Frequency Division Multiple Access Networks Research Articles

Joint Subcarrier Allocation, Modulation Mode Selection, and Trajectory Design in a UAV-Based OFDMA Network

The deployment of unmanned aerial vehicle (UAV) in scenarios with limited or no infrastructure can provide services for mobile devices flexibly. This letter investigates the UAV transmission energy minimization problem with high data rate and reliability requirements in a UAV-based Orthogonal Frequency Division Multiple Access (OFDMA) network. Considering that the formulated problem is a non-convex problem, we decompose the original problem into two subproblems: (i) joint subcarrier allocation and modulation mode selection subproblem, and (ii) UAV trajectory design subproblem. By solving these two subproblems, we propose the joint subcarrier allocation, modulation mode selection, and trajectory design (JSMT) algorithm. Simulation results show that the proposed JSMT algorithm can efficiently reduce the transmission energy of the UAV while meeting high data rate and reliability requirements.

Trajectory Optimization and Resource Allocation for OFDMA UAV Relay Networks

In this paper, we consider a single-cell multi-user orthogonal frequency division multiple access (OFDMA) network with one unmanned aerial vehicle (UAV), which works as an amplify-and-forward relay to improve the quality-of-service (QoS) of the user equipments (UEs) in the cell edge. Aiming to improve the throughput while guaranteeing the user fairness, we jointly optimize the communication mode, subchannel allocation, power allocation, and UAV trajectory, which is an NP-hard problem. To design the UAV trajectory and resource allocation efficiently, we first decompose the problem into three subproblems, i.e., mode selection and subchannel allocation, trajectory optimization, and power allocation, and then solve these subproblems iteratively. Simulation results show that the proposed algorithm outperforms the random algorithm and the cellular scheme.

Low complexity resource allocation algorithms for chunk based OFDMA multi-user networks with max–min fairness

This paper investigates the resource allocation problem in orthogonal frequency division multiple access networks with multiple users. Different from most works that perform resource allocation based on each subcarrier, we consider the subcarriers are grouped into chunks due to simplicity of implementation. The objective is to maximize the users’ minimal transmission rate by adjusting the transmission power allocation and chunk allocation while taking into account several important constraints. The problem is formulated as a mixed integer nonlinear programming problem, which is generally hard to solve. By binary relaxation, the problem is transformed to be a convex problem. By exploiting the special structure of the relaxed problem, a barrier method based fast algorithm is proposed. To achieve binary chunk allocation, a low complexity suboptimal algorithm is proposed further. When the number of chunks is less than the number of users, it is necessary to consider the joint admission control and resource allocation problem. To solve this problem, a fast algorithm based on bisection search and Hungarian method is designed. Simulations are carried out to validate the superior performance of the proposed algorithms in terms of the users’ minimal transmission rate and running time comparing with benchmark algorithms under different conditions.

Design of power and resource management in OFDMA networks using sleep mode selection technique

This paper considers the consumption of power and resource metrics in small cell networks, which are enabled through the Sleep Mode Selection (SLS) function in Orthogonal Frequency Division Multiple Access (OFDMA) system. The proposed technique considers heterogeneous networks and operates under two different schemes that includes power management using SLS and resource management using a deactivation algorithm. Further, the limitation of low power consumption schemes leads to degradation of network performance in Orthogonal Frequency Division Multiple Access (OFDMA) networks. Hence, to improve the performance, a Semi-Markov SLS (SMD-SLS) decision making process is utilized in the present study. The performance is again improved with spectrum reuse maximization, where a small cell deactivation strategy identifies well the cells in sleep modes condition and eliminates them optimally for improved spectrum reuse. The performance is evaluated for the conventional non-sleeping mode cells and a benchmark technique. The results validates the performance of proposed model against improved resource and power management.

Allocation algorithm of CPS communication resources based on cooperative game

In order to improve the communication rate of the cyber–physical fusion system, and at the same time guarantee the quality of system demand of each user, a CPS (Cyber–Physical Systems) communication resource allocation algorithm based on cooperative game was first proposed. The resource allocation process of the orthogonal frequency division multiple access network downlink in CPS is modeled as a cooperative game among multiple users, and the Pareto optimality among users is achieved by solving the Nash bargaining solution. Secondly, this paper studies the cooperative task assignment of communication resources for actuators in CPS execution network, and proposes a feasible task assignment method of communication resources based on K–M algorithm. Simulation experiments show that the task allocation result obtained by this method is better than that of auction method, and the algorithm running time can also meet the limit of actual demand. Finally, in consideration of the control center’s need for fine control of the actuator, this paper studies the wireless resource allocation problem between a control center and the actuator, and maximizes the control effect of the actuator as the daily standard, and proposes a dynamic Joint allocation scheme of subchannels and power. Simulation results show that the proposed scheme can maintain a high level of control effect even when the transmission power of the control center is small, which effectively saves the energy consumption of the control center.

Queue-aware scheduling in full-duplex wireless networks

Contemporary progress in telecommunication technologies have made full-duplex wireless communications feasible. The latter promise to double the capacity of wireless networks by allowing devices to concurrently transmit and receive on the same radio resources. In this paper, we devise mathematical optimal formulations for scheduling in full-duplex and hybrid full-duplex/half-duplex orthogonal frequency division multiple access networks. Our optimal models are queue-aware and address the new interferences that arise from working with full-duplex wireless networks: self-interference and intra-cell co-channel interference. We apply these models with different scheduling objectives, tackling issues such as signal-to-interference-plus-noise ratio (SINR) maximization and user fairness. Accordingly, we first propose an optimal full-duplex Max-SINR algorithm and an optimal full-duplex Proportional Fair algorithm. Additionally, and since full-duplex communications may not always be profitable, we introduce an optimal hybrid Max-SINR algorithm and an optimal hybrid Proportional Fair algorithm. These algorithms switch between full-duplex and half-duplex transmissions, so as to enhance network performance. Moreover, to avoid possible intractability with the optimization problems, we propose heuristic versions of our algorithms. We simulate these proposals, showing that they achieve near optimal performances, and asserting the different gains they attain with respect to their half-duplex counterparts: more than a 50% increase in user equipment throughput values alongside a three fold decrease in the average user equipment waiting delay.

An Analytical View of ASE for Multicell OFDMA Networks Based on Frequency-Reuse Scheme

This paper presents efficient interference-mitigation techniques, such as fractional frequency reuse (FFR) and soft frequency reuse (SFR) schemes, in multicell orthogonal frequency division multiple access networks under the composite multipath fading environment, where Rayleigh fading is superimposed over log-normal shadowing. We begin by outlining the obtained explicit expressions of area spectral efficiency in down-link transmission for both FFR and SFR schemes. The theoretical result are shown to be very accurate with their simulated counterparts using Monte Carlo simulations.

Joint Resource Management With Distributed Uplink Power Control in Full-Duplex OFDMA Networks

Resource allocation problems in full-duplex orthogonal frequency division multiple access (FD-OFDMA) networks are challenging due to their combinatorial, non-convex nature. In this paper, user pairing, subcarrier and power allocation in a single cell FD-OFDMA network are considered. A joint optimization problem is formulated to maximize the network's sum rate while satisfying downlink (DL) and uplink (UL) transmission power’ constraints. Due to the sheer complexity of the proposed formulation, mainly due to its combinatorial nature, an efficient, iterative two-step solution algorithm for the joint problem is proposed. In the first step, based on defining the DL user equipment (UE) signal to noise ratio (SNR) threshold, which is the least SNR that can be detected by the DL-UE, an algorithm is proposed for user pairing and subcarrier assignment. In the second step, the power allocation problem for the assigned users’ pairs is formulated and solved using the Alternating Direction Method of Multipliers (ADMM) in the high signal-to-interference-noise ratio regime. Finally, numerical results are presented to validate the performance of the proposed algorithms. We show that the performance of our proposed computationally-efficient two-step algorithm is very close to the sum rate upper bound derived from solving the dual problem.

Energy Efficiency Maximization via Joint Sub-Carrier Assignment and Power Control for OFDMA Full Duplex Networks

In this paper, we develop an energy efficient resource allocation scheme for orthogonal frequency division multiple access (OFDMA) networks with in-band full-duplex (IBFD) communication between the base station and user equipments (UEs) considering a realistic self-interference (SI) model. Our primary aim is to maximize the system energy efficiency (EE) through a joint power control and sub-carrier assignment in both the downlink (DL) and uplink (UL), where the quality of service requirements of the UEs in DL and UL are guaranteed. The formulated problem is non-convex due to the non-linear fractional objective function and the non-convex feasible set which is generally intractable. In order to handle this difficulty, we first use fractional programming to transform the fractional objective function to the subtractive form. Then, by employing Dinkelbach method, we propose an iterative algorithm in which an inner problem is solved in each iteration. Applying majorization-minimization approximation, we make the inner problem convex. Also, by introducing a penalty function to handle integer sub-carrier assignment variables, we propose an iterative algorithm for addressing the inner problem. We show that our proposed algorithm converges to the locally optimal solution which is also demonstrated by our simulation results. In addition, simulation results show that by applying the IBFD capability in OFDMA networks with efficient SI cancellation techniques, our proposed resource allocation algorithm attains a 75% increase in the EE as compared to the half-duplex system.

Joint Uplink and Downlink Transmissions in User-Centric OFDMA Cloud-RAN

This paper studies joint uplink (UL) and downlink (DL) resource allocation in user-centric orthogonal frequency division multiple access cloud radio access network (CRAN), where the users select the distributed remote radio heads (RRHs) to cooperatively serve their UL and DL transmissions over different subcarriers (SCs). The goal of this paper is to maximize the system throughput through jointly optimizing UL/DL scheduling, SC assignment, RRH grouping/clustering, and power allocation under the maximum power and fronthaul capacity constraints. The problem is formulated as a mixed integer programming problem, which is nonconvex and NP-hard. We propose an efficient algorithm based on the Lagrange duality method to obtain an asymptotically optimal solution for this problem. A heuristic algorithm is further proposed to reduce the complexity. Simulation results illustrate that the proposed heuristic algorithm also has a close-to-optimal performance, and the proposed algorithms can considerably improve the system throughput compared to other benchmark schemes.

Hybrid Radio Resource Management with Co-scheduling for Relay Extended OFDMA Networks

In orthogonal frequency division multiple access networks buffer aided non-transparent in-band half duplex decode and forward relay nodes aim to improve coverage and capacity under fairness considerations. Existing centralized radio resource management and inter cell interference coordination schemes achieve these goals at the cost of heavy signalling overhead. Especially for frequency division duplex downlink transmission this is an critical issue. Fully decentralized schemes often focus on different types of frequency reuse schemes with less amount of necessary feedback. Here, it is often overseen that in a practical deployment, the backhaul link quality is the bottleneck of the two hop transmission and needs to be taken into account. Moreover, it is often modelled way too optimistic and necessary co-scheduling with single hop UE further limits the possible data rate. In order to minimize the required overhead this work proposes a hybrid radio resource management (RRM) scheme. The RRM includes synchronous adapted two-hop proportional frequency selective resource scheduling as the decentralized part. Asynchronous subband power allocation scheme with very limited feedback is proposed to maximize the wireless backhaul link quality with no loss for single hop UE. Comprehensive system level simulation results show stable fairness and throughput when minimizing the required feedback and improvements for the backhaul links based on the centralized adapted power allocation including no losses in the overall system. In addition possible energy savings for the shared channel are presented when applying the proposed scheme.

Relay Selection and Resource Allocation for SWIPT in Multi-User OFDMA Systems

We investigate the resource allocation and relay selection in a two-hop relay-assisted multi-user orthogonal frequency division multiple access (OFDMA) network, where the end-nodes support the simultaneous wireless information and power transfer (SWIPT) employing a power splitting (PS) technique. Our goal is to optimize the end-nodes’ PS ratios as well as the relay, carrier, and power assignment so that the sum-rate of the system is maximized subject to harvested energy and transmitted power constraints. Such joint optimization with mixed-integer non-linear programming structure is combinatorial in nature. Due to the complexity of this problem, we propose to solve its dual problem, which guarantees asymptotic optimality and less execution time compared to a highly-complex exhaustive search approach. Furthermore, we also present a heuristic method to solve this problem with lower computational complexity. The simulation results reveal that the proposed algorithms provide significant performance gains compared to a semi-random resource allocation and relay selection approach and is close to the optimal solution when the number of OFDMA sub-carriers is sufficiently large.

Whitelisting in RFDMA Networks

Uplink transmissions, within coexisting distinct sub-GHz technologies operating in the same unlicensed band, can be exposed to detrimental impact of the interference. In such scenarios, transmission scheduling becomes important for mitigating interference or minimizing the impact of the interference. For this purpose, we aim to whitelist relatively better channels in terms of their yielded packet reception ratio using our proposed channel quality metric that is based on the received signal-to-interference-plus-noise ratio. In this paper, we investigate the trade-offs of the channel whitelisting in random frequency division multiple access (RFDMA) networks in the presence of the cumulative intra- and inter-technology interferences. Our main findings indicate that, although channel whitelisting reduces the degree of freedom, and thus the overall capacity, it empowers a certain amount of devices to be served at a much lower received signal power, whereas this is infeasible for non-whitelisting scenarios at larger received signal power, which signifies the energy conservation ability of our proposed whitelisting method. It is experimentally demonstrated, on Sigfox, a particular type of RFDMA network, that non-whitelisting scenarios are not capable of supporting any devices at a received signal power below -118 dBm. Even for lower received signal power, we are able to reduce the required number of retransmissions at the same reception probability, which indeed indicates that the overall reliability of the network is improved.

Common Throughput Maximization in UAV-Enabled OFDMA Systems With Delay Consideration

The use of unmanned aerial vehicles (UAVs) as communication platforms is of great practical significance in future wireless networks, especially for on-demand deployment in temporary events and emergency situations. Although prior works have shown the performance improvement by exploiting the UAV's mobility, they mainly focus on delay-tolerant applications. As delay requirements fundamentally limit the UAV's mobility, it remains unknown whether the UAV is able to provide any performance gain in delay-constrained communication scenarios. Motivated by this, we study in this paper a UAV-enabled orthogonal frequency division multiple access (OFDMA) network where a UAV is dispatched as a mobile base station (BS) to serve a group of users on the ground. We consider a minimum-rate ratio (MRR) for each user, defined as the minimum instantaneous rate required over the average achievable throughput, to flexibly adjust the percentage of its delay-constrained data traffic. Under a given set of constraints on the users' MRRs, we aim to maximize the minimum average throughput of all users by jointly optimizing the UAV trajectory and OFDMA resource allocation. First, we show that the max-min throughput in general decreases as the users' MRR constraints become more stringent, which reveals a fundamental throughput-delay tradeoff in UAV-enabled communications. Next, we propose an iterative parameter-assisted block coordinate descent method to optimize the UAV trajectory and OFDMA resource allocation alternately, by applying the successive convex optimization and the Lagrange duality, respectively. Furthermore, an efficient and systematic UAV trajectory initialization scheme is proposed based on a simple circular trajectory. Finally, simulation results are provided to verify our theoretical findings and demonstrate the effectiveness of our proposed designs.

Energy-Efficient User Scheduling and Power Control for Multi-Cell OFDMA Networks Based on Channel Distribution Information

In this paper, we investigate the energy-efficient user scheduling and power control problem in downlink multicell multiuser orthogonal frequency division multiple access networks, where only the channel distribution information is available. The resulting optimization problem is a combinatorial problem, which belongs to the class of cardinality constrained fractional programming problems subject to a maximum outage probability constraint. To solve the original problem, we derive a centralized joint user scheduling and power control solution satisfying the generalized Karush–Kuhn–Tucker conditions by resorting to the successive convex approximation (SCA). In particular, the proposed scheme can be used to solve the resource allocation problem subject to each user's minimum throughput constraint even if all the subcarriers have the same channel gain. A decentralized power control scheme is proposed to maximize the energy efficiency through combining SCA and alternating direction method of multipliers. Simulation results demonstrate the effectiveness of the proposed schemes.

Optimal Use of Harvested Solar, Hybrid Storage and Base Station Resources for Green Cellular Networks

Renewable energy (RE) is a promising solution to reduce grid energy consumption and carbon dioxide emissions of cellular networks. However, the benefit of utilizing RE is limited by its highly intermittent and unreliable nature, resulting in low savings in grid energy. To minimize the grid energy cost, we propose to utilize data buffer of user equipments as well as energy storage at the base station (BS) to better adapt the BS resource allocation and hence its energy consumption to the dynamic nature of RE. We consider the scenario of downlink orthogonal frequency division multiple access networks with non-ideal hybrid energy supply. To jointly optimize the energy consumption and the quality of service (QoS) of users, we adopt the weighted sum of users’ utility of data rates and grid energy consumption as our performance metric. We propose a low-complexity online control scheme based on Lyapunov optimization framework. The proposed technique can provide asymptotically optimal performance bound without requiring the stochastic distribution information of RE arrival and channel state condition. The experimental results demonstrate the ability of the proposed approach to significantly improve the performance in terms of grid power consumption and user QoS compared with the existing schemes.

A cross layer framework of Radio Resource Allocation for QoS provisioning in multi-channel fading wireless networks

In this paper, we present an analytical framework for the performance evaluation of Radio Resource Allocation (RRA) in Orthogonal Frequency Division Multiple Access (OFDMA) networks. We focus on Quality of Service (QoS) guaranteed traffic whose capacity, in terms of the number of active user connections, depends on the users’ QoS requirements and channel conditions, and the RRA algorithm. The required QoS is guaranteed by restricting the number of admitted calls, which in turn requires an accurate estimate of the QoS metrics and capacity supported by the RRA when a new call arrives. These estimates for OFDMA networks are variable and usually obtained through time-consuming offline computer simulations. Mathematical frameworks on the other hand yield timely and accurate results. However, earlier known works on analytical modelling of RRA either consider a single channel with random traffic arrivals or multiple channels with full buffer data traffic. In contrast, we develop a queueing theoretic framework considering randomly arriving QoS-guaranteed traffic in a variable-rate multi-channel multi-class OFDMA network. The framework can be used online leading to better dynamic Call Admission Control. We characterize the RRA algorithm using a scheduler control parameter which can regulate the call blocking probability while providing predefined QoS constraints. We model the RRA as a variable service rate, multi-server, multi-class, finite buffer queueing system and verify the derived QoS metrics using extensive Monte-Carlo discrete event simulations.

Interference Management Based on RT/nRT Traffic Classification for FFR-Aided Small Cell/Macrocell Heterogeneous Networks

Cellular networks are constantly lagging in terms of the bandwidth needed to support the growing high data rate demands. The system needs to efficiently allocate its frequency spectrum such that the spectrum utilization can be maximized while ensuring the quality of service (QoS) level. Owing to the coexistence of different types of traffic (e.g., real-time (RT) and non-real-time (nRT)) and different types of networks (e.g., small cell and macrocell), ensuring the QoS level for different types of users becomes a challenging issue in wireless networks. Fractional frequency reuse (FFR) is an effective approach for increasing spectrum utilization and reducing interference effects in orthogonal frequency division multiple access networks. In this paper, we propose a new FFR scheme in which bandwidth allocation is based on RT/nRT traffic classification. We consider the coexistence of small cells and macrocells. After applying FFR technique in macrocells, the remaining frequency bands are efficiently allocated among the small cells overlaid by a macrocell. In our proposed scheme, total frequency-band allocations for different macrocells are decided on the basis of the traffic intensity. The transmitted power levels for different frequency bands are controlled based on the level of interference from a nearby frequency band. Frequency bands with a lower level of interference are assigned to the RT traffic to ensure a higher QoS level for the RT traffic. RT traffic calls in macrocell networks are also given a higher priority compared with nRT traffic calls to ensure the low call-blocking rate. Performance analyses show significant improvement under the proposed scheme compared with conventional FFR schemes.

A joint subcarrier and power allocation technique with pro-rata fairness and unequal error protection for video transmission over OFDMA downlink

In this paper, we investigate the video quality fairness issue experienced during the transmission of video traffic from base station (BS) to users in orthogonal frequency division multiple access (OFDMA) networks. Assurance of video quality fairness is a cross-layer optimization problem when fairness is required among users in the application layer and it is achieved through resource optimization in the physical layer. For this we develop a non-iterative joint subcarrier assignment and power allocation algorithm for downlink transmission. Also we define pro-rata video quality fairness, where users are assigned video quality proportional to their demand and formulate a pro-rata fairness index to measure the fairness of the proposed algorithm. The rate compatible punctured codes (RCPC) used in the proposed work compliments video quality fairness through unequal error protection (UEP) of users based on their priority at the physical layer. The physical layer channel state information (CSI) and application layer rate distortion (RD) information of each user are used to allocate power and spectrum resources. Extensive simulation studies show that in comparison with methods which utilize only the physical layer information available at the BS, the proposed algorithm ensures significantly better video quality fairness and spectral efficiency.

Cooperative Device-to-Device Discovery Model for Multiuser and OFDMA Network Base Neighbour Discovery in In-Band 5G Cellular Networks

Device-to-device (D2D) communication in cellular networks is one of the emerging technologies for 5G communications. Initiating D2D communication device discovery is a vital research problem due to energy consumption, the need for fast discovery in dense areas and discovery in poor coverage areas. Many approaches are suggested for device discovery like Bio-inspired and Firefly proximity base discovery. Ellipsoid device discovery model is proposed for multi users and orthogonal frequency division multiple access (OFDMA) network, in which radio resources are divided into time slots and frequency divisions. In large device density areas, devices establish a local area network that can be a centralised or a distributed local area network. In this proposed model, devices which are located in poor coverage area can be discovered easily. An iterative algorithm with linear pre-processing is applied to find the position of devices that gives the ellipsoid solution of the device position. The probability of false alarm and probability of misdetection verify the proposed solution. Results show an enhancement in the system capacity, rate of detection and maximum distance discovery in comparison with the firefly proximity algorithm.