Orthogonal Frequency Division Multiple Access Research Articles

Robust Power Allocation for Multi-Homing Heterogeneous Networks with Energy Harvesting

To improve user’s data rate and network coverage, multi-homing heterogeneous network has been considered as a key technology in recent years. However, traditional power allocation schemes cannot provide good robustness and suppress the impact of parameter perturbation due to the random interference and channel delays. A robust power allocation algorithm is proposed for an orthogonal frequency division multiple access based multi-homing heterogeneous network under energy harvesting. Considering the channel uncertainties from base stations to users, the total data rate of all mobile terminals (MTs) is maximized under the rate outage constraint of MT. Based on the uniform distribution of uncertainty, the originally robust counterpart problem is transformed to a deterministic and convex one. The Lagrange dual decomposition theory is used to solve it. Simulation results demonstrate that the proposed scheme has good convergence and robustness.

Profit Maximization in 5G+ Networks with Heterogeneous Aerial and Ground Base Stations

In this paper, we propose a novel framework for 5G and beyond (5G+) heterogeneous wireless networks consisting of macro aerial base stations (MABSs), small aerial base stations (SABSs), and ground base stations (GBSs) with two types of access technologies: power domain non-orthogonal multiple access (PD-NOMA) and orthogonal frequency-division multiple access (OFDMA). We aim to maximize the total network profit under some practical network constraints, e.g., NOMA and OFDMA limitations, transmit power (TP) maximum limits, and isolation of the virtualized wireless network. We formulate the resource allocation problem encompassing joint TP allocation, ABS altitude determination, user association, and sub-carrier allocation parameters. Our optimization problem is mixed integer non-linear programming (MINLP) with high computational complexity. To propose a practical approach with reduced computational complexity, we use an alternate method where the main optimization is broken down into three sub-problems with lower computational complexity. We do this by adopting successive convex approximation (SCA), geometric programming (GP), and mesh adaptive direct search (MADS) to solve each of the resulting problems, and find power allocation, altitudes of ABSs, and assignment parameters, respectively. Simulation results reveal that our proposed scenario can improve the overall network profit by up to 47 percent compared to the case where the TPs and ABS altitudes are fixed. Besides, finding the ABS altitude with fixed TPs can improve the network profit by 20 percent compared to the power allocation case with fixed ABS altitudes. Our proposed heterogeneous approach improves the network profit by up to 18, 16, 15, and 10 percent in suburban, urban, dense urban, and high-rise urban environments, respectively, compared to the cases with homogeneous ABSs.

Resource Allocation for Cooperative Transmission in Optical Wireless Cellular Networks With Illumination Requirements

Visible light communication (VLC) often suffers from line-of-sight path blockages and high levels of inter-cell interference. Thus, the analysis and design of cooperation techniques become crucial to address these key impairments. This paper studies the performance of different resource allocation schemes that are suitable for multi-cell cooperative transmission when tri- and tetra-chromatic light-emitting diodes (LEDs) and optical orthogonal frequency-division multiple access are utilized. Firstly, guidelines are derived for maintaining the same spatial distribution of the signal-to-interference-plus-noise ratio (SINR) in every sector of the multi-cell environment in case of stand-alone (non-cooperative) and cooperative transmission. Secondly, the possible resource allocation configurations for both stand-alone and cooperative transmission modes are identified for different LED types and available orthogonal resources (i.e., frequency sub-bands per color and sectors per cell). Finally, the data rate gain of the multiple resource allocation configurations are also analyzed, while verifying the illumination constraints. The obtained results confirm that the proper design of cooperative transmission configurations will be of paramount importance to provide reliable wireless link in ultra-dense VLC deployments.

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.

A Novel Spectrum Sharing Scheme Using Dynamic Long Short-Term Memory With CP-OFDMA in 5G Networks

With the rapid increase in communication technologies, shortage of spectrum will be a major issue faced in the coming years. Cognitive radio is a promising solution to this problem and works on the principle of sharing between cellular subscribers and ad-hoc Device to Device (D2D) users. Existing 5G spectrum sharing techniques work as per a fixed rule and are pre-established. Also, recent game theoretic approaches for spectrum sharing uses unrealistic assumptions with less likely practical implications. Here, a novel spectrum sharing technique is proposed using 5G enabled bidirectional cognitive deep learning nodes (BCDLN) along with dynamic spectrum sharing long short-term memory (DSLSTM). A joint spectrum allocation and management is carried out with wireless cyclic prefix orthogonal frequency division multiple access (CP-OFDMA). The BCDLN self-learning nodes with decision making capability route information to several destinations at a constant spectrum sharing target, and cooperate via DSLSTM. BCDLN based on time balanced and unbalanced channel knowledge is also examined. With the proposed framework, expressions are derived for the spectrum allocated to multiple sources to obtain their spectrum targets as a variant of the participation node spectrum sharing ratio (PNSSR). The impression of noise when all nodes broadcast with equal spectrum allocation is also investigated.

Enhancement of LMS Convergence Rate with CLS-DFE for 5G Wireless Communication System

WiMAX physical layer implemented Orthogonal Frequency Division Multiple Access (OFDMA) as one of the medium to conduct data transmission. OFDMA suffers from Intersymbol Interference (ISI) which can distort efficiency of the signal transmitted. ISI emerges in the system because of multipath. Basic Cascaded Least Square (CLS) with Decision Feedback Equalizer (DFE) had been proposed in previous research to minimize ISI in wireless communication system. This research will improve CLS performance in terms of convergence. CLS is a cascaded of two adaptive algorithms which are Least Mean Square (LMS) and Recursive Least Square (RLS). Although basic LMS has low complexity than RLS and has been used widely in wireless environment, LMS is suffering in terms of convergence. Updated Normalized Least Mean Square (NLMS) with training rate applied in this research to overcome disadvantage in LMS algorithm. This research justified that training rate is an alternative method to improve CLS-DFE in wireless communication system.

Resource Scheduling and Energy Cooperation in HetNet with Cross-Layer Interference Constraints

Facing more and more severe global warming problems, renewable energy, as an alternative to traditional fossil fuels, is attracting more and more attentions due to its capability of reducing carbon emission. This paper considers two-tier HetNets with orthogonal frequency division multiple access (OFDMA), where the macro base station (MBS) is powered by power grid and small base stations (SBSs) have hybrid energy supplies. Through smart grid, SBSs can share their renewable energy with each other. We consider the problem of cross-layer interference caused by spectrum reuse, the burst of user data, and the randomness of renewable energy arrivals. Through energy cooperation, this paper investigates maximizing the time-average energy efficiency of SBSs. Based on user data queue and SBS energy queue, the optimal problem is decoupled into two subproblems by Lyapunov optimization: resource allocation subproblem and energy scheduling and energy cooperation subproblem. By solving two subproblems, the online solution to the optimization problem is obtained. Through theoretical analysis and simulations, both user data queues and energy queues have an upper bound, the network is stable, and the proposed algorithm performs better than the basic algorithm without energy cooperation.

Joint power and subcarrier allocation for SWIPT in cognitive relay system

In this paper, we study power and subcarrier allocation in decode-and-forward (DF) cognitive relay network based on orthogonal frequency division multiple access (OFDMA) technology, in which power splitting (PS) is used for the secondary users (SUs) supporting simultaneous wireless information and the power transfer (SWIPT). We attempt to maximize the energy efficiency (EE) of the secondary system subject to the constraints of minimum system rate, maximum transmission power and minimum harvested energy. The optimal power allocation (OPA) algorithm is proposed to determine the optimal solution of relay transmission power, power splitting ratio and subcarrier allocation. To tackle the original non-convex optimization problem, the Dinkelbach method is used for fractional programming and the problem is decomposed into two solvable sub-problems. The Lagrangian dual algorithm is utilized to determine the optimal transmission power and the power splitting ratio. The Hungarian algorithm is then introduced to determine the optimal subcarrier allocation. Compared with some existing algorithms, the simulation results show that the proposed OPA scheme is able to achieve higher energy efficiency when certain communication quality is required.

Energy-Delay Tradeoff Scheme for NOMA-Based D2D Groups With WPCNs

An integration of nonorthogonal multiple access (NOMA) in device-to-device (D2D) mobile groups (DMGs) generates a large amount of energy and delay due to sharing the same subcarrier. In this article, we investigate a distributed energy-efficient and delay tradeoff scheme for NOMA-based DMGs in wireless powered communication networks. The stochastic optimization problem is formulated to maximize the energy efficiency and minimize the delay. Many-to-one matching-based subcarrier allocation, weighted sum method, and Lyapunov optimization scheme are used to investigate the possible solution. Further, to obtain the closed-form expression of power and to optimize the time for wireless powered communication networks, we use Lagrangian function. Simulation results show that the proposed scheme achieves 2.6% and 15.78% superior performance than the existing NOMA and orthogonal frequency division multiple access (OFDMA) schemes under the condition of constant circuit power consumption.

Performance evaluation of OFDMA and MU-MIMO in 802.11ax networks

IEEE 802.11ax defines a new access method called Orthogonal Frequency Division Multiple Access (OFDMA) which can be used in both downlink (DL) and uplink (UL) directions. OFDMA divides the bandwidth into several Resource Units (RUs) and allows multiple stations to transmit or to receive simultaneously. UL OFDMA supports Scheduled Access (SA) RUs and Random Access (RA) RUs. Only scheduled stations are allowed to send on SA RUs, while the other stations should contend for the RA RUs. Moreover, 802.11ax defines UL MU-MIMO and enhances DL MU-MIMO. In this paper, we introduce and evaluate the efficiency of DL and UL multi-user transmissions using OFDMA and MIMO. Our results show that UL OFDMA is particularly useful when multiple stations regularly need to transmit few MPDUs. In this case, UL OFDMA may outperform full bandwidth access with up to 400%. Moreover, we find that increasing the number of RA RUs does not effectively reduce the collision rate but significantly decreases the throughput. Furthermore, we show that UL MU-MIMO significantly improves the network throughput and that the performance of DL MU-MIMO is clearly enhanced thanks to the decreased duration of the channel sounding procedure.

Resource Allocation and Trajectory Design in UAV-Assisted Jamming Wideband Cognitive Radio Networks

The secure performance of wideband cognitive radio networks (CRNs) with OFDMA (orthogonal frequency-division multiple access) achieved by using physical layer security is low due to the severe channel fading and the limit transmit power of the secondary base station (SBS). To improve the secure performance, an unmanned aerial vehicle (UAV) assisted jamming wideband CRNs is studied where a UAV transmits the jamming signal to interfere with the eavesdropper (Eve) and the SBS provides communication services for the secondary users (SUs) over multiple sub-carrier channels. The total average secrecy rate of the secondary network is maximized by jointly optimizing the sub-carrier allocation, the jamming UAV trajectory, and the transmission power of the UAV and the SBS. An alternative algorithm is proposed to solve the challenging non-convex optimization problem. Simulation results verify the efficiency of our proposed algorithm and show that UAV-assisted jamming is beneficial for improving secure performance of wideband CRNs. It is also shown that our proposed scheme outperforms the benchmark schemes in terms of the total average secrecy rate.

Resource Allocation for Multi-User Downlink MISO OFDMA-URLLC Systems

This article considers the resource allocation algorithm design for downlink multiple-input single-output (MISO) orthogonal frequency division multiple access (OFDMA) ultra-reliable low latency communication (URLLC) systems. To meet the stringent delay requirements of URLLC, short packet transmission is adopted and taken into account for resource allocation algorithm design. The resource allocation is optimized for maximization of the weighted system sum throughput subject to quality-of-service (QoS) constraints regarding the URLLC users’ number of transmitted bits, packet error probability, and delay. Despite the non-convexity of the resulting optimization problem, the optimal solution is found via monotonic optimization. The corresponding optimal resource allocation policy can serve as a performance upper bound for sub-optimal low-complexity solutions. We develop such a low-complexity sub-optimal resource allocation algorithm based on successive convex approximation and difference of convex programming. Our simulation results reveal the importance of using multiple antennas for reducing the latency and improving the reliability of URLLC systems. Moreover, the proposed sub-optimal algorithm is shown to closely approach the performance of the proposed optimal algorithm and outperforms two baseline schemes by a considerable margin, especially when the users have heterogeneous delay requirements. Finally, conventional resource allocation designs based on Shannon’s capacity formula are shown to be not applicable in MISO OFDMA-URLLC systems as they are not able to guarantee the users’ delay constraints.

Energy efficient power control for device to device communication in 5G networks

Next generation cellular networks require high capacity, enhanced energy efficiency and guaranteed quality of service (QoS). In order to meet these targets, device-to device (D2D) communication is being considered for future 5th generation especially for certain applications that require the proximity gain, the reuse gain, and the hop gain. In this paper, we investigate energy efficient power control for the uplink of an OFDMA (orthogonal frequency-division multiple access) single-cell communication system composed of both regular cellular users and device to device (D2D) pairs. Firstly, we analyze and mathematically model the actual requirements forD2D communications and traditional cellular links in terms of minimum rate and maximum power requirement. Secondly, we use fractional programming in order to transform the original problem into an equivalent concave one and we use the non-cooperative Game theory in order to characterize the equilibrium. Then, the solution of the game is given as a water-filling power allocation. Furthermore, we implement a distributed power allocation scheme using three ways: a) Fractional programming techniques b) Closed form expression (the novelty is the use of wright omega function). c) Inverse water filling. Finally, simulations in both static and dynamic channel setting are presented to illustrate the improved performance in term of EE, SE (spectral efficiency) and time of execution of the iterative algorithm (Dinkelbach) than the closed form algorithms.

A low complexity iterative equalization technique for OFDMA and SC-FDMA uplink systems with Tx-Rx IQ imbalance and CFO under doubly selective channels

The next-generation wireless communication systems must address the compensation of in-phase and quadrature phase imbalance (IQI), carrier frequency offset (CFO), and doubly selective channel (DSC) to provide a high quality of service for high mobility users with low-cost radio . None of the existing works consider all these RF impairments under DSC for multi-user scenario. To address this gap, in this paper, we propose an iterative equalization technique to compensate the multi-user interference (MUI) and self inter-carrier interference (S-ICI) induced by the joint effect of transmitter IQI, receiver IQI, CFO and DSC for single carrier frequency division multiple access (SC-FDMA) and orthogonal frequency division multiple access (OFDMA) uplink systems. In each iteration of the proposed equalization technique, the extrinsic information from the decoder is used to cancel the MUI and S-ICI from the received signal. After interference cancellation, each mirror subcarriers pairs are equalized simultaneously. Additionally, unlike existing works, our proposed technique does not put any restriction on the carrier assignment scheme (CAS) used with OFDMA/SC-FDMA systems. Further, to validate the performance of the proposed compensation scheme analytically, we derive an upper bound on the bit error rate (BER) of coded OFDMA and SC-FDMA system without MUI and S-ICI. It is established that the system BER with the proposed technique satisfies the derived upper bound as the iteration converges, demonstrating the effective cancellation of MUI and S-ICI due to all the impairments.

Multitask deep learning-based multiuser hybrid beamforming for mm-wave orthogonal frequency division multiple access systems

Multiuser hybrid beamforming of a wideband millimeter-wave (mm-wave) system is a complex combinatorial optimization problem. It not only needs large training data, but also tends to overfit and incur long run-time when multiple serial deep learning network models are used to solve this problem directly. Preferably, multitask deep learning (MTDL) model could jointly learn multiple related tasks and share their knowledge among the tasks, and this has been demonstrated to improve performance, compared to learning the tasks individually. Therefore, this work presents a first attempt to exploit MTDL for multiuser hybrid beamforming for mm-wave massive multiple-input multiple-output orthogonal frequency division multiple access systems. The MTDL model includes a multitask network architecture, which consists of two tasks-user scheduling and multiuser analog beamforming. First, we use the effective channel with a low dimension as input data for the two parallel tasks to reduce the computational complexity of deep neural networks. In a shallow shared layer of the MTDL model, we utilize hard parameter sharing in which the knowledge of multiuser analog beamforming task is shared with the user scheduling task to mitigate multiuser interference. Second, in the training process of the MTDL model, we use the exhaustive search algorithm to generate training data to ensure optimal performance. Finally, we choose the weight coefficient of each task by traversing all weight coefficient combinations in the training phase. Simulation results prove that our proposed MTDL-based multiuser hybrid beamforming scheme could achieve better performance than traditional algorithms and multiple serial single tasks deep learning scheme.

Multiuser Visible Light Communication Systems Using OFDMA

Visible light communications (VLC), a short-range optical wireless communication scheme using light-emitting diodes (LEDs) as transmitters, has been proposed to support multiple users, predominantly in indoor environments. This article explores using orthogonal frequency division multiple access (OFDMA) for VLC due to its high spectrum utilization efficiency and potentially high transmission data rate. The proposed optical OFDMA uses adjacent subcarriers as a set to support each user. Doing so allows some users to sample at a lower sampling rate and employ a smaller fast Fourier transform (FFT) to lower the computational complexity and hardware cost. A multi-cell structure is naturally obtained in VLC since more than one LED lamp is usually installed in an indoor environment. In this article, users located in different cells can reuse the same subcarrier sets, potentially causing multiple access interference. Analysis and simulation results are used to predict the subcarrier-set reuse probability over the entire indoor space. When the OFDM modulation index is optimized considering the peak-power-limit of the LEDs, the average transmission data rate is twice that of using OFDM that does not reuse the spectral resources, for the scenarios tested.

A Spatial Group-Based Multi-User Full-Duplex OFDMA MAC Protocol for the Next-Generation WLAN.

The Wireless Local Area Network (WLAN) has become a dominant piece of technology to carry wireless traffic for Internet of Things (IoT). The next-generation high-density WLAN scenario is very suitable for the development trend of the industrial wireless sensor network. However, in the high-density deployed WLAN scenarios, the access efficiency is low due to severe collisions, and the interference is diffused due to the scattered locations of the parallel access stations (STAs), which results in low area throughput, i.e., low spatial reuse gain. A spatial group-based multi-user full-duplex orthogonal frequency division multiple access (OFDMA) (GFDO) multiple access control (MAC) protocol is proposed. Firstly, the STAs in the network are divided into several spatial groups according to the neighbor channel sensing ability. Secondly, a two-level buffer state report (BSR) information collection mechanism based on P-probability is designed. Initially, intra-group STAs report their BSR information to the group header using low transmission power. After that, group headers report both their BSR information collected from their members and inter-group interference information to the access point (AP). Finally, AP schedules two spatial groups without mutual interference to carry on multi-user full duplex transmission on the subchannels in cascading mode. The closed-form formulas are theoretically derived, including the number of uplink STAs successfully collected by AP, the network throughput and area throughput under saturated traffic. The simulation results show that the theoretical analysis coincide with the simulation results. The system throughput of the GFDO protocol is 16.8% higher than that of EnFD-OMAX protocol.

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.

Resource allocation algorithm for downlink MIMO‐OFDMA based cognitive radio networks in spectrum underlay scenario

In this study, the sum throughput maximisation problem for cognitive radio networks (CRNs) based on the multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) structure has been investigated. Hence, the intention is to maximise the downlink sum throughput of the CRN in a way that the sum power of the cognitive base station (CBS) remains below the given power limit and the induced interference on each subcarrier guarantees the interference threshold level predefined by primary users. Here, due to combinatorial constraints, the complex problem should be resolved. Hence, the core purpose of this study is to prepare a novel resource assignment algorithm that tries to fulfil these combinatorial constraints simultaneously. Therefore, this study makes progress towards solving the problem theoretically based on convex optimisation framework. An optimal solution has been implemented by proposing the iterative algorithm in which an optimal level of Lagrangian coefficients is obtained. Then, because of the optimal algorithm intricacy, the two low complicated algorithms are further suggested based on the solutions of two simplified versions of the original problem. Numerical results demonstrate that the suggested algorithms improve sum throughput considerably in comparison with classical algorithm. The proposed simplified algorithms converge to the optimal solutions' performance while their complexities are desirable for practical implementation.

Demonstration of Pattern Division Multiple Access With Message Passing Algorithm for Multi-Channel mmWave Uplinks via RoF Mobile Fronthaul

Orthogonal multiple access (OMA) such as orthogonal frequency division multiple access (OFDMA) has been the predominant access technology adopted by the current generation of mobile communication. Representing an evolutionary step in radio access networks, non-orthogonal multiple access (NOMA) is considered to be a promising technology to meet the goals of increased capacity, enhanced flexibility, and reduced latency. Pattern division multiple access (PDMA) is a NOMA scheme using resource-element mapping as the multiple-access signature in the symbol level. This article introduces PDMA in a millimeter-wave (mmWave) radio access system with systematic experimental demonstration. One key advantage of PDMA is that it can facilitate advanced parallel interference cancellation (PIC) in the decoding process. A message passing algorithm (MPA) is developed and implemented in this article to enhance the decoding performance of PDMA. A novel PDMA system integrated with MPA is experimentally demonstrated in a multi-user mmWave radio access system that uses radio-over-fiber (RoF) mobile fronthaul, achieving reduced sensitivity penalty and improved modulation spectral efficiency compared to conventional power-domain NOMA (PD-NOMA) with successive interference cancellation (SIC). Experimental results show that PDMA is capable of supporting disparate channel conditions, adapting to various patterns, and providing improved system flexibility.