Orthogonal 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.

Simultaneous Wireless Information and Power Transfer in Multi-User OFDMA Networks with Physical Secrecy.

This paper considers simultaneous wireless information and power transfer (SWIPT) from a base station to multiple Internet of Things (IoT) nodes via orthogonal frequency-division multiple access (OFDMA), where every node can eavesdrop on the subcarriers allocated to other nodes. Application layer encryption is unsuitable for IoT nodes relying on energy harvesting, and physical layer secrecy should be deployed. The different channels among users on every subcarrier can be exploited to obtain physical layer secrecy without using artificial noise. We propose an algorithm to maximize the secrecy rate of IoT nodes by jointly optimizing the power splitting ratio and subcarrier allocation. For fairness, the lowest total secrecy rate among users is maximized. Through simulations, the proposed algorithm is compared with the minimum effort approach, which allocates each subcarrier to the strongest node and selects the minimum sufficient power splitting ratio. The obtained secrecy rate is 3 times (4.5 over 1.5 bps/Hz) higher than that of the minimum effort approach in every case of parameters: the base station’s transmit power, the minimum harvested energy requirement of an IoT node and the energy harvesting efficiency.

User cooperation to mitigate the jamming in OFDMA networks

In this paper, jamming and anti-jamming in a time slotted orthogonal frequency division multiple access (OFDMA) are investigated. The users of the network cooperate to mitigate the jamming effect. Interactions among the network users and the jammer are modeled by a mixed integer non-cooperative generalized game which is a NP-hard problem. To relax the problem, a new algorithm is proposed based on channel state information (CSI) to determine the transmission channels and the partners of users in the network. To solve the proposed game, an optimization problem is solved for each player considering the best response of the other player. Another generalized game is proposed to model the cooperation among users of the network. The latter game is transformed to an equivalent Quasi Variational Inequality (QVI). Then, a new gradient based algorithm is proposed by utilizing the Karush-Kuhn-Tucker (KKT) conditions to find the solution of the equivalent QVI. Then, solving the latter game and substituting the best related response, the solution of the former generalized game is also obtained. The convergence of the proposed algorithms, and the uniqueness related to the solution of the both generalized games are proven. Finally, the simulation results confirm the effectiveness of the proposed approach.

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.

Joint Sampling Time and Resource Allocation for Power Efficiency in Industrial Cyber–Physical Systems

Cyber-physical systems (CPSs) form from convergence of computation, networking, and control of physical processes. In this article, the focus is on an industrial CPS consisting of many control plants and rate constrained (RC) users communicating over a single-cell orthogonal frequency-division multiple access network. We formulate a multiobjective mixed integer nonlinear optimization problem that seeks to determine the next maximum acceptable sampling moment of control plants and to minimize the energy usage in the uplinks and downlinks while taking into account the dynamics and intended performance of control plants, the quality of service of RC users, and power and subcarrier constraints. To address this problem, a decoupling approach is taken, leading to a Pareto solution. Our simulations show that the proposed scheme decreases the total power consumption in the CPS to a significant degree.

Improving Power and Resource Management in Heterogeneous Downlink OFDMA Networks

In the past decade, low power consumption schemes have undergone degraded communication performance, where they fail to maintain the trade-off between the resource and power consumption. In this paper, management of resource and power consumption on small cell orthogonal frequency-division multiple access (OFDMA) networks is enacted using the sleep mode selection method. The sleep mode selection method uses both power and resource management, where the former is responsible for a heterogeneous network, and the latter is managed using a deactivation algorithm. Further, to improve the communication performance during sleep mode selection, a semi-Markov sleep mode selection decision-making process is developed. Spectrum reuse maximization is achieved using a small cell deactivation strategy that potentially identifies and eliminates the sleep mode cells. The performance of this hybrid technique is evaluated and compared against benchmark techniques. The results demonstrate that the proposed hybrid performance model shows effective power and resource management with reduced computational cost compared with benchmark techniques.

Multiple QoS provisioning with pre-emptive priority schedulers in multi-resource OFDMA networks

In this paper, we present an analytical framework for the performance evaluation of a pre-emptive priority scheduler in multi-resource networks, like those using Orthogonal Frequency Division Multiple Access (OFDMA). We focus on Quality of Service (QoS)-guaranteed traffic for which QoS is guaranteed to individual users by restricting the number of admitted users. For this, the QoS-constrained capacity, in terms of the number of supported users, needs to be ascertained a priori. The QoS-constrained capacity is a function of users’ QoS requirements, channel conditions, and radio resource allocation algorithms, which in this work is the pre-emptive priority scheduler. It is, thus, a variable quantity and mostly obtained using time-consuming offline computer simulations. Mathematical models, on the other hand, are timely and accurate, allowing the capacity to be derived in real-time as a function of the current network configuration. Existing works on mathematical modelling of pre-emptive priority schedulers have mostly focussed on single servers or multiple servers where a single server is assigned to each user. In contrast, OFDMA networks have multiple radio resources, i.e., multiple servers and each user may need more than one radio resource for a single packet transmission, i.e. it is a multi-resource system, which has been accounted for in this paper. We classify the users based on their resource requirements and model the pre-emptive priority scheduler as a multi-class, multi-server, multi-resource, non-work conserving queueing system. We derive its QoS metrics like average delay, packet drop probability, throughput, etc., from its continuous-time Markov Chain. We then use the derived QoS metrics to obtain the QoS-constrained capacity and design a threshold based predictive call admission control unit. We have validated the results using extensive discrete event simulations.

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.

Toward the energy efficiency of resource allocation algorithms for OFDMA downlink MIMO systems

The problem of the simultaneous multi-user resource allocation algorithm in orthogonal frequency division multiple access (OFDMA) based systems has recently attracted significant interest. However, most studies focus on maximizing the system throughput and spectral efficiency. As the green radio is essential in 5G and future networks, the energy efficiency becomes the major concern. In this paper, we develop four resource allocation schemes in the downlink OFDMA network and the main focus is on analyzing the energy efficiency of these schemes. Specifically, we employ the advanced multi-antenna technology in a multiple input-multiple output (MIMO) system. The first scheme is based on transmit spatial diversity (TSD), in which the vector channel with the highest gain between the base station (BTS) and specific antenna at the remote terminal (RT) is chosen for transmission. The second scheme further employs spatial multiplexing on the MIMO system to enhance the throughput. The space-division multiple-access (SDMA) scheme assigns single subcarrier simultaneously to RTs with pairwise “nearly orthogonal” spatial signatures. In the fourth scheme, we propose to design the transmit beamformers based on the zero-forcing (ZF) criterion such that the multi-user interference (MUI) is completely removed. We analyze the tradeoff between the throughput and power consumption and compare the performance of these schemes in terms of the energy efficiency.

Secrecy Energy Efficiency Optimization for Downlink Two-User OFDMA Networks With SWIPT

Simultaneous wireless information and power transfer (SWIPT), as a promising technology by which mobile devices are designed by both information decoding and energy harvesting at the same time, has recently drawn significant interests. However, in multiuser scenario, a challenging physical layer security issue arises as the confident messages sent to the intended information receivers may be eavesdropped by other receivers. To address this problem, in this paper, secrecy energy efficiency maximization (SEEM) problem is investigated for two-user orthogonal frequency-division multiple access networks with SWIPT. Specifically, a power splitting scheme is adopted for each user, which would split received radio frequency signals into two independent parts for information decoding and energy harvesting, respectively. Taking both the individual secrecy quality of service requirement and the individual harvested energy constraint into consideration, the SEEM problem is formulated as a nonlinear fractional programming problem. Moreover, according to Dinkelbach's method, a power allocation and power splitting (PAPS) algorithm is proposed by solving the equivalent convex optimization problem. Finally, numerical results verify the impact of static circuit power consumption, maximum transmit power, power split ratio, subcarrier bandwidth, and path loss on secrecy energy efficiency of our PAPS algorithm.

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.

Energy-Efficient Power Allocation with Interference Mitigation in MmWave-Based Fog Radio Access Networks

MmWave and F-RAN are recognized as promising technology for 5G communications for the huge segment of available spectrum and efficient use of the network edge. Incorporating the advantages of both technologies, we propose the concept of mmWave-based F-RAN to accommodate the exponential growth of wireless traffic. In this article, we survey the challenges and performances for the access link and fronthaul link in mmWavebased F-RAN. Then energy-efficient power allocation in an orthogonal frequency-division multiple access network is investigated in view of the interference management. The optimization problem is formulated as a nonlinear programming problem in order to achieve the maximal energy efficiency of the system. A gradient-based iteration algorithm is proposed to search the optimal solution for the energy-efficient power allocation. Simulation results are presented to demonstrate the performance of system capacity in mmWave-based F-RAN and the effectiveness of the proposed algorithms from the aspect of energy efficiency.

Resource Allocation and Admission Control for an Energy Harvesting Cooperative OFDMA Network

This paper addresses the problem of joint resource allocation and admission control for an energy harvesting (EH)-based cooperative orthogonal frequency-division multiple access network, where multiple source–destination pairs and an EH amplify-and-forward relay coexist. Specifically, the relay first employs the power splitting technique to scavenge energy from radio frequency signals emitted by source nodes and then leverages the harvested energy to forward data for source nodes when necessary. Under imperfect channel state information, we first design a distributed robust resource allocation scheme to efficiently allocate system subcarriers, and the relay's and source nodes’ transmit powers together with selecting the suitable power splitting ratios for the relay. Then, for the admission control, which is important but has hardly been studied for EH networks, we propose a fuzzy-logic-based admission control policy to determine the network access of each source–destination pair, if not all source–destination pairs’ quality-of-service (QoS) requirements can be satisfied. In particular, considering the EH nature of the relay, this policy not only considers the QoS and the priority of each source–destination pair, but also takes account of the contribution of each source–destination pair to the relay's energy harvesting, and the energy efficiency to utilize the relay's energy. Finally, we evaluate and verify the performance of the proposed resource allocation and admission control schemes through numerical experiments.

On the Design of OFDMA-Based FFR-Aided Irregular Cellular Networks With Shadowing

Owing to its high capabilities in terms of spectral efficiency and flexibility, orthogonal frequency division multiple access (OFDMA) has played a crucial role towards the success of 4G cellular systems and an increasing number of actors in the 5G arena strongly advocate for its continuation. OFDMA-based architectures do not introduce intracell interference but, due to the use of very aggressive frequency reuse plans, they must implement some form of inter-cell interference (ICI) control to warrant prescribed levels of quality of service, specially to users located near the cell edge. An efficient technique for mitigating ICI in OFDMA networks is the well-known fractional frequency reuse (FFR) scheme. In FFR, a signal-to-interference-plus-noise ratio threshold is used to categorize mobile stations (MSs) as cell-center or cell-edge MSs. Furthermore, a different number of frequency resources are allocated to cell-center and cell-edge areas according to a prescribed frequency reuse plan. This paper presents an analytical characterization of FFR-aided OFDMA-based multi-cellular networks that, unlike most previous studies, incorporates shadowing effects and, furthermore, considers that base stations are irregularly deployed. This analytical approach can incorporate different scheduling rules and can underpin different designs for which the optimal FFR parameters can be derived. The proposed framework allows the performance evaluation and optimization of any cell in the system by considering the specific network topology, the user association and categorization processes, the spatial density of users and the characteristics of both the fast multipath fading and the spatially correlated slow shadow fading.

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.

Fast Water-Filling Method for Sum-Power Minimization in OFDMA Networks

In this letter, we investigate the problem of sum-power minimization for the users in orthogonal frequency division multiple access (OFDMA) networks subject to the target rate constraint. To address this problem, two fast water-filling (WF) methods are developed under two scenarios: without and with considering the peak-power constraint on the subchannels, which are referred to as FWF and FWF-PP, respectively. We show that our proposed methods converge to the optimal solution, while the computational complexity is reduced compared to the existing WF methods. Our results are also confirmed via simulations.

Quality-oriented Rate Control and Resource Allocation in Time-Varying OFDMA Networks

In this paper, we propose a resource management scheme for on-demand video streaming in orthogonal frequency-division multiple access (OFDMA) networks with both time-varying channels and a user's personalized quality requirement. We design a user quality satisfaction model to evaluate the degree of the user quality satisfaction with respect to his/her personalized quality requirement. To perform the dynamic resource management, we propose a joint rate control (RC) associated with the quality adjustment at the application layer and resource allocation (RA) associated with the power allocation and subcarrier assignment at the physical layer. By using the Lyapunov optimization technique, we develop a joint RC and RA (JRCRA) algorithm to maximize the time-averaged quality satisfaction of all users (QSAU). We show that the QSAU achieved by the JRCRA algorithm without any prior knowledge of the channel statistics can arbitrarily attain the optimal QSAU achieved by the algorithm with a complete knowledge of the channel statistics. Simulation results verify the advantages of the proposed JRCRA algorithm.

Optimization of Discrete Power and Resource Block Allocation for Achieving Maximum Energy Efficiency in OFDMA Networks

Most of the resource allocation literature on the energy-efficient orthogonal frequency division multiple access (OFDMA)-based wireless communication systems assume continuous power allocation/control, while, in practice, the power levels are discrete (such as in 3GPP LTE). This convenient continuous power assumption has mainly been due to either the limitations of the used optimization tools and/or the high computational complexity involved in addressing the more realistic discrete power allocation/control. In this paper, we introduce a new optimization framework to maximize the energy efficiency of the downlink transmission of cellular OFDMA networks subject to power budget and quality-of-service constraints, while considering discrete power and resource blocks (RBs) allocations. The proposed framework consists of two parts: 1) we model the predefined discrete power levels and RBs allocations by a single binary variable and 2) we propose a close-to-optimal semidefinite relaxation algorithm with Gaussian randomization to efficiently solve this non-convex combinatorial optimization problem with polynomial time complexity. We notice that a small number of power levels suffice to approach the energy efficiency performance of the continuous power allocation. Based on this observation, we propose an iterative suboptimal heuristic to further reduce the computational complexity. Simulation results show the effectiveness of the proposed schemes in maximizing the energy efficiency, while considering the practical discrete power levels.

Achieving Maximum Effective Capacity in OFDMA Networks Operating Under Statistical Delay Guarantee

We propose a spectrally efficient design that guarantees the statistical delay quality-of-service (QoS) for delay-sensitive traffic in the downlink of orthogonal frequency-division multiple-access (OFDMA) networks. This design is based on the so-called effective capacity (EC) concept, which describes the maximum throughput, a system can achieve under a specific statistical delay-QoS violation probability constraint. We investigate the EC maximization problem, in which, the statistical delay profile of the traffic is characterized by the QoS-exponent $\theta $ determining the exponential decay rate of the delay-QoS violation probability. By exploiting the properties of concave programming and Slater’s condition, the Lagrangian dual decomposition method is applied and an iterative algorithm that does not depend on the instantaneous channel state information (CSI) is proposed for solving the concave problem formulated. Extensive simulations demonstrate the efficacy and robustness of the proposed iterative algorithm. Furthermore, we show that the system’s achievable EC does not depend on the specific choice of the subcarrier allocation, but rather on the number of subcarriers allocated to each user. This is, because, the EC is calculated using the channel’s statistics, instead of the instantaneous CSI, implying that the EC is more of a long term channel capacity metric.

Joint User Pairing, Subchannel, and Power Allocation in Full-Duplex Multi-User OFDMA Networks

In this paper, the resource allocation and scheduling problem for a full-duplex (FD) orthogonal frequency-division multiple-access network is studied where an FD base station simultaneously communicates with multiple pairs of uplink (UL) and downlink (DL) half-duplex (HD) users bidirectionally. In this paper, we aim to maximize the network sum-rate through joint UL and DL user pairing, OFDM subchannel assignment, and power allocation. We formulate the problem as a non-convex optimization problem. The optimal algorithm requires an exhaustive search, which will become prohibitively complicated as the numbers of users and subchannels increase. To tackle this complex problem more efficiently, we formulate the user-pairing and subchannel allocation problem as a three-sided matching problem, and propose a novel low-complexity near-optimal matching algorithm. The algorithm is analyzed, and we prove that it converges to a stable matching. Simulation results show that the FD scheme can significantly improve the spectrum efficiency compared with the HD scheme. The proposed algorithm performs very close to the optimal algorithm, and significantly outperforms other resource allocation schemes.