate. In addition, we formulate power minimization problems subject to the maximum permissible exposure and specific absorption rate safety standards, and the individual user quality‐of‐service demands to derive convex optimization‐based solution of dynamic subcarrier allocation and adaptive power management. The simulation results confirm that our green solution reduces significantly the user exposure to radiation, while providing the required quality of service. We expect that our findings can kick off new research directions for controlling the public exposure to radiation from wireless devices in dense networks toward safer fifth‐generation communication systems.

A Novel HGBBDSA-CTI Approach for Subcarrier Allocation in Heterogeneous Network

In recent times, Heterogeneous Network (HetNet) achieves the capacity and coverage for indoors through the deployment of small cells i.e. femtocells (HeNodeBs). These HeNodeBs are plug-and-play Customer Premises Equipment’s which are associated with the internet protocol backhaul to macrocell (macro-eNodeB). The random placement of HeNodeBs deployed in co-channel along with macro-eNodeB is causing severe system performance degradation. Thereby, these HeNodeBs are suggested as the ultimate and the most significant cause of interference in Orthogonal Frequency-Division Multiple-Access based HetNets due to the restricted co-channel deployment. The CTI in such systems can significantly reduce the throughput, and the outages can rise to the unacceptable limit or extremely high levels. These lead to severe system performance degradation in HetNets. This paper presents a novel HGBBDSA-CTI approach capable of strategically allocate the subcarriers and thereby improves the throughput as well as the outage. The enhanced system performance is able to mitigate CTI issues in HetNets. This paper also analyses the time complexity for the proposed HGBBDSA algorithm and also compares it with the Genetic Algorithm-based Dynamic Subcarrier Allocation (DSA), and Particle Swarm Optimization-based DSA as well. The key target of this study is to allocate the unoccupied subcarriers by sharing among the HeNodeBs. The reason is also to enhance the system performance such as throughput of HeNodeB, the average throughput of HeNodeB Users, and outage. The simulation results show that the proposed HGBBDSA-CTI approach enhances the average throughput (92.05 and 74.44%), throughput (30.50 and 74.34%), and the outage rate reduced to 52.9 and 50.76% compare with the existing approaches. The result also indicates that the proposed HGBBDSA approach has less time complexity than the existing approaches.

Pricing the Volume-Based Data Services in Cellular Wireless Markets

Over the past few years, many major wireless providers restricted their unlimited data plans and replaced them with limited-size fixed-price data packages. While this could be perceived as a disadvantage for customers, it helps the cellular wireless providers to reduce the traffic intensity at their base stations and this leads to a better service quality and higher rates for concurrently connected users. Hence, there is a tradeoff between the data volume and the data rates attributed to the users. To avoid the adverse effect of service inaccessibility, the cellular providers should carefully set the size and pricing of their data packages. Toward this end, the providers need a model that, together with proper market information, would allow to set the best prices for volume-based data and estimate the acceptable quantity of subscribers and their average data rate. In this paper, we propose such a model that quantifies the relationship between pricing and various market/system parameters such as data volume size, user budget, data rate, and service blocking probability. In particular, we formulate a set of revenue optimization problems for different spectrum assignment criteria like shared-carrier and dynamic sub-carrier allocation. Finally, several realistic scenarios are investigated in which the optimal network parameters are computed.

Dynamic OFDM Transmission for a Cognitive Radio Device Based on a Neural Network and Multiresolution Analysis

Cognitive radio communications depend on methods for sensing the spectrum as well as adapting transmission parameters to available resources. In this context, this work proposes a novel system that makes use of prediction to dynamically allocate subcarriers to different transmissions in an orthogonal frequency division multiplexing (OFDM) system. To this end, the proposal is comprised of a predictive component which makes use of a neural network and multiresolution analysis and a second component, which uses wavelet analysis and cognitive radio functions to carry out a dynamic allocation of subcarriers in an OFDM system. The use of wavelets allows the system to split the data stream in blocks of information to be transmitted over multiple orthogonal subcarriers. This proposed system makes use of the decision‐making functions of a cognitive radio device to select the number and position of the subcarriers used for communications without interference. Although there exist other OFDM systems using wavelets, they are not used in combination with the decision‐making functions implemented in cognitive radio devices. In contrast, the proposed OFDM system operates using some of these functions, thus being able to better adapt its operational parameters. The use of wavelets combined with a neural network model improves the prediction of the bandwidth utilization as shown in this work. It is concluded that the proposed system improves spectral efficiency and data rate by using the decision‐making functions of cognitive radios to select the appropriate OFDM subcarriers to be used during the data transmissions.

Optimal dynamic subcarrier allocation for dual-band OFDMA-PON supporting integrated fronthaul and backhaul in 5G networks

Abstract We propose a novel dynamic subcarrier allocation (DSCA) design for dual-band orthogonal frequency division multiple access passive optical network (DB-OFDMA-PON), supporting integrated fronthaul and backhaul services, given their stringent requirements in emerging 5G networks. An optimization problem is formulated to maximize both the bandwidth utilization and QoS guarantees. The simulation results show that our proposed DSCA achieves the desired statistical multiplexing gain and high performance in terms of throughput and delay.

Cross-layer Dynamic Subcarrier Allocation with Adaptive Service Rate Control in SC-FDMA System

In this paper, an improved utility-based cross-layer dynamic subcarrier allocation (DSA) algorithm is proposed for single carrier frequency division multiple access (SC-FDMA) system, which adopts adaptive service rate control (ASRC) to eliminate the service rate waste and improve the spectral efficiency in heterogeneous network including non-real-time traffic and real-time traffic. In this algorithm, furthermore, a first in first out (FIFO) queuing model with finite space is established on the cross-layer scheduling framework. Simulation results indicate that by taking the service rate constraint as the necessary condition for optimality, the ASRC algorithm can effectively eliminate the service rate waste without compromising the scheduling performance. Moreover, the ASRC algorithm is able to further improve the quality of service (QoS) performance and transmission throughput by contributing an attractive performance trade-off between real-time and non-real-time applications.

Outage Probability Analysis of Co-Tier Interference in Heterogeneous Network

In Heterogeneous Network (HetNet), the femtocell (HeNB) has been deployed by the telecommunication industries to provide extensive coverage as well as capacity in an indoor. These HeNBs are Customer Premise Equipment (CPE) which is randomly used in co-channel with macrocell (MeNB) and causes the Co-Tier Interference (CTI) in OFDMA. The effect of CTI in OFDMA systems can lead the system throughput degradation and service disruption. Because of quick direct changing features in Rayleigh channel, it is compulsory to succeed the satisfactory performance. The signal-to-interference noise ratio (SINR) is arbitrary which drives the highest capacity to be an irregular variable. However, this paper derives the expressions of outage probabilities based on the hybrid Genetic Algorithm (GA) with biogeography based dynamic subcarrier allocation (HGBBDSA) algorithm is implemented in reducing the outage probability. The outage probability countenance is expressed for the moment-generating function of the total SINR at the receivers end. The simulation results demonstrate that the HGBBDSA can lessen the outage to 45 % than existing methods.DOI: http://dx.doi.org/10.5755/j01.eie.23.5.19249

Fairness-Aware Dynamic Sub-Carrier Allocation in Distance-Adaptive Modulation OFDMA-PON for Elastic Lambda Aggregation Networks

In this paper, fairness-aware dynamic subcarrier allocation (DSA) in a distance-adaptive modulation orthogonal frequency division multiple access passive optical network (OFDMA-PON) is proposed and experimentally demonstrated for elastic lambda aggregation networks (EXANs). By applying the distance-adaptive modulation function to OFDMA-PONs, the system can change the transmission parameters (modulation level and symbol rate) for each user according to the user's end-to-end optical loss, which will yield additional bits. Meanwhile, by applying our proposed DSA algorithm, which allocates sub-carriers to users based on transmission parameters and traffic demands, the additional bits can be shared by all users in a fair manner regardless of a user's end-to-end optical loss. This paper conducts a real-time demonstration using an optical coherent OFDMA transceiver and a medium-access control board. The experiments confirm that our algorithm can greatly improve fairness in terms of frame loss rate among users compared to fixed sub-carrier allocation.

Dynamic Spectrum, Subcarrier and Power Allocation in Heterogeneous Cellular Networks Based on Interference and Small Cells’ Backhaul Limitations

Heterogeneous cellular networks (HCN) consist of different layers with shared spectrum; hence, resource management algorithms would play a key role in improving the network efficiency. Almost every present resource allocation algorithm in HCN assumes that the spectrum which is dedicated to each layer is fixed. In this paper, we propose a dynamic spectrum and multicell logarithmic resource allocation algorithm to select the number of shared channels between macros and small cells along with subcarrier and power allocation. Besides, backhaul bandwidth limit in multicell scenario is also suggested, which can be considered as another contribution of this paper. In order to achieve maximum downlink network throughput, we formulate the problem with two primary considerations: interference management and small cell backhaul capacity limitation. This involves the mixed continuous, nonlinear integer and a non-convex problem which in turn is broken to smaller parts. Then by using the upper bounds, a near-optimal solution is found which satisfies the Karush–Kuhn–Tucker conditions. Based on numerical analysis, the network throughput is improved up to 61 % compared to fixed spectrum allocation techniques which use half of the spectrum for shared channels.

Maximizing Energy Efficiency in Multiuser Multicarrier Broadband Wireless Systems: Convex Relaxation and Global Optimization Techniques

A key challenge toward green communications is how to maximize energy efficiency by optimally allocating wireless resources in large-scale multiuser multicarrier orthogonal frequency-division multiple-access (OFDMA) systems. The quality-of-service (QoS)-constrained energy efficiency maximization problem is generally hard to solve due to the inverse transposition of the optimization operands in the optimization objective. We apply convex relaxation to make the problem quasiconcave with respect to power and concave with respect to the subcarrier indexing coefficients. The Karush–Kuhn–Tucker (KKT) optimality conditions lead to transcendental functions, where existing solutions are only numerically tractable. Different from the existing approaches, we apply the Maclaurin series expansion technique to transform the complex transcendental functions into simple polynomial expressions that allow us to obtain the global optimum in fast polynomial time, with the tractable upper bound of truncation error. With the new solution method, we propose a joint optimal allocation policy for both adaptive power and dynamic subcarrier allocations. We gain insight on the optimality, feasibility, and computational complexity of the joint optimal solution to show that the proposed scheme is theoretically and practically sound with fast convergence toward near-optimal solutions with an explicitly tractable truncation error. The simulation results confirm that the proposed scheme achieves a much higher energy efficiency performance with the guaranteed QoS and much lower complexity than existing approaches in the literature.

QoS-Constrained Resource Allocation Scheduling for LTE Network

The goal of LTE (Long Term Evolution) is to provide high data transmission rate, scalable bandwidth, low latency, high-mobility, etc. LTE employs OFDM (Orthogonal Frequency Division Multiplexing) and SC-FDMA (Single Carrier - Frequency Division Multiple Access) for downlink and uplink data transmission, respectively. As to SC-FDMA, there are two constraints in doing resource allocation. First, the allocated resource blocks (RBs) should be contiguous. Second, those of the allocated RBs are forced to use the same modulation technique. The aim of this research is to propose a QoS-constraint resource allocation scheduling to enhance data transmission for uplink SC-FDMA. The proposed scheduling is a three-stage approach. In the first stage, it uses a time domain scheduler to differentiate user equipment (UE) services according to their distinct QoS service requirements. In the second stage, it uses a frequency domain scheduler to prioritize UE services based on channel quality. In the third stage, it limits the number of times of modulation downgrade of RBs allocation in order to enhance system throughput. In the simulations, the proposed method is compared to fixed sub-carrier dynamic resource allocation method and adaptive dynamic sub-carrier resource allocation method. Simulation results show that the proposed method outperforms the other two methods in terms of throughput, transmission delay, packet loss ratio, and RB utilization.

Genetic Algorithm Based QoS Aware Adaptive Subcarrier Allocation in Cognitive Radio Networks

In this paper, an adaptive subcarrier allocation scheme with reconfiguration of operating parameters for Cognitive Radio Networks (CRN) is presented. A QoS-conscious spectrum decision frame work is projected, where spectrum bands are determined by considering the application requirements as well as the dynamic nature of the spectrum bands. The novel subcarrier allocation algorithm is developed to fulfill different performance objective as a solution for subcarrier allocation and power allocation problem for Cognitive Radio (CR) users in CRNs. It employs operating frequency parameter modification using Proportional Resource Algorithm and Genetic Algorithm (GA). The multi objective optimization problem with equality and inequality constraint is considered. Moreover, a dynamic subcarrier allocations scheme is developed based on GA to decide on the spectrum bands adaptively dependent on the time-varying CR network capacity. The proposed algorithm targets to achieve maximum data rate for each subcarrier, maximize the overall network throughput and maximize the number of satisfied user under the constraints of bandwidth and guarantee Quality of Service (QoS) requirement from dynamic spectrum management (DSM) perspective. Moreover, it determines the best available channel.